Purpose: To determine a self-consistent set of radiobiological parameters in prostate cancer. Methods and Materials: A method to estimate intrinsic radiosensitivity (α), fractionation sensitivity (α/β), repopulation doubling time, number of clonogens, and kick-off time for accelerated repopulation of prostate cancer has been developed. Based on the generalized linear-quadratic model and without assuming the isoeffective hypothesis, the potential applications of the method were investigated using the clinical outcome of biochemical relapse-free survival recently reviewed in the literature. The strengths and limitations of the method, regarding the fitted parameters and 95% confidence intervals (CIs), are also discussed. Results: Our best estimate of α/β is 2.96 Gy (95% CI 2.41-3.53 Gy). The corresponding α value is 0.16 Gy-1 (95% CI 0.14-0.18 Gy -1), which is compatible with a realistic number of clonogens: 6.5 × 106 (95% CI 1.5 × 106-2.1 × 10 7). The estimated cell doubling time is 5.1 days (95% CI 4.2-7.2 days), very low if compared with that reported in the literature. This corresponds to the dose required to offset the repopulation occurring in 1 day of 0.52 Gy/d (95% CI 0.32-0.68 Gy/d). However, a long kick-off time of 31 days (95% CI 22-41 days) from the start of radiation therapy was found. Conclusion: The proposed analytic/graphic method has allowed the fitting of clinical data, providing a self-consistent set of radiobiological parameters for prostate cancer. With our analysis we confirm a low value for α/β with a correspondingly high value of intrinsic radiosensitivity, a realistic average number of clonogens, a long kick-off time for accelerated repopulation, and a surprisingly fast repopulation that suggests the involvement of subpopulations of specifically tumorigenic stem cells during continuing radiation therapy.
|Journal||International Journal of Radiation Oncology Biology Physics|
|Publication status||Published - Apr 1 2013|
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Cancer Research