Retrospective Study Open Access
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. Dec 27, 2023; 15(12): 1307-1314
Published online Dec 27, 2023. doi: 10.4254/wjh.v15.i12.1307
Peri-operative score for elderly patients with resectable hepatocellular carcinoma
Maria Conticchio, Antonella Delvecchio, Riccardo Memeo, Unit of Hepato-Pancreatic-Biliary Surgery, “F. Miulli” Regional General Hospital, Acquaviva Delle Fonti 70021, Italy
Riccardo Inchingolo, Interventional Radiology Unit, Department of Radiology, “F. Miulli” Regional General Hospital, Acquaviva Delle Fonti 75100, Italy
Francesca Ratti, Luca Antonio Aldrighetti, Hepatobiliary Surgery Division, IRCSS San Raffaele Scientific Institute, Milan 20132, Italy
Francesca Ratti, Luca Antonio Aldrighetti, Hepatobiliary Surgery Division, Vita-Salute San Raffaele University, Milan 20132, Italy
Maximiliano Gelli, Département de Chirurgie Viscérale, Gustave Roussy Cancer Campus Grand Paris, Paris 94800, France
Massimiliano Ferdinando Anelli, Unit of Oncologic and Pancreatic Surgery, Hospital University Reina Sofía, Cordoba 14004, Spain
Alexis Laurent, Department of Digestive and Hepatobiliary Surgery, Assistance Publique-Hôpitaux de Paris, Créteil 94000, France
Giulio Cesare Vitali, Service of Abdominal Surgery, Poliambulanza Foundation, Brescia 25124, Italy
Paolo Magistri, Giacomo Assirati, Fabrizio di Benedetto, Hepato-Pancreato-Biliary Surgery and Liver Transplantation Unit, University of Modena and Reggio Emilia, Modena 41121, Italy
Emanuele Felli, Taiga Wakabayashi, Department of Surgery, Institut de Recherche Contre les Cancers de l'Appareil Digestif (IRCAD), Strasbourg 67000, France
Patrick Pessaux, Service de Chirurgie Viscérale et Digestive, Nouvel Hôpital Civil, Unité INSERM U1110, Strasbourg 67000, France
Tullio Piardi, Department of Surgery, Hôpital Robert Debré, Reims 51092, France
Nicola de'Angelis, Assistance Publique-Hôpitaux de Paris, Centre Hospitalier Universitaire Henri Mondor, Paris 94000, France
Javier Briceño, Unit of Hepatobiliary Surgery and Liver Transplantation, Hospital University Reina Sofía, Cordoba 14004, Spain
Antonio Rampoldi, Interventional Radiology Unit, Niguarda Hospital, Milan 20162, Italy
Renè Adam, Daniel Cherqui, Department of Surgery, Centre Hepatobiliaire, Hopital Paul Brousse, Paris 94000, France
ORCID number: Maria Conticchio (0000-0003-3177-5274); Riccardo Inchingolo (0000-0002-0253-5936); Antonella Delvecchio (0000-0002-7759-4340); Francesca Ratti (0000-0002-4710-6940); Maximiliano Gelli (0000-0001-9807-4021); Massimiliano Ferdinando Anelli (0000-0002-0916-1949); Alexis Laurent (0000-0003-1372-0843); Giulio Cesare Vitali (0000-0001-8956-0247); Paolo Magistri (0000-0001-8326-069X); Giacomo Assirati (0000-0001-8240-1497); Emanuele Felli (0000-0002-6510-1457); Taiga Wakabayashi (0000-0002-5074-0205); Patrick Pessaux (0000-0001-5635-7437); Tullio Piardi (0000-0001-6704-3206); Fabrizio di Benedetto (0000-0002-6718-8760); Nicola de'Angelis (0000-0002-1211-4916); Javier Briceño (0000-0001-7027-7898); Antonio Rampoldi (0000-0003-2494-5925); Renè Adam (0000-0003-2169-5449); Daniel Cherqui (0000-0001-5270-2731); Luca Antonio Aldrighetti (0000-0001-7729-2468).
Author contributions: All authors equally contributed to this paper with conception and design of the study, literature review and analysis, drafting and critical revision and editing, and final approval of the final version.
Institutional review board statement: This study does not require approval from the hospital ethics committee.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Riccardo Inchingolo, MD, Director, Doctor, Interventional Radiology Unit, Department of Radiology, “F. Miulli” Regional General Hospital, Strada Per Santeramo, Acquaviva Delle Fonti 75100, Italy. riccardoin@hotmail.it
Received: July 28, 2023
Peer-review started: July 28, 2023
First decision: September 14, 2023
Revised: October 25, 2023
Accepted: December 4, 2023
Article in press: December 4, 2023
Published online: December 27, 2023
Processing time: 150 Days and 0.9 Hours

