Dataset Information

Analysis of prognostic factors for survival after surgery for gallbladder cancer based on a Bayesian network.

ABSTRACT: The factors underlying prognosis for gallbladder cancer (GBC) remain unclear. This study combines the Bayesian network (BN) with importance measures to identify the key factors that influence GBC patient survival time. A dataset of 366 patients who underwent surgical treatment for GBC was employed to establish and test a BN model using BayesiaLab software. A tree-augmented naïve Bayes method was also used to mine relationships between factors. Composite importance measures were applied to rank the influence of factors on survival time. The accuracy of BN model was 81.15%. For patients with long survival time (>6 months), the true-positive rate of the model was 77.78% and the false-positive rate was 15.25%. According to the built BN model, the sex, age, and pathological type were independent factors for survival of GBC patients. The N stage, liver infiltration, T stage, M stage, and surgical type were dependent variables for survival time prediction. Surgical type and TNM stages were identified as the most significant factors for the prognosis of GBC based on the analysis results of importance measures.

SUBMITTER: Cai ZQ

PROVIDER: S-EPMC5428511 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Analysis of prognostic factors for survival after surgery for gallbladder cancer based on a Bayesian network.

Cai Zhi-Qiang ZQ Guo Peng P Si Shu-Bin SB Geng Zhi-Min ZM Chen Chen C Cong Long-Long LL

Scientific reports 20170322 1

The factors underlying prognosis for gallbladder cancer (GBC) remain unclear. This study combines the Bayesian network (BN) with importance measures to identify the key factors that influence GBC patient survival time. A dataset of 366 patients who underwent surgical treatment for GBC was employed to establish and test a BN model using BayesiaLab software. A tree-augmented naïve Bayes method was also used to mine relationships between factors. Composite importance measures were applied to rank t ...[more]

PMID: 28331235

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Project description:BackgroundGallbladder cancer (GBC) is highly malignant, its early diagnosis is difficult, and the 5-year survival rate is less than 5%. For patients with advanced GBC (GBCa), combined chemotherapy, radiotherapy, targeted therapy, and immunotherapy are needed to improve the overall survival (OS) rate of patients.MethodsData were collected from 53 patients with GBCa who had volunteered to receive programmed death protein-1 (PD-1)-based treatment at the First Affiliated Hospital of Nanjing Medical University from February 2018 to February 2021. Statistical analysis of the collected data, including Kaplan-Meier method, log-rank test, Cox proportional hazard regression model and other methods.ResultsThe objective response rates (ORRs) and disease control rates (DCRs) of 53 participants 3 months after receiving immunotherapy were 30.2% and 79.2%, respectively. The ORRs and DCRs of the combined treatment group were higher than those of the camrelizumab group (CG) (P<0.05). The DCRs of the camrelizumab plus apatinib group (CAG) at 3 and 6 months were 90.9% and 45.5% (P=0.003), respectively, while the DCRs at 3 and 6 months of the camrelizumab plus chemotherapy group (CCG) were 85.7% and 71.4% (P=0.450), respectively. After treatment, there were statistically significant differences before and after CA199 for each group (P<0.05). The median progression-free survival (mPFS) of the 53 participants was 7 months, and the median overall survival (mOS) was 12 months. The mPFS and mOS of the CAG and the CCG were greater than those in the CG (6 vs. 3 months, P<0.001, 12 vs. 8 months, P=0.019; 9 vs. 3 months, P<0.001, 13 vs. 8 months, P<0.001, respectively). A total of 16 cases had grade 1 or 2 adverse events, and 3 cases had grade 3 and higher adverse events.ConclusionsFor GBCa patients, PD-1 combined with targeted therapy or chemotherapy is more effective than immunotherapy alone. The targeted therapy group has more obvious early effects on the disease control rate, and combined chemotherapy can achieve sustained effects, providing new ideas for the future GBCa application of immune, targeted, and chemotherapy sequential therapy.

Dataset Information

Analysis of prognostic factors for survival after surgery for gallbladder cancer based on a Bayesian network.

Publications

Analysis of prognostic factors for survival after surgery for gallbladder cancer based on a Bayesian network.

Similar Datasets

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