|
1
|
Lytvyak E, Wang D, Shreekumar D, Ebadi M, Alrifae Y, Mason A, Montano-Loza AJ. PSC-specific prognostic scores associated with graft loss and overall mortality in recurrent PSC after liver transplantation. Dig Liver Dis 2025:S1590-8658(25)00223-3. [PMID: 40011121 DOI: 10.1016/j.dld.2025.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 02/05/2025] [Accepted: 02/07/2025] [Indexed: 02/28/2025]
Abstract
BACKGROUND Primary sclerosing cholangitis (PSC) is a progressive liver disease with no treatment apart from liver transplantation (LT). After LT, patients can develop recurrent PSC (rPSC). The United-Kingdom (UK-PSC) and Amsterdam-Oxford (AOPSC) scores are used as prognostic models for PSC outcomes. AIM We aimed to assess these scores as predictive tools for graft loss and overall mortality in rPSC. METHODS We evaluated 67 people who developed rPSC. Using Cox regression models, we quantified associations between UK-PSC and AOPSC scores and graft loss and overall mortality. Cut-offs were established using receiver operator characteristic analysis and the highest Youden index. RESULTS Fifty-one individuals (76.1%) were males, with a mean age of 40±15 years. Both UK-PSC and AOPSC scores were independently associated with graft loss (hazard ratio [HR] 2.43 (p < 0.001) and HR 3.45 (p < 0.001), respectively), but only the UK-PSC score was independently associated with overall mortality (HR 2.63 (p = 0.009)). Individuals with UK-PSC ≥-4.2 (6.1 ± 0.8 vs. 14.7 ± 1.0 years; p = 0.001) and AOPSC ≥2.4 (5.4 ± 1.3 vs. 12.0 ± 1.1 years; p < 0.001) had shorter graft survival. CONCLUSION UK-PSC score at rPSC predicts both graft loss and overall mortality, while AOPSC scores using either age at rPSC or at diagnosis along with severe cholestasis predict graft loss in people with rPSC. These easy-to-administer tools can be utilized in clinical practice to identify high-risk rPSC patients and guide decisions about monitoring/interventions.
Collapse
Affiliation(s)
- Ellina Lytvyak
- Division of Preventive Medicine, Department of Medicine, University of Alberta, 5-30 University Terrace, 8303 112 Street, Edmonton, Alberta T6G 2T4, Canada.
| | - Dennis Wang
- Division of Gastroenterology & Liver Unit, Department of Medicine, University of Alberta, 8540 112 Street NW, Zeidler Ledcor Centre, Room 1-20B, Edmonton, Alberta T6G 2×8, Canada.
| | - Devika Shreekumar
- Division of Gastroenterology & Liver Unit, Department of Medicine, University of Alberta, 8540 112 Street NW, Zeidler Ledcor Centre, Room 1-20B, Edmonton, Alberta T6G 2×8, Canada.
| | - Maryam Ebadi
- Division of Gastroenterology & Liver Unit, Department of Medicine, University of Alberta, 8540 112 Street NW, Zeidler Ledcor Centre, Room 1-20B, Edmonton, Alberta T6G 2×8, Canada.
| | - Yousef Alrifae
- Division of Gastroenterology & Liver Unit, Department of Medicine, University of Alberta, 8540 112 Street NW, Zeidler Ledcor Centre, Room 1-20B, Edmonton, Alberta T6G 2×8, Canada.
| | - Andrew Mason
- Division of Gastroenterology & Liver Unit, Department of Medicine, University of Alberta, 8540 112 Street NW, Zeidler Ledcor Centre, Room 1-20B, Edmonton, Alberta T6G 2×8, Canada.
| | - Aldo J Montano-Loza
- Division of Gastroenterology & Liver Unit, Department of Medicine, University of Alberta, 8540 112 Street NW, Zeidler Ledcor Centre, Room 1-20B, Edmonton, Alberta T6G 2×8, Canada.
| |
Collapse
|
|
2
|
Alvares D, van Niekerk J, Krainski ET, Rue H, Rustand D. Bayesian survival analysis with INLA. Stat Med 2024; 43:3975-4010. [PMID: 38922936 DOI: 10.1002/sim.10160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 06/07/2024] [Accepted: 06/12/2024] [Indexed: 06/28/2024]
Abstract
This tutorial shows how various Bayesian survival models can be fitted using the integrated nested Laplace approximation in a clear, legible, and comprehensible manner using the INLA and INLAjoint R-packages. Such models include accelerated failure time, proportional hazards, mixture cure, competing risks, multi-state, frailty, and joint models of longitudinal and survival data, originally presented in the article "Bayesian survival analysis with BUGS." In addition, we illustrate the implementation of a new joint model for a longitudinal semicontinuous marker, recurrent events, and a terminal event. Our proposal aims to provide the reader with syntax examples for implementing survival models using a fast and accurate approximate Bayesian inferential approach.
Collapse
Affiliation(s)
- Danilo Alvares
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Janet van Niekerk
- Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia
| | - Elias Teixeira Krainski
- Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia
| | - Håvard Rue
- Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia
| | - Denis Rustand
- Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia
| |
Collapse
|
|
3
|
Che Nawi CMNH, Mohd Hairon S, Wan Yahya WNN, Wan Zaidi WA, Musa KI. Machine Learning Models for Predicting Stroke Mortality in Malaysia: An Application and Comparative Analysis. Cureus 2023; 15:e50426. [PMID: 38222138 PMCID: PMC10784718 DOI: 10.7759/cureus.50426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/11/2023] [Indexed: 01/16/2024] Open
Abstract
Background Stroke is a significant public health concern characterized by increasing mortality and morbidity. Accurate long-term outcome prediction for acute stroke patients, particularly stroke mortality, is vital for clinical decision-making and prognostic management. This study aimed to develop and compare various prognostic models for stroke mortality prediction. Methods In a retrospective cohort study from January 2016 to December 2021, we collected data from patients diagnosed with acute stroke from five selected hospitals. Data contained variables on demographics, comorbidities, and interventions retrieved from medical records. The cohort comprised 950 patients with 20 features. Outcomes (censored vs. death) were determined by linking data with the Malaysian National Mortality Registry. We employed three common survival modeling approaches, the Cox proportional hazard regression (Cox), support vector machine (SVM), and random survival forest (RSF), while enhancing the Cox model with Elastic Net (Cox-EN) for feature selection. Models were compared using the concordance index (C-index), time-dependent area under the curve (AUC), and discrimination index (D-index), with calibration assessed by the Brier score. Results The support vector machine (SVM) model excelled among the four, with three-month, one-year, and three-year time-dependent AUC values of 0.842, 0.846, and 0.791; a D-index of 5.31 (95% CI: 3.86, 7.30); and a C-index of 0.803 (95% CI: 0.758, 0.847). All models exhibited robust calibration, with three-month, one-year, and three-year Brier scores ranging from 0.103 to 0.220, all below 0.25. Conclusion The support vector machine (SVM) model demonstrated superior discriminative performance, suggesting its efficacy in developing prognostic models for stroke mortality. This study enhances stroke mortality prediction and supports clinical decision-making, emphasizing the utility of the support vector machine method.
Collapse
Affiliation(s)
| | - Suhaily Mohd Hairon
- Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, MYS
| | - Wan Nur Nafisah Wan Yahya
- Department of Internal Medicine, Universiti Kebangsaan Malaysia Medical Centre (UKMMC), Kuala Lumpur, MYS
| | - Wan Asyraf Wan Zaidi
- Department of Internal Medicine, Universiti Kebangsaan Malaysia Medical Centre (UKMMC), Kuala Lumpur, MYS
| | - Kamarul Imran Musa
- Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, MYS
| |
Collapse
|
|
4
|
Yang S, Li G, Yin X, Wang Y, Jiang X, Bian X, Fang T, Yin S, Zhang L, Xue Y. Cancer-associated fibroblast expression of glutamine fructose-6-phosphate aminotransferase 2 (GFPT2) is a prognostic marker in gastric cancer. J Pathol Clin Res 2023; 9:391-408. [PMID: 37395335 PMCID: PMC10397376 DOI: 10.1002/cjp2.333] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 04/12/2023] [Accepted: 05/12/2023] [Indexed: 07/04/2023]
Abstract
Glutamine fructose-6-phosphate aminotransferase 2 (GFPT2) is a rate-limiting enzyme in hexosamine biosynthesis involved in the occurrence and progress of many cancers. What role it plays in gastric cancer (GC) is still unclear. In this study, transcriptome sequencing data from the Harbin Medical University (HMU)-GC cohort and The Cancer Genome Atlas (TCGA) dataset were combined with the HMU-TCGA training cohort to analyze the biological function and clinical significance of GFPT2. The correlation of GFPT2 with immune cells and stromal cells was analyzed in the GC immune microenvironment through transcriptome sequencing data and a public single-cell sequencing database. In cell lines, GC tissues, and the tissue microarray, GFPT2 protein expression was confirmed by western blotting and immunohistochemistry. The mRNA of GFPT2 was highly expressed in the tumor (p < 0.001), and GC cells and tumors expressed high levels of GFPT2 protein. Compared to low expression, high GFPT2 mRNA expression was associated with higher levels of tumor invasion, higher pathological stages, and poor prognosis (p = 0.02) in GC patients. In a drug susceptibility analysis, GFPT2 mRNA expression was associated with multiple chemotherapeutic drug sensitivity, including docetaxel, paclitaxel, and cisplatin. Gene enrichment analysis found that GFPT2 was mainly primarily involved in the extracellular matrix receptor interaction pathway. The ESTIMATE, CIBERSORT, and ssGSEA algorithms showed that GFPT2 was associated with immune cell infiltration. In addition, GFPT2 was more likely to be expressed within cancer-associated fibroblasts (CAFs), and high levels of GFPT2 expression were highly correlated with four CAFs scores (all p < 0.05). Finally, a prognostic model to assess the risk of death in GC patients was constructed based on GFPT2 protein expression and lymph node metastasis rate. In conclusion, GFPT2 plays an essential role in the function of CAFs in GC. It can be used as a biomarker to assess GC prognosis and immune infiltration.