Abstract
BACKGROUND

Liver resection is the mainstay for a curative treatment for patients with resectable hepatocellular carcinoma (HCC), also in elderly population. Despite this, the evaluation of patient condition, liver function and extent of disease remains a demanding process with the aim to reduce postoperative morbidity and mortality.

AIM

To identify new perioperative risk factors that could be associated with higher 90- and 180-d mortality in elderly patients eligible for liver resection for HCC considering traditional perioperative risk scores and to develop a risk score.

METHODS

A multicentric, retrospective study was performed by reviewing the medical records of patients aged 70 years or older who electively underwent liver resection for HCC; several independent variables correlated with death from all causes at 90 and 180 d were studied. The coefficients of Cox regression proportional-hazards model for six-month mortality were rounded to the nearest integer to assign risk factors' weights and derive the scoring algorithm.

RESULTS

Multivariate analysis found variables (American Society of Anesthesiology score, high rate of comorbidities, Mayo end stage liver disease score and size of biggest lesion) that had independent correlations with increased 90- and 180-d mortality. A clinical risk score was developed with survival profiles.

CONCLUSION

This score can aid in stratifying this population in order to assess who can benefit from surgical treatment in terms of postoperative mortality.

Key Words: Hepatocellular carcinoma; Score; Laparoscopy; Surgical resection; Elderly patients; Multivariate analysis

Core Tip: To support the decision-making process in elderly patient with resectable hepatocellular carcinoma (HCC) and understand who can benefit from surgical treatment in terms of postoperative mortality, we analyzed data from 11 hepato-biliary centers during a 10-years period. A multivariate analysis was performed to find variables (American Society of Anesthesiology score, high rate of comorbidities, Mayo end stage liver disease score and size of biggest lesion) that had independent correlations with increased 90‐ and 180‐d mortality. The evaluation of elderly patients who underwent liver resection for HCC need to be supported by any form of possible analysis of risk.


  • Citation: Conticchio M, Inchingolo R, Delvecchio A, Ratti F, Gelli M, Anelli MF, Laurent A, Vitali GC, Magistri P, Assirati G, Felli E, Wakabayashi T, Pessaux P, Piardi T, di Benedetto F, de'Angelis N, Briceño J, Rampoldi A, Adam R, Cherqui D, Aldrighetti LA, Memeo R. Peri-operative score for elderly patients with resectable hepatocellular carcinoma. World J Hepatol 2023; 15(12): 1307-1314
  • URL: https://www.wjgnet.com/1948-5182/full/v15/i12/1307.htm
  • DOI: https://dx.doi.org/10.4254/wjh.v15.i12.1307

INTRODUCTION

The life expectancy of the population has increased in recent years, and this led to an increased rate of malignant disease in elderly population[1,2]. Hepatocellular carcinoma (HCC) became even more frequent in elderly population[3,4].

According to current guidelines liver resection, ablation and liver transplant are still the mainstay treatments for HCC.

Liver resection presented better overall and disease-free survival than other curative treatments[5]. Despite this, liver resection presented a significant risk postoperative morbidity and mortality.

