World journal of surgery · 2018
A Nomogram to Predict Prognosis in Malignant Pleural Mesothelioma.
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Wang Shuai, Ma Ke, Chen Zongwei, Yang Xiaodong, Sun Fenghao, Jin Yulin, Shi Yu, Jiang Wei, Wang Qun, Zhan Cheng
Аннотация
BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare malignancy with heterogeneous outcomes. This study was aimed to develop a nomogram to precisely and visually predict survival of MPM patients.
METHODS: Data from Surveillance, Epidemiology, and End Results database (1973-2014) on MPM were screened and retrieved. The prognostic effects of variables, including age, sex, race, year of diagnosis, laterality, histology, tumor stage, surgery, chemotherapy, and radiotherapy were analyzed using Kaplan-Meier method and Cox proportional hazard model. A nomogram was formulated to predict overall survival of MPM patients.
RESULTS: A total of 1092 cases who met inclusion criteria were included in this study. The overall 1-, 2-, and 3-year survival rate in the entire cohort was 45.1, 23.0, and 12.1%, with median survival of 11 months. Cox regression analysis showed that age (P < 0.001), race (P = 0.003), histology type (P < 0.001), T stage (P < 0.001), M stage (P < 0.001), TNM stage (P < 0.001), cancer-directed surgery (P < 0.001), and chemotherapy (P < 0.001) were all independent prognostic factors of MPM patients. A nomogram was established based on the results of multivariate analysis. The internal bootstrap resampling approach suggested the nomogram had sufficient discriminatory power with the C-index of 0.705 (95% CI 0.681-0.729). The calibration plots also demonstrated good consistence between the prediction and the observation.
CONCLUSIONS: We developed a nomogram to accurately predict clinical outcomes of MPM patients based on individual characteristics. Risk stratification by the survival nomogram could optimize individual therapies and follow-up.
METHODS: Data from Surveillance, Epidemiology, and End Results database (1973-2014) on MPM were screened and retrieved. The prognostic effects of variables, including age, sex, race, year of diagnosis, laterality, histology, tumor stage, surgery, chemotherapy, and radiotherapy were analyzed using Kaplan-Meier method and Cox proportional hazard model. A nomogram was formulated to predict overall survival of MPM patients.
RESULTS: A total of 1092 cases who met inclusion criteria were included in this study. The overall 1-, 2-, and 3-year survival rate in the entire cohort was 45.1, 23.0, and 12.1%, with median survival of 11 months. Cox regression analysis showed that age (P < 0.001), race (P = 0.003), histology type (P < 0.001), T stage (P < 0.001), M stage (P < 0.001), TNM stage (P < 0.001), cancer-directed surgery (P < 0.001), and chemotherapy (P < 0.001) were all independent prognostic factors of MPM patients. A nomogram was established based on the results of multivariate analysis. The internal bootstrap resampling approach suggested the nomogram had sufficient discriminatory power with the C-index of 0.705 (95% CI 0.681-0.729). The calibration plots also demonstrated good consistence between the prediction and the observation.
CONCLUSIONS: We developed a nomogram to accurately predict clinical outcomes of MPM patients based on individual characteristics. Risk stratification by the survival nomogram could optimize individual therapies and follow-up.