Predicting Pathological Complete Response in Rectal Cancer: External Validation of Clinical Models

Introduction: A pathological complete response (pCR) to neoadjuvant therapy is what makes organ preservation possible in rectal cancer, so a reliable pre-treatment estimate of the likelihood of pCR would influence management. Prediction research has focused on imaging and artificial intelligence, leaving the clinical models that any unit should be able to apply largely untested beyond their original cohorts. We validated two such models eiyh our own patients, examined whether local refitting helped, and measured how often pCR occurs across the regimens we use. Methods: This was a single-centre cohort of consecutive rectal cancer patients treated with neoadjuvant therapy and resection between 2016 and 2025, drawn from a prospectively maintained registry. pCR was defined as ypT0N0 (no residual invasive tumour in the rectal wall or in the regional lymph nodes on the resection specimen). Two published clinical models (Wang and colleagues; Tan and colleagues) were applied using their original coefficients and assessed for discrimination and calibration; the better-performing model was then adjusted to the local data and its clinical utility was examined via decision-curve analysis. A local six-predictor model was developed and internally validated via bootstrappaing. Reporting followed TRIPOD and STROBE guidelines. Results: Of 425 treated and resected patients, 85 achieved pCR (20.0%). The pCR yield differed markedly by regimen, from 27.9% with total neoadjuvant therapy and 22.8% with chemoradiotherapy to 10.3% with short-course radiotherapy. The model of Wang and colleagues separated responders from non-responders only modestly (c-statistic 0.62, 95% confidence interval 0.54-0.69), and its predictors' effects proved nearly twice as strong in our patients (slope 0.57); the model of Tan and colleagues performed worse (c-statistic 0.58). A locally refitted model performed no better (optimism-corrected c-statistic 0.60). Adjusting the best model to the local data brought its risk estimates closer to observed responses but did not sharpen discrimination, and decision-curve analysis showed only a small net benefit over default strategies. Conclusions: Two established clinical models for pCR could only be modestly applied to a contemporary European cohort; the risks they predicted overshot what we observed, and local refitting changed nothing-a low ceiling that lies in the predictors, not their coefficients. A clinical model alone should not be used to identify who is offered organ preservation.