Dataset Information

Development and Validation of a Nomogram for Predicting Survival in Gallbladder Cancer Patients With Recurrence After Surgery.

ABSTRACT:

Background

The management of gallbladder cancer (GBC) patients with recurrence who need additional therapy or intensive follow-up remains controversial. Therefore, we aim to develop a nomogram to predict survival in GBC patients with recurrence after surgery.

Methods

A total of 313 GBC patients with recurrence from our center was identified as a primary cohort, which were randomly divided into a training cohort (N = 209) and an internal validation cohort (N = 104). In addition, 105 patients from other centers were selected as an external validation cohort. Independent prognostic factors, identified by univariate and multivariable analysis, were used to construct a nomogram. The performance of this nomogram was measured using Harrell's concordance index (C-index) and calibration curves.

Results

Our nomogram was established by four factors, including time-to-recurrence, site of recurrence, CA19-9 at recurrence, and treatment of recurrence. The C-index of this nomogram in the training, internal and external validation cohort was 0.871, 0.812, and 0.754, respectively. The calibration curves showed an optimal agreement between nomogram prediction and actual observation. Notably, this nomogram could accurately stratify patients into different risk subgroups, which allowed more significant distinction of Kaplan-Meier curves than that of using T category. The 3-year post-recurrence survival (PRS) rates in the low-, medium-, and high-risk subgroups from the external validation cohort were 53.3, 26.2, and 4.1%, respectively.

Conclusion

This nomogram provides a tool to predict 1- and 3-year PRS rates in GBC patients with recurrence after surgery.

SUBMITTER: Chen M

PROVIDER: S-EPMC7829964 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Development and Validation of a Nomogram for Predicting Survival in Gallbladder Cancer Patients With Recurrence After Surgery.

Chen Mingyu M Li Shijie S Topatana Win W Lv Xiaozhong X Cao Jiasheng J Hu Jiahao J Lin Jian J Juengpanich Sarun S Shen Jiliang J Cai Xiujun X

Frontiers in oncology 20210111

<h4>Background</h4>The management of gallbladder cancer (GBC) patients with recurrence who need additional therapy or intensive follow-up remains controversial. Therefore, we aim to develop a nomogram to predict survival in GBC patients with recurrence after surgery.<h4>Methods</h4>A total of 313 GBC patients with recurrence from our center was identified as a primary cohort, which were randomly divided into a training cohort (N = 209) and an internal validation cohort (N = 104). In addition, 10 ...[more]

PMID: 33505902

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Dataset Information

Development and Validation of a Nomogram for Predicting Survival in Gallbladder Cancer Patients With Recurrence After Surgery.

Background

Methods

Results

Conclusion

Publications

Development and Validation of a Nomogram for Predicting Survival in Gallbladder Cancer Patients With Recurrence After Surgery.

Similar Datasets

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