The approach of liver disease in elderly population needed of an accurate stratification of patients at risk, with the involvement of multidisciplinary preoperative assessment.

The aim of our study was to analyze a population of elderly patients who underwent liver resection for HCC, to investigate the possible presence of risk predictors of postoperative mortality at 90 and 180 d.

MATERIALS AND METHODS
Study Design

A multicentric, retrospective cohort study was carried out by reviewing the medical records of patients aged > 70 years or over undergoing liver resection for HCC from January 2009 to January 2019. We evaluated all preoperative independent variables linked with patients (demographics data), with lesion (number and size, calculated on the preoperative imaging) and preoperative clinical assessment in eligible patients. The primary endpoint was to define 90 d and 180 d mortality rate. The second one was to explore the association among variables and post operative mortality rate.

Statistical Analysis

All analyses were conducted using STATA software, version 16 (Stata-Corp LP, College Station, Tex). Data are reported as means (standard deviations) for continuous variables or numbers (percentages) of patients for categorical variables. Six-month follow-up was chosen to analyze at least 20 fatal events after the surgery. Associations between baseline pre-operative variables with six-month mortality were evaluated using a univariate Cox proportional-hazards model. A score point system was derived from the multivariable Cox proportional-hazards model including univariate predictors with P < 0.05. For a dichotomous risk factor, the estimated regression coefficient was rounded to the nearest integer. For a non-dichotomous risk factor, continuous or discrete, the estimated regression coefficient was multiplied by observed values, rounded to the nearest integer and rescaled to assign zero points to the lowest risk-category. Hazard ratios (HRs) with their 95%CI were reported. The discriminative ability of the models was assessed using the Harrell’s concordance index (C-index). Patients were stratified into three groups of risk by the estimated six-month mortality probability (low-risk < 5%, mid-risk 5%-10%, and high-risk > 10%). The cumulative mortality was displayed using Kaplan-Meier estimates with comparison between curves based on the Log-Rank statistic. The score was internally validated by resampling 1000 bootstrap replications. The bias was calculated as the difference between estimation and the mean of the bootstrap sample. Theoretical profiles were constructed by combining variables of the final model as well as a risk score for death in the period. The cut off of 6 mo as final follow up has been chosen to obtain an appropriate number of events, but its significance was validated at 3 mo. A P value < 0.05 was considered statistically significant.

RESULTS

A total of 429 patients, who underwent liver resection for HCC were included (Table 1). The majority of patients were male (n = 319, 74.3%, and 110 females, 25.7%), aged ≥ 70 years (mean of 75.3 ± 4.1 years); 20 deaths (4.7%) occurred up to 180 d after surgery, as shown in Table 1.

