Evidence map›Paper›PMID 41995717›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2026

Generalized Pairwise Comparisons in Dose Optimization Oncology Trials: Beyond Safety to Multi-outcome Dose Selection.

Emily Alger, Ruitao Lin, J Jack Lee, Ying Yuan, Christina Yap

Abstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Emily AlgerClinical Trial and Statistics Unit, Institute of Cancer Research, London, United Kingdom.ORCID 0000-0002-5378-7439
Ruitao LinThe University of Texas MD Anderson Cancer Center , Houston, Texas.ORCID 0000-0003-2244-131X
J Jack LeeThe University of Texas MD Anderson Cancer Center , Houston, Texas.ORCID 0000-0001-5469-9214
Ying YuanThe University of Texas MD Anderson Cancer Center , Houston, Texas.ORCID 0000-0003-3163-480X
Christina YapClinical Trial and Statistics Unit, Institute of Cancer Research, London, United Kingdom.ORCID 0000-0002-6715-2514

Funding

Cancer Research UK (CRUK) CTUQQR-Dec22/100004MRC-NIHR Trials Methodology Research Partnership MR/S014357/1National Cancer Institute (NCI) and U24CA274212National Cancer Institute (NCI) CA016672National Cancer Institute (NCI) P50CA127001National Cancer Institute (NCI) P50CA281701
6 · The paper itself

Abstract

purposeThe primary objective of dose-finding oncology trials (DFOT) is to determine the recommended phase II dose. Although dose selection has traditionally relied on clinician-reported safety outcomes, the goal of DFOTs increasingly focuses on the integration of safety, activity, and tolerability within decision-making, in line with modern dose optimization strategies. Seamless phase I/II designs often use decision frameworks to quantify trade-offs between outcomes to guide dose selection. However, assigning numerical values to reflect such trade-offs can be difficult as clinical judgments and interpretations often vary between investigators. EXPERIMENTAL

designWith stakeholders, including clinical teams and patients, potentially considering their own prioritization of outcomes, generalized pairwise comparisons, including the win ratio (WR), provide a statistical framework mirroring this clinical decision-making by evaluating treatment benefit against prioritized outcomes. Using the WR, doses are compared across prespecified prioritized outcomes sequentially, with the optimal dose yielding the largest proportion of favorable (winning) patient-pair comparisons. This article presents WIN-DOSE, a hierarchical, multi-outcome WR-based approach for dose optimization. We demonstrate the performance of WIN-DOSE in a two-arm randomized dose optimization trial incorporating dose-limiting toxicities for safety, preliminary response for activity, and both dose intensity and patient-reported outcomes for tolerability.

resultsWhen one dose is clearly favorable, WIN-DOSE consistently identifies the optimal dose. We also demonstrate how the WR can accommodate different trade-offs between safety, activity, and tolerability, supporting transparent and clinically relevant dose selection.

conclusionsThe WR can support transparent and clinically relevant patient-centric dose selection decision-making, aligning with the broader goals of early-phase DFOTs.

Indexed as

Antineoplastic AgentsNeoplasmsClinical Trials, Phase I as TopicClinical Trials, Phase II as TopicDose-Response Relationship, DrugHumansMaximum Tolerated DoseResearch DesignTreatment OutcomeAntineoplastic Agents

Identifiers

PMID41995717
PMCPMC13320202

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.