P Mbanu1, E Vasquez Osorio2, H Mistry3, L Malcomson4, S Yousif5, M Aznar2, R Kochhar6, M Van Herk2, A G Renehan4, M P Saunders7. 1. Department of Clinical Oncology, Christie NHS Foundation Trust, Manchester, United Kingdom. Electronic address: Peter.mbanu1@nhs.net. 2. Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom. 3. Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom; Division of Pharmacy, University of Manchester, Manchester, United Kingdom. 4. Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom; Colorectal and Peritoneal Oncology Centre, Christie NHS Foundation Trust, Manchester, United Kingdom. 5. Department of Clinical Oncology, Lancashire Teaching Hospital, Preston, United Kingdom. 6. Department of Radiological Oncology, Christie NHS Foundation Trust, Manchester, United Kingdom. 7. Department of Clinical Oncology, Christie NHS Foundation Trust, Manchester, United Kingdom.
Abstract
PURPOSE: Prediction of clinical complete response in rectal cancer before neoadjuvant chemo-radiotherapy treatment enables treatment selection. Patients predicted to have complete response could have chemo-radiotherapy, and others could have additional doublet chemotherapy at this stage of their treatment to improve their overall outcome. This work investigates the role of clinical variables in predicting clinical complete response. METHOD: Using the UK-based OnCoRe database (2008 to 2019), we performed a propensity-score matched study of 322 patients who received neoadjuvant chemoradiotherapy. We collected pre-treatment clinic-pathological, inflammatory and radiotherapy-related characteristics. We determined the odds for the occurrence of cCR using conditional logistic regression models. We derived the post-model Area under the Curve (AUC) as an indicator of discrimination performance and stated a priori that an AUC of 0.75 or greater was required for potential clinical utility. RESULTS: Pre-treatment tumour diameter, mrT-stage, haemoglobin, alkaline phosphate and total radiotherapy depths were associated with cCR on univariable and multivariable analysis. Additionally, neutrophil to lymphocyte ratio (NLR), neutrophil-monocyte to lymphocyte ratio (NMLR), lymphocyte count and albumin were all significantly associated with cCR on multivariable analysis. A nomogram using the above parameters was developed with a resulting ROC AUC of 0.75. CONCLUSION: We identified routine clinic-pathological, inflammatory and radiotherapy-related variables which are independently associated with cCR. A nomogram was developed to predict cCR. The performance characteristics from this model were on the prior clinical utility threshold. Additional research is required to develop more associated variables to better select patients with rectal cancer undergoing chemoradiotherapy who may benefit from pursuing a W&W strategy. Crown
PURPOSE: Prediction of clinical complete response in rectal cancer before neoadjuvant chemo-radiotherapy treatment enables treatment selection. Patients predicted to have complete response could have chemo-radiotherapy, and others could have additional doublet chemotherapy at this stage of their treatment to improve their overall outcome. This work investigates the role of clinical variables in predicting clinical complete response. METHOD: Using the UK-based OnCoRe database (2008 to 2019), we performed a propensity-score matched study of 322 patients who received neoadjuvant chemoradiotherapy. We collected pre-treatment clinic-pathological, inflammatory and radiotherapy-related characteristics. We determined the odds for the occurrence of cCR using conditional logistic regression models. We derived the post-model Area under the Curve (AUC) as an indicator of discrimination performance and stated a priori that an AUC of 0.75 or greater was required for potential clinical utility. RESULTS: Pre-treatment tumour diameter, mrT-stage, haemoglobin, alkaline phosphate and total radiotherapy depths were associated with cCR on univariable and multivariable analysis. Additionally, neutrophil to lymphocyte ratio (NLR), neutrophil-monocyte to lymphocyte ratio (NMLR), lymphocyte count and albumin were all significantly associated with cCR on multivariable analysis. A nomogram using the above parameters was developed with a resulting ROC AUC of 0.75. CONCLUSION: We identified routine clinic-pathological, inflammatory and radiotherapy-related variables which are independently associated with cCR. A nomogram was developed to predict cCR. The performance characteristics from this model were on the prior clinical utility threshold. Additional research is required to develop more associated variables to better select patients with rectal cancer undergoing chemoradiotherapy who may benefit from pursuing a W&W strategy. Crown