Development and validation of a nomogram for predicting survival of pulmonary invasive mucinous adenocarcinoma based on surveillance, epidemiology, and end results (SEER) database

Abstract

Abstract Background Lung cancer remains the leading cause of cancer death globally. In 2015, the cancer classification guidelines of the World Health Organization were updated. The term “invasive mucinous adenocarcinoma (IMA)” aroused people’s attention, while the clinicopathological factors that may influence survival were unclear. Methods Data of IMA patients was downloaded from SEER database. Kaplan-Meier methods and log-rank tests were used to compare the differences in OS and LCSS. The nomogram was developed based on the result of the multivariable analysis. The discrimination and accuracy were tested by Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve and decision curve analyses (DCA). Integrated discrimination improvement (IDI) index was used to evaluate the clinical efficacy. Results According to multivariate analysis, the prognosis of IMAs was associated with age, differentiation grade, TNM stage and treatments. Surgery might be the only way that would improve survival. Area under the curve (AUC) of the training cohort was 0.834and 0.830 for3-and 5-year OS, respectively. AUC for 3-and 5-year LCSS were separately 0.839 and 0.839. The new model was then evaluated by calibration curve, DCA and IDI index. Conclusion Based on this study, prognosis of IMAs was systematically reviewed, and a new nomogram was developed and validated. This model helps us understand IMA in depth and provides new ideas for IMA treatment.