More than a decade of randomized controlled trials in prostate cancer has established a positive radiation dose response at moderate doses and a consistently low α/β ratio in the linear quadratic model for moderate hypofractionation. The recently published large randomized trial of ultrahypofractionated prostate cancer radiation therapy adds substantially to our current knowledge of dose response and fractionation sensitivity.
Randomized trials of dose escalation and hypofractionation of radiation therapy were meta-analyzed to yield the overall best estimate of the α/β ratio. Additionally, a putative saturation of dose effect previously reported at approximately 80 Gy EQD2 was investigated by mapping the relative effectiveness assessed at 5 years onto a single reference dose-response curve.
Meta-analysis of 14 randomized trials including 13,384 patients yielded a best estimate of α/β = 1.6 Gy (95% confidence interval, 1.3-2.0 Gy) but with highly significant heterogeneity (I2 = 70%, P = .0005). Further analysis indicated an association between increasing dose per fraction in the experimental arm and increasing α/β ratio (slope, 0.6 Gy increase in α/β per Gy increase in fraction size; P = .017). This deviation from the linear quadratic model could, however, also be explained by biochemical control maxing out at doses above approximately 80 Gy.
Biochemical control data from randomized controlled trials of dose-per-fraction escalation in prostate cancer radiation therapy are inconsistent with the presence of a constant fractionation sensitivity in the linear-quadratic model and/or a monotonic dose response for biochemical control beyond 80 Gy equivalent dose. These observations have a potential effect on the optimal doses in future trials and the interpretation of ongoing trials of ultrahypofractionation.
International journal of radiation oncology, biology, physics. 2020 Jan 25 [Epub]
Ivan R Vogelius, Søren M Bentzen
Department of Oncology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark; Department of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland. Electronic address: ., Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland; Division of Biostatistics and Bioinformatics, University of Maryland Greenebaum Comprehensive Cancer Center, Baltimore, Maryland.