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Zhang Z, Zeng Y, Liu W. The role of systemic immune-inflammation index in predicting pathological complete response of breast cancer after neoadjuvant therapy and the establishment of related predictive model. Front Oncol 2024; 14:1437140. [PMID: 39555449 PMCID: PMC11564179 DOI: 10.3389/fonc.2024.1437140] [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] [Received: 05/23/2024] [Accepted: 10/17/2024] [Indexed: 11/19/2024] Open
Abstract
Objective To investigate the role of systemic immune-inflammation index (SII) in complete pathological response (pCR) of breast cancer patients after neoadjuvant chemotherapy, and to establish and validate a nomogram for predicting pCR. Methods Breast cancer patients were selected from the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to December 2023. The optimal cut-off value of SII was calculated via ROC curve. The correlation between SII and clinicopathological characteristics was analyzed by Chi-square test. Logistic regression analysis was performed to evaluate the factors that might affect pCR. Based on the results of Logistic regression analysis, a nomogram for predicting pCR was established and validated. Results A total of 112 breast cancer patients were included in this study. 33.04% of the patients achieved pCR after neoadjuvant therapy. Chi-square test showed that SII was significantly correlated with pCR (P=0.001). Logistic regression analysis suggested that Ki-67 (P=0.039), therapy cycle (P<0.001), CEA (P=0.025) and SII (P=0.019) were independent predictors of pCR after neoadjuvant chemotherapy. A nomogram based on Ki-67, therapy cycle, CEA and SII showed a good predictive ability. Conclusion Ki-67, therapy cycle, CEA and SII were independent predictors of pCR of breast cancer after neoadjuvant chemotherapy. The nomogram based on the above positive factors showed a good predictive ability.
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Affiliation(s)
- Ziyue Zhang
- Faculty of Medicine, Debrecen University, Debrecen, Hungary
| | - Yixuan Zeng
- Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Wenbo Liu
- Department of Plastic and Cosmetic Maxillofacial Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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Dai X, Li Y, Wang H, Dai Z, Chen Y, Liu Y, Huang S. Development and validation of nomograms based on pre-/post-operative CEA and CA19-9 for survival predicting in stage I-III colorectal cancer patients after radical resection. Front Oncol 2024; 14:1402847. [PMID: 39464705 PMCID: PMC11502300 DOI: 10.3389/fonc.2024.1402847] [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] [Received: 03/18/2024] [Accepted: 09/24/2024] [Indexed: 10/29/2024] Open
Abstract
Background Carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) are the predominant serum tumour markers (STMs) for predicting the prognosis of colorectal cancer (CRC). The objective of this research is to develop clinical prediction models based on preoperative and postoperative CEA and CA19-9 levels. Methods 1,452 consecutive participants with stage I-III colorectal cancer were included. Kaplan-Meier method, log-rank test, and multivariate COX regression were used to evaluate the significance of preoperative and postoperative STMs. Patients were grouped into a discovery cohort (70%) and a validation cohort (30%). Variables for the nomograms were selected according to the Akaike information criterion (AIC). Subsequently, two clinical predictive models were constructed, evaluated, validated, and then compared with the AJCC 8th TNM stage. Results The overall survival (OS) rate and disease-free survival(DFS) rate declined progressively as the number of positive tumour markers(NPTMs) before and after surgery increased. For both OS and DFS, age, sex, pN stage, and NPTMs before and after surgery were independent prognostic factors, and then clinical prediction models were developed. The Concordance index (C-index), Receiver operating characteristic (ROC) curve, calibration curve, Decision curve analysis (DCA), and risk score stratification all indicated that the models possessed robust predictive efficacy and clinical applicability. The Net reclassification index (NRI) and Integrated discrimination improvement (IDI) indicated that the performance of models was significantly superior to the TNM stage. Conclusion Nomograms based on pre-and postoperative CEA and CA19-9 can accurately predict survival and recurrence for stage I-III CRC patients after radical surgery, and were significantly better than the AJCC 8th TNM stage.
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Affiliation(s)
- Xuan Dai
- Department of Colorectal and Anal Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yifan Li
- Department of Gastrointestinal Surgery, Huaihe Hospital of Henan University, Kaifeng, Henan, China
| | - Haoran Wang
- The First Clinical School, Xinxiang Medical University, Xinxiang, Henan, China
| | - Zhujiang Dai
- Department of Colorectal and Anal Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuanyuan Chen
- Department of Colorectal and Anal Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yun Liu
- Department of Colorectal and Anal Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shiyong Huang
- Department of Colorectal and Anal Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Lee JY, Lee SY. Development of an AI-Based Predictive Algorithm for Early Diagnosis of High-Risk Dementia Groups among the Elderly: Utilizing Health Lifelog Data. Healthcare (Basel) 2024; 12:1872. [PMID: 39337213 PMCID: PMC11431183 DOI: 10.3390/healthcare12181872] [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: 08/19/2024] [Revised: 09/16/2024] [Accepted: 09/17/2024] [Indexed: 09/30/2024] Open
Abstract
BACKGROUND/OBJECTIVES This study aimed to develop a predictive algorithm for the early diagnosis of dementia in the high-risk group of older adults using artificial intelligence technologies. The objective is to create an accessible diagnostic method that does not rely on traditional medical equipment, thereby improving the early detection and management of dementia. METHODS Lifelog data from wearable devices targeting this high-risk group were collected from the AI Hub platform. Various indicators from these data were analyzed to develop a dementia diagnostic model. Machine learning techniques such as Logistic Regression, Random Forest, LightGBM, and Support Vector Machine were employed. Data augmentation techniques were applied to address data imbalance, thereby enhancing the model performance. RESULTS Data augmentation significantly improved the model's accuracy in classifying dementia cases. Specifically, in gait data, the SVM model performed with an accuracy of 0.879. In sleep data, a Logistic Regression was performed, yielding an accuracy of 0.818. This indicates that the lifelog data can effectively contribute to the early diagnosis of dementia, providing a practical solution that can be easily integrated into healthcare systems. CONCLUSIONS This study demonstrates that lifelog data, which are easily collected in daily life, can significantly enhance the accessibility and efficiency of dementia diagnosis, aiding in the effective use of medical resources and potentially delaying disease progression.
