Investigating Predictive Factors of Pathological Complete Response After Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer. - Rakhsha, Afshin; Khandani, Maryam Kalantari; Shokri, Fateme (International Journal of Cancer Management)
Background: Standard treatment for locally advanced rectal cancer (LARC) includes neoadjuvant chemoradiotherapy (CRT) followed by surgery and adjuvant chemotherapy. Although achieving a pathological complete response (pCR) is considered a favorable prognostic factor, the parameters influencing pCR remain incompletely defined. Objectives: This study investigated predictive factors for achieving pCR in patients with LARC who underwent neoadjuvant CRT. Methods: This retrospective cross-sectional study included 100 patients with LARC who underwent neoadjuvant CRT between May 2018 and September 2023 at Shohadaye Tajrish Hospital, Tehran, Iran. Patients' demographics, clinicopathological data, and treatment details, including chemotherapy and radiotherapy data, were reviewed to analyze their correlation with pCR. Statistical analysis was performed using the chi-square test, Student's t-test, and Fisher's exact test to assess factors associated with pCR. A P-value of < 0.05 was considered statistically significant. Results: Pathological complete response was obtained in 28% of the cases. Clinical stage and induction chemotherapy were independent predictors of pCR (P < 0.05). Patients with T3N1 and T3N2 stages had higher pCR rates, whereas none of the T4N2 patients achieved pCR. The number of induction chemotherapy cycles was strongly associated with pCR. The pCR rates were significantly higher for those patients who received four cycles or more (P < 0.05). No significant association was found between pCR and age, gender, Body Mass Index (BMI), tumor differentiation, or radiotherapy dosimetry. Conclusions: The clinical stage at diagnosis and the extent of induction chemotherapy were significant predictors of pCR in this study. Further prospective studies are warranted to validate these findings and explore additional predictive factors.