5 years ago

The proposed ‘concordance-statistic for benefit’ provided a useful metric when modeling heterogeneous treatment effects

Clinical prediction models that support treatment decisions are usually evaluated for their ability to predict the risk of an outcome rather than treatment benefit – the difference between outcome risk with versus without therapy. We aimed to define performance metrics for a model’s ability to predict treatment benefit. Study Design and Setting We analyzed data of the Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) trial, and of 3 recombinant tissue plasminogen activator trials. We assessed alternative prediction models with a conventional risk concordance-statistic (c-statistic) and a novel c-statistic for benefit. We defined observed treatment benefit by the outcomes in pairs of patients matched on predicted benefit but discordant for treatment assignment. The ‘c-for-benefit’ represents the probability that from two randomly chosen matched patient pairs with unequal observed benefit, the pair with greater observed benefit also has a higher predicted benefit. Results Compared to a model without treatment interactions, the SYNTAX Score II had improved ability to discriminate treatment benefit (c-for-benefit 0.590 versus 0.552), despite having similar risk discrimination (c-statistic 0.725 versus 0.719). However, for the simplified Stroke-Thrombolytic Predictive Instrument (TPI) versus the original Stroke-TPI, the c-for-benefit (0.584 versus 0.578) was similar. Conclusion The proposed methodology has the potential to measure a model’s ability to predict treatment benefit not captured with conventional performance metrics.

Publisher URL: www.sciencedirect.com/science

DOI: S0895435617303037

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.