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Affiliation(s)
- Ji-Yong Lee
- Center for Sports and Performance Analysis, Korea National Sport University, Seoul 05541, Republic of Korea
| | - So Yoon Lee
- Department of Physical Education, Korea National Sport University, Seoul 05541, Republic of Korea
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Zhang L, Chen YP, Ji M, Ying LQ, Huang CC, Zhou JY, Liu L. Inflammation-related markers and prognosis of alpha-fetoprotein producing gastric cancer. World J Gastrointest Oncol 2024; 16:3875-3886. [PMID: 39350978 PMCID: PMC11438777 DOI: 10.4251/wjgo.v16.i9.3875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Revised: 06/20/2024] [Accepted: 07/15/2024] [Indexed: 09/09/2024] Open
Abstract
BACKGROUND Inflammation-related markers including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI) and prognostic nutritional index (PNI) could reflect tumor immune microenvironment and predict prognosis of cancers. However, it had not been explored in alpha-fetoprotein (AFP) producing gastric cancer (GC). AIM To determine the predictive value of inflammation-related peripheral blood markers including as NLR, PLR, MLR, SII, SIRI and PNI in the prognosis of AFP- producing GC (AFPGC). Besides, this study would also compare the differences in tumor immune microenvironment, clinical characteristics and prognosis between AFPGC and AFP- GC patients to improve the understanding of this disease. METHODS 573 patients enrolled were retrospectively studied. They were divided into AFP+ group (AFP ≥ 20 ng/mL) and AFP- group (AFP < 20 ng/mL), comparing the levels of NLR/PLR/MLR/SII/SIRI/PNI and prognosis. In AFP+ group, the impact of NLR/PLR/MLR/SII/SIRI/PNI and their dynamic changes on prognosis were further explored. RESULTS Compared with AFP- patients, AFP+ patients had higher NLR/PLR/MLR/SII/SIRI and lower PNI levels and poorer overall survival (OS). In the AFP+ group, mortality was significantly lower in the lower NLR/PLR/MLR/SII/SIRI group and higher PNI group. Moreover, the dynamic increase (NLR/PLR/MLR/SII/SIRI) or decrease (PNI) was associated with the rise of mortality within 1 year of follow-up. CONCLUSION Compared with AFP- patients, the level of inflammation-related peripheral blood markers significantly increased in AFP+ patients, which was correlated with OS of AFP+ patients. Also, the gradual increase of SII and SIRI was associated with the risk of death within one year in AFP+ patients. AFPGC should be considered as a separate type and distinguished from AFP- GC because of the difference in tumor immune microenvironment. It requires basic experiments and large clinical samples in the future.
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Affiliation(s)
- Lu Zhang
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China
| | - Yan-Ping Chen
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China
| | - Min Ji
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China
| | - Le-Qian Ying
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China
| | - Chun-Chun Huang
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China
| | - Jing-Yi Zhou
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China
| | - Lin Liu
- Department of Oncology, Zhongda Hospital, Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China
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Zhang W, Hou Z, Zhang L, Hong X, Wang W, Wu X, Xu D, Lu Z, Chen J, Peng J. A log odds of positive lymph nodes-based predictive model effectively forecasts prognosis and guides postoperative adjuvant chemotherapy duration in stage III colon cancer: a multi-center retrospective cohort study. BMC Cancer 2024; 24:1088. [PMID: 39223610 PMCID: PMC11370012 DOI: 10.1186/s12885-024-12875-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Accepted: 08/29/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND The log odds of positive lymph nodes (LODDS) was considered a superior staging system to N stage in colon cancer, yet its value in determining the optimal duration of adjuvant chemotherapy for stage III colon cancer patients has not been evaluated. This study aims to assess the prognostic value of a model that combines LODDS with clinicopathological information for stage III colon cancer patients and aims to stratify these patients using the model, identifying individuals who could benefit from varying durations of adjuvant chemotherapy. METHOD A total of 663 consecutive patients diagnosed with stage III colon cancer, who underwent colon tumor resection between November 2007 and June 2020 at Sun Yat-sen University Cancer Center and Longyan First Affiliated Hospital of Fujian Medical University, were enrolled in this study. Survival outcomes were analyzed using Kaplan-Meier, Cox regression. Nomograms were developed to forecast patient DFS, with the Area Under the Curve (AUC) values of time-dependent Receiver Operating Characteristic (timeROC) and calibration plots utilized to assess the accuracy and reliability of the nomograms. RESULTS Multivariate analysis revealed that perineural invasion (HR = 1.776, 95% CI: 1.052-3.003, P = 0.032), poor tumor differentiation (HR = 1.638, 95% CI: 1.084-2.475, P = 0.019), and LODDS groupings of 2 and 1 (HR = 1.920, 95% CI: 1.297-2.842, P = 0.001) were independent predictors of disease-free survival (DFS) in the training cohort. Nomograms constructed from LODDS, perineural invasion, and poor tumor differentiation demonstrated robust predictive performance for 3-year and 5-year DFS in both training (3-year AUC = 0.706, 5-year AUC = 0.678) and validation cohorts (3-year AUC = 0.744, 5-year AUC = 0.762). Stratification according to this model showed that patients in the high-risk group derived significant benefit from completing 8 cycles of chemotherapy (training cohort, 82.97% vs 67.17%, P = 0.013; validation cohort, 89.49% vs 63.97%, P = 0.030). CONCLUSION The prognostic model, integrating LODDS, pathological differentiation, and neural invasion, demonstrates strong predictive accuracy for stage III colon cancer prognosis. Moreover, stratification via this model offers valuable insights into optimal durations of postoperative adjuvant chemotherapy.
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Affiliation(s)
- Weili Zhang
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicineof Colorectal Surgery, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Zhenlin Hou
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicineof Colorectal Surgery, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Linjie Zhang
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicineof Colorectal Surgery, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Xuanlin Hong
- Medical College, Shaoguan University, Shaoguan, Guangdong, 512005, People's Republic of China
| | - Weifeng Wang
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicineof Colorectal Surgery, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Xiaojun Wu
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicineof Colorectal Surgery, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Dongbo Xu
- Department of Gastrointestinal Surgery, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, 364000, People's Republic of China
| | - Zhenhai Lu
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicineof Colorectal Surgery, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Jianxun Chen
- Department of Gastrointestinal Surgery, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, 364000, People's Republic of China.
| | - Jianhong Peng
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicineof Colorectal Surgery, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China.