Table 1 Characteristics of samples used to study the variables and deaths 180 d after surgery, n (%).
All
Alive at 180 d
Death at 180 d
HRP value
N
n = 429
N
n = 409
N
n = 20
Age, yr42975.3 ± 4.140975.3 ± 4.12076.9 ± 4.91.52 (0.94-2.47)0.086
Male429319 (74.4)409306 (74.8)2013 (65.0)0.61 (0.24-1.54)0.296
BMI42926.9 ± 3.540926.9 ± 3.62026.9 ± 0.90.97 (0.52-1.82)0.921
ASA score4292.60 ± 0.504092.59 ± 0.50202.90 ± 0.314.49 (1.47-13.74)0.008
Comorbidity > 2429142 (33.1)409129 (31.5)2013 (65.0)3.92 (1.56-9.82)0.004
HBV42980 (18.6)40980 (19.6)200 (0.0)--
HCV429217 (50.6)409210 (51.3)207 (35.0)0.51 (0.2-1.28)0.151
ALD42960 (14.0)40956 (13.7)204 (20.0)1.58 (0.53-4.72)0.415
Others42972 (16.8)40963 (15.4)209 (45.0)4.3 (1.78-10.37)0.001
F4 cirrhosis429178 (41.5)409173 (42.3)205 (25.0)0.46 (0.17-1.27)0.134
CHILD A429370 (86.2)409353 (86.3)2017 (85.0)0.92 (0.27-3.13)0.891
MELD score4297.4 ± 2.14097.4 ± 2.0208.9 ± 2.71.25 (1.09-1.44)0.001
Albumin3823.80 ± 0.603673.80 ± 0.60153.71 ± 0.770.75 (0.33-1.73)0.504
Bilirubin4241.05 ± 0.644041.05 ± 0.64200.99 ± 0.540.81 (0.37-1.76)0.587
Creatinin4251.03 ± 0.364051.02 ± 0.36201.17 ± 0.422.55 (0.9-7.2)0.077
INR4221.20 ± 0.234021.20 ± 0.23201.17 ± 0.280.51 (0.07-3.8)0.508
AST42468 ± 6140569 ± 611948 ± 410.92 (0.85-1)0.045
ALT20151 ± 8018252 ± 821941 ± 480.98 (0.91-1.05)0.540
GGT192145 ± 218174145 ± 21818146 ± 2281 (0.98-1.02)0.958
Platelets425191 ± 92406191 ± 9219177 ± 850.98 (0.93-1.04)0.509
Number of lesions4291.09 ± 0.304091.09 ± 0.31201.05 ± 0.220.54 (0.08-3.77)0.531
Size of biggest lesion (mm)42933 ± 1040932 ± 102037 ± 131.26 (1.01-1.58)0.043
Bilobar lesion4298 (1.9)4098 (2.0)200 (0.0)--
Preop treatment42953 (12.4)40950 (12.2)203 (15.0)1.24 (0.36-4.23)0.732
Major HTC42956 (13.1)40955 (13.4)201 (5.0)0.34 (0.05-2.56)0.297

Two hundred fifty-seven patients, 60% presented an American Society of Anesthesiology (ASA) score III-IV, and the median range of Mayo end stage liver disease (MELD) score was 7 (7.4 ± 2.1). Roughly one third of patients was affected by more of 2 comorbidities (n = 142, 33.1%). Most patients presented a single, unilobar lesion (n = 421, 98%). Most of patients underwent to a minor hepatectomy, while only 54 patients (13.1%) underwent to a major hepatectomy, according to Brisbane classification.

The overall survival curve calculated by the Kaplan–Meier estimator is shown in Figure 1. The ASA score, MELD score, the presence of Comorbidities > 2 and the size of the biggest lesion presented in the univariate analysis an HR greater than 1, as shown in Table 1. They are used as predictor factors in the multivariate analysis (Table 2). Table 3 showed a score system which provides a balanced weight for each variable. Combining the four variables we obtained different profiles of patients with a different preoperative risk, based on personal score, groupable in a low-risk (< 5% at 6 mo), mid-risk (5%-10% at 6 mo) and high-risk class (> 10% at 6 mo) (Table 4 and Figure 2).

Figure 1
Figure 1  Overall mortality.
Figure 2
Figure 2  Profile risk of six-month mortality probability.
Table 2 Multivariate analysis.

Beta
HR
P value
ASA score1.1893.28 (1.04-10.34)0.042
Comorbidity 21.0712.92 (1.14-7.45)0.025
MELD0.2021.22 (1.06-1.41)0.005
Size of largest lesion0.0461.05 (1.01-1.09)0.034
C-index = 0.807---
Table 3 Score point system.