Collapse
Affiliation(s)
- Shuo Yang
- Department of Pathology, Basic Medical Science CollegeHarbin Medical UniversityHarbinPR China
| | - Guoli Li
- Department of Colorectal and Anal Surgery, Chifeng Municipal HospitalChifeng Clinical Medical School of Inner Mongolia Medical UniversityChifengPR China
| | - Xin Yin
- Department of Gastroenterological SurgeryHarbin Medical University Cancer Hospital, Harbin Medical UniversityHarbinPR China
| | - Yufei Wang
- Department of Gastroenterological SurgeryHarbin Medical University Cancer Hospital, Harbin Medical UniversityHarbinPR China
| | - Xinju Jiang
- Department of Pathology, Basic Medical Science CollegeHarbin Medical UniversityHarbinPR China
| | - Xiulan Bian
- Department of Pathology, Basic Medical Science CollegeHarbin Medical UniversityHarbinPR China
| | - Tianyi Fang
- Department of Gastroenterological SurgeryHarbin Medical University Cancer Hospital, Harbin Medical UniversityHarbinPR China
| | - Shengjie Yin
- Department of Medical Oncology, Municipal Hospital of ChifengInner Mongolia Autonomous RegionChifengPR China
| | - Lei Zhang
- Department of Pathology, Basic Medical Science CollegeHarbin Medical UniversityHarbinPR China
| | - Yingwei Xue
- Department of Gastroenterological SurgeryHarbin Medical University Cancer Hospital, Harbin Medical UniversityHarbinPR China
| |
Collapse
|
|
5
|
Montano-Loza AJ, Ronca V, Ebadi M, Hansen BE, Hirschfield G, Elwir S, Alsaed M, Milkiewicz P, Janik MK, Marschall HU, Burza MA, Efe C, Calışkan AR, Harputluoglu M, Kabaçam G, Terrabuio D, de Quadros Onofrio F, Selzner N, Bonder A, Parés A, Llovet L, Akyıldız M, Arikan C, Manns MP, Taubert R, Weber AL, Schiano TD, Haydel B, Czubkowski P, Socha P, Ołdak N, Akamatsu N, Tanaka A, Levy C, Martin EF, Goel A, Sedki M, Jankowska I, Ikegami T, Rodriguez M, Sterneck M, Weiler-Normann C, Schramm C, Donato MF, Lohse A, Andrade RJ, Patwardhan VR, van Hoek B, Biewenga M, Kremer AE, Ueda Y, Deneau M, Pedersen M, Mayo MJ, Floreani A, Burra P, Secchi MF, Beretta-Piccoli BT, Sciveres M, Maggiore G, Jafri SM, Debray D, Girard M, Lacaille F, Lytvyak E, Mason AL, Heneghan M, Oo YH. Risk factors and outcomes associated with recurrent autoimmune hepatitis following liver transplantation. J Hepatol 2022; 77:84-97. [PMID: 35143897 DOI: 10.1016/j.jhep.2022.01.022] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 01/26/2022] [Accepted: 01/27/2022] [Indexed: 12/19/2022]
Abstract
BACKGROUND & AIMS Autoimmune hepatitis can recur after liver transplantation (LT), though the impact of recurrence on patient and graft survival has not been well characterized. We evaluated a large, international, multicenter cohort to identify the probability and risk factors associated with recurrent AIH and the association between recurrent disease and patient and graft survival. METHODS We included 736 patients (77% female, mean age 42±1 years) with AIH who underwent LT from January 1987 through June 2020, among 33 centers in North America, South America, Europe and Asia. Clinical data before and after LT, biochemical data within the first 12 months after LT, and immunosuppression after LT were analyzed to identify patients at higher risk of AIH recurrence based on histological diagnosis. RESULTS AIH recurred in 20% of patients after 5 years and 31% after 10 years. Age at LT ≤42 years (hazard ratio [HR] 3.15; 95% CI 1.22-8.16; p = 0.02), use of mycophenolate mofetil post-LT (HR 3.06; 95% CI 1.39-6.73; p = 0.005), donor and recipient sex mismatch (HR 2.57; 95% CI 1.39-4.76; p = 0.003) and high IgG pre-LT (HR 1.04; 95% CI 1.01-1.06; p = 0.004) were associated with higher risk of AIH recurrence after adjusting for other confounders. In multivariate Cox regression, recurrent AIH (as a time-dependent covariate) was significantly associated with graft loss (HR 10.79, 95% CI 5.37-21.66, p <0.001) and death (HR 2.53, 95% CI 1.48-4.33, p = 0.001). CONCLUSION Recurrence of AIH following transplant is frequent and is associated with younger age at LT, use of mycophenolate mofetil post-LT, sex mismatch and high IgG pre-LT. We demonstrate an association between disease recurrence and impaired graft and overall survival in patients with AIH, highlighting the importance of ongoing efforts to better characterize, prevent and treat recurrent AIH. LAY SUMMARY Recurrent autoimmune hepatitis following liver transplant is frequent and is associated with some recipient features and the type of immunosuppressive medications use. Recurrent autoimmune hepatitis negatively affects outcomes after liver transplantation. Thus, improved measures are required to prevent and treat this condition.
Collapse
Affiliation(s)
- Aldo J Montano-Loza
- Division of Gastroenterology and Liver Unit, University of Alberta, Edmonton, AB, Canada.
| | - Vincenzo Ronca
- Center for Liver Research & NIHR Birmingham BRC, University of Birmingham & University Hospital Birmingham NHS Foundation Trust, Institute of Immunology and Immunotherapy, University of Birmingham, UK
| | - Maryam Ebadi
- Division of Gastroenterology and Liver Unit, University of Alberta, Edmonton, AB, Canada
| | - Bettina E Hansen
- Toronto Center for Liver Disease, University Health Network, University of Toronto, Toronto, Canada
| | - Gideon Hirschfield
- Toronto Center for Liver Disease, University Health Network, University of Toronto, Toronto, Canada
| | - Saleh Elwir
- Baylor University Medical Center, Dallas, USA
| | | | - Piotr Milkiewicz
- Liver and Internal Medicine Unit, Medical University of Warsaw, Poland
| | - Maciej K Janik
- Liver and Internal Medicine Unit, Medical University of Warsaw, Poland
| | | | | | - Cumali Efe
- Department of Gastroenterology, Harran University Hospital, Şanlıurfa, Turkey
| | - Ali Rıza Calışkan
- Department of Gastroenterology, Inönü University School of Medicine, Malatya, Turkey
| | - Murat Harputluoglu
- Department of Gastroenterology, Inönü University School of Medicine, Malatya, Turkey
| | - Gökhan Kabaçam
- Clinic of Gastroenterology and Liver Transplantation, Guven Hospital Ankara, Turkey
| | - Débora Terrabuio
- Department of Gastroenterology - University of São Paulo School of Medicine, São Paulo, Brazil
| | | | - Nazia Selzner
- Toronto Center for Liver Disease, University Health Network, University of Toronto, Toronto, Canada
| | - Alan Bonder
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA
| | - Albert Parés
- Liver Unit, Hospital Clínic, University of Barcelona, IDIBAPS, CIBERehd, Barcelona, Spain
| | - Laura Llovet
- Liver Unit, Hospital Clínic, University of Barcelona, IDIBAPS, CIBERehd, Barcelona, Spain
| | - Murat Akyıldız
- Koç University School of Medicine, Department of Gastroenterology and Liver Transplantation Center, Istanbul, Turkey
| | - Cigdem Arikan
- Koc University School of Medicine, Pediatric Gastroenterology and Hepatology, Organ Transplantation Center, Koc University Research Center for Translational Medicine (KUTTAM), Istanbul, Turkey
| | - Michael P Manns
- European Reference Network on Hepatological Diseases (ERN RARE-LIVER), Department Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
| | - Richard Taubert
- European Reference Network on Hepatological Diseases (ERN RARE-LIVER), Department Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
| | - Anna-Lena Weber
- European Reference Network on Hepatological Diseases (ERN RARE-LIVER), Department Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
| | - Thomas D Schiano
- Recanati/Miller Transplantation Institute/Division of Liver Diseases, Mount Sinai Medical Center, New York, USA
| | - Brandy Haydel
- Recanati/Miller Transplantation Institute/Division of Liver Diseases, Mount Sinai Medical Center, New York, USA
| | - Piotr Czubkowski
- Department of Gastroenterology, Hepatology, Nutritional Disorders and Pediatrics, The Children's Memorial Health Institute, Warsaw, Poland
| | - Piotr Socha
- Department of Gastroenterology, Hepatology, Nutritional Disorders and Pediatrics, The Children's Memorial Health Institute, Warsaw, Poland
| | - Natalia Ołdak
- Department of Gastroenterology, Hepatology, Nutritional Disorders and Pediatrics, The Children's Memorial Health Institute, Warsaw, Poland
| | | | - Atsushi Tanaka
- Department of Medicine, Teikyo University School of Medicine, Tokyo, Japan
| | - Cynthia Levy
- University of Miami Miller School of Medicine, Miami, USA
| | - Eric F Martin
- University of Miami Miller School of Medicine, Miami, USA
| | | | | | | | - Toru Ikegami
- Department of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | | | | | | | | | - Maria Francesca Donato
- Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Liver Tranplant Hepatology Unit, Division of Gastroenterology and Hepatology, Milan, Italy
| | | | - Raul J Andrade
- Gastroenterology Service -IBIMA. University Hospital and CIBERehd. University of Málaga, Spain
| | - Vilas R Patwardhan
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA
| | - Bart van Hoek
- Leiden University Medical Center, Leiden, Netherlands
| | | | - Andreas E Kremer
- Department of Medicine, University Hospital Erlangen and Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany; Department of Gastroenterology and Hepatology, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Yoshihide Ueda
- Department of Gastroenterology and Hepatology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | | | - Mark Pedersen
- University of Texas Southwestern Medical Center, Dallas, USA
| | - Marlyn J Mayo
- University of Texas Southwestern Medical Center, Dallas, USA
| | - Annarosa Floreani
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | - Patrizia Burra
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | | | | | | | - Giuseppe Maggiore
- Hepatogastroenterology, Nutrition and Liver Transplant IRCCS Bambino Gesù Pediatric Hospital, Rome, Italy
| | | | - Dominique Debray
- Pediatric Liver Unit, French National Reference Center for Rare Diseases BA and Genetic Cholestasis, Hôpital Necker, Université de Paris, Paris, France
| | - Muriel Girard
- Pediatric Liver Unit, French National Reference Center for Rare Diseases BA and Genetic Cholestasis, Hôpital Necker, Université de Paris, Paris, France
| | - Florence Lacaille
- Gastroenterology-Hepatology-Nutrition Unit, Hôpital Necker-Enfants Malades, Paris, France
| | - Ellina Lytvyak
- Division of Gastroenterology and Liver Unit, University of Alberta, Edmonton, AB, Canada
| | - Andrew L Mason
- Division of Gastroenterology and Liver Unit, University of Alberta, Edmonton, AB, Canada
| | | | - Ye Htun Oo
- Center for Liver and Gastro Research & National Institute of Health Research Birmingham Biomedical Research Centre, University of Birmingham; Centre for Rare Disease and ERN Rare Liver Centre, Liver Transplant and Hepatobiliary Unit, University Hospital Birmingham NHS Foundation Trust, UK.
| |
Collapse
|
|
6
|
Schumacher AE, McCormick TH, Wakefield J, Chu Y, Perin J, Villavicencio F, Simon N, Liu L. A FLEXIBLE BAYESIAN FRAMEWORK TO ESTIMATE AGE- AND CAUSE-SPECIFIC CHILD MORTALITY OVER TIME FROM SAMPLE REGISTRATION DATA. Ann Appl Stat 2022; 16:124-143. [PMID: 37621750 PMCID: PMC10448806 DOI: 10.1214/21-aoas1489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
In order to implement disease-specific interventions in young age groups, policy makers in low- and middle-income countries require timely and accurate estimates of age- and cause-specific child mortality. High-quality data is not available in settings where these interventions are most needed, but there is a push to create sample registration systems that collect detailed mortality information. current methods that estimate mortality from this data employ multistage frameworks without rigorous statistical justification that separately estimate all-cause and cause-specific mortality and are not sufficiently adaptable to capture important features of the data. We propose a flexible Bayesian modeling framework to estimate age- and cause-specific child mortality from sample registration data. We provide a theoretical justification for the framework, explore its properties via simulation, and use it to estimate mortality trends using data from the Maternal and Child Health Surveillance System in China.
Collapse
Affiliation(s)
| | | | - Jon Wakefield
- Departments of Biostatistics and Statistics, University of Washington
| | - Yue Chu
- Department of Sociology, The Ohio State University
| | - Jamie Perin
- Department of International Health, Johns Hopkins Bloomberg School of Public Health
| | | | - Noah Simon
- Department of Biostatistics, University of Washington
| | - Li Liu
- Departments of Population, Family and Reproductive Health and International Health, Johns Hopkins Bloomberg School of Public Health
| |
Collapse
|
|
7
|
Bräuner EV, Wilson LF, Koch T, Christensen J, Dehlendorff C, Duun-Henriksen AK, Priskorn L, Abildgaard J, Simonsen MK, Jørgensen JT, Lim YH, Andersen ZJ, Juul A, Hickey M. The long-term association between bilateral oophorectomy and depression: a prospective cohort study. Menopause 2022; 29:276-283. [PMID: 35213515 DOI: 10.1097/gme.0000000000001913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Depression is a leading cause of disability globally and affects more women than men. Ovarian sex steroids are thought to modify depression risk in women and interventions such as bilateral oophorectomy that permanently change the sex steroid milieu may increase the risk of depression. This study aimed to investigate the associations between unilateral and bilateral oophorectomy and depression over a 25-year period (1993-2018) and whether this varied by age at oophorectomy or use of menopausal hormone therapy. METHODS Twenty-five thousand one hundred eighty-eight nurses aged ≥45 years from the Danish Nurse Cohort were included. Nurses with depression prior to baseline were excluded. Poisson regression models, with log-transformed person-years as offset, were used to assess the associations between oophorectomy and incident depression. Nurses who retained their ovaries were the reference group. RESULTS Compared with nurses with retained ovaries, bilateral oophorectomy was associated with a slightly higher rate of depression (rate ratio [RR], 1.08; 95% confidence interval [CI], 0.95-1.23), but without statistical significance. However, when stratified by age at oophorectomy, compared with nurses with retained ovaries, bilateral oophorectomy at age ≥51 years was associated with higher rates of depression (RR 1.16; 95% CI, 1.00-1.34), but not bilateral oophorectomy at age <51 years (RR 0.86; 95% CI, 0.69-1.07); P value for difference in estimates = 0.02. No association between unilateral oophorectomy and depression was observed. CONCLUSIONS In this cohort of Danish female nurses, bilateral oophorectomy at age ≥51 years, but not at younger ages, was associated with a slightly higher rate of depression compared with those who retained their ovaries.
