Evidence map›Paper›PMID 38172190›Full record

ArticleScientific reports2024

Magnitude of effect and sample size justification in trials supporting anti-cancer drug approval by the US Food and Drug Administration.

Michelle B Nadler, Brooke E Wilson, Alexandra Desnoyers, Consolacion Molto Valiente, Ramy R Saleh, Eitan Amir

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
5.0field-weighted citation impact, top 5% of its field
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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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

6 authors at 4 institutions in 1 country.

Michelle B NadlerDivision of Medical Oncology and Hematology, Princess Margaret Cancer Centre and Department of Medicine, The University of Toronto, Toronto, ON, Canada. michelle.nadler@uhn.ca.
Brooke E WilsonDivision of Medical Oncology and Hematology, Princess Margaret Cancer Centre and Department of Medicine, The University of Toronto, Toronto, ON, Canada.
Alexandra DesnoyersDivision of Medical Oncology and Hematology, Princess Margaret Cancer Centre and Department of Medicine, The University of Toronto, Toronto, ON, Canada.
Consolacion Molto ValienteDivision of Medical Oncology and Hematology, Princess Margaret Cancer Centre and Department of Medicine, The University of Toronto, Toronto, ON, Canada.
Ramy R SalehDivision of Medical Division of Medical Oncology, McGill University Health Centre, Montreal, QC, Canada.
Eitan AmirDivision of Medical Oncology and Hematology, Princess Margaret Cancer Centre and Department of Medicine, The University of Toronto, Toronto, ON, Canada.
Princess Margaret Cancer Centre · CAMcGill University Health Centre · CAUniversité de Sherbrooke · CAUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Approval of drugs is based on randomized trials observing statistically significant superiority of an experimental agent over a standard. Statistical significance results from a combination of effect size and sampling, with larger effect size more likely to translate to population effectiveness. We assess sample size justification in trials supporting cancer drug approvals. We identified US FDA anti-cancer drug approvals for solid tumors from 2015 to 2019. We extracted data on study characteristics, statistical plan, accrual, and outcomes. Observed power (P

Indexed as

Antineoplastic AgentsBreast NeoplasmsDrug ApprovalFemaleHumansSample SizeUnited StatesUnited States Food and Drug AdministrationAntineoplastic Agents

Identifiers

PMID38172190
PMCPMC10764749
OpenAlexW4390571373

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.