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Verification of QUANTEC Lyman Kutcher Burman (LKB) Model for Grade>=2(2+) Late Rectal Complication Rates Using a Database of 79 Prostate Patients Treated with IMRT

M Fatyga

M Fatyga1*, S Schild1 , S Vora1 , M Schild1 , W Wong1 , X Liu2 , J Li2 , T Wu2 , (1) Mayo Clinic Arizona, Phoenix, AZ, (2) Arizona State University, Tempe, AZ


SU-E-T-803 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall

QUANTEC review of best parameters for the LKB NTCP model of rectal complications is based exclusively on datasets obtained with 3D conformal techniques. The report suggests that inherent differences in rectal dose distributions obtained with IMRT techniques could require modification of the parameters which provide the best fit to clinical data.

We compiled a database of 79 prostate patients who were treated with an IMRT technique to a dose of 77.4 Gy, 1.8Gy/fx, with an integrated boost to 81-83Gy in a sub-volume of a prostate which was identified on a pre-treatment MRI study. Rectal toxicities were graded according to CTCAE v4 by a physician who retrospectively reviewed patient’s medical records. Late grade 2+ toxicities were defined as toxicities occurring later than 90 days following the end of treatment. We defined the model in terms of parameters, m,n and TD_50, as recommended in the Quantec report. We converted the dose to 2Gy equivalent dose using linear-quadratic model with alpha over beta of 3Gy. We applied QUANTEC model to our data and compared results to our own fit of LKB model using two sample t-test.

Grade 2+ late rectal toxicity occurred in 4% (3/79 patients). The best fit of LKB model to data was obtained for n = 0.26, m = 0.25, and TD_50 = 81.53Gy. The two sample t-test yielded p value of 0.67. Average NTCP predicted by our parametrization is 3.8% while average NTCP predicted by QUANTEC parametrization is 3.5%.

Predictions of late rectal toxicities in IMRT patients using LKB model with parameters from QUANTEC report match observed toxicity rates. Independent fit of LKB model to IMRT data produces somewhat different parameter set, but two parametrizations are equivalent within statistical uncertainties.

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