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Wang J, Yang Y, Li W, Yang B, Tian Z, Wang G. Application value of laparoscopic surgery in elderly patients (≥ 75 years) with colorectal cancer and prognostic factors influencing 5-year overall survival. Am J Transl Res 2024; 16:2633-2644. [PMID: 39006255 PMCID: PMC11236657 DOI: 10.62347/rdmb8197] [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: 04/09/2024] [Accepted: 05/28/2024] [Indexed: 07/16/2024]
Abstract
OBJECTIVE To investigate the application value of laparoscopic surgery in elderly patients (≥ 75 years) with colorectal cancer, and to identify the prognostic factors influencing the long-term survival in this demographic, and to establish a predictive nomogram model. METHODS A retrospective analysis was conducted on 146 elderly (≥ 75 years old) colorectal cancer patients who underwent radical surgery in Baoji People's Hospital from August 2016 to February 2018, including 55 patients who underwent laparotomy and 91 patients who underwent laparoscopic surgery. Survival curves were plotted using the Kaplan-Meier method, and differences in prognosis were assessed using the Log-rank test. Prognostic impacts of various factors on 5-year survival were analyzed using a Cox proportional hazards model. Significant predictors identified in the Cox model were used to construct a nomogram for predicting survival, which was then validated for accuracy and clinical utility. RESULTS Laparoscopic surgery was associated with shorter hospital stays (P = 0.022), although at a higher cost (P = 0.011). The laparoscopic group also had less intraoperative bleeding (P < 0.001), incision length (P < 0.001), time to first postoperative expectoration (P < 0.001), time to first postoperative feeding (P = 0.002), and time to postoperative peritoneal drainage (P = 0.003) compared to the open surgery group. Additionally, the rate of postoperative wound complications was also lower in the laparoscopic group (P = 0.014). There was no significant difference in the 5-year post-treatment survival between the two groups (P = 0.150). Multifactorial Cox regression analysis revealed that a history of diabetes mellitus (P = 0.037), vascular infiltration (P = 0.026), nerve bundle invasion (P = 0.001), and TNM stage (P = 0.001) were independent prognostic factors affecting the 5-year survival of patients with advanced colorectal cancer. The constructed nomogram showed high predictive accuracy for 1-, 3-, and 5-year survival, with AUC values of 0.91, 0.87, and 0.79, respectively. Calibration curves and decision curve analysis confirmed the model's clinical utility. Risk formula: History of diabetes mellitus * -0.696194503 + Vascular infiltration * -0.769736513 + Nerve bundle invasion * -1.1709777 + TNM staging * 1.201933691. CONCLUSION Laparoscopic surgery can reduce intraoperative trauma and accelerate postoperative recovery in elderly colorectal cancer patients (≥ 75 years) compared to open surgery. The developed nomogram model based on independent prognostic factors such as diabetes history, vascular infiltration, nerve bundle invasion, and TNM staging, facilitates tailored prognostic assessment, enhancing individual patient management.
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Affiliation(s)
- Jia Wang
- Department of General Surgery, Baoji People's Hospital Baoji 721000, Shaanxi, China
| | - Yang Yang
- Department of General Surgery, Baoji People's Hospital Baoji 721000, Shaanxi, China
| | - Wenqing Li
- Department of General Surgery, Baoji People's Hospital Baoji 721000, Shaanxi, China
| | - Bowei Yang
- Department of General Surgery, Baoji People's Hospital Baoji 721000, Shaanxi, China
| | - Zhiqiang Tian
- Department of General Surgery, Baoji People's Hospital Baoji 721000, Shaanxi, China
| | - Gaobo Wang
- Department of General Surgery, Baoji People's Hospital Baoji 721000, Shaanxi, China
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Wu K, Shi Q, Cui G, Xu Y, Yu H, Li Q, Dai W, Li X, Tang C. Effects of T2DM on postoperative outcome of patients with colorectal cancer: a study on the relationship between blood glucose control and survival rate. Am J Cancer Res 2024; 14:1892-1903. [PMID: 38726261 PMCID: PMC11076264 DOI: 10.62347/htrz8589] [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: 12/12/2023] [Accepted: 04/13/2024] [Indexed: 05/12/2024] Open
Abstract
To investigate the impact of type 2 diabetes (T2DM) on the prognosis of colorectal cancer (CRC). The data of 312 patients with CRC treated in the First Affiliated Hospital of Huzhou University from 2012 to 2018 were analyzed retrospectively. The patients were divided into a comorbidity group (n = 62) and a non-comorbidity group (n = 250) according to the presence of T2DM. The baseline data of the two groups were balanced by 1:2 propensity score matching (PSM). Kaplan-Meier analysis and Log-rank test were employed to compare the 5-year overall survival (OS) rates of patients. Cox regression model and inverse probability of treatment weighting (IPTW) were utilized to assess the influence of T2DM on 5-year OS of patients. Based on the results of Cox regression, a nomogram model of T2DM on 5-year OS of patients was constructed. A total of 62 patients in the comorbidity group and 124 patients in the non-comorbidity group were matched using PSM. The 5-year OS rate was lower in the comorbidity group than in the non-comorbidity group (82.23% VS 90.32%, P = 0.038). Subgroup analysis showed that the 5-year overall survival rate was higher in the good blood glucose control group than in the poor blood glucose control group (97.14% VS 62.96%, P<0.01). Multivariate Cox regression showed that the 5-year mortality risk in the comorbidity group was 2.641 times higher than that in the non-comorbidity group (P = 0.026). IPTW analysis showed that the 5-year risk of death in the comorbidity group was 2.458 times that of the non-comorbidity group (P = 0.019). The results showed that poor blood glucose control, BMI≥25 kg/m2, low differentiation, III/IV stage, and postoperative infection were independent factors affecting the 5-year overall survival rate of CRC patients (P<0.05). The ROC curve showed that the AUCs of the constructed model in predicting the 5-year OS in the training set and the testing set were 0.784 and 0.776, respectively. T2DM is identified as a risk factor for reduced 5-year survival among CRC patients, necessitating increased attention for this subgroup, particularly those with poor blood glucose control.
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Affiliation(s)
- Kangzhong Wu
- Department of General Surgery, First Affiliated Hospital of Huzhou UniversityHuzhou 313000, Zhejiang, China
| | - Qian Shi
- Central Laboratory, First Affiliated Hospital of Huzhou UniversityHuzhou 313000, Zhejiang, China
| | - Ge Cui
- Department of Pathology, First Affiliated Hospital of Huzhou UniversityHuzhou 313000, Zhejiang, China
| | - Yongqiang Xu
- Department of General Surgery, First Affiliated Hospital of Huzhou UniversityHuzhou 313000, Zhejiang, China
| | - Hongbin Yu
- Department of General Surgery, First Affiliated Hospital of Huzhou UniversityHuzhou 313000, Zhejiang, China
| | - Qingguo Li
- Department of Colorectal Surgery, Fudan University Shanghai Cancer CenterShanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan UniversityShanghai 200032, China
| | - Weixing Dai
- Department of Colorectal Surgery, Fudan University Shanghai Cancer CenterShanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan UniversityShanghai 200032, China
| | - Xinxiang Li
- Department of Colorectal Surgery, Fudan University Shanghai Cancer CenterShanghai 200032, China
- Department of Oncology, Shanghai Medical College, Fudan UniversityShanghai 200032, China
| | - Chengwu Tang
- Huzhou Key Laboratory of Translational Medicine, First Affiliated Hospital of Huzhou UniversityHuzhou 313000, Zhejiang, China
- Department of Hepatopancreatobiliary Surgery, First Affiliated Hospital of Huzhou UniversityHuzhou 313000, Zhejiang, China
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Zhang H, Wang R, Yu T, Yu D, Song C, Ma B, Li J. A prognostic nomogram integrating carcinoembryonic antigen levels for predicting overall survival in elderly patients with stage II-III colorectal cancer. J Gastrointest Oncol 2024; 15:164-178. [PMID: 38482246 PMCID: PMC10932663 DOI: 10.21037/jgo-23-863] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 01/19/2024] [Indexed: 09/17/2024] Open
Abstract
Background With the aging of the population, colorectal surgeons will have to face more elderly colorectal cancer (CRC) patients in the future. We aim to analyze independent risk factors affecting overall survival in elderly (age ≥65 years) patients with stage II-III CRC and construct a nomogram to predict patient survival. Methods A total of 3,016 elderly CRC patients with stage II-III were obtained from the SEER database. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) regression analyses were used to screen independent prognostic factors, and a survival prediction nomogram was constructed based on the results. The consistency index (C-index), decision curve analysis (DCA), Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to compare the predictive ability between the nomogram and tumor-node-metastasis (TNM) stage system. All patients were classified into high-risk and low-risk groups based on risk scores calculated by nomogram. The Kaplan-Meier method was used to compare the survival differences between two groups. Results The 3- and 5-year area under the curve (AUC) values of the prediction nomogram model were 76.6% and 74.8%, respectively. The AIC, BIC, and C-index values of the nomogram model were 6,032.502, 15,728.72, and 0.707, respectively, which were better than the TNM staging system. Kaplan-Meier survival analysis showed a significant survival difference between high-risk and low-risk groups (P<0.0001). Conclusions We constructed a prediction nomogram for stage II-III elderly CRC patients by combining pre-treatment carcinoembryonic antigen (CEA) levels, which can accurately predict patient survival. This facilitates clinicians to accurately assess patient prognosis and identify high-risk patients to adopt more aggressive and effective treatment strategies.
