Prognostic Assessment and Risk Stratification in Patients With Postoperative Major Salivary Acinar Cell Carcinoma

ObjectiveTo investigate the clinicopathological features and prognosis of postoperative major salivary acinar cell carcinoma (MSACC) and develop a prognostic model. Study DesignRetrospective cohort analysis of a public database. SettingPatients with MSACC were identified from the Surveillance, Epidemiology, and End Results database (1975-2019). MethodsOverall survival (OS) was evaluated using Kaplan-Meier curves and a log-rank test. Univariate and multivariate Cox analyses were performed to explore independent prognostic factors. The prognostic model was constructed using screened variables and further visualized with a nomogram and web calculator, and assessed by concordance index, the area under the curve, calibration curve, and decision-making curve analysis. ResultsAn upward trend in the incidence of MSACC was observed throughout the study period. A total of 1398 patients were enrolled (training cohort: 978; validation cohort: 420), and the 5- and 10-year OS rates were 97.7% and 81.6%, respectively. Age, marital status, sex, histological grade, T stage, and lymph node status were identified as prognostic factors for OS. A novel nomogram was developed and showed excellent discrimination and clinical applicability. Additionally, a web calculator was designed to dynamically predict patient survival. Based on the nomogram-based score, a risk stratification system was constructed to distinguish patients with different risks. The OS of high-risk patients was significantly lower than that of the low-risk subgroup. ConclusionLong-term survival in postoperative MSACC was influenced by 6 prognostic factors. The proposed model enables individualized survival prediction and risk stratification, prompting us to be vigilant in high-risk subgroups and consider timely adjustment of subsequent treatment.

Automated summary

The study aimed to investigate the clinicopathological features and prognosis of postoperative major salivary acinar cell carcinoma (MSACC) and develop a prognostic model. A total of 1398 patients were enrolled from the Surveillance, Epidemiology, and End Results database. Age, marital status, sex, histological grade, T stage, and lymph node status were identified as prognostic factors. A novel nomogram and web calculator were developed for individualized survival prediction and risk stratification. The proposed model provides valuable information for treatment adjustment in high-risk subgroups.