Clinical efficacy and predictive indicators of cindilizumab combined with XELIRI protocol in advanced colorectal carcinoma patients.

OBJECTIVE

To evaluate the therapeutic efficacy of adding cindilizumab to the Xeloda-Irinotecan (XELIRI) regimen in patients with advanced colorectal cancer and to identify clinical and molecular biomarkers predictive of treatment response.

METHODS

A retrospective analysis was conducted on 197 patients with advanced colorectal carcinoma treated between January 2019 and June 2023. Patients were divided into two cohorts: the standard treatment group receiving XELIRI alone (n=103) and the combined treatment group receiving XELIRI with cindilizumab (n=94). Treatment response was assessed according to RECIST criteria and classified as responsive (complete response [CR] or partial response [PR]) or non-responsive (stable disease [SD] or progressive disease [PD]). Logistic regression analysis was performed to identify independent predictors of treatment response. Adverse events were recorded throughout the treatment course.

RESULTS

The experimental cohort demonstrated statistically higher objective response rate (ORR) and disease control rate (DCR) compared to the standard treatment cohort (ORR: 38.30% versus 22.33%, P=0.015; DCR: 80.85% versus 66.02%, P=0.019). The incidence of hypothyroidism and renal impairment was significantly higher in the combination group (P=0.002). Logistic regression identified carcinoembryonic antigen (CEA) (OR=1.336, P<0.001), tumor diameter (OR=2.818, P=0.001), KRAS/NRAS gene status (OR=6.229, P=0.001), and treatment regimen (OR=0.079, P<0.001) as independent predictors of treatment response. Receiver operating characteristic (ROC) curve analysis showed that their combined prediction significantly improved predictive efficacy (AUC=0.881), with high sensitivity and specificity.

CONCLUSION

Cindilizumab combined with XELIRI regimen improves ORR and DCR in patients with advanced colorectal cancer but may increase the risk of hypothyroidism and renal impairment. CEA, tumor diameter, KRAS/NRAS gene, and treatment regimen are independent predictors of treatment response. The combined predictive model demonstrates robust diagnostic performance.