Randomized test-treatment studies with an outlook on adaptive designs

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Randomized test-treatment studies with an outlook on adaptive designs. / Hot, Amra; Bossuyt, Patrick M; Gerke, Oke; Wahl, Simone; Vach, Werner; Zapf, Antonia.

In: BMC MED RES METHODOL, Vol. 21, No. 1, 01.06.2021, p. 110.

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@article{9ed72289543f46a69418105594cc7b14,
title = "Randomized test-treatment studies with an outlook on adaptive designs",
abstract = "BACKGROUND: Diagnostic accuracy studies aim to examine the diagnostic accuracy of a new experimental test, but do not address the actual merit of the resulting diagnostic information to a patient in clinical practice. In order to assess the impact of diagnostic information on subsequent treatment strategies regarding patient-relevant outcomes, randomized test-treatment studies were introduced. Various designs for randomized test-treatment studies, including an evaluation of biomarkers as part of randomized biomarker-guided treatment studies, are suggested in the literature, but the nomenclature is not consistent.METHODS: The aim was to provide a clear description of the different study designs within a pre-specified framework, considering their underlying assumptions, advantages as well as limitations and derivation of effect sizes required for sample size calculations. Furthermore, an outlook on adaptive designs within randomized test-treatment studies is given.RESULTS: The need to integrate adaptive design procedures in randomized test-treatment studies is apparent. The derivation of effect sizes induces that sample size calculation will always be based on rather vague assumptions resulting in over- or underpowered study results. Therefore, it might be advantageous to conduct a sample size re-estimation based on a nuisance parameter during the ongoing trial.CONCLUSIONS: Due to their increased complexity, compared to common treatment trials, the implementation of randomized test-treatment studies poses practical challenges including a huge uncertainty regarding study parameters like the expected outcome in specific subgroups or disease prevalence which might affect the sample size calculation. Since research on adaptive designs within randomized test-treatment studies is limited so far, further research is recommended.",
author = "Amra Hot and Bossuyt, {Patrick M} and Oke Gerke and Simone Wahl and Werner Vach and Antonia Zapf",
year = "2021",
month = jun,
day = "1",
doi = "10.1186/s12874-021-01293-y",
language = "English",
volume = "21",
pages = "110",
journal = "BMC MED RES METHODOL",
issn = "1471-2288",
publisher = "BioMed Central Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Randomized test-treatment studies with an outlook on adaptive designs

AU - Hot, Amra

AU - Bossuyt, Patrick M

AU - Gerke, Oke

AU - Wahl, Simone

AU - Vach, Werner

AU - Zapf, Antonia

PY - 2021/6/1

Y1 - 2021/6/1

N2 - BACKGROUND: Diagnostic accuracy studies aim to examine the diagnostic accuracy of a new experimental test, but do not address the actual merit of the resulting diagnostic information to a patient in clinical practice. In order to assess the impact of diagnostic information on subsequent treatment strategies regarding patient-relevant outcomes, randomized test-treatment studies were introduced. Various designs for randomized test-treatment studies, including an evaluation of biomarkers as part of randomized biomarker-guided treatment studies, are suggested in the literature, but the nomenclature is not consistent.METHODS: The aim was to provide a clear description of the different study designs within a pre-specified framework, considering their underlying assumptions, advantages as well as limitations and derivation of effect sizes required for sample size calculations. Furthermore, an outlook on adaptive designs within randomized test-treatment studies is given.RESULTS: The need to integrate adaptive design procedures in randomized test-treatment studies is apparent. The derivation of effect sizes induces that sample size calculation will always be based on rather vague assumptions resulting in over- or underpowered study results. Therefore, it might be advantageous to conduct a sample size re-estimation based on a nuisance parameter during the ongoing trial.CONCLUSIONS: Due to their increased complexity, compared to common treatment trials, the implementation of randomized test-treatment studies poses practical challenges including a huge uncertainty regarding study parameters like the expected outcome in specific subgroups or disease prevalence which might affect the sample size calculation. Since research on adaptive designs within randomized test-treatment studies is limited so far, further research is recommended.

AB - BACKGROUND: Diagnostic accuracy studies aim to examine the diagnostic accuracy of a new experimental test, but do not address the actual merit of the resulting diagnostic information to a patient in clinical practice. In order to assess the impact of diagnostic information on subsequent treatment strategies regarding patient-relevant outcomes, randomized test-treatment studies were introduced. Various designs for randomized test-treatment studies, including an evaluation of biomarkers as part of randomized biomarker-guided treatment studies, are suggested in the literature, but the nomenclature is not consistent.METHODS: The aim was to provide a clear description of the different study designs within a pre-specified framework, considering their underlying assumptions, advantages as well as limitations and derivation of effect sizes required for sample size calculations. Furthermore, an outlook on adaptive designs within randomized test-treatment studies is given.RESULTS: The need to integrate adaptive design procedures in randomized test-treatment studies is apparent. The derivation of effect sizes induces that sample size calculation will always be based on rather vague assumptions resulting in over- or underpowered study results. Therefore, it might be advantageous to conduct a sample size re-estimation based on a nuisance parameter during the ongoing trial.CONCLUSIONS: Due to their increased complexity, compared to common treatment trials, the implementation of randomized test-treatment studies poses practical challenges including a huge uncertainty regarding study parameters like the expected outcome in specific subgroups or disease prevalence which might affect the sample size calculation. Since research on adaptive designs within randomized test-treatment studies is limited so far, further research is recommended.

U2 - 10.1186/s12874-021-01293-y

DO - 10.1186/s12874-021-01293-y

M3 - SCORING: Journal article

C2 - 34074263

VL - 21

SP - 110

JO - BMC MED RES METHODOL

JF - BMC MED RES METHODOL

SN - 1471-2288

IS - 1

ER -