Values
Points
ASA score10
20
32
43
Comorbidity > 2Yes1
MELD< 80
8-121
> 122
Size of largest lesion (mm)≤ 100
10-321
> 322
Max score8
Table 4 Stratification of mortality risk on preoperative score.
Score
Number and prevalence, n (%)
Three-month mortality, %
Six-month mortality, %
≥ 2 vs ≤ 1366 (85.3) vs 63 (14.7)3.3 vs 0.05.7 vs 0.0
≥ 3 vs ≤ 2296 (69.0) vs 133 (31.0)4.1 vs 0.07.0 vs 0.0
≥ 4 vs ≤ 3213 (49.7) vs 216 (50.3)5.3 vs 0.59.3 vs 0.5
≥ 5 vs ≤ 4102 (23.8) vs 327 (76.2)5.0 vs 2.213.6 vs 2.2
≥ 6 vs ≤ 528 (6.5) vs 401 (93.5)11.3 vs 2.322.9 vs 3.6

Figure 2 showed the curves of six-month mortality probability, according to the different profile created on various score. The rate of mortality probability significantly increased from patients with score 2 to patients with score 6: Patients with a score ≥ 2 presented a 5.7% of mortality, patients with a score ≥ 3 presented a 7%, patients with a score ≥ 4 showed a 9.3% of mortality, patients with a score ≥ 5 showed a 13.6%, patients with a score ≥ 6 presented 22.9% of mortality.

We performed an Internal validation using a bootstrapping technique with 1000 resamples, the derived score point system had good discrimination as 0.803 of the Harrell C-Index (bootstrap 95%CI 0.741-0.875). The bias of the estimated risk assigned to 1 point of the score, as the difference between coefficient estimation in the derivation model (0.875) and the mean of the bootstrap sample (0.888), it was negligible (-0.013).

DISCUSSION

The present study observed a population of elderly patients (≥ 70 years) who underwent liver resection for HCC, and it showed that a simple preoperative score, resulting from the evaluation of presence and degree of ASA score, MELD score, the presence of more than 2 comorbidities and the size of the biggest lesion, can predict 90 d and 180 d mortality rate.

The process of ‘aging society’ resulted in an increasing rate of surgical oncological elderly patients and it made necessary to provide an accurate preoperative assessment to optimize the choice of the best possible treatment. Liver resection represented the treatment of choice for resectable HCC, even in elderly population[6-9]. Age itself should not be a contraindication to liver resection in treatment of HCC, but this population needed a more accurate selection and preoperative evaluation of benefits and drawback.

The assessment of liver function needed to be linked with the identification of modifiable and not modifiable risk factors to improve surgical outcomes. There were several predictive of 30 d mortality after liver resection for HCC[10-13]. MELD score was often considered a significant parameter, as well in our study where this score was ranged in 3 degrees with a different impact on final sum. Conversely Lee et al[14] in a nationwide cohort study recognized the Platelet-Albumin-Bilirubin score had an higher sensitivity and specificity than MELD or Albumin-Bilirubin score[15].

With the aim to better explore the concept of ‘frailty’ in this population also the ASA score gained more relevance. In our results an ASA score of 1-2 or 3-4 can weight in a different significantly way on the final score and so have impact on the post operative mortality probability. Not only the evaluation of the degree of pathological physical state, but also the presence of more of 2 comorbidities resulted significant as risk predictor in our score. The limit was represented by not knowing the type of comorbidity which made impossible to optimize the stratification. Preoperative evaluation of the physiological age could be more useful in predicting risk of postoperative morbidity and mortality than chronological age[16,17], but several external validation of comprehensive score are needed.

As previously reported the size of largest tumor was a useful factor to predict prognostic outcomes after liver resection for HCC[13,18,19]. Also our results showed in univariate and multivariate analysis how an increasing size could be a risk factor on postoperative mortality. In the setting of liver disease almost completely represented by a single nodule of HCC, a size > 32 mm could impact on postoperative mortality risk as a MELD score > 12. The idea of the importance of morphological tumor data was yet explored by Mazzaferro[18] with ‘Metroticket paradigm’ before, and ‘Up to7 criteria’ after, more useful in the context of liver transplantation, but it had represented the substrate for comprehensive measures as reported by Tokumitsu et al[12] with its NxS score which provide a cut off value of tumor burden to predict the prognosis following hepatectomies for HCC[12]. Despite this, prognosis of HCC was more complex than other solid tumors because it depended not only from tumor burden but also from liver function reserve.

