Predictive and Prognostic Effects of Primary Tumor Size on Colorectal Cancer Survival - Alese, Olatunji B.; Zhou, Wei; Jiang, Renjian; Zakka, Katerina; Huang, Zhonglu; Okoli, Chimuanya; Shaib, Walid L.; Akce, Mehmet; Diab, Maria; Wu, Christina; El-Rayes, Bassel F. (Frontiers in Oncology, 2021)
Background: Pathologic staging is crucial in colorectal cancer (CRC). Unlike the majority of solid tumors, the current staging model does not use tumor size as a criterion. We evaluated the predictive and prognostic impact of primary tumor size on all stages of CRC. Methods: Using the National Cancer Database (NCDB), we conducted an analysis of CRC patients diagnosed between 2010 and 2015 who underwent resection of their primary cancer. Univariate and multivariate analyses were used to identify predictive and prognostic factors, Kaplan-Meier analysis and Cox proportional hazards models for association between tumor size and survival. Results: About 61,000 patients met the inclusion criteria. Median age was 63 years and majority of the tumors were colon primary (82.7%). AJCC stage distribution was: I - 20.1%; II - 32.1%; III - 34.7% and IV - 13.1%. The prognostic impact of tumor size was strongly associated with survival in stage III disease. Compared to patients with tumors <2cm; those with 2-5cm (HR 1.33; 1.19-1.49; p<0.001), 5-10cm (HR 1.51 (1.34-1.70; p<0.001) and >10cm (HR 1.95 (1.65-2.31; p<0.001) had worse survival independent of other variables. Stage II treated without adjuvant chemotherapy had comparable survival outcomes (HR 1.09; 0.97-1.523; p=0.148) with stage III patients who did, while Stage II patients who received adjuvant chemotherapy did much better than both groups (HR 0.76; 0.67-0.86; p<0.001). Stage III patients who did not receive adjuvant chemotherapy had the worst outcomes among the non-metastatic disease subgroups (HR 2.66; 2.48-2.86; p<0.001). Larger tumors were associated with advanced stage, MSI high, non-rectal primary and positive resection margins. Conclusions: Further studies are needed to clarify the role of tumor size in prognostic staging models, and how to incorporate it into therapy decisions.