Predicting Pathologic Response in Locally Advanced Rectal Cancer Using Inflammatory, Nutritional, and...

Total neoadjuvant therapy (TNT) is the standard approach for locally advanced rectal cancer (LARC), yet pathological complete response (pCR) is achieved in only a subset. Systemic inflammation, nutritional status, and sarcopenia influence outcomes, yet integrated predictive models are lacking. We aimed to develop clinical, laboratory, and AI-based models to predict pathological response.

This retrospective study included stage II to III LARC patients treated at Ankara Etlik City Hospital (Nov 2022-Dec 2024). Eligible patients received ≥ 12 weeks of TNT followed by curative surgery. Sarcopenia was assessed using CT-based skeletal muscle area at the third lumbar vertebra (L3). C-reactive protein/albumin ratio (CAR) and systemic immune-inflammation index (SII) were used to assess inflammatory and nutritional status. Composite scores (CINR-pCR, CINR-Ryan) were calculated using z-transformed CAR and SII weighted by regression coefficients. Outcomes included pCR and good pathological response, defined as tumor regression grade (TRG) 0 to 1 per the modified Ryan grading system. Logistic regression and Random Forest (RF) models were used.

gov: NCT07049627.

Among 136 patients, 93 met the inclusion criteria. pCR and TRG 0 to 1 was achieved in 20 (21.5%) and 43 (46.2%) patients, respectively. Independent predictors of pCR included absence of post-TNT sarcopenia (OR 0.30, 95% CI, 0.09-0.95, P = .007), low CAR (OR 0.14, 95% CI, 0.03-0.70, P = .008), low SII (OR 0.28, 95% CI, 0.08-0.96, P = .042), low LDH (OR 0.10, 95% CI, 0.02-0.70, P = .020), and metformin use (OR 2.52, 95% CI, 1.40-3.78, P = .031). For TRG 0 to 1, significant predictors included low CAR (OR 0.42, 95% CI, 0.23-0.76, P = .005), low SII (OR 0.13, 95% CI, 0.03-0.56, P = .006), absence of ≥ 10% weight loss (OR 0.12, 95% CI, 0.02-0.66, P = .016), absence of post-TNT sarcopenia (OR 0.18, 95% CI, 0.05-0.70, P = .014), and shorter RT-to-surgery interval (OR 3.14, 95% CI, 1.17-6.43, P = .004). CINR scores showed strong predictive value (AUCs: 0.868 and 0.846), and RF models showed excellent performance (AUCs: 0.933 and 0.910, respectively).

Inflammatory, nutritional, and sarcopenia-based markers, including CINR scores and AI models, accurately predict pathological response in LARC. Importantly, the ROC-derived cut-off values (CINR-pCR: 1.58; CINR-Ryan: 0.45) stratified patients into low- and high-risk groups, supporting clinical decision-making in organ-preservation strategies and surgical timing. Prospective multicenter validation is warranted.