ASA score, MELD score, the presence of more than 2 comorbidities and the size of the lesion were all non-modifiable factor. Our work underlined how the process of decision making could be delicate in elderly patients with HCC. The association of evaluation of liver (functional and oncological) disease and the physiological age of patients needed to be assessed before surgery[19-20] to better stratifying patients at risk and to implement preoperative and postoperative programs of rehabilitation which could bridge the gap of physiopathological state[21].

However, this study had some limitations. First of all, because of its retrospective nature, there was a possibility of an unavoidable selection bias. Secondly, the surgical procedures included were laparoscopic and open approach without considering their different impact on the postoperative outcomes. In addition, our aim was to evaluate 90 and 180 d mortality but another key point was represented by postoperative complications and their correlations with preoperative and intraoperative data. This could be the focus for future works.

CONCLUSION

In conclusion, our score resulted from granular evaluation of possible risk factors for the postoperative mortality at 90 d and 180 d in elderly patients resected for HCC.

It would be a simple and useful tool to provide a better cognition of patients who could benefit of liver resection and to improve 180 d mortality.

ARTICLE HIGHLIGHTS
Research background

Liver resection represented one of the mainstay treatment for hepatocellular carcinoma (HCC). The approach of liver disease in elderly population needed of an accurate stratification of patients at risk, with the involvement of multidisciplinary preoperative assessment.

Research motivation

Liver resection is burdened by a variable rate of postoperative morbidity and mortality. Elderly patients represented more often the major rate of patients who underwent liver resection for HCC. This aspect makes mandatory an accurate preoperative assessment and a specific evaluation of potential postoperative risk.

Research objectives

The aim of our study was to analyze a population of elderly patients who underwent liver resection for HCC, to investigate the possible presence of risk predictors of postoperative mortality at 90 and 180 d.

Research methods

Associations between baseline pre-operative variables with six-month mortality were evaluated using a unit-variate Cox proportional-hazards model. A score point system was derived from the multi-variable Cox proportional-hazards model.

Research results

The American Society of Anesthesiology (ASA) score, Mayo end stage liver disease score, the presence of comorbidities > 2 and the size of the biggest lesion are included in the stratification of the score. Combining the four variables we obtained different profiles of patients with a different preoperative risk at 6 mo: Low-risk < 5%, mid-risk 5%-10% and high-risk class > 10%.

Research conclusions

This score can aid in stratifying this population in order to assess who can benefit from surgical treatment in terms of postoperative mortality.

Research perspectives

Randomized controlled studies are needed to better explore these results.

Footnotes

Provenance and peer review: Invited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Gastroenterology and hepatology

Country/Territory of origin: Italy

Peer-review report’s scientific quality classification

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P-Reviewer: Fernández-Placencia RM, Peru; Li YW, China S-Editor: Li L L-Editor: A P-Editor: Cai YX

