A potential for seamless designs in diagnostic research could be identified.


Journal

Journal of clinical epidemiology
ISSN: 1878-5921
Titre abrégé: J Clin Epidemiol
Pays: United States
ID NLM: 8801383

Informations de publication

Date de publication:
01 2021
Historique:
received: 29 03 2020
revised: 26 08 2020
accepted: 23 09 2020
pubmed: 30 9 2020
medline: 7 9 2021
entrez: 29 9 2020
Statut: ppublish

Résumé

New diagnostic tests to identify a well-established disease state must undergo a series of scientific studies from test construction to finally demonstrating a societal impact. Traditionally, these studies are performed with substantial time gaps in between, resulting in a long time period from the initial idea to roll out in clinical practice including reimbursement. Seamless designs allowing us to combine a sequence of studies in one protocol may hence accelerate this process. Currently, a systematic investigation of the potential of seamless designs in diagnostic research is lacking. We identify major study types in diagnostic research and their basic characteristics with respect to the application of seamless designs. This information is used to identify major hurdles and opportunities for seamless designs. The following major study types were identified: Variable construction studies, cut point finding studies, variable value studies, single-arm accuracy studies, comparative accuracy studies, change-in-management studies, observational discordant pair studies, randomized discordant pair studies, and randomized diagnostic studies. The following characteristics were identified: Type of recruitment (case-control vs. population-based), application of a reference standard, inclusion of a comparator, paired or unpaired application of a comparator, assessment of patient-relevant outcomes, and possibility for blinding of test results. Two basic hurdles could be identified: 1) Accuracy studies are hard to combine with postaccuracy studies in a seamless design for the following reasons. First, because the former are required to justify the latter and application of a reference test in outcome studies may be a threat to the integrity of the study. 2) Randomized diagnostic studies are probably best placed as singular studies at the end of the process, as all other questions should be clarified before performing such a study. However, otherwise there is a substantial potential for seamless designs. All steps from the construction to the comparison with the comparator can be combined in one protocol. This may include a switch from case-control to population-based recruitment as well as a switch from a single-arm study to a comparative accuracy study. In addition, change-in-management studies can be combined with an outcome study in discordant pairs. There is a potential for seamless designs in diagnostic research. It is wise to have the whole sequence of necessary studies in mind and to plan a full programme than rather individual studies one by one.

Sections du résumé

BACKGROUND AND OBJECTIVE
New diagnostic tests to identify a well-established disease state must undergo a series of scientific studies from test construction to finally demonstrating a societal impact. Traditionally, these studies are performed with substantial time gaps in between, resulting in a long time period from the initial idea to roll out in clinical practice including reimbursement. Seamless designs allowing us to combine a sequence of studies in one protocol may hence accelerate this process. Currently, a systematic investigation of the potential of seamless designs in diagnostic research is lacking.
METHODS
We identify major study types in diagnostic research and their basic characteristics with respect to the application of seamless designs. This information is used to identify major hurdles and opportunities for seamless designs.
RESULTS
The following major study types were identified: Variable construction studies, cut point finding studies, variable value studies, single-arm accuracy studies, comparative accuracy studies, change-in-management studies, observational discordant pair studies, randomized discordant pair studies, and randomized diagnostic studies. The following characteristics were identified: Type of recruitment (case-control vs. population-based), application of a reference standard, inclusion of a comparator, paired or unpaired application of a comparator, assessment of patient-relevant outcomes, and possibility for blinding of test results. Two basic hurdles could be identified: 1) Accuracy studies are hard to combine with postaccuracy studies in a seamless design for the following reasons. First, because the former are required to justify the latter and application of a reference test in outcome studies may be a threat to the integrity of the study. 2) Randomized diagnostic studies are probably best placed as singular studies at the end of the process, as all other questions should be clarified before performing such a study. However, otherwise there is a substantial potential for seamless designs. All steps from the construction to the comparison with the comparator can be combined in one protocol. This may include a switch from case-control to population-based recruitment as well as a switch from a single-arm study to a comparative accuracy study. In addition, change-in-management studies can be combined with an outcome study in discordant pairs.
CONCLUSION
There is a potential for seamless designs in diagnostic research. It is wise to have the whole sequence of necessary studies in mind and to plan a full programme than rather individual studies one by one.

Identifiants

pubmed: 32991994
pii: S0895-4356(20)31105-7
doi: 10.1016/j.jclinepi.2020.09.019
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

51-59

Informations de copyright

Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

Auteurs

Werner Vach (W)

Basel Academy for Quality and Research in Medicine, Basel, Switzerland, & Department of Environmental Sciences, University of Basel, Basel, Switzerland. Electronic address: werner.vach@unibas.ch.

Eric Bibiza (E)

Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Oke Gerke (O)

Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark.

Patrick M Bossuyt (PM)

Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam University Medical Centers Amsterdam, Netherlands.

Tim Friede (T)

Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.

Antonia Zapf (A)

Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

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