A novel nomogram model for predicting prognosis of non–small cell lung cancer with malignant pleural effusion
Suning Li, Dan Ding, Meijia Wang, Yong CaoBackground:
The patients of non–small cell lung cancer (NSCLC) with malignant pleural effusion (MPE) typically had poor prognosis. It was still challenging to predict overall survival (OS) and make reasonable clinical treatment.
Methods:
Patients diagnosed with NSCLC and MPE between January 2018 and January 2023 at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, were retrospectively identified. The cohort was randomly divided into the training and validation groups. Propensity score matching was performed, followed by COX regression analysis based on the matched patients. A nomogram was constructed based on the multivariate COX regression results. The performance of the nomogram was evaluated using calibration and concordance indices, as well as receiver operating characteristic curves.
Results:
A total of 306 patients were included in this study. The median OS for the entire cohort was 233 days (95% confidence interval, 168.68–297.33), which improved to 242 days (95% confidence interval, 158.28–325.72) post–propensity score matching. Independent risk factors affecting OS included a history of respiratory system diseases, leukocyte count, neutrophil-to-lymphocyte ratio, serum albumin level, and targeted therapy. A nomogram predicting OS was developed based on the COX multivariate regression analysis. The concordance indices for these nomograms were 0.732 and 0.747 for the training and validation cohorts, respectively. Calibration curves demonstrated a good alignment between the predicted and actual survival probabilities at various time points in both cohorts.
Conclusions:
The nomogram was successfully constructed to predict OS at 6 months, 1 year, and 2 years for NSCLC patients with MPE. This nomogram can potentially aid in clinical decision-making regarding the benefits of targeted therapy in this patient population.