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<p>Real-world studies have become more common in clinical literature in recent years, but many clinicians remain unfamiliar with real-world study design and statistical approaches. This vodcast intends to be a practical guide for clinicians by clarifying aspects of real-world study methodology. As both practicing oncologists and researchers with extensive real-world data experience, the hosts discuss types of study designs and real-world data source considerations. An overview of statistical techniques for mitigating treatment-selection bias is also provided, including propensity score matching, inverse probability of treatment weighting, and multivariable analysis. By combining high-quality data sources, careful sample size considerations, and rigorous statistical techniques, real-world studies can offer valuable insights into therapeutic effectiveness in routine clinical practice that supplement learnings from randomized clinical trials. This vodcast is designed to equip clinicians with the knowledge to critically evaluate real-world evidence and potentially apply it to their practice.</p><p>Vodcast and infographic available for this article.</p><p><MediaObject ID="MOESM1"> <VideoObject FileRef="MediaObjects/40487_2025_366_MOESM1_ESM.mp4" VideoID="1yydXoS2V_iBWmty7kBCRP"> <Caption Language="En" xml:lang="en"> <CaptionContent> <p>Vodcast (MP4 1207725 KB)</p> </CaptionContent> </Caption> </VideoObject> </MediaObject></p> Infographic <p></p>

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A Practical Approach to Understanding Real-World Study Methodology in Cancer Research: A Vodcast

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月11日

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  • Adam Brufsky,
  • Winson Cheung,
  • Joanne C. Ryan

摘要

Real-world studies have become more common in clinical literature in recent years, but many clinicians remain unfamiliar with real-world study design and statistical approaches. This vodcast intends to be a practical guide for clinicians by clarifying aspects of real-world study methodology. As both practicing oncologists and researchers with extensive real-world data experience, the hosts discuss types of study designs and real-world data source considerations. An overview of statistical techniques for mitigating treatment-selection bias is also provided, including propensity score matching, inverse probability of treatment weighting, and multivariable analysis. By combining high-quality data sources, careful sample size considerations, and rigorous statistical techniques, real-world studies can offer valuable insights into therapeutic effectiveness in routine clinical practice that supplement learnings from randomized clinical trials. This vodcast is designed to equip clinicians with the knowledge to critically evaluate real-world evidence and potentially apply it to their practice.

Vodcast and infographic available for this article.

Vodcast (MP4 1207725 KB)

Infographic