Development and Validation of a Predictive Model for Toxicity of Neoadjuvant Chemoradiotherapy in Rectal Cancer in the CAO/ARO/AIO-04 Phase III Trial.

Clicks: 104
ID: 276124
2022
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
There is a lack of predictive models to identify patients at risk of high neoadjuvant chemoradiotherapy (CRT)-related acute toxicity in rectal cancer.The CAO/ARO/AIO-04 trial was divided into a development (n = 831) and a validation (n = 405) cohort. Using a best subset selection approach, predictive models for grade 3-4 acute toxicity were calculated including clinicopathologic characteristics, pretreatment blood parameters, and baseline results of quality-of-life questionnaires and evaluated using the area under the ROC curve. The final model was internally and externally validated.In the development cohort, 155 patients developed grade 3-4 toxicities due to CRT. In the final evaluation, 15 parameters were included in the logistic regression models using best-subset selection. BMI, gender, and emotional functioning remained significant for predicting toxicity, with a discrimination ability adjusted for overfitting of AUC 0.687. The odds of experiencing high-grade toxicity were 3.8 times higher in the intermediate and 6.4 times higher in the high-risk group ( < 0.001). Rates of toxicity ( = 0.001) and low treatment adherence ( = 0.007) remained significantly different in the validation cohort, whereas discrimination ability was not significantly worse (DeLong test 0.09).We developed and validated a predictive model for toxicity using gender, BMI, and emotional functioning. Such a model could help identify patients at risk for treatment-related high-grade toxicity to assist in treatment guidance and patient participation in shared decision making.
Reference Key
diefenhardt2022developmentcancers Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Diefenhardt, Markus;Martin, Daniel;Ludmir, Ethan B;Fleischmann, Maximilian;Hofheinz, Ralf-Dieter;Ghadimi, Michael;Kosmala, Rebekka;Polat, Bülent;Friede, Tim;Minsky, Bruce D;Rödel, Claus;Fokas, Emmanouil;
Journal Cancers
Year 2022
DOI
4425
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.