Development and validation of a nomogram for predicting survival in patients with surgically resected lung invasive mucinous adenocarcinoma

Background: Lung invasive mucinous adenocarcinoma (LIMA) is a unique and rare subtype of lung adenocarcinoma. We identified prognostic factors and developed a nomogram for predicting overall survival (OS) in LIMA patients after surgery. Methods: Patients diagnosed with LIMA between 2008 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database were randomized into training (n=1,254) and test (n=538) cohorts. A nomogram was established using the prognostic signature from the training cohort after multivariable Cox regression analysis. We externally validated the nomogram in a group of 369 patients from China. We separately tested for accuracy and clinical practicability using Harrell's concordance-index (C-index), calibration plots, and decision curve analysis (DCA). Results: We included 2,161 patients in the analysis. Seven factors, all of which significantly affected OS, were incorporated into the final model, including age, sex, differentiation grade, the extent of surgery, lymphadenectomy, and T, N, and M stage. C-indexes for the training, test, and external validation cohorts were 0.735, 0.736, and 0.773, respectively. The areas under the time-dependent receiver operating characteristic curves at five years were 0.747, 0.798, and 0.777, respectively. The nomogram was discriminative and well-calibrated when applied to the test and external validation cohorts. Significant between-group differences in OS were observed when classifying groups by nomogram score (log-rank P<0.001). An online web server for clinical use was developed using the nomogram. Conclusions: The nomogram facilitates accurate prediction of survival for patients with LIMA and can be used to stratify clinical risk groups for individualized treatment.