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Title: Predicting Grade 3 Acute Diarrhea During Radiation Therapy for Rectal Cancer Using a Cutoff-Dose Logistic Regression Normal Tissue Complication Probability Model

Abstract

Purpose: Understanding the dose-volume relationship of small bowel irradiation and severe acute diarrhea may help reduce the incidence of this side effect during adjuvant treatment for rectal cancer. Methods and Materials: Consecutive patients treated curatively for rectal cancer were reviewed, and the maximum grade of acute diarrhea was determined. The small bowel was outlined on the treatment planning CT scan, and a dose-volume histogram was calculated for the initial pelvic treatment (45 Gy). Logistic regression models were fitted for varying cutoff-dose levels from 5 to 45 Gy in 5-Gy increments. The model with the highest LogLikelihood was used to develop a cutoff-dose normal tissue complication probability (NTCP) model. Results: There were a total of 152 patients (48% preoperative, 47% postoperative, 5% other), predominantly treated prone (95%) with a three-field technique (94%) and a protracted venous infusion of 5-fluorouracil (78%). Acute Grade 3 diarrhea occurred in 21%. The largest LogLikelihood was found for the cutoff-dose logistic regression model with 15 Gy as the cutoff-dose, although the models for 20 Gy and 25 Gy had similar significance. According to this model, highly significant correlations (p <0.001) between small bowel volumes receiving at least 15 Gy and toxicity exist in the considered patientmore » population. Similar findings applied to both the preoperatively (p = 0.001) and postoperatively irradiated groups (p = 0.001). Conclusion: The incidence of Grade 3 diarrhea was significantly correlated with the volume of small bowel receiving at least 15 Gy using a cutoff-dose NTCP model.« less

Authors:
 [1];  [2]
  1. University of Tuebingen, Tuebingen (Germany)
  2. William Beaumont Hospital, Royal Oak, Michigan (United States)
Publication Date:
OSTI Identifier:
21372241
Resource Type:
Journal Article
Journal Name:
International Journal of Radiation Oncology, Biology and Physics
Additional Journal Information:
Journal Volume: 77; Journal Issue: 1; Other Information: DOI: 10.1016/j.ijrobp.2009.04.048; PII: S0360-3016(09)00646-4; Copyright (c) 2010 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Journal ID: ISSN 0360-3016
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; CAT SCANNING; DIARRHEA; FLUOROURACILS; INFUSION; NEOPLASMS; PLANNING; RADIOTHERAPY; RECTUM; SIDE EFFECTS; THREE-DIMENSIONAL CALCULATIONS; TOXICITY; ANTIMETABOLITES; AZINES; BODY; COMPUTERIZED TOMOGRAPHY; DIAGNOSTIC TECHNIQUES; DIGESTIVE SYSTEM; DISEASES; DRUGS; GASTROINTESTINAL TRACT; HETEROCYCLIC COMPOUNDS; HYDROXY COMPOUNDS; INTAKE; INTESTINES; LARGE INTESTINE; MEDICINE; NUCLEAR MEDICINE; ORGANIC COMPOUNDS; ORGANIC FLUORINE COMPOUNDS; ORGANIC HALOGEN COMPOUNDS; ORGANIC NITROGEN COMPOUNDS; ORGANS; PYRIMIDINES; RADIOLOGY; SYMPTOMS; THERAPY; TOMOGRAPHY; URACILS

Citation Formats

Robertson, John M., E-mail: jrobertson@beaumont.ed, Soehn, Matthias, and Di, Yan. Predicting Grade 3 Acute Diarrhea During Radiation Therapy for Rectal Cancer Using a Cutoff-Dose Logistic Regression Normal Tissue Complication Probability Model. United States: N. p., 2010. Web. doi:10.1016/j.ijrobp.2009.04.048.
Robertson, John M., E-mail: jrobertson@beaumont.ed, Soehn, Matthias, & Di, Yan. Predicting Grade 3 Acute Diarrhea During Radiation Therapy for Rectal Cancer Using a Cutoff-Dose Logistic Regression Normal Tissue Complication Probability Model. United States. https://doi.org/10.1016/j.ijrobp.2009.04.048
Robertson, John M., E-mail: jrobertson@beaumont.ed, Soehn, Matthias, and Di, Yan. 2010. "Predicting Grade 3 Acute Diarrhea During Radiation Therapy for Rectal Cancer Using a Cutoff-Dose Logistic Regression Normal Tissue Complication Probability Model". United States. https://doi.org/10.1016/j.ijrobp.2009.04.048.
@article{osti_21372241,
title = {Predicting Grade 3 Acute Diarrhea During Radiation Therapy for Rectal Cancer Using a Cutoff-Dose Logistic Regression Normal Tissue Complication Probability Model},
author = {Robertson, John M., E-mail: jrobertson@beaumont.ed and Soehn, Matthias and Di, Yan},
abstractNote = {Purpose: Understanding the dose-volume relationship of small bowel irradiation and severe acute diarrhea may help reduce the incidence of this side effect during adjuvant treatment for rectal cancer. Methods and Materials: Consecutive patients treated curatively for rectal cancer were reviewed, and the maximum grade of acute diarrhea was determined. The small bowel was outlined on the treatment planning CT scan, and a dose-volume histogram was calculated for the initial pelvic treatment (45 Gy). Logistic regression models were fitted for varying cutoff-dose levels from 5 to 45 Gy in 5-Gy increments. The model with the highest LogLikelihood was used to develop a cutoff-dose normal tissue complication probability (NTCP) model. Results: There were a total of 152 patients (48% preoperative, 47% postoperative, 5% other), predominantly treated prone (95%) with a three-field technique (94%) and a protracted venous infusion of 5-fluorouracil (78%). Acute Grade 3 diarrhea occurred in 21%. The largest LogLikelihood was found for the cutoff-dose logistic regression model with 15 Gy as the cutoff-dose, although the models for 20 Gy and 25 Gy had similar significance. According to this model, highly significant correlations (p <0.001) between small bowel volumes receiving at least 15 Gy and toxicity exist in the considered patient population. Similar findings applied to both the preoperatively (p = 0.001) and postoperatively irradiated groups (p = 0.001). Conclusion: The incidence of Grade 3 diarrhea was significantly correlated with the volume of small bowel receiving at least 15 Gy using a cutoff-dose NTCP model.},
doi = {10.1016/j.ijrobp.2009.04.048},
url = {https://www.osti.gov/biblio/21372241}, journal = {International Journal of Radiation Oncology, Biology and Physics},
issn = {0360-3016},
number = 1,
volume = 77,
place = {United States},
year = {Sat May 01 00:00:00 EDT 2010},
month = {Sat May 01 00:00:00 EDT 2010}
}