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A nomogram for prediction of stage III/IV gastric cancer outcome after surgery: A multicenter population-based study.

ABSTRACT: Most patients with gastric cancer (GC) are first diagnosed at stage III-IV and surgery resection remains the primary therapeutic modality for these patients. However, clinical staging used for prediction of those patients provides limited information. We collected clinicopathological data and disease-progression information from 508 patients with stage III-IV GC at three Chinese hospitals and 1298 patients from the Surveillance, Epidemiology, and End Results database. Based on the stepwise multivariate regression model, we constructed a novel nomogram to predict overall survival (OS). The performance of discrimination for this model was measured using Harrell's concordance index (C-index) and receiver-operating characteristic curve (ROC), and was validated using calibration plots. Multivariate Cox regression analyses showed that tumor size, age at diagnosis, N stage, tumor grade, and distant metastases were outstanding independent prognostic factors of stage III-IV GC. We developed a nomogram based on these five prognostic predictors. In the training set, the C-index of the nomogram was 0.645 (95% CI: 0.611-0.679), which was higher than that of the American Joint Committee on Cancer TNM system alone (sixth TNM: 0.544; seventh TNM: 0.575; eighth TNM: 0.568). Similar results were observed in validation cohort. Moreover, calibration blots demonstrated good consistency between the actual and predicted OS probabilities. According to the nomogram, GC individuals could be classified into three groups (low-, middle-, and high-risk) (P < .001). Our nomogram complements the current staging system for prediction of individual prognosis with stage III-IV GC, and may be helpful for making individualized treatment decisions.

SUBMITTER: Gao Z

PROVIDER: S-EPMC7402842 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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A nomogram for prediction of stage III/IV gastric cancer outcome after surgery: A multicenter population-based study.

Gao Zhiying Z Ni Jing J Ding Hui H Yan Caiwang C Ren Chuanli C Li Gang G Pan Feng F Jin Guangfu G

Cancer medicine 20200615 15

Most patients with gastric cancer (GC) are first diagnosed at stage III-IV and surgery resection remains the primary therapeutic modality for these patients. However, clinical staging used for prediction of those patients provides limited information. We collected clinicopathological data and disease-progression information from 508 patients with stage III-IV GC at three Chinese hospitals and 1298 patients from the Surveillance, Epidemiology, and End Results database. Based on the stepwise multi ...[more]

PMID: 32543092

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Project description:ObjectivesThe advanced gastric adenocarcinoma (GAC) patients (stage III/IV) with surgery may have inconsistent prognoses due to different demographic and clinicopathological factors. In this retrospective study, we developed clinical prediction models for estimating the overall survival (OS) and cancer-specific survival (CSS) in advanced GAC patients with surgery.MethodsA retrospective analysis was conducted using the Surveillance, Epidemiology, and End Results (SEER) database. The total population from 2004 to 2015 was divided into four levels according to age, of which 179 were younger than 45 years old, 695 were 45-59 years old, 1064 were 60-74 years old, and 708 were older than 75 years old. There were 1,712 men and 934 women. Univariate and multivariate Cox regression analyses were performed to identify prognostic factors for OS and CSS. Nomograms were constructed to predict the 1-, 3-, and 5-year OS and CSS. The models' calibration and discrimination efficiency were validated. Discrimination and accuracy were evaluated using the consistency index, area under the receiver operating characteristic curve, and calibration plots; and clinical usefulness was assessed using decision curve analysis. Cross-validation was also conducted to evaluate the accuracy and stability of the models. Prognostic factors identified by Cox regression were analyzed using Kaplan-Meier survival analysis.ResultsA total of 2,646 patients were included in our OS study. Age, primary site, differentiation grade, AJCC 6th_TNM stage, chemotherapy, radiotherapy, and number of regional nodes examined were identified as prognostic factors for OS in advanced GAC patients with surgery (P < 0.05). A total of 2,369 patients were included in our CSS study. Age, primary site, differentiation grade, AJCC 6th_TNM stage, chemotherapy, radiotherapy, and number of regional nodes examined were identified as risk factors for CSS in these patients (P < 0.05). These factors were used to construct the nomogram to predict the 1-, 3-, and 5-year OS and CSS of advanced GAC patients with surgery. The consistency index and area under the receiver operating characteristic curve demonstrated that the models effectively differentiated between events and nonevents. The calibration plots for 1-, 3-, and 5-year OS and CSS probability showed good consistence between the predicted and the actual events. The decision curve analysis indicated that the nomogram had higher clinical predictive value and more significant net gain than AJCC 6th_TNM stage in predicting OS and CSS of advanced GAC patients with surgery. Cross-validation also revealed good accuracy and stability of the models.ConclusionThe developed predictive models provided available prognostic estimates for advanced GAC patients with surgery. Our findings suggested that both OS and CSS can benefit from chemotherapy or radiotherapy in these patients.

Dataset Information

A nomogram for prediction of stage III/IV gastric cancer outcome after surgery: A multicenter population-based study.

Publications

A nomogram for prediction of stage III/IV gastric cancer outcome after surgery: A multicenter population-based study.

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