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Affiliation(s)
- Haijiao Zhang
- Department of General Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Rangrang Wang
- Department of General Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Tianyu Yu
- Department of General Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Dingye Yu
- Department of General Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Changfeng Song
- Department of General Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Bingwei Ma
- Department of General Surgery, Shanghai Tenth People’s Hospital of Tongji University, Tongji University, Shanghai, China
| | - Jiyu Li
- Department of General Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China
- Geriatric Cancer Center, Huadong Hospital Affiliated to Fudan University, Shanghai, China
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Ma R, Gong M, Sun T, Su L, Li K. The prognostic role of γδ T cells in colorectal cancer based on nomogram. Eur J Med Res 2023; 28:467. [PMID: 37884961 PMCID: PMC10604779 DOI: 10.1186/s40001-023-01452-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 10/17/2023] [Indexed: 10/28/2023] Open
Abstract
OBJECTIVE The aim of the present study was to explore the prognostic role of γδ T cells in colorectal cancer, and establish a nomogram for predicting the survival of the patients. METHODS Immunohistochemistry was performed to analyze the infiltration degree of γδ T cells in tumor and normal tissues of colorectal cancer. The relationship between γδ T cells infiltration in tumor tissues and the prognosis of patients with colorectal cancer were determined by Cox regression analysis and survival analysis. R software was used to establish and verify a nomogram for predicting the prognosis of patients with colorectal cancer. RESULTS The degree of γδ T cell infiltration in tumor tissues and normal tissues of CRC was not different (t = 0.35, P = 0.73). However, the infiltration of γδ T cell was related to the survival status of the patients (x2 = 4.88, P = 0.03). Besides, the infiltrating degree of γδ T cells in tumor tissue was obviously related to the prognostic improvement of the patients with colorectal cancer (log-rank P = 0.02) and could reflect the benefit of adjuvant chemotherapy. The nomogram based on tumor diameter, tumor location, AJCC stage, chemotherapy, serum CEA level and γδ T cell infiltration was established and could provide a reference for predicting the survival of colorectal cancer patients. CONCLUSION γδ T cell infiltration degree in tumor tissue was an important factor to improve the outcome of patients with colorectal cancer, and can predict the benefit of adjuvant chemotherapy.
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Affiliation(s)
- Rulan Ma
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
- Biobank, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Meijun Gong
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Tuanhe Sun
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Lin Su
- Biobank, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Kang Li
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China.
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Steeghs JPJM, Offermans K, Jenniskens JCA, Samarska I, Fazzi GE, van den Brandt PA, Grabsch HI. Relationship between the Warburg effect in tumour cells and the tumour microenvironment in colorectal cancer patients: Results from a large multicentre study. Pathol Res Pract 2023; 247:154518. [PMID: 37209573 DOI: 10.1016/j.prp.2023.154518] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 05/06/2023] [Indexed: 05/22/2023]
Abstract
Colorectal cancer (CRC) remains one of the most prevalent and deadly cancers worldwide. The tumour-node-metastasis stage (TNM) is currently the most clinically important tool to predict prognosis for CRC patients. However, patients with the same TNM stage can have different prognoses. The metabolic status of tumour cells (Warburg-subtype) has been proposed as potential prognostic factor in CRC. However, potential biological mechanisms underlying the relationship between Warburg-subtype and prognosis have not been investigated in detail. One potential mechanism could be that the metabolic status of tumour cells affects the tumour microenvironment (TME). Our objective was to investigate the relationship between Warburg-subtypes and the TME. Haematoxylin/Eosin stained tumour tissue microarray cores from 2171 CRC patients from the Netherlands Cohort Study were semi quantitatively assessed for tumour infiltrating lymphocytes (TILs) and relative tumour stroma content. 5745 cores were assessed by putting each core in one of four categories for both TILs and stroma. The relationship between Warburg-subtype, TILs, and tumour stroma content was investigated. The frequency of CRC in the different TIL categories was (n, %): very low (2538, 44.2), low (2463, 42.9), high (722, 12.6), and very high (22, 0.4). The frequency of CRC in the different tumour stroma content categories was: ≤ 25% (2755, 47.9), > 25% ≤ 50% (1553, 27) > 50% ≤ 75% (905, 15.8), and > 75% (532, 9.3). There was neither an association between Warburg-subtype and tumour stroma content (p = 0.229) nor between Warburg-subtype and TILs (p = 0.429). This is the first study to investigate the relationship between Warburg-subtypes and the TME in a large population-based series of CRC patients. Our data suggest that the prognostic value of Warburg-subtypes cannot be directly attributed to differences in TILs or tumour stroma content. Our results require confirmation in an independent series.
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Affiliation(s)
- Jorn P J M Steeghs
- Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands; Department of Pathology, GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Kelly Offermans
- Department of Epidemiology, GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Josien C A Jenniskens
- Department of Epidemiology, GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Iryna Samarska
- Department of Pathology, GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Gregorio E Fazzi
- Department of Pathology, GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Piet A van den Brandt
- Department of Epidemiology, GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands; Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Heike I Grabsch
- Department of Pathology, GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands; Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK.