Collapse
Affiliation(s)
- Elvira V Bräuner
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- The International Research and Research Training Centre in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Louise F Wilson
- NHMRC Centre for Research Excellence on Women and Non-communicable Diseases (CREWaND), School of Public Health, The University of Queensland, Herston, Queensland, Australia
| | - Trine Koch
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- The International Research and Research Training Centre in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Jane Christensen
- Statistics and Data Analysis, Danish Cancer Society, Copenhagen, Denmark
| | | | | | - Lærke Priskorn
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- The International Research and Research Training Centre in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Julie Abildgaard
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- The International Research and Research Training Centre in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Centre for Physical Activity Research, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Mette K Simonsen
- Department of Neurology and Parker Institute, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Jeanette T Jørgensen
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Youn-Hee Lim
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
- Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Zorana J Andersen
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Anders Juul
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- The International Research and Research Training Centre in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, University of Melbourne and the Royal Women's Hospital, Melbourne, Victoria, Australia
| |
Collapse
|
|
8
|
Koch T, Therming Jørgensen J, Christensen J, Duun-Henriksen AK, Priskorn L, Kildevaeld Simonsen M, Dehlendorff C, Jovanovic Andersen Z, Juul A, Bräuner EV, Hickey M. Bilateral oophorectomy and rate of colorectal cancer: A prospective cohort study. Int J Cancer 2022; 150:38-46. [PMID: 34449872 DOI: 10.1002/ijc.33776] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 08/17/2021] [Accepted: 08/18/2021] [Indexed: 11/11/2022]
Abstract
Worldwide, colorectal cancer is the second most common cancer and third cause of cancer death in women. Estrogen exposure has been inversely associated with colorectal cancer. Oophorectomy reduces circulating estrogen, but the effect on colorectal cancer remains uncertain. The aim of this study was to examine the association between unilateral and bilateral oophorectomy and subsequent risk of colorectal cancer, and whether this association varied by menopausal status at time of oophorectomy, use of hormone replacement therapy (HRT) at baseline, hysterectomy and baseline body mass index (BMI). The study included 25 698 female nurses (aged ≥45 years) participating in the Danish Nurse Cohort. Nurses were followed from baseline until date of colorectal cancer, death, emigration or end of follow-up at December 31, 2018, whichever came first. We examined the association between oophorectomy and colorectal cancer (all ages and stratified by menopausal status). The potential modifying effects of hysterectomy, HRT use at baseline and BMI were investigated. During 542 140 person-years of follow-up, 863 (3.4%) nurses were diagnosed with colorectal cancer. Bilateral oophorectomy was associated with a 79% increased colorectal cancer rate, adjusted rate ratio (aRR) (95% confidence interval [CI]): 1.79 (1.33-2.42). Effect estimates following unilateral oophorectomy also showed higher rate of colorectal cancer, although less pronounced and nonstatistically significant (aRR) (95% CI): 1.25 (0.86-1.82). Similar results were seen when stratifying by menopausal status. The association was not modified by baseline HRT use, hysterectomy or BMI. Oophorectomy was associated with increased rate of colorectal cancer, with highest rates among women with bilateral oophorectomy.
Collapse
Affiliation(s)
- Trine Koch
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- The International Research and Research Training Centre in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | | | - Jane Christensen
- Statistics and Data Analysis, Danish Cancer Society, Copenhagen, Denmark
| | | | - Laerke Priskorn
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- The International Research and Research Training Centre in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Zorana Jovanovic Andersen
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
- Centre for Epidemiological Research, Nykøbing F Hospital, Nykøbing F, Denmark
| | - Anders Juul
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- The International Research and Research Training Centre in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Elvira V Bräuner
- Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- The International Research and Research Training Centre in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, University of Melbourne, Melbourne, Victoria, Australia
| |
Collapse
|
|
9
|
Kvamme H, Borgan Ø. Continuous and discrete-time survival prediction with neural networks. LIFETIME DATA ANALYSIS 2021; 27:710-736. [PMID: 34618267 PMCID: PMC8536596 DOI: 10.1007/s10985-021-09532-6] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 08/26/2021] [Indexed: 06/06/2023]
Abstract
Due to rapid developments in machine learning, and in particular neural networks, a number of new methods for time-to-event predictions have been developed in the last few years. As neural networks are parametric models, it is more straightforward to integrate parametric survival models in the neural network framework than the popular semi-parametric Cox model. In particular, discrete-time survival models, which are fully parametric, are interesting candidates to extend with neural networks. The likelihood for discrete-time survival data may be parameterized by the probability mass function (PMF) or by the discrete hazard rate, and both of these formulations have been used to develop neural network-based methods for time-to-event predictions. In this paper, we review and compare these approaches. More importantly, we show how the discrete-time methods may be adopted as approximations for continuous-time data. To this end, we introduce two discretization schemes, corresponding to equidistant times or equidistant marginal survival probabilities, and two ways of interpolating the discrete-time predictions, corresponding to piecewise constant density functions or piecewise constant hazard rates. Through simulations and study of real-world data, the methods based on the hazard rate parametrization are found to perform slightly better than the methods that use the PMF parametrization. Inspired by these investigations, we also propose a continuous-time method by assuming that the continuous-time hazard rate is piecewise constant. The method, named PC-Hazard, is found to be highly competitive with the aforementioned methods in addition to other methods for survival prediction found in the literature.
Collapse
Affiliation(s)
- Håvard Kvamme
- Department of Mathematics, University of Oslo, P.O. Box 1053 Blindern, 0316 Oslo, Norway
| | - Ørnulf Borgan
- Department of Mathematics, University of Oslo, P.O. Box 1053 Blindern, 0316 Oslo, Norway
| |
Collapse
|
|
10
|
Xiao J, Mo M, Wang Z, Zhou C, Shen J, Yuan J, He Y, Zheng Y. Machine Learning Models for the Prediction of Breast Cancer Prognostic: Application and Comparison Based on a Retrospective Cohort Study (Preprint). JMIR Med Inform 2021; 10:e33440. [PMID: 35179504 PMCID: PMC8900909 DOI: 10.2196/33440] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 12/15/2021] [Accepted: 01/02/2022] [Indexed: 11/17/2022] Open
Abstract
Background Over the recent years, machine learning methods have been increasingly explored in cancer prognosis because of the appearance of improved machine learning algorithms. These algorithms can use censored data for modeling, such as support vector machines for survival analysis and random survival forest (RSF). However, it is still debated whether traditional (Cox proportional hazard regression) or machine learning-based prognostic models have better predictive performance. Objective This study aimed to compare the performance of breast cancer prognostic prediction models based on machine learning and Cox regression. Methods This retrospective cohort study included all patients diagnosed with breast cancer and subsequently hospitalized in Fudan University Shanghai Cancer Center between January 1, 2008, and December 31, 2016. After all exclusions, a total of 22,176 cases with 21 features were eligible for model development. The data set was randomly split into a training set (15,523 cases, 70%) and a test set (6653 cases, 30%) for developing 4 models and predicting the overall survival of patients diagnosed with breast cancer. The discriminative ability of models was evaluated by the concordance index (C-index), the time-dependent area under the curve, and D-index; the calibration ability of models was evaluated by the Brier score. Results The RSF model revealed the best discriminative performance among the 4 models with 3-year, 5-year, and 10-year time-dependent area under the curve of 0.857, 0.838, and 0.781, a D-index of 7.643 (95% CI 6.542, 8.930) and a C-index of 0.827 (95% CI 0.809, 0.845). The statistical difference of the C-index was tested, and the RSF model significantly outperformed the Cox-EN (elastic net) model (C-index 0.816, 95% CI 0.796, 0.836; P=.01), the Cox model (C-index 0.814, 95% CI 0.794, 0.835; P=.003), and the support vector machine model (C-index 0.812, 95% CI 0.793, 0.832; P<.001). The 4 models’ 3-year, 5-year, and 10-year Brier scores were very close, ranging from 0.027 to 0.094 and less than 0.1, which meant all models had good calibration. In the context of feature importance, elastic net and RSF both indicated that TNM staging, neoadjuvant therapy, number of lymph node metastases, age, and tumor diameter were the top 5 important features for predicting the prognosis of breast cancer. A final online tool was developed to predict the overall survival of patients with breast cancer. Conclusions The RSF model slightly outperformed the other models on discriminative ability, revealing the potential of the RSF method as an effective approach to building prognostic prediction models in the context of survival analysis.
Collapse
Affiliation(s)
- Jialong Xiao
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
- Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Miao Mo
- Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zezhou Wang
- Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Changming Zhou
- Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jie Shen
- Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jing Yuan
- Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yulian He
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
- Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Ying Zheng
- Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of Artificial Intelligence Technology for Tumor Diseases, Shanghai, China
| |
Collapse
|
|
11
|
Hall VJ, Foulkes S, Saei A, Andrews N, Oguti B, Charlett A, Wellington E, Stowe J, Gillson N, Atti A, Islam J, Karagiannis I, Munro K, Khawam J, Chand MA, Brown CS, Ramsay M, Lopez-Bernal J, Hopkins S. COVID-19 vaccine coverage in health-care workers in England and effectiveness of BNT162b2 mRNA vaccine against infection (SIREN): a prospective, multicentre, cohort study. Lancet 2021; 397:1725-1735. [PMID: 33901423 PMCID: PMC8064668 DOI: 10.1016/s0140-6736(21)00790-x] [Citation(s) in RCA: 547] [Impact Index Per Article: 136.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 03/18/2021] [Accepted: 03/29/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND BNT162b2 mRNA and ChAdOx1 nCOV-19 adenoviral vector vaccines have been rapidly rolled out in the UK from December, 2020. We aimed to determine the factors associated with vaccine coverage for both vaccines and documented the vaccine effectiveness of the BNT162b2 mRNA vaccine in a cohort of health-care workers undergoing regular asymptomatic testing. METHODS The SIREN study is a prospective cohort study among staff (aged ≥18 years) working in publicly-funded hospitals in the UK. Participants were assigned into either the positive cohort (antibody positive or history of infection [indicated by previous positivity of antibody or PCR tests]) or the negative cohort (antibody negative with no previous positive test) at the beginning of the follow-up period. Baseline risk factors were collected at enrolment, symptom status was collected every 2 weeks, and vaccination status was collected through linkage to the National Immunisations Management System and questionnaires. Participants had fortnightly asymptomatic SARS-CoV-2 PCR testing and monthly antibody testing, and all tests (including symptomatic testing) outside SIREN were captured. Data cutoff for this analysis was Feb 5, 2021. The follow-up period was Dec 7, 2020, to Feb 5, 2021. The primary outcomes were vaccinated participants (binary ever vacinated variable; indicated by at least one vaccine dose recorded by at least one of the two vaccination data sources) for the vaccine coverage analysis and SARS-CoV-2 infection confirmed by a PCR test for the vaccine effectiveness analysis. We did a mixed-effect logistic regression analysis to identify factors associated with vaccine coverage. We used a piecewise exponential hazard mixed-effects model (shared frailty-type model) using a Poisson distribution to calculate hazard ratios to compare time-to-infection in unvaccinated and vaccinated participants and estimate the impact of the BNT162b2 vaccine on all PCR-positive infections (asymptomatic and symptomatic). This study is registered with ISRCTN, number ISRCTN11041050, and is ongoing. FINDINGS 23 324 participants from 104 sites (all in England) met the inclusion criteria for this analysis and were enrolled. Included participants had a median age of 46·1 years (IQR 36·0-54·1) and 19 692 (84%) were female; 8203 (35%) were assigned to the positive cohort at the start of the analysis period, and 15 121 (65%) assigned to the negative cohort. Total follow-up time was 2 calendar months and 1 106 905 person-days (396 318 vaccinated and 710 587 unvaccinated). Vaccine coverage was 89% on Feb 5, 2021, 94% of whom had BNT162b2 vaccine. Significantly lower coverage was associated with previous infection, gender, age, ethnicity, job role, and Index of Multiple Deprivation score. During follow-up, there were 977 new infections in the unvaccinated cohort, an incidence density of 14 infections per 10 000 person-days; the vaccinated cohort had 71 new infections 21 days or more after their first dose (incidence density of eight infections per 10 000 person-days) and nine infections 7 days after the second dose (incidence density four infections per 10 000 person-days). In the unvaccinated cohort, 543 (56%) participants had typical COVID-19 symptoms and 140 (14%) were asymptomatic on or 14 days before their PCR positive test date, compared with 29 (36%) with typical COVID-19 symptoms and 15 (19%) asymptomatic in the vaccinated cohort. A single dose of BNT162b2 vaccine showed vaccine effectiveness of 70% (95% CI 55-85) 21 days after first dose and 85% (74-96) 7 days after two doses in the study population. INTERPRETATION Our findings show that the BNT162b2 vaccine can prevent both symptomatic and asymptomatic infection in working-age adults. This cohort was vaccinated when the dominant variant in circulation was B1.1.7 and shows effectiveness against this variant. FUNDING Public Health England, UK Department of Health and Social Care, and the National Institute for Health Research.
