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Development of the individual participant data integrity tool for assessing the integrity of randomised trials using individual participant data.
Hunter, Kylie E; Aberoumand, Mason; Libesman, Sol; Sotiropoulos, James X; Williams, Jonathan G; Li, Wentao; Aagerup, Jannik; Mol, Ben W; Wang, Rui; Barba, Angie; Shrestha, Nipun; Webster, Angela C; Seidler, Anna Lene.
Afiliación
  • Hunter KE; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
  • Aberoumand M; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
  • Libesman S; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
  • Sotiropoulos JX; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
  • Williams JG; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
  • Li W; Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC, Australia.
  • Aagerup J; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
  • Mol BW; Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC, Australia.
  • Wang R; Department of Obstetrics and Gynaecology, Monash University, Clayton, VIC, Australia.
  • Barba A; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
  • Shrestha N; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
  • Webster AC; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
  • Seidler AL; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
Res Synth Methods ; 2024 Aug 18.
Article en En | MEDLINE | ID: mdl-39155538
ABSTRACT
Increasing integrity concerns in medical research have prompted the development of tools to detect untrustworthy studies. Existing tools primarily assess published aggregate data (AD), though scrutiny of individual participant data (IPD) is often required to detect trustworthiness issues. Thus, we developed the IPD Integrity Tool for detecting integrity issues in randomised trials with IPD available. This manuscript describes the development of this tool. We conducted a literature review to collate and map existing integrity items. These were discussed with an expert advisory group; agreed items were included in a standardised tool and automated where possible. We piloted this tool in two IPD meta-analyses (including 116 trials) and conducted preliminary validation checks on 13 datasets with and without known integrity issues. We identified 120 integrity items 54 could be conducted using AD, 48 required IPD, and 18 were possible with AD, but more comprehensive with IPD. An initial reduced tool was developed through consensus involving 13 advisors, featuring 11 AD items across four domains, and 12 IPD items across eight domains. The tool was iteratively refined throughout piloting and validation. All studies with known integrity issues were accurately identified during validation. The final tool includes seven AD domains with 13 items and eight IPD domains with 18 items. The quality of evidence informing healthcare relies on trustworthy data. We describe the development of a tool to enable researchers, editors, and others to detect integrity issues using IPD. Detailed instructions for its application are published as a complementary manuscript in this issue.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Res Synth Methods Año: 2024 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Res Synth Methods Año: 2024 Tipo del documento: Article País de afiliación: Australia