Computational Pathology-Enabled Residual Tumor Estimation is a Prognostic Factor for Overall Survival in Anal Squamous Cell Carcinoma.

Abstract

Anal squamous cell carcinoma (SCC) incidence has increased, and treatment has shifted from surgery to chemoradiotherapy (CRT), with salvage abdominoperineal resection (APR) being reserved for persistent/recurrent cases. This study evaluates the utility of different Tumor Regression Scoring Systems (TRSS) in predicting survival in anal SCC patients, using pathologists' observations and digital pathology. Cases managed surgically from 2005 to 2019 were collected. Residual tumor was assessed by multiple methods (gross tumor size, largest focus of tumor on H&E slide, average of residual tumor in all submitted H&E slides, JES, Chirieac, Schneider, Hermann, CAP scoring system). Three expert pathologists individually estimated ("eyeballed") the residual tumor % based on residual tumor/tumor bed (single representative H&E slide). The QuPath software was used to measure tumor volume on the same slide. American Joint Committee on Cancer (AJCC) 8th staging, and outcome data were retrieved from electronic medical records. The study involved 48 participants, predominantly female (56%), with a median age of 57. Most were Caucasian. HPV-positive was present in 77% of those assessed (17/22). Initial treatment included chemoradiation (CRT), followed by APR (79%) or pelvic exenteration (21%). Complications (13%), persistent disease (33%), and recurrence (54%) led to surgical interventions. 51% had moderately differentiated SCC, whereas 42% were poorly differentiated. Lymphovascular invasion (44%), perineural invasion (38%), and lymph node metastasis (13%) were present. Distant metastasis was rare (2%). Median overall survival was 3.2 years. Positive margins (HR 4.12, 95% CI 1.83, 9.28) and larger tumor size (HR 1.02 95% CI 1.01, 1.03) were associated with an increased hazard of death. Most residual tumor measurement methods were not significantly associated with overall survival. Interobserver agreement (based on "eyeballing") was moderate (kappa 0.4). Computational pathology-based residual tumor percentage was the only method significantly associated with outcome, with each 10% increase in the residual tumor percentage corresponding to a 1.23-fold higher hazard death (95% CI 1.03, 1.46; p=0.024). This study highlights computational pathology's important role in predicting outcomes in anal SCC treated with CRT and surgery. Specifically, the computational assessment of the residual tumor percentage proves to be a strong predictor of overall survival, outperforming other established TRSS methods.