Statistical noise in PD-(L)1 inhibitor trials: unraveling the durable-responder effect

Programmed-death-1/ligand-1 (PD-1(L)1) inhibitors are crucial cancer treatments, with global spending expected to surpass $75 billion by 2026. Multiple versions of these medicines are available, all designed to boost the immune system to fight cancer. We would expect them all to work similarly, but clinical trials show mixed results-some seem effective for certain cancers but not others, without a clear pattern. This article uses simulations (virtual trials) to suggest that these inconsistent results may be due to chance, caused by a small group of patients who respond very well to the treatment. Larger trials or specific analysis methods could help reduce the chance effects and provide more robust data for clinician and patient decision-making.

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Publication Details

Journal
Journal of Clinical Epidemiology
Published
2024-11-05
DOI
https://doi.org/10.1016/j.jclinepi.2024.111589
Primary Topic
Statistical Methods in Clinical Trials
Type
article
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article

Statistical noise in PD-(L)1 inhibitor trials: unraveling the durable-responder effect

Michael Coory, Susan J. Jordan
Journal of Clinical Epidemiology
Statistical Methods in Clinical Trials
article

Statistical noise in PD-(L)1 inhibitor trials: unraveling the durable-responder effect

Michael Coory, Susan J. Jordan
article en

Abstract

Programmed-death-1/ligand-1 (PD-1(L)1) inhibitors are crucial cancer treatments, with global spending expected to surpass $75 billion by 2026. Multiple versions of these medicines are available, all designed to boost the immune system to fight cancer. We would expect them all to work similarly, but clinical trials show mixed results-some seem effective for certain cancers but not others, without a clear pattern. This article uses simulations (virtual trials) to suggest that these inconsistent results may be due to chance, caused by a small group of patients who respond very well to the treatment. Larger trials or specific analysis methods could help reduce the chance effects and provide more robust data for clinician and patient decision-making.

Journal of Clinical EpidemiologyVol. 177
The University of Queensland (AU), Mater Research (AU)
Openalex Percentile: Top 80%
Statistical Methods in Clinical Trials
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Statistical noise in PD-(L)1 inhibitor trials: unraveling the durable-responder effect — Michael Coory, Susan J. Jordan · Journal of Clinical Epidemiology (2024) | TGRS Research Map | TGRS