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11
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Ma R, Yuan D, Mo C, Zhu K, Dang C, Zhang Y, Yin J, Li K. Factors affecting the ORR after neoadjuvant therapy of TP regimen combined with PD-1 inhibitors for esophageal cancer. Sci Rep 2023; 13:6080. [PMID: 37055490 PMCID: PMC10102326 DOI: 10.1038/s41598-023-33038-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 04/06/2023] [Indexed: 04/15/2023] Open
Abstract
The aim of this study is to evaluate the factors affecting the objective response rate (ORR) after neoadjuvant therapy of taxol plus platinum (TP) regimen combined with programmed cell death protein-1 (PD-1) inhibitors for esophageal cancer, and establish a predictive model for forecasting ORR. According to the inclusion and exclusion criteria, consecutive esophageal cancer patients who were treated in the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to February 2022 were enrolled in this study as a training cohort, while patients who were treated in the Shaanxi Provincial Cancer Hospital Affiliated to Medical College of Xi'an Jiaotong University from January 2020 to December 2021 were enrolled as a validation cohort. All patients were treated with resectable locally advanced esophageal cancer and received neoadjuvant chemotherapy combined with immunotherapy. The ORR was defined as the sum of complete pathological response, major pathological response and partial pathological response. Logistic regression analysis was performed to determine the factors that might be related to the ORR of the patients after neoadjuvant therapy. The nomogram based on the result of regression analysis was established and verified to predict the ORR. In this study, 42 patients were included as training cohort and 53 patients were included as validation cohort. Chi-square analysis showed that neutrophil, platelet, platelet-to-lymphocytes ratio (PLR), systemic immune-inflammation index (SII), D-dimer and carcinoembryonic antigen (CEA) between ORR group and non-ORR group were significantly different. Logistic regression analysis showed that aspartate aminotransferase (AST), D-dimer and CEA were independent predictors of ORR after neoadjuvant immunotherapy. Finally, a nomogram was established based on AST, D-dimer and CEA. Internal validation and external validation revealed that the nomogram had a good ability to predict ORR after neoadjuvant immunotherapy. In conclusion, AST, D-dimer and CEA were the independent predictors of ORR after neoadjuvant immunotherapy. The nomogram based on these three indicators showed a good predictive ability.
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Affiliation(s)
- Rulan Ma
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Dawei Yuan
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Caijing Mo
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Kun Zhu
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Chengxue Dang
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Yong Zhang
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Jianhao Yin
- Department of General Surgery, Shaanxi Provincial Cancer Hospital Affiliated to Medical College of Xi'an Jiaotong University, 309 West Yanta Road, Xi'an, 710061, Shaanxi, China.
| | - Kang Li
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China.
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12
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Ma R, Wei W, Ye H, Dang C, Li K, Yuan D. A nomogram based on platelet-to-lymphocyte ratio for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy. BMC Cancer 2023; 23:245. [PMID: 36918796 PMCID: PMC10015959 DOI: 10.1186/s12885-023-10703-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 03/06/2023] [Indexed: 03/16/2023] Open
Abstract
OBJECTIVE To investigate the role of platelet-to-lymphocyte ratio (PLR) in complete pathological response (pCR) of breast cancer (BC) patients after neoadjuvant chemotherapy (NAC), as well as to establish and validate a nomogram for predicting pCR. METHODS BC patients diagnosed and treated in the First Affiliated Hospital of Xi'an Jiaotong University from January 2019 to June 2022 were included. The correlation between pCR and clinicopathological characteristics was analyzed by Chi-square test. Logistic regression analysis was performed to evaluate the factors that might affect pCR. Based on the results of regression analysis, a nomogram for predicting pCR was established and validated. RESULTS A total of 112 BC patients were included in this study. 50.89% of the patients acquired pCR after NAC. Chi-square test showed that PLR was significantly correlated with pCR (X2 = 18.878, P < 0.001). And the PLR before NAC in pCR group was lower than that in Non-pCR group (t = 3.290, P = 0.001). Logistic regression analysis suggested that white blood cell (WBC) [odds ratio (OR): 0.19, 95% confidence interval (CI): 0.04-0.85, P = 0.030)], platelet (PLT) (OR: 0.19, 95%CI: 0.04-0.85, P = 0.030), PLR (OR: 0.18, 95%CI: 0.04-0.90, P = 0.036) and tumor grade (OR: 9.24, 95%CI: 1.89-45.07, P = 0.006) were independent predictors of pCR after NAC. A nomogram prediction model based on WBC, PLR, PLR and tumor grade showed a good predictive ability. CONCLUSION PLR, PLT, WBC and tumor grade were independent predictors of pCR in BC patients after NAC. The nomogram based on the above positive factors showed a good predictive ability.
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Affiliation(s)
- Rulan Ma
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, 710061, Xi'an, China
| | - Wanzhen Wei
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, 710061, Xi'an, China
| | - Haixia Ye
- The Second Clinical College, Department of Medicine, Wuhan University, Hubei, 430071, Wuhan, China
| | - Chengxue Dang
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, 710061, Xi'an, China
| | - Kang Li
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, 710061, Xi'an, China.
| | - Dawei Yuan
- Department of Surgical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, 710061, Xi'an, China.
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13
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A machine learning method for improving liver cancer staging. J Biomed Inform 2023; 137:104266. [PMID: 36494059 DOI: 10.1016/j.jbi.2022.104266] [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: 07/27/2022] [Revised: 11/13/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022]
Abstract
Liver cancer is a common malignant tumor, and its clinical stage is closely related to the clinical treatment and prognosis of patients. Currently, the BCLC staging system revised by the BCLC group of University of Barcelona is the globally recognized staging system for liver cancer. However, with the deepening of related research, the current staging system can no longer fully meet the clinical needs. In this work, we propose a novel machine learning method for constructing an automatic hepatocellular carcinoma staging model that incorporates far more clinical variables than any existing staging system. Our model is based on random survival forests, which generates a unique hazard function for each patient. B-splines are used to embed hazard functions into vectors in low-dimensional space and hierarchical clustering method groups similar patients to form staging cohorts. The resulting staging system significantly outperforms the BCLC system in terms of distinctiveness between patients in different stages.
