International journal of radiation oncology, biology, physics · 2025
Incorporating Individual Early Response in the Dose-Effect Relationship of Complete Pathological Response Following Neoadjuvant Radiochemotherapy for Rectal Cancer.
СтатьяВалидационное исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Cicchetti Alessandro, Mori Martina, Passoni Paolo, Broggi Sara, Reni Michele, De Cobelli Francesco, Rosati Riccardo, Placidi Lorenzo, Romano Angela, Chiloiro Giuditta, Boldrini Luca, Gambacorta Maria Antonietta, Del Vecchio Antonella, Di Muzio Nadia Gisella, Fiorino Claudio
Аннотация
PURPOSE: To develop and externally validate a model predicting pathological complete response (pCR) in patients with rectal cancer treated with neoadjuvant radiochemotherapy. The approach combines the classical logit dose-effect curve with individual early response assessed by magnetic resonance imaging during radiochemotherapy.
METHODS AND MATERIALS: The dose-response model incorporating the early regression index (ERI) was derived from 2 published data sets. A population-averaged dose-response curve was obtained by fitting data from a recent meta-analysis. Then, an ERI-based model for pCR prediction was fit to 95 patients treated at San Raffaele Hospital; ERI was incorporated as a dynamic dose-modifying factor in the Hill model, based on Equivalent Uniform Dose to 2 Gy and including the time factor. The model was validated on an external cohort of 132 patients treated at Policlinico Gemelli with standard and dose-escalated schedules. Calibration plots, area under the curve, and average precision were used to assess performance. Recalibration refined predictions for the external cohort.
RESULTS: The final Hill model showed best-fit values of TD50 = 52.2 Gy, dynamic dose-modifying factor = (0.89 + 0.02 × ERI), and steepness k = 5.91 + 0.11 × ERI. The validation cohort had a pCR rate of 35.6%. Agreement between prediction and observed rates was high (offset, 0; slope, 0.84). Discriminative ability was robust (area under the curve, 0.77; average precision, 0.65 vs 0.356 for baseline). ERI-stratified dose-pCR relationships confirmed predictive value across 4 ERI categories: highly responsive (ERI, 1-6.9; pCR, 65%), moderately responsive (ERI, 6.9-13.1; pCR, 55%), poorly responsive (ERI, 13.1-36; pCR, 14% and 35%), and nonresponsive (ERI, >36; pCR, 0%). Predictions aligned with results using median ERI values per group.
CONCLUSIONS: The ERI-dose model was validated on an external cohort with distinct radiation therapy regimens. Dose escalation of 8.5 Equivalent Uniform Dose to 2 Gy in moderate-to-good responders corresponds to an increase of approximately 20% in pCR, whereas no benefit was reported in nonresponders. These findings highlight the model's potential for personalizing radiation therapy protocols by optimizing dose escalation based on ERI.
METHODS AND MATERIALS: The dose-response model incorporating the early regression index (ERI) was derived from 2 published data sets. A population-averaged dose-response curve was obtained by fitting data from a recent meta-analysis. Then, an ERI-based model for pCR prediction was fit to 95 patients treated at San Raffaele Hospital; ERI was incorporated as a dynamic dose-modifying factor in the Hill model, based on Equivalent Uniform Dose to 2 Gy and including the time factor. The model was validated on an external cohort of 132 patients treated at Policlinico Gemelli with standard and dose-escalated schedules. Calibration plots, area under the curve, and average precision were used to assess performance. Recalibration refined predictions for the external cohort.
RESULTS: The final Hill model showed best-fit values of TD50 = 52.2 Gy, dynamic dose-modifying factor = (0.89 + 0.02 × ERI), and steepness k = 5.91 + 0.11 × ERI. The validation cohort had a pCR rate of 35.6%. Agreement between prediction and observed rates was high (offset, 0; slope, 0.84). Discriminative ability was robust (area under the curve, 0.77; average precision, 0.65 vs 0.356 for baseline). ERI-stratified dose-pCR relationships confirmed predictive value across 4 ERI categories: highly responsive (ERI, 1-6.9; pCR, 65%), moderately responsive (ERI, 6.9-13.1; pCR, 55%), poorly responsive (ERI, 13.1-36; pCR, 14% and 35%), and nonresponsive (ERI, >36; pCR, 0%). Predictions aligned with results using median ERI values per group.
CONCLUSIONS: The ERI-dose model was validated on an external cohort with distinct radiation therapy regimens. Dose escalation of 8.5 Equivalent Uniform Dose to 2 Gy in moderate-to-good responders corresponds to an increase of approximately 20% in pCR, whereas no benefit was reported in nonresponders. These findings highlight the model's potential for personalizing radiation therapy protocols by optimizing dose escalation based on ERI.