Management of Incidentally Detected Gallbladder Cancer After Cholecystectomy

Søreide, Kjetil

doi:10.1007/978-981-19-6442-8_8

Cited by 2 publications

(1 citation statement)

References 133 publications

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“…Key contributing factors include gallstones, large gallbladder polyps, obesity, advanced age, female sex, hereditary factors, exposure to speci c toxins, and certain microbial infections 1 . Most GBC cases are incidentally found during cholecystectomy for gallstones, with approximately 0.25-0.89% of cholecystectomy specimens revealing GBC upon pathological examination 1,10 . Curative resection remains the main therapeutic approach for early stage tumors and is the primary means of achieving long-term survival.…”

Section: Introductionmentioning

confidence: 99%

Novel Multi-factor Predictive Model for Postoperative Survival in Gallbladder Cancer: A Multi-Center Study

Deng,

Xing,

et al. 2024

Preprint

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Background and study purpose: Gallbladder cancer (GBC) is a highly aggressive malignancy, and surgery is the primary curative option. However, postoperative survival of patients with GBC remains limited. This study aimed to develop a practical model for predicting the postoperative overall survival (OS) of patients with GBC. The model aims to guide surgical decisions and benefit-risk assessments, addressing an unmet need in current practice. Methods A total of 287 patients from three medical institutions were analyzed. Univariate Cox regression analysis was used to screen for prognostic factors. Bidirectional stepwise multivariate Cox regression analysis was used for the feature selection. A nomogram was constructed to predict 1-, 3-, and 5-year postoperative survival rates. The predictive performance of the nomogram was assessed using Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration curves. Kaplan-Meier curves and log-rank tests were used to compare survival between the high-risk and low-risk groups determined by the nomogram. Decision curves were used to evaluate the clinical benefits of the nomograms. After training in one institution, internal and external validation were performed in the other two institutions to assess the reliability of the nomogram. Results Eight factors were selected via stepwise regression: TNM stage, serum carbohydrate antigen 125 (CA125), carbohydrate antigen 199 (CA199), R0 resection, body mass index (BMI), serum albumin, age-adjusted Charlson Comorbidity Index (aCCI), and serum platelet count. The C-index values were 0.770 and 0.757 before and after bootstrap resampling, respectively. The time-dependent C-index consistently exceeded 0.70 from 6 months to 5 years postoperatively, significantly outperforming TNM staging and CA199 levels. Time-dependent ROC analysis showed an area under the curve (AUC) of over 75% when predicting 1-, 3-, and 5-year postoperative survival. The calibration curves demonstrated good concordance between the predicted and observed 1-, 3-, and 5-year postoperative survival rates. The high-risk group identified by the nomogram exhibited significantly better survival than the low-risk group in both the overall population and in late-stage patients. Decision curves indicated the superior clinical benefits of the novel model compared to TNM staging and CA199 levels. The model performance in the validation process was comparable to that in the training process, demonstrating good reliability. Conclusions Our innovative multi-factor nomogram exhibits excellent discriminative and predictive efficacy, along with robust generalizability. The nomogram model has the potential to be a high-quality tool for forecasting postoperative survival in GBC, aiding clinical decision-making.

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Section: Introductionmentioning

confidence: 99%

Novel Multi-factor Predictive Model for Postoperative Survival in Gallbladder Cancer: A Multi-Center Study

Deng,

Xing,

et al. 2024

Preprint

View full text Add to dashboard Cite

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Novel multifactor predictive model for postoperative survival in gallbladder cancer: a multi-center study

Deng,

Xing,

et al. 2024

World J Surg Onc

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Background Gallbladder cancer (GBC) is a highly aggressive malignancy, with limited survival profiles after curative surgeries. This study aimed to develop a practical model for predicting the postoperative overall survival (OS) in GBC patients. Methods Patients from three hospitals were included. Two centers ( N = 102 and 100) were adopted for model development and internal validation, and the third center ( N = 85) was used for external testing. Univariate and stepwise multivariate Cox regression were used for feature selection. A nomogram for 1-, 3-, and 5-year postoperative survival rates was constructed accordingly. Performance assessment included Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves. Kaplan-Meier curves were utilized to evaluate the risk stratification results of the nomogram. Decision curves were used to reflect the net benefit. Results Eight factors, TNM stage, age-adjusted Charlson Comorbidity Index (aCCI), body mass index (BMI), R0 resection, blood platelet count, and serum levels of albumin, CA125, CA199 were incorporated in the nomogram. The time-dependent C-index consistently exceeded 0.70 from 6 months to 5 years, and time-dependent ROC revealed an area under the curve (AUC) of over 75% for 1-, 3-, and 5-year survival. The calibration curves, Kaplan-Meier curves and decision curves also indicated good prognostic performance and clinical benefit, surpassing traditional indicators TNM staging and CA199 levels. The reliability of results was further proved in the independent external testing set. Conclusions The novel nomogram exhibited good prognostic efficacy and robust generalizability in GBC patients, which might be a promising tool for aiding clinical decision-making. Supplementary Information The online version contains supplementary material available at 10.1186/s12957-024-03533-z.

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Management of Incidentally Detected Gallbladder Cancer After Cholecystectomy

Cited by 2 publications

References 133 publications

Novel Multi-factor Predictive Model for Postoperative Survival in Gallbladder Cancer: A Multi-Center Study

Novel Multi-factor Predictive Model for Postoperative Survival in Gallbladder Cancer: A Multi-Center Study

Novel multifactor predictive model for postoperative survival in gallbladder cancer: a multi-center study

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