Early stopping in clinical PET studies: How to reduce expense and exposure
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Early stopping in clinical PET studies : How to reduce expense and exposure. / Svensson, Jonas E.; Schain, Martin; Knudsen, Gitte M.; Ogden, R. Todd; Plavén-Sigray, Pontus.
In: Journal of Cerebral Blood Flow and Metabolism, Vol. 41, No. 11, 2021, p. 2805-2819.Research output: Contribution to journal › Review › Research › peer-review
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TY - JOUR
T1 - Early stopping in clinical PET studies
T2 - How to reduce expense and exposure
AU - Svensson, Jonas E.
AU - Schain, Martin
AU - Knudsen, Gitte M.
AU - Ogden, R. Todd
AU - Plavén-Sigray, Pontus
N1 - Publisher Copyright: © The Author(s) 2021.
PY - 2021
Y1 - 2021
N2 - Clinical positron emission tomography (PET) research is costly and entails exposing participants to radioactivity. Researchers should therefore aim to include just the number of subjects needed to fulfill the purpose of the study. In this tutorial we show how to apply sequential Bayes Factor testing in order to stop the recruitment of subjects in a clinical PET study as soon as enough data have been collected to make a conclusion. By using simulations, we demonstrate that it is possible to stop a study early, while keeping the number of erroneous conclusions low. We then apply sequential Bayes Factor testing to a real PET data set and show that it is possible to obtain support in favor of an effect while simultaneously reducing the sample size with 30%. Using this procedure allows researchers to reduce expense and radioactivity exposure for a range of effect sizes relevant for PET research.
AB - Clinical positron emission tomography (PET) research is costly and entails exposing participants to radioactivity. Researchers should therefore aim to include just the number of subjects needed to fulfill the purpose of the study. In this tutorial we show how to apply sequential Bayes Factor testing in order to stop the recruitment of subjects in a clinical PET study as soon as enough data have been collected to make a conclusion. By using simulations, we demonstrate that it is possible to stop a study early, while keeping the number of erroneous conclusions low. We then apply sequential Bayes Factor testing to a real PET data set and show that it is possible to obtain support in favor of an effect while simultaneously reducing the sample size with 30%. Using this procedure allows researchers to reduce expense and radioactivity exposure for a range of effect sizes relevant for PET research.
KW - Bayes factor
KW - Early stopping
KW - positron emission tomography
KW - sequential testing
KW - tutorial
U2 - 10.1177/0271678X211017796
DO - 10.1177/0271678X211017796
M3 - Review
C2 - 34018825
AN - SCOPUS:85106419996
VL - 41
SP - 2805
EP - 2819
JO - Journal of Cerebral Blood Flow and Metabolism
JF - Journal of Cerebral Blood Flow and Metabolism
SN - 0271-678X
IS - 11
ER -
ID: 272236593