Validation of a Predictive Model After Complete Response in Rectal Cancer

Overview

Background of the study: Prediction of rectal tumor response after chemoradiotherapy (CRT) might be helpful in individualizing treatment strategies, i.e., selecting patients who need less invasive surgery or another radiotherapy strategy instead of resection. For rectal cancer it is known that 10-30% of the patients will respond with a pathologic complete response (pCR) after CRT. From a retrospective study with multivariate analysis of both clinical and 2-\[18F\] fluoro-2-deoxy-D-glucose and positron emission tomography (FDG-PET) data, it was found that adding FDG-PET data collected before and after CRT leads to a more predictive model compared to evaluating only pretreatment clinical data. To validate this model, this registration study is proposed. Furthermore, it has been found that FDG-PET during treatment is very predictive for response and a more favorable time point to adapt treatment. Also, there are indications that adding blood biomarkers to the data, results in higher accuracy for response prediction compared to clinical and imaging data alone. Therefore, FDG-PET during treatment and blood sampling are included in the protocol to improve the accuracy of the prediction models. Objective of the study: The long-term research objective is to be able to select rectum cancer patients who could receive a less invasive treatment. If prediction of response is possible, surgery may be avoided when complete response after chemoradiotherapy is expected or performed with smaller incisions if stage reduction is significant. This support decision system helps to individualize patient treatment and can improve the quality of life for the patient. Study design: 28x radiotherapy. On day 15 of radiotherapy en 8 weeks after radiotherapy: 1 PET-CT scan Before radiotherapy, on day 15 and 8 weeks after radiotherapy: blood sample taken.

General objective The long-term research objective is to be able to select rectum cancer patients who could receive a less invasive treatment. If prediction of response is possible, surgery may be avoided when complete response after chemoradiotherapy is expected or performed with smaller incisions if stage reduction is significant. This support decision system helps to individualize patient treatment and can improve the quality of life for the patient. Aim of the study The main aim is to validate a predictive model for pathologic complete response (ypT0N0) in rectal cancer patients treated with chemoradiotherapy by multi-centric prospective data collection. The second aim is to collect extra data for improvement of the accuracy of the prediction models with new variables. This new model will be validated later in the model development process. Hypothesis General hypothesis: The validated accuracy of predictive models for pathologic complete response after chemoradiotherapy in rectal cancer patients is high enough to tailor treatment (surgery/non-surgery and/or administer extra radiation boosts) in clinical practice. Specific hypotheses: 1. The performance of the developed models on the validation data is at least equal to the performance achieved during the model development process. 2. The performance of a new model based on the addition of variables performs better than the previous model