Perform tumor-specific survival analysis for Merkel cell carcinoma patients undergoing surgical resection based on the SEER database by constructing a nomogram chart

基于SEER数据库,通过构建列线图,对接受手术切除的默克尔细胞癌患者进行肿瘤特异性生存分析。

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Abstract

OBJECTIVE: To explore the postoperative risk factors of Merkel cell carcinoma patients who have undergone surgical resection, and to construct a survival prognosis column chart. METHOD: Patients diagnosed with Merkel cell carcinoma and underwent surgical resection from 2000 to 2019 were selected from the surveillance, epidemiology, and end results database. COX regression analysis was used to screen for independent prognostic factors, and a column chart was constructed. The predictive performance of the column chart was evaluated using consistency index, receiver operating characteristic curve, and calibration curve. RESULTS: The results of multi-factor COX regression showed that T stage and N stage were independent prognostic factors affecting cancer-specific survival (CSS) in patients after Merkel cell carcinoma resection. Construct a column chart based on the above two factors. The C-index of the column chart in the modeling group is 0.732 [95% CI (0.649, 0.814)], and the area under the curve (AUC) for the first and second years are 0.816 [95% CI (0.728, 0.904)] and 0.693 [95% CI (0.593, 0.792)], respectively. The C-index in the validation group was 0.724 [95% CI (0.569, 0.879)], and the AUC in the first and second years were 0.739 [95% CI (0.644, 0.833)] and 0.658 [95% CI (0.556, 0.759)], respectively. CONCLUSION: The predictive model constructed based on two factors, T stage and N stage, has good prognostic diagnostic accuracy and is helpful for clinical decision-making and personalized treatment.

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