References
1.  Marosi C, Köller M. Challenge of cancer in the elderly. ESMO Open. 2016;1:e000020.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 68]  [Cited by in F6Publishing: 96]  [Article Influence: 12.0]  [Reference Citation Analysis (0)]
2.  Sav A, McMillan SS, Akosile A. Burden of Treatment among Elderly Patients with Cancer: A Scoping Review. Healthcare (Basel). 2021;9.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
3.  Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, Parkin DM, Forman D, Bray F. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015;136:E359-E386.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20108]  [Cited by in F6Publishing: 20120]  [Article Influence: 2235.6]  [Reference Citation Analysis (18)]
4.  Petrick JL, Florio AA, Znaor A, Ruggieri D, Laversanne M, Alvarez CS, Ferlay J, Valery PC, Bray F, McGlynn KA. International trends in hepatocellular carcinoma incidence, 1978-2012. Int J Cancer. 2020;147:317-330.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 315]  [Cited by in F6Publishing: 320]  [Article Influence: 80.0]  [Reference Citation Analysis (0)]
5.  Galle PR, Forner A, Llovet JM, Mazzaferro V, Piscaglia F, Raoul JL, Schirmacher P, Vilgrain V; European Association for the Study of the Liver. EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. J Hepatol. 2018;69:182-236.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3934]  [Cited by in F6Publishing: 5395]  [Article Influence: 899.2]  [Reference Citation Analysis (0)]
6.  Kaibori M, Yoshii K, Yokota I, Hasegawa K, Nagashima F, Kubo S, Kon M, Izumi N, Kadoya M, Kudo M, Kumada T, Sakamoto M, Nakashima O, Matsuyama Y, Takayama T, Kokudo N; Liver Cancer Study Group of Japan. Impact of Advanced Age on Survival in Patients Undergoing Resection of Hepatocellular Carcinoma: Report of a Japanese Nationwide Survey. Ann Surg. 2019;269:692-699.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 42]  [Cited by in F6Publishing: 43]  [Article Influence: 8.6]  [Reference Citation Analysis (0)]
7.  Smith BD, Smith GL, Hurria A, Hortobagyi GN, Buchholz TA. Future of cancer incidence in the United States: burdens upon an aging, changing nation. J Clin Oncol. 2009;27:2758-2765.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1195]  [Cited by in F6Publishing: 1273]  [Article Influence: 84.9]  [Reference Citation Analysis (0)]
8.  Conticchio M, Inchingolo R, Delvecchio A, Laera L, Ratti F, Gelli M, Anelli F, Laurent A, Vitali G, Magistri P, Assirati G, Felli E, Wakabayashi T, Pessaux P, Piardi T, di Benedetto F, de'Angelis N, Briceño J, Rampoldi A, Adam R, Cherqui D, Aldrighetti LA, Memeo R. Radiofrequency ablation vs surgical resection in elderly patients with hepatocellular carcinoma in Milan criteria. World J Gastroenterol. 2021;27:2205-2218.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 8]  [Cited by in F6Publishing: 10]  [Article Influence: 3.3]  [Reference Citation Analysis (1)]
9.  Conticchio M, Delvecchio A, Ratti F, Gelli M, Anelli FM, Laurent A, Vitali GC, Magistri P, Assirati G, Felli E, Wakabayashi T, Pessaux P, Piardi T, Di Benedetto F, de'Angelis N, Javier Briceno DF, Rampoldi AG, Adam R, Cherqui D, Aldrighetti L, Memeo R. Laparoscopic surgery versus radiofrequency ablation for the treatment of single hepatocellular carcinoma ≤3 cm in the elderly: a propensity score matching analysis. HPB (Oxford). 2022;24:79-86.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 11]  [Article Influence: 5.5]  [Reference Citation Analysis (0)]
10.  Takagi K, Umeda Y, Yoshida R, Nobuoka D, Kuise T, Fushimi T, Fujiwara T, Yagi T. Preoperative Controlling Nutritional Status Score Predicts Mortality after Hepatectomy for Hepatocellular Carcinoma. Dig Surg. 2019;36:226-232.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 22]  [Article Influence: 3.7]  [Reference Citation Analysis (0)]
11.  Shen J, Tang L, Zhang X, Peng W, Wen T, Li C, Yang J, Liu G. A Novel Index in Hepatocellular Carcinoma Patients After Curative Hepatectomy: Albumin to Gamma-Glutamyltransferase Ratio (AGR). Front Oncol. 2019;9:817.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 17]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
