A competing risk nomogram predicting cause-specific mortality in patients with lung adenosquamous carcinoma
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RESEARCH ARTICLE
Open Access
A competing risk nomogram predicting cause-specific mortality in patients with lung adenosquamous carcinoma Xiao Wu1†, Wenfeng Yu1†, R. H. Petersen2, Hongxu Sheng1, Yiqing Wang1, Wang Lv1 and Jian Hu1*
Abstract Background: Adenosquamous carcinoma (ASC) is an uncommon histological subtype of lung cancer. The purpose of this study was to assess the cumulative incidences of lung cancer-specific mortality (LC-SM) and other causespecific mortality (OCSM) in lung ASC patients, and construct a corresponding competing risk nomogram for LCSM. Methods: Data on 2705 patients with first primary lung ASC histologically diagnosed between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The cumulative incidence function (CIF) was utilized to calculate the 3-year and 5-year probabilities of LC-SM and OCSM, and a competing risk model was built. Based on the model, we developed a competing risk nomogram to predict the 3-year and 5-year cumulative probabilities of LC-SM and the corresponding concordance indexes (C-indexes) and calibration curves were derived to assess the model performance. To evaluate the clinical usefulness of the nomogram, decision curve analysis (DCA) was conducted. Furthermore, patients were categorized into three groups according to the tertile values of the nomogram-based scores, and their survival differences were assessed using CIF curves. Results: The 3-year and 5-year cumulative mortalities were 49.6 and 55.8% for LC-SM and 8.2 and 11.8% for OCSM, respectively. In multivariate analysis, increasing age, male sex, no surgery, and advanced T, N and M stages were related to a significantly higher likelihood of LC-SM. The nomogram showed good calibration, and the 3-year and 5-year C-indexes for predicting the probabilities of LC-SM in the validation cohort were both 0.79, which were almost equal to those of the ten-fold cross validation. DCA demonstrated that using the nomogram gained more benefit when the threshold probabilities were set within the ranges of 0.24–0.89 and 0.25–0.91 for 3-year and 5year LCSM, respectively. In both the training and validation cohorts, the high-risk group had the highest probabilities of LC-SM, followed by the medium-risk and low-risk groups (both P < 0.0001). Conclusions: The competing risk nomogram displayed excellent discrimination and calibration for predicting LC-SM. With the aid of this individualized predictive tool, clinicians can more expediently devise appropriate treatment protocols and follow-up schedules. Keywords: Adenosquamous carcinoma, Lung cancer, Competing-risk analysis, Cumulative incidence, Nomogram
* Correspondence: [email protected] † Xiao Wu and Wenfeng Yu contributed equally to this work. 1 Department of Thoracic Surgery, First Affiliated Hospital, College of Medicine, Zhejiang University, No. 79, Qingchun Road, Hangzhou 310003, China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a
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