Assessing and Reporting Heterogeneity in Treatment Effects in Clinical Trials¶
Kent, D. M., Rothwell, P. M., Ioannidis, J. P., Altman, D. G., & Hayward, R. A. (2010). Assessing and Reporting Heterogeneity in Treatment Effects in Clinical Trials: A Proposal. Trials, 11.
Cited by¶
1 citation across 1 artifact.
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Primes¶
- Outlier Leverage
- And in multi-site clinical trials, a handful of strong responders can drive a positive mean treatment effect even when the median patient is unaffected
This sourceTrial summary results reflect the arithmetic mean and can be unrepresentative of the typical (median) patient, so a positive mean effect can be driven by a high-risk/high-response subgroup while the median patient is largely unaffected — motivating subgroup/influence sensitivity analysis.
Supported in partVerified against the work's full text
Kent et al. show a favorable trial-average result can mask most patients getting no net benefit, driven by risk subgroups; they do not describe a 'handful' of outlier responders.
“despite the fact that 75% of study subjects received absolutely no net benefit”
- And in multi-site clinical trials, a handful of strong responders can drive a positive mean treatment effect even when the median patient is unaffected
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