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Liu LL, Sun JD, Xiang ZL. Survival nomograms for colorectal carcinoma patients with lung metastasis and lung-only metastasis, based on the SEER database and a single-center external validation cohort. BMC Gastroenterol 2022; 22:446. [PMID: 36335295 PMCID: PMC9636633 DOI: 10.1186/s12876-022-02547-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 10/19/2022] [Indexed: 11/06/2022] Open
Abstract
Background We analysed the survival of colorectal cancer (CRC) patients with lung metastasis and lung-only metastasis and determined the risk factors for lung metastasis in CRC patients. Methods Data from colorectal cancer patients with lung metastasis diagnosed from 2010 to 2015 were obtained from the SEER database. Survival was analysed using the Kaplan–Meier method and log-rank test, the Cox proportional hazards regression model, and a competing risk model. The predictive ability of the nomgram was assessed by the concordance index (C-index) and calibration curves. The data from the SEER database for the period 2016–2019 was used as an external validation set. The characteristics of 70 CRC patients treated at Shanghai East Hospital between 2016 and 2019 were retrospectively analysed and data from China was chosen as an external validation set. Results The median survival time for colorectal cancer patients with lung metastasis was 12 months, while this value was 24 months in patients with lung-only metastasis. Among all CRC patients with lung metastasis, age, grade, T stage, N stage, presence of liver, brain or bone metastasis, anatomic site and surgery were related to overall survival (OS). In CRC patients with lung-only metastasis, age, T stage, marital status, chemotherapy and surgery were independent prognostic factors affecting OS. Two nomograms predicting OS were established, with great discrimination (C-index between 0.67 and 0.81) and excellent calibration. Factors including age, race, sex, tumour grade, T stage, N stage, presence of liver, brain or bone metastasis, marital status, insurance status and anatomic location were related to the occurrence of lung metastasis in CRC patients. Conclusion We developed two reliable clinical prediction models among CRC patients to predict the OS rates in patients with lung metastasis and lung metastasis only. Supplementary Information The online version contains supplementary material available at 10.1186/s12876-022-02547-9.
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Construction of a Colorectal Cancer Prognostic Risk Model and Screening of Prognostic Risk Genes Using Machine-Learning Algorithms. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:9408839. [PMID: 36267311 PMCID: PMC9578894 DOI: 10.1155/2022/9408839] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/14/2022] [Accepted: 09/19/2022] [Indexed: 12/09/2022]
Abstract
This study is aimed at constructing a prognostic risk model for colorectal cancer (CRC) using machine-learning algorithms to provide accurate staging and screening of credible prognostic risk genes. We extracted CRC data from GSE126092 and GSE156355 of the Gene Expression Omnibus (GEO) database and datasets from TCGA to analyze the differentially expressed genes (DEGs) using bioinformatics analysis. Among the 330 shared DEGs related to CRC prognosis, we divided the analysis period into different phases and applied univariate COX regression, LASSO, and multivariate COX regression analysis. GO analysis and KEGG analysis revealed that the functions of these DEGs were primarily focused on cell cycle, DNA replication, cell mitosis, and other related functions, and this confirmed our results from a biological perspective. Finally, a prognostic risk model for CRC based on the CHGA, CLU, PLK1, AXIN2, NR3C2, IL17RB, GCG, and AJUBA genes was constructed, and the risk score enabled us to predict the prognosis for CRC. To obtain a comprehensive and accurate model, we used both internal and external evaluations, and the model was able to correctly differentiate patients with CRC into a high-risk group with poor prognosis and a low-risk group with good prognosis. The AUC values of the 3-, 5-, and 10-year survival ROC curves were 0.715, 0.721, and 0.777, respectively, according to the internal evaluation, and the AUC values were 0.606, 0.698, and 0.608, respectively, for the external evaluation using GSE39582 from the GEO database. We determined that CLU, PLK1, and IL17RB could be considered to be independent prognostic factors for CRC with significantly different expression (P < 0.05). Using machine-learning methods, a prognostic risk model comprised of eight genes was constructed. Not only does this model provide improved treatment guidance, but it also provides a novel perspective for analyzing survival conditions at a deeper biological level.
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16
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A Commentary on “Construction of a nomogram to predict overall survival for patients with M1 stage of colorectal cancer: A retrospective cohort study” (Int J Surg 2019;72:96–101). Int J Surg 2022; 106:106914. [DOI: 10.1016/j.ijsu.2022.106914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 09/09/2022] [Indexed: 11/21/2022]
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Cheng P, Chen H, Huang F, Li J, Liu H, Zheng Z, Lu Z. Nomograms predicting cancer-specific survival for stage IV colorectal cancer with synchronous lung metastases. Sci Rep 2022; 12:13952. [PMID: 35977984 PMCID: PMC9385743 DOI: 10.1038/s41598-022-18258-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 08/08/2022] [Indexed: 12/24/2022] Open
Abstract
This study aimed to establish a nomogram for the prediction of cancer-specific survival (CSS) of CRC patients with synchronous LM. The final prognostic nomogram based on prognostic factors was evaluated by concordance index (C-index), time-dependent receiver operating characteristic curves, and calibration curves. In the training and validation groups, the C-index for the nomogram was 0.648 and 0.638, and the AUC was 0.793 and 0.785, respectively. The high quality of the calibration curves in the nomogram models for CSS at 1-, 3-, and 5-year was observed. The nomogram model provided a conventional and useful tool to evaluate the 1-, 3-, and 5-year CSS of CRC patients with synchronous LM.
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Affiliation(s)
- Pu Cheng
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Haipeng Chen
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fei Huang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiyun Li
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hengchang Liu
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhaoxu Zheng
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Zhao Lu
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
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Offermans K, Jenniskens JCA, Simons CCJM, Samarska I, Fazzi GE, van der Meer JRM, Smits KM, Schouten LJ, Weijenberg MP, Grabsch HI, van den Brandt PA. Association between mutational subgroups, Warburg-subtypes, and survival in patients with colorectal cancer. Cancer Med 2022; 12:1137-1156. [PMID: 35785488 PMCID: PMC9883416 DOI: 10.1002/cam4.4968] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/24/2022] [Accepted: 06/11/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Previous research suggests that Warburg-subtypes are related to potentially important survival differences in colorectal cancer (CRC) patients. In the present study, we investigated whether mutational subgroups based on somatic mutations in RAS, BRAF, PIK3CA, and MET, which are known to promote the Warburg-effect, as well as mismatch repair (MMR) status, hold prognostic value in CRC. In addition, we investigated whether Warburg-subtypes provide additional prognostic information, independent of known prognostic factors like TNM stage. METHODS CRC patients (n = 2344) from the prospective Netherlands Cohort Study (NLCS) were classified into eight mutually exclusive mutational subgroups, based on observed mutations in RAS, BRAF, PIK3CA, and MET, and MMR status: All-wild-type + MMRproficient , KRASmut + MMRproficient , KRASmut + PIK3CAmut + MMRproficient , PIK3CAmut + MMRproficient , BRAFmut + MMRproficient , BRAFmut + MMRdeficient , other + MMRproficient , and other + MMRdeficient . Kaplan-Meier curves and Cox regression models were used to investigate associations between mutational subgroups and survival, as well as associations between our previously established Warburg-subtypes and survival within these mutational subgroups. RESULTS Compared to patients with all-wild-type + MMRproficient CRC, patients with KRASmut + MMRproficient , KRASmut + PIK3CAmut + MMRproficient , BRAFmut + MMRproficient , or other + MMRproficient CRC had a statistically significant worse survival (HRCRC-specific ranged from 1.29 to 1.88). In contrast, patients with other + MMRdeficient CRC had the most favorable survival (HRCRC-specific 0.48). No statistically significant survival differences were observed for the Warburg-subtypes within mutational subgroups. CONCLUSION Our results highlight the prognostic potential of mutational subgroups in CRC. Warburg-subtypes did not provide additional prognostic information within these mutational subgroups. Future larger-scale prospective studies are necessary to validate our findings and to examine the potential clinical utility of CRC subtyping based on mutational subgroups.
