ArticleThe oncologist2026
Assessing contribution of effect in oncology combination therapies: lessons learned to inform and optimize future registrational trial designs.
Article in The oncologist, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
Abstract
Combination therapies can be used to significantly improve clinical outcomes in patients undergoing treatment for cancer; however, they also present challenges when establishing the contribution of effect (COE) for each component. Although factorial trials remain the most rigorous approach for determining COE, they are often impractical, such as in settings with rare cancers, aggressive disease, evolving standards of care, or monotherapy components with limited activity. As more combination regimens are co-developed from the outset, alternative approaches to registrational trial designs are needed to balance scientific rigor with feasibility and patient acceptability. Thoughtfully designed alternative approaches can support an understanding of COE when grounded in prior evidence and mechanistic understanding. Four major categories of evidence emerge to support designing combination trials without factorial arms: (1) data from trials of the same combination in other tumor types; (2) data from trials of agents with similar mechanisms of action; (3) data from early-phase or parallel trials of the combination within the same disease setting; and (4) strong mechanistic or clinical evidence that a monotherapy component lacks activity and/or imposes harm, supporting omission of inactive arms. Early regulatory engagement, prespecified decision rules, and transparent justification of design choices are essential to ensure that combination regimens provide meaningful improvement in efficacy over monotherapies while minimizing unnecessary toxicity. Applying these principles to combination therapy development can maximize patient benefit while maintaining scientific rigor.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.