Development and Validation of a Nomogram for Assessing Survival in Patients With Metastatic Lung Cancer Referred for Radiotherapy for Bone Metastases

Abstract

Importance: A survival prediction model for patients with bone metastases arising from lung cancer would be highly valuable. Objective: To develop and validate a nomogram for assessing the survival probability of patients with metastatic lung cancer receiving radiotherapy for osseous metastases. Design, Setting, Participants: In this prognostic study, the putative prognostic indicators for constructing the nomogram were identified using multivariable Cox regression analysis with backward elimination and model selection based on the Akaike information criterion. The nomogram was subjected to internal (bootstrap) and external validation; its calibration and discriminative ability were evaluated with calibration plots and the Uno C statistic, respectively. The training and validation set cohorts were from a tertiary medical center in northern Taiwan and a tertiary institution in southern Taiwan, respectively. The training set comprised 477 patients with metastatic lung cancer who received radiotherapy for osseous metastases between January 2000 and December 2013. The validation set comprised 235 similar patients treated between January 2011 and December 2017. Data analysis was conducted May 2018 to July 2018. Main Outcomes and Measures: The nomogram end points were death within 3, 6, and 12 months. Results: Of 477 patients in the training set, 292 patients (61.2%) were male, and the mean (SD) age was 62.86 (11.66) years. Of 235 patients in the validating set, 113 patients (48.1%) were male, and the mean (SD) age was 62.65 (11.49) years. In the training set, 186 (39%), 291 (61%), and 359 (75%) patients died within 3, 6, and 12 months, respectively, and the median overall survival was 4.21 (95% CI, 3.68-4.90) months. In the validating set, 84 (36%), 120 (51%), and 144 (61%) patients died within 3, 6, and 12 months, respectively, and the median overall survival was 5.20 (95% CI, 4.07-7.17) months. Body mass index (18.5 to <25 vs ≥25: hazard ratio [HR], 1.42; 95% CI, 1.14-1.78 and <18.5 vs ≥25: HR, 2.31; 95% CI, 1.56-3.44), histology (non-small cell vs small cell lung cancer: HR, 0.59; 95% CI, 0.41-0.86), epidermal growth factor receptor mutation (positive vs unknown: HR, 0.66; 95% CI, 0.46-0.93 and negative vs unknown: HR, 0.98; 95% CI, 0.66-1.45), smoking status (ever smoker vs never smoker: HR, 1.50; 95% CI, 1.24-1.83), age, and neutrophil to lymphocyte ratio were incorporated. The HRs of age and neutrophil to lymphocyte ratio were modeled nonlinearly with restricted cubic splines (both P < .001). The nomogram's discriminative ability was good in the training set (C statistic, ≥0.77; P < .001) and was validated using both an internal bootstrap method (C statistic, ≥0.76; P < .001) and an external validating set (C statistic, ≥0.75; P