Model to Predict Cause-specific Mortality in Patients With Olfactory Neuroblastoma: A Competing Risk Analysis

Purpose: The main objective of this study was to evaluate the cumulative incidence of cause-specific mortality and other causes of mortality for patients with olfactory neuroblastoma (ONB). The secondary aim was to model the probability of cause-specific death and build a competing risk nomogram to predict cause-specific mortality for this disease. Methods: : Patients with ONB from 1975 to 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. We estimated the cumulative incidence function (CIF) for cause-specific mortality and other causes of mortality, and constructed the Fine and Gray’s proportional subdistribution hazard model, as well as a competing-risk nomogram based on Fine and Gray’s model, to predict the probability of cause-specific mortality for patients with ONB. Results: : After data selection, 826 cases were included for analysis. Five-year cumulative incidence of cause-specific mortality was 19.5% and cumulative incidence of other causes of mortality was 11.3%. Predictors of cause-specific mortality for ONB included tumor stage, surgery and chemotherapy. Age was most strongly predictive of other causes of mortality: patients aged >60 years exhibited subdistribution hazard ratios (SHRs) of 1.063 (95% confidence interval [CI], 1.05-1.08; p =0.001). The competing risk nomogram for cause-specific mortality was well-calibrated, and had good discriminative ability (concordance index=0.79). Conclusion: We calculated the CIF of cause-specific mortality and other causes of mortality in patients with the rare malignancy ONB. We also built the first competing risk nomogram to provide useful individualized predictive information for patients with ONB.