Establishment and Validation of Prognostic Nomograms for Patients With Parotid Gland Adenocarcinoma Not Otherwise Specified: A SEER Analysis From 2004 to 2016.

Parotid gland adenocarcinoma not otherwise specified (PANOS) is a rare malignant tumor with limited data on its characteristics and prognosis. This research is aimed at characterizing PANOS and developing prognostic prediction models for patients with PANOS. Cases from 2004-2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) Program database. Univariate and multivariate Cox regression were applied to ascertain the factors associated with survival. Competing risk analysis and Gray's tests were employed to analyze cancer-specific death. Propensity score matching (1:1) was conducted to reduce the influence of confounding variables. A total of 446 patients with a median age of 66 years were selected, of which 307 were diagnosed with stage III/IV PANOS. The 5-year overall survival (OS) rate of all patients was 51.8%, and the median survival time was 66 months. Surgical treatment clearly improved survival time ( < 0.001). In the subgroup analysis, radiotherapy showed survival benefits in patients with stage III/IV disease ( < 0.001). Multivariate Cox regression analyses showed that age, T classification, N classification, M classification and surgery were independent prognostic indicators for OS; T classification, N classification, M classification and surgery were independent risk factors for cancer-specific survival (CSS). In addition, age was independently associated with other cause-specific death. Based on the results of multivariate analysis, two nomograms were developed and verified by the concordance index (C-index) (0.747 and 0.780 for OS and CSS) and the area under the time-dependent receiver operating characteristic (ROC) curve (0.756, 0.764, and 0.819 regarding for nomograms predicting 3-, 5-, and 10- year OS, respectively and 0.794, 0.789, and 0.806 for CSS, respectively). Our study clearly presents the clinicopathological features and survival analysis of patients with PANOS. In addition, our constructed nomogram prediction models may assist physicians in evaluating the individualized prognosis and deciding on treatment for patients.