Collapse
Affiliation(s)
- Victoria Jane Hall
- Public Health England Colindale, London, UK; The National Institute for Health Research Health Protection Research (NIHR) Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK
| | | | - Ayoub Saei
- Public Health England Colindale, London, UK
| | - Nick Andrews
- Public Health England Colindale, London, UK; NIHR Health Protection Research Unit in Immunisation at the London School of Hygiene and Tropical Medicine in partnership with Public Health England, London, UK
| | - Blanche Oguti
- Public Health England Colindale, London, UK; Oxford Vaccine Group, University of Oxford, Oxford, UK
| | - Andre Charlett
- Public Health England Colindale, London, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluation at University of Bristol in partnership with Public Health England, Bristol, UK; NIHR Health Protection Research Unit in Immunisation at the London School of Hygiene and Tropical Medicine in partnership with Public Health England, London, UK
| | | | | | | | - Ana Atti
- Public Health England Colindale, London, UK
| | | | | | | | | | - Meera A Chand
- Public Health England Colindale, London, UK; Guys and St Thomas's Hospital NHS Trust, London, UK
| | | | - Mary Ramsay
- Public Health England Colindale, London, UK; NIHR Health Protection Research Unit in Immunisation at the London School of Hygiene and Tropical Medicine in partnership with Public Health England, London, UK
| | | | - Susan Hopkins
- Public Health England Colindale, London, UK; The National Institute for Health Research Health Protection Research (NIHR) Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK.
| |
Collapse
|
|
12
|
Affiliation(s)
- Jing Wu
- Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI
| | - Ming-Hui Chen
- Department of Statistics, University of Connecticut, Storrs, CT
| | | | - Jun Yan
- Department of Statistics, University of Connecticut, Storrs, CT
| |
Collapse
|
|
13
|
Kuss O, Hoyer A. A proportional risk model for time-to-event analysis in randomized controlled trials. Stat Methods Med Res 2020; 30:411-424. [PMID: 32960748 DOI: 10.1177/0962280220953599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Regression models for continuous, binary, nominal, and ordinal outcomes almost completely rely on parametric models, whereas time-to-event outcomes are mainly analyzed by Cox's Proportional Hazards model, an essentially non-parametric method. This is done despite a long list of disadvantages that have been reported for the hazard ratio, and also for the odds ratio, another effect measure sometimes used for time-to-event modelling. In this paper, we propose a parametric proportional risk model for time-to-event outcomes in a two-group situation. Modelling explicitly a risk instead of a hazard or an odds solves the current interpretational and technical problems of the latter two effect measures. The model further allows for computing absolute effect measures like risk differences or numbers needed to treat. As an additional benefit, results from the model can also be communicated on the original time scale, as an accelerated or a prolongated failure time thus facilitating interpretation for a non-technical audience. Parameter estimation by maximum likelihood, while properly accounting for censoring, is straightforward and can be implemented in each statistical package that allows coding and maximizing a univariate likelihood function. We illustrate the model with an example from a randomized controlled trial on efficacy of a new glucose-lowering drug for the treatment of type 2 diabetes mellitus and give the results of a small simulation study.
Collapse
Affiliation(s)
- Oliver Kuss
- German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Institute for Biometrics and Epidemiology, Düsseldorf, Germany
| | - Annika Hoyer
- Department of Statistics, Ludwig-Maximilians-University Munich, Munich, Germany
| |
Collapse
|
|
14
|
Chapple AG, Peak T, Hemal A. A novel Bayesian continuous piecewise linear log-hazard model, with estimation and inference via reversible jump Markov chain Monte Carlo. Stat Med 2020; 39:1766-1780. [PMID: 32086957 DOI: 10.1002/sim.8511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 12/20/2019] [Accepted: 02/01/2020] [Indexed: 11/10/2022]
Abstract
We present a reversible jump Bayesian piecewise log-linear hazard model that extends the Bayesian piecewise exponential hazard to a continuous function of piecewise linear log hazards. A simulation study encompassing several different hazard shapes, accrual rates, censoring proportion, and sample sizes showed that the Bayesian piecewise linear log-hazard model estimated the true mean survival time and survival distributions better than the piecewsie exponential hazard. Survival data from Wake Forest Baptist Medical Center is analyzed by both methods and the posterior results are compared.
Collapse
Affiliation(s)
- Andrew G Chapple
- Biostatistics Program, Louisiana State University Health Sciences Center, School of Public Health, New Orleans, Louisiana
| | - Taylor Peak
- Department of Urology, Wake Forest Baptist Medical Center, Winston-Salem, North Carolina
| | - Ashok Hemal
- Department of Urology, Wake Forest Baptist Medical Center, Winston-Salem, North Carolina
| |
Collapse
|
|
15
|
Biccler JL, Bøgsted M, Van Aelst S, Verdonck T. Outlier robust modeling of survival curves in the presence of potentially time-varying coefficients. Stat Methods Med Res 2020; 29:2683-2696. [PMID: 32180501 DOI: 10.1177/0962280220910193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In time to event studies, censoring often occurs and models that take this into account are wide-spread. In the presence of outliers, standard estimators of model parameters may be affected such that results and conclusions are not reliable anymore. This in turn also hampers the detection of these outliers due to masking effects. To cope with outliers when using proportional hazard models, we propose to use the Brier score as a loss function. Since the coefficients often vary over time, we focus on the piecewise constant hazard model, which can flexibly model time-varying coefficients if a large number of cut-points is used. To prevent overfitting, we add a penalty term that potentially shrinks time-varying effects to constant effects. By fitting the coefficients of the piecewise constant hazard model using a penalized Brier score loss, we obtain a robust model that can handle time-varying coefficients. Its good performance is illustrated in a simulation study and using two datasets from practice.
Collapse
Affiliation(s)
- Jorne Lionel Biccler
- Department of Haematology, Aalborg University Hospital, Aalborg, Denmark.,Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Martin Bøgsted
- Department of Haematology, Aalborg University Hospital, Aalborg, Denmark.,Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | | | - Tim Verdonck
- Department of Mathematics, KU Leuven, Leuven, Belgium.,Department of Mathematics, University of Antwerp, Antwerp, Belgium
| |
Collapse
|
|
16
|
Cologne J, Kim J, Sugiyama H, French B, Cullings HM, Preston DL, Mabuchi K, Ozasa K. Effect of Heterogeneity in Background Incidence on Inference about the Solid-Cancer Radiation Dose Response in Atomic Bomb Survivors. Radiat Res 2019; 192:388-398. [PMID: 31355713 PMCID: PMC6827345 DOI: 10.1667/rr15127.1] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
A recent analysis of solid cancer incidence in the Life Span Study of atomic bomb survivors (Hiroshima and Nagasaki, Japan) found evidence of a nonlinear, upwardly curving radiation dose response among males but not among females. Further analysis of this new and unexpected finding was necessary. We used two approaches to investigate this finding. In one approach, we excluded individual cancer sites or groups of sites from all solid cancers. In the other approach, we used joint analysis to allow for heterogeneity in background-rate parameters across groups of cancers with dissimilar trends in background rates. Exclusion of a few sites led to the disappearance of curvature among males in the remaining collection of solid cancers; some of these influential sites have unique features in their background age-specific incidence that are not captured by a background-rate model fit to all solid cancers combined. Exclusion of a few sites also led to an appearance of curvature among females. Misspecification of background rates can cause bias in inference about the shape of the dose response, so heterogeneity of background rates might explain at least part of the all solid cancer dose-response difference in curvature between males and females. We conclude that analysis based on all solid cancers as a single outcome is not the optimal method to assess radiation risk for solid cancer in the Life Span Study; joint analysis with suitable choices of cancer groups might be preferable by allowing for background-rate heterogeneity across sites while providing greater power to assess radiation risk than analyses of individual sites.
Collapse
Affiliation(s)
- John Cologne
- Department of Statistics, Radiation Effects Research Foundation, Hiroshima, Japan
| | - Jaeyoung Kim
- Department of Preventive Medicine, College of Medicine, Keimyung University, Daegu, Korea
| | - Hiromi Sugiyama
- Department of Epidemiology, Radiation Effects Research Foundation, Hiroshima, Japan
| | - Benjamin French
- Department of Statistics, Radiation Effects Research Foundation, Hiroshima, Japan
| | - Harry M. Cullings
- Department of Statistics, Radiation Effects Research Foundation, Hiroshima, Japan
| | | | - Kiyohiko Mabuchi
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Kotaro Ozasa
- Department of Epidemiology, Radiation Effects Research Foundation, Hiroshima, Japan
| |
Collapse
|
|
17
|
Hoyer A, Kuss O. Meta-analysis of full ROC curves: Additional flexibility by using semiparametric distributions of diagnostic test values. Res Synth Methods 2019; 10:528-538. [PMID: 31231986 DOI: 10.1002/jrsm.1364] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Revised: 05/10/2019] [Accepted: 06/07/2019] [Indexed: 11/07/2022]
Abstract
Diagnostic test accuracy studies frequently report on sensitivities and specificities for more than one threshold of the diagnostic test under study. Although it is obvious that the information from all thresholds should be used for a meta-analysis, in practice, frequently, only a single pair of sensitivity and specificity is selected. To overcome this disadvantage, we recently proposed a statistical model for the meta-analysis of such full receiver operating characteristic (ROC) curves that uses the relationship between a ROC curve and a bivariate model for interval-censored data. In this model, diagnostic tests values reported by the single studies were assumed to follow a parametric distribution. We propose a generalization of this model that allows for a flexible semiparametric modelling of the underlying distribution of the diagnostic test values by using the idea of piecewise constant hazard modelling. We show the results of a simulation study that indicates that the approach works reasonably well in practice. Finally, we illustrate the model by the example of population-based screening for type 2 diabetes mellitus.