12.  Tokumitsu Y, Shindo Y, Matsui H, Matsukuma S, Nakajima M, Suzuki N, Takeda S, Wada H, Kobayashi S, Eguchi H, Ueno T, Nagano H. Utility of scoring systems combining the product of tumor number and size with liver function for predicting the prognosis of patients with hepatocellular carcinoma after hepatectomy. Oncol Lett. 2019;18:3903-3913.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 3]  [Article Influence: 0.6]  [Reference Citation Analysis (0)]
13.  Moris D, Shaw BI, Ong C, Connor A, Samoylova ML, Kesseli SJ, Abraham N, Gloria J, Schmitz R, Fitch ZW, Clary BM, Barbas AS. A simple scoring system to estimate perioperative mortality following liver resection for primary liver malignancy-the Hepatectomy Risk Score (HeRS). Hepatobiliary Surg Nutr. 2021;10:315-324.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 2]  [Article Influence: 0.7]  [Reference Citation Analysis (0)]
14.  Lee SK, Song MJ, Kim SH, Park M. Comparing various scoring system for predicting overall survival according to treatment modalities in hepatocellular carcinoma focused on Platelet-albumin-bilirubin (PALBI) and albumin-bilirubin (ALBI) grade: A nationwide cohort study. PLoS One. 2019;14:e0216173.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 16]  [Cited by in F6Publishing: 32]  [Article Influence: 6.4]  [Reference Citation Analysis (0)]
15.  Okinaga H, Yasunaga H, Hasegawa K, Fushimi K, Kokudo N. Short-Term Outcomes following Hepatectomy in Elderly Patients with Hepatocellular Carcinoma: An Analysis of 10,805 Septuagenarians and 2,381 Octo- and Nonagenarians in Japan. Liver Cancer. 2018;7:55-64.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 23]  [Cited by in F6Publishing: 25]  [Article Influence: 4.2]  [Reference Citation Analysis (0)]
16.  Tokumitsu Y, Sakamoto K, Tokuhisa Y, Matsui H, Matsukuma S, Maeda Y, Sakata K, Wada H, Eguchi H, Ogihara H, Fujita Y, Hamamoto Y, Iizuka N, Ueno T, Nagano H. A new prognostic model for hepatocellular carcinoma recurrence after curative hepatectomy. Oncol Lett. 2018;15:4411-4422.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 14]  [Article Influence: 2.3]  [Reference Citation Analysis (0)]
17.  Tokumitsu Y, Tamesa T, Matsukuma S, Hashimoto N, Maeda Y, Tokuhisa Y, Sakamoto K, Ueno T, Hazama S, Ogihara H, Fujita Y, Hamamoto Y, Oka M, Iizuka N. An accurate prognostic staging system for hepatocellular carcinoma patients after curative hepatectomy. Int J Oncol. 2015;46:944-952.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 7]  [Cited by in F6Publishing: 7]  [Article Influence: 0.7]  [Reference Citation Analysis (0)]
18.  Mazzaferro V. Results of liver transplantation: with or without Milan criteria? Liver Transpl. 2007;13:S44-S47.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 53]  [Cited by in F6Publishing: 57]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
19.  McCorkle R, Strumpf NE, Nuamah IF, Adler DC, Cooley ME, Jepson C, Lusk EJ, Torosian M. A specialized home care intervention improves survival among older post-surgical cancer patients. J Am Geriatr Soc. 2000;48:1707-1713.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 233]  [Cited by in F6Publishing: 241]  [Article Influence: 10.0]  [Reference Citation Analysis (0)]
20.  Kaibori M, Matsushima H, Ishizaki M, Kosaka H, Matsui K, Ogawa A, Yoshii K, Sekimoto M. Perioperative Geriatric Assessment as A Predictor of Long-Term Hepatectomy Outcomes in Elderly Patients with Hepatocellular Carcinoma. Cancers (Basel). 2021;13.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 5]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
21.  Melloul E, Hübner M, Scott M, Snowden C, Prentis J, Dejong CH, Garden OJ, Farges O, Kokudo N, Vauthey JN, Clavien PA, Demartines N. Guidelines for Perioperative Care for Liver Surgery: Enhanced Recovery After Surgery (ERAS) Society Recommendations. World J Surg. 2016;40:2425-2440.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 307]  [Cited by in F6Publishing: 381]  [Article Influence: 54.4]  [Reference Citation Analysis (0)]