Evidence map›Paper›PMID 37877379›Full record

ArticleClinical trials (London, England)2024

Design of a clinical trial using generalized pairwise comparisons to test a less intensive treatment regimen.

Mickaël De Backer, Manju Sengar, Vikram Mathews, Samuel Salvaggio, Vaiva Deltuvaite-Thomas, Jean-Christophe Chiêm, Everardo D Saad, Marc Buyse

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Generalized Pairwise Comparisons in Dose Optimization Oncology Trials: Beyond Safety to Multi-outcome Dose Selection.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Article
  3. Article
  4. Making Sense of Hierarchical Composite End Points in Randomized Clinical Trials-A Primer for Infectious Diseases Clinicians and Researchers.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025
    Review
  5. Review
  6. Article
  7. Article
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

8 authors.

Mickaël De BackerIDDI (International Drug Development Institute), Louvain-la-Neuve, Belgium.
Manju SengarMedical Oncology, Tata Memorial Centre, Mumbai, India.
Vikram MathewsChristian Medical College Vellore, Vellore, India.
Samuel SalvaggioIDDI (International Drug Development Institute), Louvain-la-Neuve, Belgium.
Vaiva Deltuvaite-ThomasIDDI (International Drug Development Institute), Louvain-la-Neuve, Belgium.
Jean-Christophe ChiêmIDDI (International Drug Development Institute), Louvain-la-Neuve, Belgium.
Everardo D SaadIDDI (International Drug Development Institute), Louvain-la-Neuve, Belgium.ORCID 0000-0003-4039-588X
Marc BuyseIDDI (International Drug Development Institute), Louvain-la-Neuve, Belgium.ORCID 0000-0002-4559-0994

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimsShowing "similar efficacy" of a less intensive treatment typically requires a non-inferiority trial. Yet such trials may be challenging to design and conduct. In acute promyelocytic leukemia, great progress has been achieved with the introduction of targeted therapies, but toxicity remains a major clinical issue. There is a pressing need to show the favorable benefit/risk of less intensive treatment regimens.

methodsWe designed a clinical trial that uses generalized pairwise comparisons of five prioritized outcomes (alive and event-free at 2 years, grade 3/4 documented infections, differentiation syndrome, hepatotoxicity, and neuropathy) to confirm a favorable benefit/risk of a less intensive treatment regimen. We conducted simulations based on historical data and assumptions about the differences expected between the standard of care and the less intensive treatment regimen to calculate the sample size required to have high power to show a positive Net Treatment Benefit in favor of the less intensive treatment regimen.

resultsAcross 10,000 simulations, average sample sizes of 260 to 300 patients are required for a trial using generalized pairwise comparisons to detect typical Net Treatment Benefits of 0.19 (interquartile range 0.14-0.23 for a sample size of 280). The Net Treatment Benefit is interpreted as a difference between the probability of doing better on the less intensive treatment regimen than on the standard of care, minus the probability of the opposite situation. A Net Treatment Benefit of 0.19 translates to a number needed to treat of about 5.3 patients (1/0.19 ≃ 5.3).

conclusionGeneralized pairwise comparisons allow for simultaneous assessment of efficacy and safety, with priority given to the former. The sample size required would be of the order of 300 patients, as compared with more than 700 patients for a non-inferiority trial using a margin of 4% against the less intensive treatment regimen for the absolute difference in event-free survival at 2 years, as considered here.

Indexed as

Clinical Trials as TopicResearch Designacute promyelocytic leukemiabenefit/riskGeneralized pairwise comparisonsnet treatment benefitnon-inferiorityprioritized outcomes

Identifiers

PMID37877379
PMCPMC11195000

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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.