BACKGROUND AND PURPOSE: The aim of this study was to investigate the impact of appropriate dosimetry quality assurance (QA) on patient number required in radiotherapy randomized control trials (RCT). MATERIALS AND METHODS: The steepness of clinical dose-response curves, gamma(clin.), was calculated by a convoluting a biological dose-response distribution and the distribution of technical and dosimetrical factors. Population size calculation was performed taking into account gamma(clin.) and expected difference in outcome between two arms of an RCT, for different levels of variation in dose to the patient population. RESULTS: Uncertainties in dose reduces gamma(clin.) to the largest extent when the initial gamma-value is high and less so for low gamma-value. Reduced uncertainty in dose led to a significant reduction in the number of patients required in an RCT if the expected difference between the experimental and conventional arm is small. The reduction in patient numbers is less when the differences between the conventional and experimental arm is larger. CONCLUSION: The number of patients required in an RCT may be reduced by introducing appropriate dosimetry QA as the risk of under-powering the study is minimized. Dosimetry QA in clinical studies is therefore cost-effective.
BACKGROUND AND PURPOSE: The aim of this study was to investigate the impact of appropriate dosimetry quality assurance (QA) on patient number required in radiotherapy randomized control trials (RCT). MATERIALS AND METHODS: The steepness of clinical dose-response curves, gamma(clin.), was calculated by a convoluting a biological dose-response distribution and the distribution of technical and dosimetrical factors. Population size calculation was performed taking into account gamma(clin.) and expected difference in outcome between two arms of an RCT, for different levels of variation in dose to the patient population. RESULTS: Uncertainties in dose reduces gamma(clin.) to the largest extent when the initial gamma-value is high and less so for low gamma-value. Reduced uncertainty in dose led to a significant reduction in the number of patients required in an RCT if the expected difference between the experimental and conventional arm is small. The reduction in patient numbers is less when the differences between the conventional and experimental arm is larger. CONCLUSION: The number of patients required in an RCT may be reduced by introducing appropriate dosimetry QA as the risk of under-powering the study is minimized. Dosimetry QA in clinical studies is therefore cost-effective.
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