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Affiliation(s)
- Kelly Offermans
- Department of Epidemiology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands
| | - Josien C. A. Jenniskens
- Department of Epidemiology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands
| | - Colinda C. J. M. Simons
- Department of Epidemiology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands
| | - Iryna Samarska
- Department of Pathology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands
| | - Gregorio E. Fazzi
- Department of Pathology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands
| | - Jaleesa R. M. van der Meer
- Department of Pathology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands
| | - Kim M. Smits
- Department of Pathology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands
| | - Leo J. Schouten
- Department of Epidemiology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands
| | - Matty P. Weijenberg
- Department of Epidemiology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands
| | - Heike I. Grabsch
- Department of Pathology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands,Pathology and Data Analytics, Leeds Institute of Medical Research at St James'sUniversity of LeedsLeedsUK
| | - Piet A. van den Brandt
- Department of Epidemiology, GROW School for Oncology and ReproductionMaastricht University Medical Center+MaastrichtThe Netherlands,Department of Epidemiology, Care and Public Health Research Institute (CAPHRI)Maastricht University Medical Center+MaastrichtThe Netherlands
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Offermans K, Jenniskens JC, Simons CC, Samarska I, Fazzi GE, Smits KM, Schouten LJ, Weijenberg MP, Grabsch HI, van den Brandt PA. Expression of proteins associated with the Warburg-effect and survival in colorectal cancer. JOURNAL OF PATHOLOGY CLINICAL RESEARCH 2021; 8:169-180. [PMID: 34791830 PMCID: PMC8822385 DOI: 10.1002/cjp2.250] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 09/17/2021] [Accepted: 09/30/2021] [Indexed: 12/23/2022]
Abstract
Previous research has suggested that the expression of proteins related to the Warburg effect may have prognostic value in colorectal cancer (CRC), but results remain inconsistent. Our objective was to investigate the relationship between Warburg-subtypes and patient survival in a large population-based series of CRC patients. In the present study, we investigated the expression of six proteins related to the Warburg effect (LDHA, GLUT1, MCT4, PKM2, p53, PTEN) by immunohistochemistry on tissue microarrays (TMAs) from 2,399 incident CRC patients from the prospective Netherlands Cohort Study. Expression levels of the six proteins were combined into a pathway-based sum-score and patients were categorised into three Warburg-subtypes (low/moderate/high). The associations between Warburg-subtypes and CRC-specific and overall survival were investigated using Kaplan-Meier curves and Cox regression models. CRC patients were classified as Warburg-low (n = 695, 29.0%), Warburg-moderate (n = 858, 35.8%) or Warburg-high (n = 841, 35.1%). Patients with Warburg-high CRC had the poorest CRC-specific [hazard ratio (HR) 1.17; 95% CI 1.00-1.38] and overall survival (HR 1.19; 95% CI 1.05-1.35), independent of known prognostic factors. In stratified analyses, this was particularly true for patients with tumour-node-metastasis (TNM) stage III CRC (HRCRC-specific 1.45; 95% CI 1.10-1.92 and HRoverall 1.47; 95% CI 1.15-1.87), and cancers located in the rectum (HRoverall 1.56; 95% CI 1.15-2.13). To our knowledge, this is the first study to identify the prognostic value of immunohistochemistry-based Warburg-subtypes in CRC. Our data suggest that Warburg-subtypes are related to potentially important differences in CRC survival. Further research is required to validate our findings and to investigate the potential clinical utility of these Warburg-subtypes in CRC.
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Affiliation(s)
- Kelly Offermans
- Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Josien Ca Jenniskens
- Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Colinda Cjm Simons
- Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Iryna Samarska
- Department of Pathology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Gregorio E Fazzi
- Department of Pathology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Kim M Smits
- Department of Pathology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Leo J Schouten
- Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Matty P Weijenberg
- Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Heike I Grabsch
- Department of Pathology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands.,Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK
| | - Piet A van den Brandt
- Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands.,Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+, Maastricht, The Netherlands
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Li X, Xiong Z, Xie M, Huang Q, Jin L, Yin S, Chen S, Lan P, Lian L. Prognostic value of the ratio of carcinoembryonic antigen concentration to maximum tumor diameter in patients with stage II colorectal cancer. J Gastrointest Oncol 2021; 12:1470-1481. [PMID: 34532103 DOI: 10.21037/jgo-21-61] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 06/08/2021] [Indexed: 12/16/2022] Open
Abstract
Background Recently, a study from our center indicated that the ratio of preoperative carcinoembryonic antigen (CEA) concentration to maximum tumor diameter (DMAX) may be a prognostic marker for patients with rectal cancer. Therefore, the study aimed to evaluate whether this ratio (CEA/DMAX) has prognostic value for patients with stage II colorectal cancer (CRC). Methods A prospectively maintained database was searched for patients with pathologically confirmed stage II CRC who underwent surgery between January 2010 and March 2019. Patients were stratified according to the mean CEA/DMAX value into low and high CEA/DMAX groups. Kaplan-Meier, univariable, and multivariable Cox regression analyses were used to evaluate whether the CEA/DMAX could predict overall survival (OS) and disease-free survival (DFS). Nomograms were constructed in terms of the results of multivariable Cox regression analyses. Results The study included 2,499 patients with stage II CRC. The mean CEA/DMAX value was 2.33 (ng/mL per cm). Kaplan-Meier analyses revealed that, relative to the low CEA/DMAX group, the high CEA/DMAX group had significantly poorer OS (67.31% vs. 85.02%, P<0.001) and DFS (61.41% vs. 77.10%, P<0.001). The multivariable Cox regression analysis revealed that CEA/DMAX independently predicted OS (hazard ratio: 2.58, 95% confidence interval: 1.51-4.38, P<0.001) and DFS (hazard ratio: 1.97, 95% confidence interval: 1.38-2.83, P<0.001). Two simple-to-use nomograms comprising CEA/DMAX, age, T stage, and lymphovascular invasion were developed to predict 1-, 3-, and 5-year rates of OS and DFS among patients with stage II CRC. The nomograms had good performance based on the concordance index, receiver operating characteristic (ROC) curve analysis, and calibration curves. Subgroup analyses further confirmed that a high CEA/DMAX was associated with poor OS and DFS among patients with stage II colon cancer and among patients with stage II rectal cancer (both P<0.05). Conclusions Among patients with stage II CRC, a high CEA/DMAX independently predicted poor OS and DFS, and the predictive abilities were also observed in subgroup analyses of patients with stage II colon cancer or rectal cancer. Furthermore, we developed two nomograms that had good accuracy for predicting the prognosis of stage II CRC.
