Identification of characteristics and construction of nomogram to predict the survival probability of mesonephric carcinoma patients: A population‐based analysis and a case report

Abstract Background Mesonephric carcinoma (MC) is a very rare tumor with less than 70 cases had been reported. The rarity of MC has restricted its research, resulting in the lack of published guidelines. Objective To summarize the characteristics and construct an external‐validated nomogram to predict the survival of MC patients. Method Sixty‐four qualified patients derived from the Surveillance, Epidemiology, and End Results Plus database, and one patient from the Guangzhou Red Cross Hospital were enrolled. The entire cohort was randomly divided into a development (70%) and a validation cohort (30%). The Kaplan–Meier method and univariate and multivariate Cox regression analyses were applied. Two nomograms were established to predict the 3‐to‐8‐year survival probability of MC patients, which were evaluated by C‐index, ROC curves, DCA curves, and calibration plots. Results The average survival time of MC patients was 84.22 ± 50.66 months. No significant difference was shown among different groups of race, primary site, tumor differentiated grade, and FIGO stages, while different SEER stages did distinguish patients' survival time, which indicated that the SEER stage standards might be a better staging system in the MC patients than FIGO stage (p = .0835). Additional survival analyses showed that MC patients benefited from shorter waiting times to begin treatment, accepting surgery, regional lymph node examination, radiotherapy, and chemotherapy. Two nomograms were established, both of which got satisfied scores in C‐index, ROC curves, DCA curves, and calibration plots. Conclusion Sufficient regional lymph nodes examined, and applying radiotherapy in high‐risk patients are recommended in MC patients. Nomograms established in the present study had good predicting and discriminating capabilities, which would be helpful in patients' individual risk estimation, management, counseling, and follow‐up.