Incorporating tumor grade and histology into an externally validated modified salivary gland staging system improved hazard discrimination in patient subgroups.
An externally validated modified salivary gland carcinoma staging system incorporating both histology and tumor grade was an independent predictor of survival outcomes coupled with the current standard American Joint Cancer Committee (AJCC) staging system in subgroups of patients with major salivary gland carcinomas, according to findings from a study published in JCO Global Oncology.1
Age of more than 65 years (HR 2.72; 95% CI, 2.49-2.97), male sex (HR 1.24; 95% CI, 1.14-1.35), metastatic disease (HR 3.8; 95% CI 2.86-5.05), high histologic risk by World Health Organization (WHO; HR, 2.38; 95% CI, 2.06-2.74) criteria, intermediate and high tumor grade (HR, 1.2; 95% CI, 1.02-1.41), AJCC stage (HR, 1.81; 95% CI, 1.11-2.96), and primary disease site (HR, 1.18; 95% CI, 1.05-1.32) were determined to be significant factors impacting overall survival (OS) and disease-specific survival (DSS). In particular, WHO stratification and stage correlated the most with OS and DSS, according to a correlation analysis and interaction testing. Moreover, age, grade, sex, and metastatic disease status had an intermediate correlation and demonstrated multicollinearity. Adding histological risk stratification to AJCC stage yielded an improved fit, as evidenced by reduced Akaike information criterion (AIC) index.
“Our analysis shows the importance of including grade and histology in the current staging AJCC system for better stratification,” the investigators wrote. “Similar results in the external validation cohort lend credence to our concept of including tumor grade and histology in the staging of salivary gland tumors. Multiple studies have shown that tumor grade…is a significant predictor for survival.”
A total of 4 potential predictive models were generated using histological risk stratification and AJCC staging. Model 1 used histologic risk only and 2 stages, and was found to perform poorly. Models 2 and 3 were also found to have poor performance in discriminating between stage IVA and IVB disease with notable overlap in 95% confidence intervals (CIs). Investigators reported that model 4, which used both histology and grade, discriminated between outcomes best in the study cohort. The model was preferred due to its simplicity, lower AIC, high C-index, better calibration, better stratification, and minimal overlap of CIs. Moreover, external validation outside of the study cohort upheld the efficacy of this model.
The analysis consisted of cases pulled from the SEER database from 2000 to 2018. Of an initial 16,270 patients, 6246 were included in the analysis. Forty percent of the population were women and 60% were men, and the median follow-up of 58 months. The median age was 65 years.
The parotid gland was the primary tumor site for 84% of patients and the submandibular gland was the primary site for 13%. Patients with low-grade tumors constituted 17.6% of the cohort, whereas those with intermediate- and high-grade tumors constituted 36.8% and 45.6%, respectively. Mucoepidermoid and squamous carcinoma were the most common histologies, constituting 37.5% and 19.7% of the cohort, respectively. All patients had undergone major salivary gland resection, with 50.8% having undergone neck dissection and 21.6% having undergone lymph node sampling. Investigators divided the study cohort into low aggression (33%) and high aggression (67%) based on WHO 2017 pathological classification.
“This staging system can be easily implemented in clinical practice as we have externally validated the model. However, consensus on definition of grades and histological reporting needs to be formulated to ensure reproducibility across all centers and facilitate accurate comparisons between institutions,” investigators concluded.
The possible inclusion of incomplete or flawed medical records and the lack of randomized treatment allocation were among the limitations of this analysis. Future studies accounting for lymphovascular extensions, perineural invasions, nodal status, molecular markers, and adjuvant therapy use in patients will further refine the proposed staging system.
Ramalingam N, Thiagarajan S, Chidambaranathan N, Singh AG, Chaukar D, Chaturvedi P. Regression derived staging model to predict overall and disease specific survival in patients with major salivary gland carcinomas with independent external validation. JCO Glob Oncol. Published online August 18, 2022. doi:10.1200/GO.22.00150