Model to Predict Cause-Specific Mortality in Patients with Head and Neck Adenoid Cystic Carcinoma: A Competing Risk Analysis

Purpose. The main objective of this study was to evaluate the cumulative incidence of cause-specific death and other causes of death for patients with head and neck adenoid cystic carcinoma (ACC). 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. Data were extracted from the US National Cancer Institute's Surveillance Epidemiology, and End Results (SEER)-18 dataset. The study cohort included patients with a diagnosis of primary head and neck ACC during the period 2004-2013. We calculated the cumulative incidence function (CIF) for cause-specific death and other causes of death, 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 death for patients with head and neck ACC. Results. After data selection, 1435 cases were included for analysis. Five-year cumulative incidence of cause-specific death was 17.4% (95% confidence interval [CI] 15.1-19.8%) and cumulative incidence of other causes of death was 5.8% (95% CI 4.4-7.4%). Predictors of cause-specific death for head and neck ACC included age, tumor size, advanced T stage, positive lymph node, distant metastasis, and surgery. The nomogram was well-calibrated, and had good discriminative ability. Conclusion. The large sample allowed us to construct a reliable predictive model for rare malignancy. The model performance was good, with a concordance index of 0.79, and the nomogram can provide useful individualized predictive information for patients with head and neck ACC.