Random forests to predict rectal toxicity following prostate cancer radiation therapy - Abstract

PURPOSE: To propose a random forest normal tissue complication probability (RF-NTCP) model to predict late rectal toxicity following prostate cancer radiation therapy, and to compare its performance to that of classic NTCP models.

METHODS AND MATERIALS: Clinical data and dose-volume histograms (DVH) were collected from 261 patients who received 3-dimensional conformal radiation therapy for prostate cancer with at least 5 years of follow-up. The series was split 1000 times into training and validation cohorts. A RF was trained to predict the risk of 5-year overall rectal toxicity and bleeding. Parameters of the Lyman-Kutcher-Burman (LKB) model were identified and a logistic regression model was fit. The performance of all the models was assessed by computing the area under the receiving operating characteristic curve (AUC).

RESULTS: The 5-year grade ≥2 overall rectal toxicity and grade ≥1 and grade ≥2 rectal bleeding rates were 16%, 25%, and 10%, respectively. Predictive capabilities were obtained using the RF-NTCP model for all 3 toxicity endpoints, including both the training and validation cohorts. The age and use of anticoagulants were found to be predictors of rectal bleeding. The AUC for RF-NTCP ranged from 0.66 to 0.76, depending on the toxicity endpoint. The AUC values for the LKB-NTCP were statistically significantly inferior, ranging from 0.62 to 0.69.

CONCLUSIONS: The RF-NTCP model may be a useful new tool in predicting late rectal toxicity, including variables other than DVH, and thus appears as a strong competitor to classic NTCP models.

Written by:
Ospina JD, Zhu J, Chira C, Bossi A, Delobel JB, Beckendorf V, Dubray B, Lagrange JL, Correa JC, Simon A, Acosta O, de Crevoisier R.   Are you the author?
LTSI, Université de Rennes 1, Rennes, France; INSERM, U1099, Rennes, France; Escuela de Estadística, Universidad Nacional de Colombia Sede Medellín, Medellín, Colombia; LTSI, Université de Rennes 1, Rennes, France; Laboratory of Image Science and Technology, Southeast University, Nanjing, PR China; Department of Radiation Physics, Shandong Cancer Hospital and Institute, Jinan, PR China; Centre de Recherche en Information Biomédical Sino-Français, Rennes, France; Département de Radiothérapie, Centre Eugène Marquis, Rennes, France; Département de Radiothérapie, Institut Gustave-Roussy, Villejuif, France; Département de Radiothérapie, Centre Alexis Vautrin, Nancy, France; Département de Radiothérapie, CRLCC Henri Becquerel, Rouen, France; Département de Radiothérapie, Hôpital Henri Mondor, Créteil, France; Escuela de Estadística, Universidad Nacional de Colombia Sede Medellín, Medellín, Colombia; Centre de Recherche en Information Biomédical Sino-Français, Rennes, France.  

Reference: Int J Radiat Oncol Biol Phys. 2014 Aug 1;89(5):1024-31.
doi: 10.1016/j.ijrobp.2014.04.027


PubMed Abstract
PMID: 25035205

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