ArticleJournal of hematology & oncology2020
Treating non-responders: pitfalls and implications for cancer immunotherapy trial design.
Article in Journal of hematology & oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Blockade of TSP-1/CD47 signal axis promotes donor hematopoietic engraftment by improving SEC/MK niche function.iScience · 2025Article
- Pan-Cancer Analysis Identifies YKT6 as a Prognostic and Immunotherapy Biomarker, with an Emphasis on Cervical Cancer.OncoTargets and therapy · 2025Article
- Behavioral factors to modulate immunotherapy efficacy in cancer.Frontiers in immunology · 2022Article
- Review
- Design for immuno-oncology clinical trials enrolling both responders and nonresponders.Statistics in medicine · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundConventional trial design and analysis strategies fail to address the typical challenge of immune-oncology (IO) studies: only a limited percentage of treated patients respond to the experimental treatment. Treating non-responders, we hypothesize, would in part drive non-proportional hazards (NPH) patterns in Kaplan-Meier curves that violates the proportional hazards (PH) assumption required by conventional strategies. Ignoring such violation incurred from treating non-responders in the design and analysis strategy may result in underpowered or even falsely negative studies. Hence, designing innovative IO trials to address such pitfall becomes essential.
methodsWe empirically tested the hypothesis that treating non-responders in studies of inadequate size is sufficient to cause NPH patterns and thereby proposed a novel strategy, p-embedded, to incorporate the dichotomized response incurred from treating non-responders, as measured by the baseline proportion of responders among treated patients p%, into the design and analysis procedures, aiming to ensure an adequate study power when the PH assumption is violated.
resultsEmpirical studies confirmed the hypothetical cause contributes to the manifestation of NPH patterns. Further evaluations revealed a significant quantitative impact of p% on study efficiency. The p-embedded strategy incorporating the properly pre-specified p% ensures an adequate study power whereas the conventional design ignoring it leads to a severe power loss.
conclusionThe p-embedded strategy allows us to quantify the impact of treating non-responders on study efficiency. Implicit in such strategy is the solution to mitigate the occurrence of NPH patterns and enhance the study efficiency for IO trials via enrolling more prospective responders.
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