Dataset Information

Development and validation of a new staging system for node-negative gastric cancer based on recursive partitioning analysis: An international multi-institutional study.

ABSTRACT:

Background

Whether the tumor-node-metastasis (TNM) staging system is appropriate for patients with node-negative gastric cancer (GC) is still inconclusive. The modified staging system developed by recursive partitioning analysis (RPA) showed good prognostic performance in a variety of cancers. The application of RPA has not been reported in the prognostic prediction of GC.

Methods

Node-negative GC patients who underwent radical resection at Fujian Medical University Union Hospital (n = 862) and Sun Yat-sen University Cancer Center (n = 311) with at least 5 years of follow-up were selected as the training set. RPA was used to develop a modified staging system. Patients from the Surveillance, Epidemiology, and End Results database (n = 1415) were selected as the validation set.

Results

The 5-year overall survival (OS) rates of patients with 8th AJCC-TNM stage IA-IIIA in the training set were IA 95.2%, IB 87.1%, IIA 78.3%, IIB 75.8%, and IIIA 72.6%. Multivariate analysis (MVA) showed that larger tumor size, elder age, and deeper depth of invasion were independent predictors for OS in patients with node-negative GC (all P < 0.05). Patients were reclassified into RPA I, RPA II, RPA III, and RPA IV stages based on RPA; the 5-year OS rates were 96.1%, 87.2%, 81.0%, and 64.3%, respectively, with significant difference (P < 0.05). Two-step MVA showed that the RPA staging system was an independent predictor of OS (P < 0.05). Compared with the 8th AJCC-TNM staging system, the RPA staging system had a smaller AIC value (2544.9 vs 2576.2), higher ?² score (104.2 vs 69.6) and higher Harrell's C-index (0.697 vs 0.669, P = 0.007). The similar results were found in the validation set.

Conclusions

A new prognostic predictive system based on RPA was successfully developed and validated, which may be suggested for staging node-negative GC in future.

SUBMITTER: Lin JX

PROVIDER: S-EPMC6558615 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

Development and validation of a new staging system for node-negative gastric cancer based on recursive partitioning analysis: An international multi-institutional study.

Lin Jian-Xian JX Wang Zu-Kai ZK Wang Wei W Xie Jian-Wei JW Wang Jia-Bin JB Lu Jun J Chen Qi-Yue QY Cao Long-Long LL Lin Mi M Tu Ru-Hong RH Zheng Chao-Hui CH Li Ping P Zhou Zhi-Wei ZW Huang Chang-Ming CM

Cancer medicine 20190508 6

<h4>Background</h4>Whether the tumor-node-metastasis (TNM) staging system is appropriate for patients with node-negative gastric cancer (GC) is still inconclusive. The modified staging system developed by recursive partitioning analysis (RPA) showed good prognostic performance in a variety of cancers. The application of RPA has not been reported in the prognostic prediction of GC.<h4>Methods</h4>Node-negative GC patients who underwent radical resection at Fujian Medical University Union Hospital ...[more]

PMID: 31070023

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Project description:BackgroundThe benefits of neoadjuvant therapy for patients with locally advanced gastric cancer (GC) are increasingly recognized. The 8th edition of the American Joint Committee on Cancer (AJCC) Staging Manual first proposed ypTNM staging, but its accuracy is controversial. This study aims to develop a modified ypTNM staging.Patients and methodsClinicopathological data of 1,791 patients who underwent curative-intent gastrectomy after neoadjuvant therapy in the Surveillance, Epidemiology, and End Results database, as the development cohort, were retrospectively analyzed. Modified ypTNM staging was established based on overall survival (OS). We compared the prognostic performance of the AJCC 8th edition ypTNM staging and the modified staging for patients after neoadjuvant therapy.ResultsIn the development cohort, the 5-year OS for AJCC stages I, II, and III was 58.8%, 39.1%, and 21.6%, respectively, compared with 69.9%, 54.4%, 34.4%, 24.1%, and 13.6% for modified ypTNM stages IA, IB, II, IIIA, and IIIB. The modified staging had better discriminatory ability (C-index: 0.620 vs. 0.589, p < .001), predictive homogeneity (likelihood ratio chi-square: 140.71 vs. 218.66, p < .001), predictive accuracy (mean difference in Bayesian information criterion: 64.94; net reclassification index: 35.54%; integrated discrimination improvement index: 0.032; all p < .001), and model stability (time-dependent receiver operating characteristics curves) over AJCC. Decision curve analysis showed that the modified staging achieved a better net benefit than AJCC. In external validation (n = 266), the modified ypTNM staging had superior prognostic predictive power (all p < .05).ConclusionWe have developed and validated a modified ypTNM staging through multicenter data that is superior to the AJCC 8th edition ypTNM staging, allowing more accurate assessment of the prognosis of patients with GC after neoadjuvant therapy.Implications for practiceThe 8th edition of the American Joint Committee on Cancer (AJCC) Staging Manual first proposed ypTNM staging, but its accuracy is controversial. Based on multi-institutional data, this study developed a modified ypTNM staging, which is superior to the AJCC 8th edition ypTNM staging, allowing more accurate assessment of the prognosis of patients with gastric cancer after neoadjuvant therapy.

Dataset Information

Development and validation of a new staging system for node-negative gastric cancer based on recursive partitioning analysis: An international multi-institutional study.

Background

Methods

Results

Conclusions

Publications

Development and validation of a new staging system for node-negative gastric cancer based on recursive partitioning analysis: An international multi-institutional study.

Similar Datasets

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