Collapse
Affiliation(s)
- Annika Hoyer
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Oliver Kuss
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Medical Statistics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| |
Collapse
|
|
18
|
Montano-Loza AJ, Hansen BE, Corpechot C, Roccarina D, Thorburn D, Trivedi P, Hirschfield G, McDowell P, Poupon R, Dumortier J, Bosch A, Giostria E, Conti F, Parés A, Reig A, Floreani A, Russo FP, Goet JC, Harms MH, van Buuren H, Van den Ende N, Nevens F, Verhelst X, Donato MF, Malinverno F, Ebadi M, Mason AL. Factors Associated With Recurrence of Primary Biliary Cholangitis After Liver Transplantation and Effects on Graft and Patient Survival. Gastroenterology 2019; 156:96-107.e1. [PMID: 30296431 DOI: 10.1053/j.gastro.2018.10.001] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 09/18/2018] [Accepted: 10/02/2018] [Indexed: 01/05/2023]
Abstract
BACKGROUND & AIMS Primary biliary cholangitis (PBC) frequently recurs after liver transplantation. We evaluated risk factors associated with recurrence of PBC and its effects on patient and graft survival in a multicenter, international cohort (the Global PBC Study Group). METHODS We collected demographic and clinical data from 785 patients (89% female) with PBC who underwent liver transplantation (mean age, 54 ± 9 years) from February 1983 through June 2016, among 13 centers in North America and Europe. Results from biochemical tests performed within 12 months of liver transplantation were analyzed to determine whether markers of cholestasis could identify patients with recurrence of PBC (based on histologic analysis). Patients were followed for a median 6.9 years (interquartile range, 6.1-7.9 years). RESULTS PBC recurred in 22% of patients after 5 years and 36% after 10 years. Age at diagnosis <50 years (hazard ratio [HR], 1.79; 95% CI, 1.36-2.36; P < .001), age at liver transplantation <60 years (HR, 1.39; 95% CI, 1.02-1.90; P = .04), use of tacrolimus (HR, 2.31; 95% CI, 1.72-3.10; P < .001), and biochemical markers of severe cholestasis (bilirubin ≥100 μmol or alkaline phosphatase >3-fold the upper limit of normal) at 6 months after liver transplantation (HR, 1.79; 95% CI, 1.16-2.76; P = .008) were associated with higher risk of PBC recurrence, whereas use of cyclosporine reduced risk of PBC recurrence (HR, 0.62; 95% CI, 0.46-0.82; P = .001). In multivariable Cox regression with time-dependent covariate, recurrence of PBC significantly associated with graft loss (HR, 2.01; 95% CI, 1.16-3.51; P = .01) and death (HR, 1.72; 95% CI, 1.11-2.65; P = .02). CONCLUSIONS Younger age at the time of diagnosis with PBC or at liver transplantation, tacrolimus use, and biochemical markers of cholestasis after liver transplantation are associated with PBC recurrence. PBC recurrence reduces odds of graft and patient survival. Strategies are needed to prevent PBC recurrence or reduce its negative effects.
Collapse
Affiliation(s)
- Aldo J Montano-Loza
- Division of Gastroenterology and Liver Unit, University of Alberta, Edmonton, Alberta, Canada.
| | - Bettina E Hansen
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Christophe Corpechot
- Reference Center for Inflammatory Biliary Diseases, Saint-Antoine Hospital, Paris, France
| | - Davide Roccarina
- University College London Institute for Liver and Digestive Health, Royal Free Hospital, London, United Kingdom
| | - Douglas Thorburn
- University College London Institute for Liver and Digestive Health, Royal Free Hospital, London, United Kingdom
| | - Palak Trivedi
- National Institute for Health Research, Centre for Liver Research, University Hospitals Birmingham, Institute of Immunology and Immunotherapy, University of Birmingham, United Kingdom
| | - Gideon Hirschfield
- National Institute for Health Research, Centre for Liver Research, University Hospitals Birmingham, Institute of Immunology and Immunotherapy, University of Birmingham, United Kingdom; Department of Gastroenterology, University Hospitals Birmingham National Health Service Foundation Trust, Queen Elizabeth Hospital, Birmingham, United Kingdom; Toronto Centre for Liver Disease, University Health Network, University of Toronto, Toronto, Canada
| | - Patrick McDowell
- Department of Gastroenterology, University Hospitals Birmingham National Health Service Foundation Trust, Queen Elizabeth Hospital, Birmingham, United Kingdom
| | - Raoul Poupon
- Reference Center for Inflammatory Biliary Diseases, Saint-Antoine Hospital, Paris, France
| | - Jerome Dumortier
- Liver Transplant Unit, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, France
| | - Alexie Bosch
- Liver Transplant Unit, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, France
| | - Emiliano Giostria
- Hepatology and Gastroenterology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Filomena Conti
- Liver Transplant Unit, Pitié-Salpêtrière Hôpital, Paris France
| | - Albert Parés
- Liver Unit, Hospital Clínic, University of Barcelona, The August Pi i Sunyer Biomedical Research Institute, Biomedical Research Networking Center in Hepatic and Digestive Diseases, Barcelona Spain
| | - Anna Reig
- Liver Unit, Hospital Clínic, University of Barcelona, The August Pi i Sunyer Biomedical Research Institute, Biomedical Research Networking Center in Hepatic and Digestive Diseases, Barcelona Spain
| | - Annarosa Floreani
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | - Francesco Paolo Russo
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | - Jorn C Goet
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Maren H Harms
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Henk van Buuren
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Frederik Nevens
- Division Liver and Biliopancreatic Disorders, Leuven, Belgium
| | - Xavier Verhelst
- Department of Gastroenterology and Hepatology, Ghent University Hospital, Ghent, Belgium
| | - Maria Francesca Donato
- Transplant Hepatology Unit, Division of Gastroenterology and Hepatology, Maggiore Hospital Policlinico, Milan, Italy
| | - Federica Malinverno
- Transplant Hepatology Unit, Division of Gastroenterology and Hepatology, Maggiore Hospital Policlinico, Milan, Italy
| | - Maryam Ebadi
- Division of Gastroenterology and Liver Unit, University of Alberta, Edmonton, Alberta, Canada
| | - Andrew L Mason
- Division of Gastroenterology and Liver Unit, University of Alberta, Edmonton, Alberta, Canada
| |
Collapse
|
|
19
|
Biccler JL, Eloranta S, de Nully Brown P, Frederiksen H, Jerkeman M, Jørgensen J, Jakobsen LH, Smedby KE, Bøgsted M, El-Galaly TC. Optimizing Outcome Prediction in Diffuse Large B-Cell Lymphoma by Use of Machine Learning and Nationwide Lymphoma Registries: A Nordic Lymphoma Group Study. JCO Clin Cancer Inform 2018; 2:1-13. [DOI: 10.1200/cci.18.00025] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Purpose Prognostic models for diffuse large B-cell lymphoma (DLBCL), such as the International Prognostic Index (IPI) are widely used in clinical practice. The models are typically developed with simplicity in mind and thus do not exploit the full potential of detailed clinical data. This study investigated whether nationwide lymphoma registries containing clinical data and machine learning techniques could prove to be useful for building modern prognostic tools. Patients and Methods This study was based on nationwide lymphoma registries from Denmark and Sweden, which include large amounts of clinicopathologic data. Using the Danish DLBCL cohort, a stacking approach was used to build a new prognostic model that leverages the strengths of different survival models. To compare the performance of the stacking approach with established prognostic models, cross-validation was used to estimate the concordance index (C-index), time-varying area under the curve, and integrated Brier score. Finally, the generalizability was tested by applying the new model to the Swedish cohort. Results In total, 2,759 and 2,414 patients were included from the Danish and Swedish cohorts, respectively. In the Danish cohort, the stacking approach led to the lowest integrated Brier score, indicating that the survival curves obtained from the stacking model fitted the observed survival the best. The C-index and time-varying area under the curve indicated that the stacked model (C-index: Denmark [DK], 0.756; Sweden [SE], 0.744) had good discriminative capabilities compared with the other considered prognostic models (IPI: DK, 0.662; SE, 0.661; and National Comprehensive Cancer Network–IPI: DK, 0.681; SE, 0.681). Furthermore, these results were reproducible in the independent Swedish cohort. Conclusion A new prognostic model based on machine learning techniques was developed and was shown to significantly outperform established prognostic indices for DLBCL. The model is available at https://lymphomapredictor.org .
Collapse
Affiliation(s)
- Jorne L. Biccler
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| | - Sandra Eloranta
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| | - Peter de Nully Brown
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| | - Henrik Frederiksen
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| | - Mats Jerkeman
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| | - Judit Jørgensen
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| | - Lasse Hjort Jakobsen
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| | - Karin E. Smedby
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| | - Martin Bøgsted
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| | - Tarec C. El-Galaly
- Jorne L. Biccler, Lasse Hjort Jakobsen, Martin Bøgsted, and Tarec C. El-Galaly, Aalborg University Hospital and Aalborg University, Aalborg; Peter de Nully Brown, Copenhagen University Hospital, Copenhagen; Henrik Frederiksen, Odense University Hospital, Odense; Judit Jørgensen, Aarhus University Hospital, Aarhus; Denmark; Sandra Eloranta and Karin E. Smedby, Karolinska Institutet, Stockholm; Mats Jerkeman, Lund University, Lund; and Karin E. Smedby, Karolinska University Hospital, Solna, Sweden
| |
Collapse
|
|
20
|
Hagar Y, Dignam JJ, Dukic V. Flexible modeling of the hazard rate and treatment effects in long-term survival studies. Stat Methods Med Res 2017; 26:2455-2480. [PMID: 28150523 PMCID: PMC5651995 DOI: 10.1177/0962280216688034] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The effects of predictors on time to failure may be difficult to assess in cancer studies with longer follow-up, as the commonly used assumption of proportionality of hazards holding over an extended period is often questionable. Motivated by a long-term prostate cancer clinical trial, we contrast and compare four powerful methods for estimation of the hazard rate. These four methods allow for varying degrees of smoothness as well as covariates with effects that vary over time. We pay particular attention to an extended multiresolution hazard estimator, which is a flexible, semi-parametric, Bayesian method for joint estimation of predictor effects and the hazard rate. We compare the results of the extended multiresolution hazard model to three other commonly used, comparable models: Aalen's additive model, Kooperberg's hazard regression model, and an extended Cox model. Through simulations and the analysis of a large-scale randomized prostate cancer clinical trial, we use the different methods to examine patterns of biochemical failure and to estimate the time-varying effects of androgen deprivation therapy treatment and other covariates.
Collapse
Affiliation(s)
- Yolanda Hagar
- Department of Applied Mathematics, University of Colorado, CO, USA
| | - James J Dignam
- Department of Public Health Sciences, University of Chicago, IL, USA
| | - Vanja Dukic
- Department of Applied Mathematics, University of Colorado, CO, USA
| |
Collapse
|
|
21
|
Murray TA, Thall PF, Yuan Y, McAvoy S, Gomez DR. Robust treatment comparison based on utilities of semi-competing risks in non-small-cell lung cancer. J Am Stat Assoc 2017; 112:11-23. [PMID: 28943681 PMCID: PMC5607962 DOI: 10.1080/01621459.2016.1176926] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Revised: 01/01/2016] [Indexed: 12/25/2022]
Abstract
A design is presented for a randomized clinical trial comparing two second-line treatments, chemotherapy versus chemotherapy plus reirradiation, for treatment of recurrent non-small-cell lung cancer. The central research question is whether the potential efficacy benefit that adding reirradiation to chemotherapy may provide justifies its potential for increasing the risk of toxicity. The design uses two co-primary outcomes: time to disease progression or death, and time to severe toxicity. Because patients may be given an active third-line treatment at disease progression that confounds second-line treatment effects on toxicity and survival following disease progression, for the purpose of this comparative study follow-up ends at disease progression or death. In contrast, follow-up for disease progression or death continues after severe toxicity, so these are semi-competing risks. A conditionally conjugate Bayesian model that is robust to misspecification is formulated using piecewise exponential distributions. A numerical utility function is elicited from the physicians that characterizes desirabilities of the possible co-primary outcome realizations. A comparative test based on posterior mean utilities is proposed. A simulation study is presented to evaluate test performance for a variety of treatment differences, and a sensitivity assessment to the elicited utility function is performed. General guidelines are given for constructing a design in similar settings, and a computer program for simulation and trial conduct is provided.