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Affiliation(s)
- Xianzhe Li
- Department of Colorectal Surgery, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zhizhong Xiong
- Department of Colorectal Surgery, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Minghao Xie
- Department of Colorectal Surgery, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Qunsheng Huang
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Longyang Jin
- Department of Colorectal Surgery, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shi Yin
- Department of Colorectal Surgery, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shuanggang Chen
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Ping Lan
- Department of Colorectal Surgery, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Lei Lian
- Department of Colorectal Surgery, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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21
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Zhu J, Hao J, Ma Q, Shi T, Wang S, Yan J, Chen R, Xu D, Jiang Y, Zhang J, Li J. A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme. Front Oncol 2021; 11:661040. [PMID: 33937076 PMCID: PMC8085421 DOI: 10.3389/fonc.2021.661040] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 03/22/2021] [Indexed: 12/24/2022] Open
Abstract
Background Emerging evidence shows that serum tumor biomarkers (TBs) and log odds of positive lymph node scheme (LODDS) are closely associated with the prognosis of colorectal cancer (CRC) patients. The aim of our study is to validate the predictive value of TBs and LODDS clinically and to develop a robust prognostic model to predict the overall survival (OS) of patients with CRC. Methods CRC patients who underwent radical resection and with no preoperative chemotherapy were enrolled in the study. The eligible population were randomized into training (70%) and test (30%) cohorts for the comprehensive evaluation of the prognostic model. Clinical implications of serum biomarkers and LODDS were identified by univariate and multivariate Cox proportion regression analysis. The predictive ability and discriminative performance were evaluated by Kaplan–Meier (K–M) curves and receiver operating characteristic (ROC) curves. Clinical applicability of the prognostic model was assessed by decision curve analysis (DCA), and the corresponding nomogram was constructed based on the above factors. Results A total of 1,202 eligible CRC patients were incorporated into our study. Multivariable COX analysis demonstrated that CA199 (HR = 1.304), CA125 (HR = 1.429), CEA (HR = 1.307), and LODDS (HR = 1.488) were independent risk factors for OS (all P < 0.0001). K–M curves showed that the high-risk group possessed a shorter OS than the low-risk counterparts. The area under curves (AUCs) of the model for 1-, 3- and 5-year OS were 86.04, 78.70, and 76.66% respectively for the train cohort (80.35, 77.59, and 74.26% for test cohort). Logistic DCA and survival DCA confirmed that the prognostic model displayed more clinical benefits than the conventional AJCC 8th TNM stage and CEA model. The nomograms were built accordingly, and the calibration plot for the probability of survival at 3- or 5-years after surgery showed an optimal agreement between prediction and actual observation. Conclusions Preoperative serum TBs and LODDS have significant clinical implications for CRC patients. A novel prognostic model incorporating common TBs (CA199, CA125, and CEA) and LODDS displayed better predictive performance than both single factor and the TNM classification. A novel nomogram incorporating TBs and LODDS could individually predict OS in patients with CRC.
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Affiliation(s)
- Jun Zhu
- State Key Laboratory of Cancer Biology, Institute of Digestive Diseases, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Jun Hao
- Department of Experiment Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Qian Ma
- School of Clinical Medicine, Xi'an Medical University, Xi'an, China
| | - Tingyu Shi
- Health Company, Airborne Special Operations Brigade Support Battalion, Xiaogan, China
| | - Shuai Wang
- State Key Laboratory of Cancer Biology, Institute of Digestive Diseases, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Jingchuan Yan
- Department of Basic Medicine, The Fourth Military Medical University, Xi'an, China
| | - Rujie Chen
- State Key Laboratory of Cancer Biology, Institute of Digestive Diseases, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Dong Xu
- Department of Experiment Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yu Jiang
- Department of Experiment Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Jian Zhang
- State Key Laboratory of Cancer Biology, Department of Biochemistry and Molecular Biology, The Fourth Military Medical University, Xi'an, China
| | - Jipeng Li
- State Key Laboratory of Cancer Biology, Institute of Digestive Diseases, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
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Fan S, Cui X, Liu C, Li X, Zheng L, Song Q, Qi J, Ma W, Ye Z. CT-Based Radiomics Signature: A Potential Biomarker for Predicting Postoperative Recurrence Risk in Stage II Colorectal Cancer. Front Oncol 2021; 11:644933. [PMID: 33816297 PMCID: PMC8017337 DOI: 10.3389/fonc.2021.644933] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 02/24/2021] [Indexed: 12/27/2022] Open
Abstract
Objective: To evaluate whether a radiomics signature could improve stratification of postoperative risk and prediction of chemotherapy benefit in stage II colorectal cancer (CRC) patients. Material and Methods: This retrospective study enrolled 299 stage II CRC patients from January 2010 to December 2015. Based on preoperative portal venous-phase CT scans, radiomics features were generated and selected to build a radiomics score (Rad-score) using the Least Absolute Shrinkage and Selection Operator (LASSO) method. The minority group was balanced by the synthetic minority over-sampling technique (SMOTE). Predictive models were built with the Rad-score and clinicopathological factors, and the area under the curve (AUC) was used to evaluate their performance. A nomogram was also constructed for predicting 3-year disease-free survival (DFS). The performance of the nomogram was assessed with a concordance index (C-index) and calibration plots. Results: Overall, 114 features were selected to construct the Rad-score, which was significantly associated with the 3-year DFS. Multivariate analysis demonstrated that the Rad-score, CA724 level, mismatch repair status, and perineural invasion were independent predictors of recurrence. Results showed that the Rad-score can classify patients into high-risk and low-risk groups in the training cohort (AUC 0.886) and the validation cohort (AUC 0.874). On this basis, a nomogram that integrated the Rad-score and clinical variables demonstrated superior performance (AUC 0.954, 0.906) than the clinical model alone (AUC 0.765, 0.705) in the training and validation cohorts, respectively. The C-index of the nomogram was 0.872, and the performance was acceptable. Conclusion: Our radiomics-based model can reliably predict recurrence risk in stage II CRC patients and potentially provide complementary prognostic value to the traditional clinicopathological risk factors for better identification of patients who are most likely to benefit from adjuvant therapy. The proposed nomogram promises to be an effective tool for personalized postoperative surveillance for stage II CRC patients.
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Affiliation(s)
- Shuxuan Fan
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Xiaonan Cui
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Chunli Liu
- School of Electronics and Information Engineering, TianGong University, Tianjin, China
| | - Xubin Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Lei Zheng
- Department of Colorectal Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Qian Song
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jin Qi
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center, Tampa, FL, United States
| | - Wenjuan Ma
- Department of Breast Imaging, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
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