错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Adaptive Universal Principles for Real-world Observational Studies (AUPROS): an approach to designing real-world observational studies for clinical, epidemiologic, and precision oncology research

  • Samir H. Barghout,
  • Nicholas Meti,
  • Simren Chotai,
  • Christina J. H. Kim,
  • Devalben Patel,
  • M. Catherine Brown,
  • Katrina Hueniken,
  • Luna J. Zhan,
  • Stavroula Raptis,
  • Faisal Al-Agha,
  • Christopher Deutschman,
  • Benjamin Grant,
  • Martha Pienkowski,
  • Patrick Moriarty,
  • John de Almeida,
  • David P. Goldstein,
  • Scott V. Bratman,
  • Frances A. Shepherd,
  • Ming S. Tsao,
  • Andrew N. Freedman,
  • Wei Xu,
  • Geoffrey Liu

摘要

The field of precision oncology has witnessed several advances that stimulated the development of new clinical trial designs and the emergence of real-world data (RWD) as an important resource for evidence generation in healthcare decision-making. Here, we highlight our experience with an innovative approach to a set of Adaptive, Universal Principles for Real-world Observational Studies (AUPROS). To demonstrate the utility of these principles, we used a mixed-methods approach to assess three studies that follow AUPROS at Princess Margaret Cancer Centre: (1) Molecular Epidemiology of ThorAcic Lesions (METAL), (2) Translational Head And NecK Study (THANKS), and (3) CAnadian CAncers With Rare Molecular Alterations (CARMA; NCT04151342). We performed resource assessments, stakeholder-directed surveys and discussions, analysis of funding, research output, collaborations, and a Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis. Based on these analyses, AUPROS is an approach that is applicable to a wide range of observational study designs. The universality of AUPROS allows for multi-purpose analyses of various RWD, and the adaptive nature creates opportunities for multi-source funding and collaborations. Following AUPROS can offer cost and logistical benefits and may lead to increased research productivity. Several challenges were identified pertinent to ethics approvals, sustainability, complex coordination, and data quality that require local adaptation of these principles.