Collapse
Affiliation(s)
| | - Peter F Thall
- Department of Biostatistics, MD Anderson Cancer Center
| | - Ying Yuan
- Department of Biostatistics, MD Anderson Cancer Center
| | - Sarah McAvoy
- Department of Radiation Oncology, MD Anderson Cancer Center
| | - Daniel R Gomez
- Department of Radiation Oncology, MD Anderson Cancer Center
| |
Collapse
|
|
22
|
Hagar Y, Hayden M, Wiedinmyer C, Dukic V. Comparison of Models Analyzing a Small Number of Observed Meningitis Cases in Navrongo, Ghana. JOURNAL OF AGRICULTURAL, BIOLOGICAL, AND ENVIRONMENTAL STATISTICS 2017; 22:76-104. [PMID: 38178919 PMCID: PMC10766423 DOI: 10.1007/s13253-016-0270-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Accepted: 11/17/2016] [Indexed: 01/06/2024]
Abstract
The "meningitis belt" is a region in sub-Saharan Africa where annual outbreaks of meningitis occur, with epidemics observed cyclically. While we know that meningitis is heavily dependent on seasonal trends, the exact pathways for contracting the disease are not fully understood and warrant further investigation. Most previous approaches have used large sample inference to assess impacts of weather on meningitis rates. However, in the case of rare events, the validity of such assumptions is uncertain. This work examines the meningitis trends in the context of rare events, with the specific objective of quantifying the underlying seasonal patterns in meningitis rates. We compare three main classes of models: the Poisson generalized linear model, the Poisson generalized additive model, and a Bayesian hazard model extended to accommodate count data and a changing at-risk population. We compare the accuracy and robustness of the models through the bias, RMSE, and standard deviation of the estimators, and also provide a detailed case study of meningitis patterns for data collected in Navrongo, Ghana.
Collapse
Affiliation(s)
- Y Hagar
- Applied Mathematics, University of Colorado at Boulder, Boulder, Colorado, USA
| | - M Hayden
- National Center of Atmospheric Research (NCAR), Boulder, Colorado, USA
| | - C Wiedinmyer
- National Center of Atmospheric Research (NCAR), Boulder, Colorado, USA
| | - V Dukic
- Applied Mathematics, University of Colorado at Boulder, Boulder, Colorado, USA
| |
Collapse
|
|
23
|
Hirsch K, Wienke A, Kuss O. Log-normal frailty models fitted as Poisson generalized linear mixed models. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2016; 137:167-175. [PMID: 28110722 DOI: 10.1016/j.cmpb.2016.09.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Revised: 08/26/2016] [Accepted: 09/09/2016] [Indexed: 06/06/2023]
Abstract
BACKGROUND AND OBJECTIVES The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. METHODS In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. RESULTS The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. CONCLUSIONS The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters.
Collapse
Affiliation(s)
- Katharina Hirsch
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Faculty of Medicine, Martin-Luther-University Halle-Wittenberg, D-06097 Halle (Saale), Germany.
| | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Faculty of Medicine, Martin-Luther-University Halle-Wittenberg, D-06097 Halle (Saale), Germany
| | - Oliver Kuss
- Institute for Biometry and Epidemiology, Leibniz Institute for Diabetes Research, Heinrich Heine University Düsseldorf, D-40225 Duesseldorf, Germany
| |
Collapse
|
|
24
|
Delayed tooth emergence in children infected with human immunodeficiency virus. Oral Surg Oral Med Oral Pathol Oral Radiol 2016; 122:442-7. [PMID: 27554377 DOI: 10.1016/j.oooo.2016.06.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Revised: 06/07/2016] [Accepted: 06/11/2016] [Indexed: 11/23/2022]
Abstract
OBJECTIVE There is limited evidence that early deficits in growth might be reflected in tooth emergence in children infected with human immunodeficiency virus (HIV). The purpose of this study was to prospectively evaluate tooth emergence timing between children positive and negative for HIV in the exposed and unexposed groups, respectively. STUDY DESIGN A longitudinal study of children positive for HIV and HIV-negative household peers, aged 2 to 15 years was conducted between 1993 and 1996. Emergence status was determined for the maxillary and the mandibular permanent first molars and the central and lateral incisors. A multivariable, discrete time, proportional hazards model was fitted to the data. Median age of emergence for each of the six pairs of teeth was calculated using the parameter estimates from the regression model. RESULTS A total of 116 participants (62 HIV positive, 54 HIV negative) completed six examinations over the 36-month study period. Statistical differences in tooth emergence timing were observed for five of the six tooth pairs, with children positive for HIV being less likely to have emergence of the corresponding tooth compared with the children negative for HIV. Age differences for each tooth pair ranged from 0.7 to 1.5 years, with a median emergence age difference of 1.03 years. CONCLUSIONS Delayed tooth emergence of the permanent dentition was observed in children with HIV.
Collapse
|
|
25
|
Swihart BJ, Punjabi NM, Crainiceanu CM. Modeling sleep fragmentation in sleep hypnograms: An instance of fast, scalable discrete-state, discrete-time analyses. Comput Stat Data Anal 2015; 89:1-11. [PMID: 27182097 DOI: 10.1016/j.csda.2015.03.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Methods are introduced for the analysis of large sets of sleep study data (hypnograms) using a 5-state 20-transition-type structure defined by the American Academy of Sleep Medicine. Application of these methods to the hypnograms of 5598 subjects from the Sleep Heart Health Study provide: the first analysis of sleep hypnogram data of such size and complexity in a community cohort with a range of sleep-disordered breathing severity; introduce a novel approach to compare 5-state (20-transition-type) to 3-state (6-transition-type) sleep structures to assess information loss from combining sleep state categories; extend current approaches of multivariate survival data analysis to clustered, recurrent event discrete-state discrete-time processes; and provide scalable solutions for data analyses required by the case study. The analysis provides detailed new insights into the association between sleep-disordered breathing and sleep architecture. The example data and both R and SAS code are included in online supplementary materials.
Collapse
Affiliation(s)
- Bruce J Swihart
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, United States
| | | | - Ciprian M Crainiceanu
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, United States
| |
Collapse
|
|
26
|
Oh C, Holford TR. Age-Period-Cohort approaches to back-calculation of cancer incidence rate. Stat Med 2015; 34:1953-64. [PMID: 25715831 DOI: 10.1002/sim.6464] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2012] [Revised: 01/28/2015] [Accepted: 02/11/2015] [Indexed: 11/10/2022]
Abstract
A compartment model for cancer incidence and mortality is developed in which healthy subjects may develop cancer and subsequently die of cancer or another cause. In order to adequately represent the experience of a defined population, it is also necessary to allow for subjects who are diagnosed at death, as well as subjects who migrate and are subsequently lost to follow-up. Expressions are derived for the number of cancer deaths as a function of the number of incidence cases and vice versa, which allows for the use of mortality statistics to obtain estimates of incidence using survival information. In addition, the model can be used to obtain estimates of cancer prevalence, which is useful for health care planning. The method is illustrated using data on lung cancer among males in Connecticut.
Collapse
Affiliation(s)
- Cheongeun Oh
- Biostatistics, Department of Population Health, New York University School of Medicine, New York, NY, 10016, U.S.A
| | | |
Collapse
|
|
27
|
Argyropoulos C, Unruh ML. Analysis of time to event outcomes in randomized controlled trials by generalized additive models. PLoS One 2015; 10:e0123784. [PMID: 25906075 PMCID: PMC4408032 DOI: 10.1371/journal.pone.0123784] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2014] [Accepted: 03/08/2015] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Randomized Controlled Trials almost invariably utilize the hazard ratio calculated with a Cox proportional hazard model as a treatment efficacy measure. Despite the widespread adoption of HRs, these provide a limited understanding of the treatment effect and may even provide a biased estimate when the assumption of proportional hazards in the Cox model is not verified by the trial data. Additional treatment effect measures on the survival probability or the time scale may be used to supplement HRs but a framework for the simultaneous generation of these measures is lacking. METHODS By splitting follow-up time at the nodes of a Gauss Lobatto numerical quadrature rule, techniques for Poisson Generalized Additive Models (PGAM) can be adopted for flexible hazard modeling. Straightforward simulation post-estimation transforms PGAM estimates for the log hazard into estimates of the survival function. These in turn were used to calculate relative and absolute risks or even differences in restricted mean survival time between treatment arms. We illustrate our approach with extensive simulations and in two trials: IPASS (in which the proportionality of hazards was violated) and HEMO a long duration study conducted under evolving standards of care on a heterogeneous patient population. FINDINGS PGAM can generate estimates of the survival function and the hazard ratio that are essentially identical to those obtained by Kaplan Meier curve analysis and the Cox model. PGAMs can simultaneously provide multiple measures of treatment efficacy after a single data pass. Furthermore, supported unadjusted (overall treatment effect) but also subgroup and adjusted analyses, while incorporating multiple time scales and accounting for non-proportional hazards in survival data. CONCLUSIONS By augmenting the HR conventionally reported, PGAMs have the potential to support the inferential goals of multiple stakeholders involved in the evaluation and appraisal of clinical trial results under proportional and non-proportional hazards.
Collapse
Affiliation(s)
- Christos Argyropoulos
- Department of Internal Medicine, Division of Nephrology, University of New Mexico, Albuquerque, New Mexico, United States of America
- * E-mail:
| | - Mark L. Unruh
- Department of Internal Medicine, Division of Nephrology, University of New Mexico, Albuquerque, New Mexico, United States of America
| |
Collapse
|
|
28
|
Oueslati A, Lopez O. A proportional hazards regression model with change-points in the baseline function. LIFETIME DATA ANALYSIS 2013; 19:59-78. [PMID: 23054240 DOI: 10.1007/s10985-012-9231-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2012] [Accepted: 09/17/2012] [Indexed: 06/01/2023]
Abstract
In this article, we consider a new regression model for counting processes under a proportional hazards assumption. This model is motivated by the need of understanding the evolution of the booking process of a railway company. The main novelty of the approach consists in assuming that the baseline hazard function is piecewise constant, with unknown times of jump (these times of jump are estimated from the data as model parameters). Hence, the parameters of the model can be separated into two different types: parameters that measure the influence of the covariates, and parameters from a multiple change-point model for the baseline. Cox's semiparametric regression can be seen as a limit case of our model. We develop an iterative procedure to estimate the different parameters, and a test procedure that allows to perform change-point detection in the baseline. Our technique is supported by simulation studies and a real data analysis, which show that our model can be a reasonable alternative to Cox's regression model, particularly in the presence of tied event times.
Collapse
Affiliation(s)
- Abdullah Oueslati
- Innovation and Research Department, SNCF, 40 Avenue des Terroirs de France, 75611 Paris Cedex 12, France.
| | | |
Collapse
|
|
29
|
Crowther MJ, Riley RD, Staessen JA, Wang J, Gueyffier F, Lambert PC. Individual patient data meta-analysis of survival data using Poisson regression models. BMC Med Res Methodol 2012; 12:34. [PMID: 22443286 PMCID: PMC3398853 DOI: 10.1186/1471-2288-12-34] [Citation(s) in RCA: 60] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2011] [Accepted: 03/23/2012] [Indexed: 11/21/2022] Open
Abstract
Background An Individual Patient Data (IPD) meta-analysis is often considered the gold-standard for synthesising survival data from clinical trials. An IPD meta-analysis can be achieved by either a two-stage or a one-stage approach, depending on whether the trials are analysed separately or simultaneously. A range of one-stage hierarchical Cox models have been previously proposed, but these are known to be computationally intensive and are not currently available in all standard statistical software. We describe an alternative approach using Poisson based Generalised Linear Models (GLMs). Methods We illustrate, through application and simulation, the Poisson approach both classically and in a Bayesian framework, in two-stage and one-stage approaches. We outline the benefits of our one-stage approach through extension to modelling treatment-covariate interactions and non-proportional hazards. Ten trials of hypertension treatment, with all-cause death the outcome of interest, are used to apply and assess the approach. Results We show that the Poisson approach obtains almost identical estimates to the Cox model, is additionally computationally efficient and directly estimates the baseline hazard. Some downward bias is observed in classical estimates of the heterogeneity in the treatment effect, with improved performance from the Bayesian approach. Conclusion Our approach provides a highly flexible and computationally efficient framework, available in all standard statistical software, to the investigation of not only heterogeneity, but the presence of non-proportional hazards and treatment effect modifiers.
