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Prediction of presurgical metabolic syndrome for gastric cancer-specific mortality is more evident in smokers: The FIESTA study

Cancer Med. 2022 Aug 26. doi: 10.1002/cam4.5116. Online ahead of print.

ABSTRACT

BACKGROUNDS: We aimed to test whether the prediction of presurgical metabolic syndrome for postsurgical survival outcomes of gastric cancer hinges upon cigarette smoking status.

METHODS: This study is a part of the ongoing Fujian prospective investigation of cancer (FIESTA) study. Patients with gastric cancer received radical resection of primary gastric cancer between January 2000 and December 2010, with the latest follow-up ended in December 2015. The 1:1 propensity score matching analysis was adopted to balance confounders between smokers and never-smokers. Effect-size estimates are expressed as hazard ratio (HR) with 95% confidence interval (CI). Model performance was evaluated using the Hosmer and Lemeshow test and 10-fold cross-validated area under the receiver operating characteristic curve (AUROC). Statistical analyses were completed with SAS software (v9.4).

RESULTS: Total 2779 patients with gastric cancer were analyzed, including 2223 smokers and 556 never-smokers. Median follow-up time was 45.6 months. Cigarette smoking was not associated with postsurgical survival differences. Presurgical metabolic syndrome complication was significantly associated with increased gastric cancer-specific mortality in smokers (HR [95% CI]: 2.73 [1.53-4.89], p < 0.001), but not in never-smokers. Relative excess risk due to interaction was estimated to be 2.43 (95% CI: 0.40-4.45). After constructing a risk assessment score, one unit increment was associated with 10% reduced risk of gastric cancer-specific mortality (HR [95% CI]: 0.90 [0.88-0.91], p < 0.001), with 10-fold cross-validated AUROC being 0.82 (95% CI: 0.74-0.92).

CONCLUSIONS: Our findings showed that the prediction of presurgical metabolic syndrome for gastric cancer-specific mortality was more evident in smokers. Practically, this study provides evidence base for future personalized prediction and helped risk-stratify gastric cancer patients who might experience serious postsurgical consequences.

PMID:36028993 | DOI:10.1002/cam4.5116

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