Collapse
Affiliation(s)
- Michael J Crowther
- Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Adrian Building, University Road, Leicester LE1 7RH, UK
| | | | | | | | | | | |
Collapse
|
|
30
|
Whittemore AS. Analyzing Cohort Mortality Data. AM STAT 2012. [DOI: 10.1080/00031305.1985.10479480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
|
|
31
|
Greven S, Dominici F, Zeger S. An Approach to the Estimation of Chronic Air Pollution Effects Using Spatio-Temporal Information. J Am Stat Assoc 2012; 106:396-406. [PMID: 28751799 PMCID: PMC5525028 DOI: 10.1198/jasa.2011.ap09392] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
There is substantial observational evidence that long-term exposure to particulate air pollution is associated with premature death in urban populations. Estimates of the magnitude of these effects derive largely from cross-sectional comparisons of adjusted mortality rates among cities with varying pollution levels. Such estimates are potentially confounded by other differences among the populations correlated with air pollution, for example, socioeconomic factors. An alternative approach is to study covariation of particulate matter and mortality across time within a city, as has been done in investigations of short-term exposures. In either event, observational studies like these are subject to confounding by unmeasured variables. Therefore the ability to detect such confounding and to derive estimates less affected by confounding are a high priority. In this article, we describe and apply a method of decomposing the exposure variable into components with variation at distinct temporal, spatial, and time by space scales, here focusing on the components involving time. Starting from a proportional hazard model, we derive a Poisson regression model and estimate two regression coefficients: the "global" coefficient that measures the association between national trends in pollution and mortality; and the "local" coefficient, derived from space by time variation, that measures the association between location-specific trends in pollution and mortality adjusted by the national trends. Absent unmeasured confounders and given valid model assumptions, the scale-specific coefficients should be similar; substantial differences in these coefficients constitute a basis for questioning the model. We derive a backfitting algorithm to fit our model to very large spatio-temporal datasets. We apply our methods to the Medicare Cohort Air Pollution Study (MCAPS), which includes individual-level information on time of death and age on a population of 18.2 million for the period 2000-2006. Results based on the global coefficient indicate a large increase in the national life expectancy for reductions in the yearly national average of PM2.5. However, this coefficient based on national trends in PM2.5 and mortality is likely to be confounded by other variables trending on the national level. Confounding of the local coefficient by unmeasured factors is less likely, although it cannot be ruled out. Based on the local coefficient alone, we are not able to demonstrate any change in life expectancy for a reduction in PM2.5. We use additional survey data available for a subset of the data to investigate sensitivity of results to the inclusion of additional covariates, but both coefficients remain largely unchanged.
Collapse
Affiliation(s)
- Sonja Greven
- Emmy Noether Junior Research Group Leader, Department of Statistics, Ludwig-Maximilians-Universität München, 80539 Munich, Germany
| | - Francesca Dominici
- Professor, Department of Biostatistics, Harvard University, Boston, MA 02115
| | - Scott Zeger
- Professor, Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205
| |
Collapse
|
|
32
|
Swihart BJ, Caffo BS, Crainiceanu CM, Punjabi NM. Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data. Stat Med 2012; 31:855-70. [PMID: 22241689 DOI: 10.1002/sim.4457] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2010] [Accepted: 10/14/2011] [Indexed: 11/11/2022]
Abstract
Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased with non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear generalized estimating equations (GEE) models for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis.
Collapse
Affiliation(s)
- Bruce J Swihart
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
| | | | | | | |
Collapse
|
|
33
|
Montano-Loza AJ, Wasilenko S, Bintner J, Mason AL. Cyclosporine A protects against primary biliary cirrhosis recurrence after liver transplantation. Am J Transplant 2010; 10:852-858. [PMID: 20132169 DOI: 10.1111/j.1600-6143.2009.03006.x] [Citation(s) in RCA: 68] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Primary biliary cirrhosis (PBC) reoccurs in a proportion of patients following liver transplantation (LT). The aims of our study were to evaluate the risk factors associated with PBC recurrence and determine whether recurrent disease constitutes a negative predictor for survival. One hundred and eight patients receiving LT for end-stage PBC were studied. Recurrent disease was diagnosed in 28 patients (26%). Probability of recurrent PBC at 5 years was 13% and 29% at 10 years with an overall incidence of 3.97 cases per 100 patient years. By univariate Cox analysis use of tacrolimus (HR 6.28, 95% CI, 2.44-16.11, p < 0.001) and mycophenolate mofetil (HR 5.21, 95% CI, 1.89-14.33, p = 0.001) were associated with higher risk of recurrence; whereas use of cyclosporine A (CsA) and azathioprine were associated with reduced risk of recurrence (HR 0.13, 95% CI 0.05-0.35, p < 0.001 and HR 0.27, 95% CI 0.11-0.64, p = 0.003, respectively). In the multivariate Cox analysis, only CsA was independently associated with protection against recurrence (HR 0.17, 95% CI 0.06-0.71, p = 0.02). Five-year probability of survival was 83% and 96%, in patients without and with recurrence (log-rank test, p = 0.3). Although PBC transplant recipients receiving CsA have a lower risk of disease recurrence, the development of recurrent PBC did not impact on long-term patient survival.
Collapse
Affiliation(s)
- A J Montano-Loza
- Division of Gastroenterology & Liver Unit, Zeidler Ledcor Centre, University of Alberta Hospital, Edmonton, Alberta, Canada
| | - S Wasilenko
- Division of Gastroenterology & Liver Unit, Zeidler Ledcor Centre, University of Alberta Hospital, Edmonton, Alberta, Canada
| | - J Bintner
- Division of Gastroenterology & Liver Unit, Zeidler Ledcor Centre, University of Alberta Hospital, Edmonton, Alberta, Canada
| | - A L Mason
- Division of Gastroenterology & Liver Unit, Zeidler Ledcor Centre, University of Alberta Hospital, Edmonton, Alberta, Canada
| |
Collapse
|
|
34
|
Demarqui FN, Loschi RH, Colosimo EA. Estimating the grid of time-points for the piecewise exponential model. LIFETIME DATA ANALYSIS 2008; 14:333-356. [PMID: 18463801 DOI: 10.1007/s10985-008-9086-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2006] [Accepted: 04/15/2008] [Indexed: 05/26/2023]
Abstract
One of the greatest challenges related to the use of piecewise exponential models (PEMs) is to find an adequate grid of time-points needed in its construction. In general, the number of intervals in such a grid and the position of their endpoints are ad-hoc choices. We extend previous works by introducing a full Bayesian approach for the piecewise exponential model in which the grid of time-points (and, consequently, the endpoints and the number of intervals) is random. We estimate the failure rates using the proposed procedure and compare the results with the non-parametric piecewise exponential estimates. Estimates for the survival function using the most probable partition are compared with the Kaplan-Meier estimators (KMEs). A sensitivity analysis for the proposed model is provided considering different prior specifications for the failure rates and for the grid. We also evaluate the effect of different percentage of censoring observations in the estimates. An application to a real data set is also provided. We notice that the posteriors are strongly influenced by prior specifications, mainly for the failure rates parameters. Thus, the priors must be fairly built, say, really disclosing the expert prior opinion.
Collapse
Affiliation(s)
- Fabio N Demarqui
- Departamento de Estatistica, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6.627, Pampulha, 31270-010, Belo Horizonte, MG, Brazil
| | | | | |
Collapse
|
|
35
|
Abstract
Discrete-time survival data typically possess three features: discreteness, ties, and concomitant information, which require appropriate discrete-time models to analyze. In this paper, we first review some existing discrete-time survival models and then extend them to discrete-time cure survival models, which account for the presence of long-term survivors (cured individuals). The maximum likelihood estimation as well as approximate partial likelihood approaches are used to estimate the model parameters. Simulation results are shown to support the suitability of such models for discrete-time survival data with long-term survivors. An example of applications on a set of bladder tumor recurrence data is also presented.
Collapse
Affiliation(s)
- Xiaobing Zhao
- Department of Statistics, East China Normal University, Shanghai, China
| | | |
Collapse
|
|
36
|
Simon GR, Extermann M, Chiappori A, Williams CC, Begum M, Kapoor R, Haura EB, Ismail-Khan R, Schell MJ, Antonia SJ, Bepler G. Phase 2 trial of docetaxel and gefitinib in the first-line treatment of patients with advanced nonsmall-cell lung cancer (NSCLC) who are 70 years of age or older. Cancer 2008; 112:2021-9. [DOI: 10.1002/cncr.23360] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
|
37
|
Naito S, Koga H, Yamaguchi A, Fujimoto N, Hasui Y, Kuramoto H, Iguchi A, Kinukawa N. Prevention of recurrence with epirubicin and lactobacillus casei after transurethral resection of bladder cancer. J Urol 2008; 179:485-90. [PMID: 18076918 DOI: 10.1016/j.juro.2007.09.031] [Citation(s) in RCA: 90] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2007] [Indexed: 10/22/2022]
Abstract
PURPOSE A prospective, randomized, controlled trial was done to evaluate whether oral administration of a preparation of the probiotic agent Lactobacillus casei (Yakult Honsha, Tokyo, Japan) could enhance the prevention of recurrence by intravesical instillation of epirubicin after transurethral resection for superficial bladder cancer. MATERIALS AND METHODS Between August 1999 and December 2002, 207 patients clinically diagnosed with superficial bladder cancer were included as study candidates and underwent transurethral resection, followed by intravesical instillation of 30 mg epirubicin/30 ml saline twice during 1 week. After histological confirmation of superficial bladder cancer they were again included as study participants with 102 randomized to receive treatment with 6 additional intravesical instillations of epirubicin during the 3-month period after transurethral resection (epirubicin group) and 100 randomized to intravesical chemotherapy on the same schedule as the epirubicin group plus oral administration of 3 gm Lactobacillus casei preparation per day for 1 year (epirubicin plus Lactobacillus casei group). Patients were evaluated for intravesical recurrence, disease progression, prognosis and adverse drug reactions. RESULTS The 3-year recurrence-free survival rate was significantly higher in the epirubicin plus Lactobacillus casei group than in the epirubicin group (74.6% vs 59.9%, p = 0.0234), although neither progression-free nor overall survival differed between the groups. The incidence of adverse drug reactions did not significantly differ between the groups and there were no serious adverse drug reactions. CONCLUSIONS Intravesical instillation of epirubicin plus oral administration of Lactobacillus casei preparation is a novel, promising treatment for preventing recurrence after transurethral resection for superficial bladder cancer.
Collapse
Affiliation(s)
- Seiji Naito
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | | | | | | | | | | | | | | | | |
Collapse
|
|
38
|
Barton RR, Turnbull BW. A survey of covariance models for censored life data with an application to recidivism analysis. COMMUN STAT-THEOR M 2007. [DOI: 10.1080/03610927908827797] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
|
|
39
|
Chen QG. The Analysis of Life Table and Follow-up Data with Covariates Using Poisson Regression Model. Biom J 2007. [DOI: 10.1002/bimj.4710300314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
|
|
40
|
Litman HJ, Horton NJ, Murphy JM, Laird NM. Marginal regression models with a time to event outcome and discrete multiple source predictors. LIFETIME DATA ANALYSIS 2006; 12:249-65. [PMID: 17021951 PMCID: PMC1851698 DOI: 10.1007/s10985-006-9013-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2005] [Accepted: 05/15/2006] [Indexed: 05/12/2023]
Abstract
Information from multiple informants is frequently used to assess psychopathology. We consider marginal regression models with multiple informants as discrete predictors and a time to event outcome. We fit these models to data from the Stirling County Study; specifically, the models predict mortality from self report of psychiatric disorders and also predict mortality from physician report of psychiatric disorders. Previously, Horton et al. found little relationship between self and physician reports of psychopathology, but that the relationship of self report of psychopathology with mortality was similar to that of physician report of psychopathology with mortality. Generalized estimating equations (GEE) have been used to fit marginal models with multiple informant covariates; here we develop a maximum likelihood (ML) approach and show how it relates to the GEE approach. In a simple setting using a saturated model, the ML approach can be constructed to provide estimates that match those found using GEE. We extend the ML technique to consider multiple informant predictors with missingness and compare the method to using inverse probability weighted (IPW) GEE. Our simulation study illustrates that IPW GEE loses little efficiency compared with ML in the presence of monotone missingness. Our example data has non-monotone missingness; in this case, ML offers a modest decrease in variance compared with IPW GEE, particularly for estimating covariates in the marginal models. In more general settings, e.g., categorical predictors and piecewise exponential models, the likelihood parameters from the ML technique do not have the same interpretation as the GEE. Thus, the GEE is recommended to fit marginal models for its flexibility, ease of interpretation and comparable efficiency to ML in the presence of missing data.
Collapse
Affiliation(s)
- Heather J Litman
- New England Research Institutes, 9 Galen Street, Watertown, MA 02472, USA.
| | | | | | | |
Collapse
|
|
41
|
Tadesse MG, Ibrahim JG, Gentleman R, Chiaretti S, Ritz J, Foa R. Bayesian error-in-variable survival model for the analysis of GeneChip arrays. Biometrics 2005; 61:488-97. [PMID: 16011696 DOI: 10.1111/j.1541-0420.2005.00313.x] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
DNA microarrays in conjunction with statistical models may help gain a deeper understanding of the molecular basis for specific diseases. An intense area of research is concerned with the identification of genes related to particular phenotypes. The technology, however, is subject to various sources of error that may lead to expression readings that are substantially different from the true transcript levels. Few methods for microarray data analysis have accounted for measurement error in a substantial way and that is the purpose of this investigation. We describe a Bayesian error-in-variable model for the analysis of microarray data from a clinical study of patients with acute lymphoblastic leukemia. We focus in particular on the problem of identifying genes whose expression patterns are associated with duration of remission. This is a question of great practical interest since relapse is a major concern in the treatment of this disease. We explore the effects of ignoring the uncertainty in the expression estimates on the selection and ranking of genes.
Collapse
Affiliation(s)
- Mahlet G Tadesse
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021, USA.
| | | | | | | | | | | |
Collapse
|
|
42
|
Kawamura E, Habu D, Hayashi T, Oe A, Kotani J, Ishizu H, Torii K, Kawabe J, Fukushima W, Tanaka T, Nishiguchi S, Shiomi S. Natural history of major complications in hepatitis C virus-related cirrhosis evaluated by per-rectal portal scintigraphy. World J Gastroenterol 2005; 11:3882-6. [PMID: 15991287 PMCID: PMC4504890 DOI: 10.3748/wjg.v11.i25.3882] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
AIM: To examine the correlation between the porto-systemic hypertension evaluated by portal shunt index (PSI) and life-threatening complications, including hepatocellular carcinoma (HCC), liver failure (Child-Pugh stage progression), and esophagogastric varices.
METHODS: Two hundred and twelve consecutive subjects with HCV-related cirrhosis (LC-C) underwent per-rectal portal scintigraphy. They were allocated into three groups according to their PSI: group I, PSI ≤ 10%; group II, 10%<PSI<30%; and group III, 30% ≤ PSI. Of these, selected 122 Child-Pugh stage A (Child A) subjects were included in analysis (a mean follow-up period of 5.9 ± 5.4 years, range 6 mo-21 years).
RESULTS: No significant correlation between PSI and cumulative probability of HCC incidence was observed. Cumulative probability of Child A to B progression was tended to be higher in group III than in group I, and significantly higher in group III than in group II (62% vs 34%, 62% vs 37%; P = 0.060, <0.01; respectively). Cumulative probability of varices tended to be higher in group III than in group I (31% vs 12%, P = 0.090). On multivariate analyses, significant correlation between PSI and Child A to B progression was observed, and no significant correlation between PSI and HCC incidence or varices progression was observed.
CONCLUSION: Patients with LC-C of Child A will progress to Child B rapidly after their PSI reaches 30% or higher. PSI can be used to predict occult progressive porto-systemic shunting and liver failure non-invasively. It indicates that PSI may play an important role in follow-up of the porto-systemic hypertension gradient for outpatients with LC unlike hepatic venous catheterization.
Collapse
Affiliation(s)
- Etsushi Kawamura
- Department of Nuclear Medicine, Graduate School of Medicine, Osaka City University, 1-4-3, Asahimachi, Abenoku, Osaka 545-8585, Japan.
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
|
43
|
Koga H, Kuroiwa K, Yamaguchi A, Osada Y, Tsuneyoshi M, Naito S. A Randomized Controlled Trial of Short-Term Versus Long-Term Prophylactic Intravesical Instillation Chemotherapy for Recurrence After Transurethral Resection of Ta/T1 Transitional Cell Carcinoma of the Bladder. J Urol 2004; 171:153-7. [PMID: 14665865 DOI: 10.1097/01.ju.0000100386.07370.0a] [Citation(s) in RCA: 40] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE In a prospective randomized controlled study, we investigated the optimal schedule for intravesical instillation of epirubicin for maximizing its effect on prophylaxis and disease progression after transurethral resection of newly diagnosed Ta/T1 bladder cancer. MATERIALS AND METHODS The patients were instilled with epirubicin (30 mg/30 ml in normal saline) within 24 hours after transurethral resection and then randomized into 2 groups after a definite histopathological diagnosis of Ta/T1 bladder cancer. One group of 77 patients received 19 intravesical instillations of epirubicin in the year after transurethral resection (group 1). The second group of 73 patients received 9 intravesical instillations of epirubicin during the 3 months after transurethral resection (group 2). Nonrecurrence rates and toxicity were compared. RESULTS In the followup period, 10 group 1 patients (13.0%) and 23 group 2 patients (31.5%) had recurrent disease. The 3-year nonrecurrence rate was 85.2% in group 1, whereas it was 63.9% in group 2. The nonrecurrence rate of group 1 was significantly higher than that of group 2 throughout the observation period (p = 0.005). The incidence and severity of toxicity were not significantly different between the 2 groups. CONCLUSIONS Our study indicates that long-term instillation of epirubicin is more effective than short-term instillation in preventing recurrence after transurethral resection of Ta/T1 bladder cancer.
Collapse
Affiliation(s)
- Hirofumi Koga
- Department of Urology, Graduate School of Medicine, Kyushu University, Japan
| | | | | | | | | | | |
Collapse
|
|
44
|
Boracchi P, Biganzoli E, Marubini E. Joint modelling of cause-specific hazard functions with cubic splines: an application to a large series of breast cancer patients. Comput Stat Data Anal 2003. [DOI: 10.1016/s0167-9473(02)00122-6] [Citation(s) in RCA: 33] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
|
|
45
|
Abstract
"Several models have been proposed for the analysis of cohort mortality in the presence of competing risks.... This paper describes a maximum likelihood approach to the analysis of follow up data in life table format for the case of two competing risks--a specific cause and its competing complement. The model developed uses a robust survivorship assumption--the piecewise exponential--and takes into account information on time to death and time to withdrawal." (summary in GER)
Collapse
|
|
46
|
Arani RB, Soong SJ, Weiss HL, Wood MJ, Fiddian PA, Gnann JW, Whitley R. Phase specific analysis of herpes zoster associated pain data: a new statistical approach. Stat Med 2001; 20:2429-39. [PMID: 11512133 DOI: 10.1002/sim.851] [Citation(s) in RCA: 55] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Herpes zoster or shingles is a frequent occurrence in both elderly individuals and immunocompromised hosts. The pain associated with herpes zoster is the most debilitating complication of the disease. It can be described as acute pain and post-herpetic neuralgia or zoster associated pain (ZAP). The latter definition encompasses pain from the onset of disease through its resolution and provides a convenient analytic tool for evaluation of antiviral therapy. A heuristic examination of ZAP historical data suggests the existence of three phases of pain resolution: the acute, subacute and chronic phases. The subacute and chronic phases comprise the post-herpetic neuralgia (PHN) stage. Common analytic methods, such as a Kaplan-Meier survival function or a Cox's model, have been used to assess the pain. However, such approaches do not adequately allow for phase comparison. Notably, in the clinical trial setting the comparison of specific treatment effects on the latter stages of pain are of the greatest medical relevance since this is the most debilitating phase of the illness. In order to incorporate the phase-specific information in the modelling of time to cessation of ZAP, we assumed the hazard function was a stepwise constant. Utilizing the full likelihood function, we obtained the maximum likelihood estimate for the transition times (that is, change-points), and other parameters of medical importance. The standard error of the change-point estimates were obtained through a bootstrapping method. The asymptotic properties of the parameter estimates are also discussed. Hence, the rates of pain resolution across all phases can be examined in order to precisely define the existence of multiple phases. In addition, the covariates effect can be examined across phases and populations, thereby allowing us to translate potential efficacy of a standard therapy to different populations. These results can be utilized in the design of clinical trials or in targeting the outcome for a specific phase while controlling for the effect of other variables.
Collapse
Affiliation(s)
- R B Arani
- Biostatistics Unit, Comprehensive Cancer Center, University of Alabama at Birmingham, 35294-3300, USA
| | | | | | | | | | | | | |
Collapse
|
|
47
|
Sakamoto N, Naito S, Kumazawa J, Ariyoshi A, Osada Y, Omoto T, Fujisawa Y, Morita I, Yamashita H. Prophylactic intravesical instillation of mitomycin C and cytosine arabinoside for prevention of recurrent bladder tumors following surgery for upper urinary tract tumors: a prospective randomized study. Int J Urol 2001; 8:212-6. [PMID: 11328420 DOI: 10.1046/j.1442-2042.2001.00286.x] [Citation(s) in RCA: 37] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
BACKGROUND A recurrence of bladder tumors following surgery for transitional cell carcinoma of the upper urinary tract is not rarely observed. A prospective randomized study was conducted to examine the significance of prophylactic intravesical instillation of mitomycin C (MMC) and cytosine arabinoside (Ara-C) to prevent recurrent bladder tumors after surgery for superficial transitional cell carcinoma of the upper urinary tract. METHODS The patients were randomized into an instillation group, who received postoperative intravesical instillation of MMC (20 mg) and Ara-C (200 mg) 28 times over a period of 2 years, and a non-instillation group. The non-recurrence rate was then compared between the groups. RESULTS Of the 27 patients registered, 25 patients (13 with instillation and 12 without instillation) were able to be evaluated, with a median follow-up period of 45 months. The non-recurrence rate of bladder tumors in the instillation group was higher than that in the non-instillation group. Although the difference was not statistically significant, the P-value (P = 0.079) demonstrated a strong trend. When any possible bias was allowed for a multivariate analysis, the difference was almost significant (P = 0.0567). No patients withdrew from this study due to any side-effects. CONCLUSION The postoperative instillation of MMC and Ara-C may be a useful approach for reducing the recurrence of bladder tumors after surgery for upper urinary tract tumors.
Collapse
Affiliation(s)
- N Sakamoto
- Department of Urology, Graduate School of Medical Sciences, Kyushu University, Japan
| | | | | | | | | | | | | | | | | |
Collapse
|
|
48
|
Derendorf H, Lesko LJ, Chaikin P, Colburn WA, Lee P, Miller R, Powell R, Rhodes G, Stanski D, Venitz J. Pharmacokinetic/Pharmacodynamic Modeling in Drug Research and Development. J Clin Pharmacol 2000. [DOI: 10.1177/009127000004001211] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
| | - Lawrence J. Lesko
- Center for Drug Evaluation and Research, Food and Drug Administration (FDA), Rockville, Maryland
| | | | | | - Peter Lee
- Center for Drug Evaluation and Research, Food and Drug Administration (FDA), Rockville, Maryland
| | | | | | | | | | | |
Collapse
|
|
49
|
Karrison TG. Use of Irwin's restricted mean as an index for comparing survival in different treatment groups--interpretation and power considerations. CONTROLLED CLINICAL TRIALS 1997; 18:151-67. [PMID: 9129859 DOI: 10.1016/s0197-2456(96)00089-x] [Citation(s) in RCA: 52] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
In the analysis of survival data from clinical trials and other studies, the censoring generally precludes estimation of the mean survival time. To accommodate censoring, Irwin (1949) proposed, as an alternative, estimation of the mean lifetime restricted to a suitably chosen time T. In this article we consider the use of Irwin's restricted mean as an index for comparing survival in different groups, using as an example published data from a randomized clinical trial in patients with primary biliary cirrhosis. Irwin's method, originally based on the actuarial survival estimator, is extended to incorporate covariates into the analysis through the use of piecewise exponential models. For comparing two survival curves, the logrank test is known to be optimal under proportional hazards alternatives. However, comparison of restricted means may outperform the logrank test in situations involving nonproportional hazard rates. We examine the size and power of these two procedures under various proportional and nonproportional hazards alternatives, with and without covariate adjustment. For survival curves that separate early in time the censored data generalization of the Wilcoxon test is known to exhibit high power, and we examine how the comparison of restricted means performs relative to this procedure also.
Collapse
Affiliation(s)
- T G Karrison
- Department of Medicine, University of Chicago, IL 60637, USA
| |
Collapse
|
|
50
|
|