Evidence map›Paper›PMID 39654374›Full record

ArticleJournal of clinical pharmacology2025

The Impact of Survival Benefit and Study Design on FDA Approval for Anticancer Drugs Over the Past Decades.

Koji Ishizuka, Shunsuke Ono

Abstract read
In one paragraph

Article in Journal of clinical pharmacology, 2025. 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

2 authors.

Koji IshizukaLaboratory of Pharmaceutical Regulatory Science, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan.ORCID 0009-0007-7414-0427
Shunsuke OnoLaboratory of Pharmaceutical Regulatory Science, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan.

Funding

Ministry of Education, Culture, Sports, Science and Technology KAKEN-HI:19K07215Ministry of Education, Culture, Sports, Science and Technology (MEXT)
6 · The paper itself

Abstract

Despite the tremendous effort in the oncology community, the success rate of anticancer development remained low at 30% to 40% from the Phase 3 study to the regulatory approval. The factors associated with the regulatory approval for market authorization have gained interest in the community to improve the success rate of drug development. Using the data from 208 Phase 3 studies for anticancer drugs, we explored the possible factors associated with the US Food and Drug Administration's (FDA's) approval by multivariate logistic regression analysis. The model incorporated 21 factors from therapeutic context, study design, and outcomes. The hazard ratio (HR) for overall survival (OS) showed a significant association with FDA approval (coefficient: -29.907, P < .001), and the age of control drugs in the market followed (coefficient: -2.581, P = .008). In the model, if the HR for OS changes from 0.75 to 0.85, the probability of FDA approval remarkably decreases from 79.6% to 16.4%. A 50% likelihood of FDA approval is predicted at HR 0.795 for OS. Furthermore, the P-value for the OS test and the width of the confidence interval on HR for OS showed a significant association with the probability of FDA approval. These findings consistently underscore the rigorous standard required for new anticancer drugs to obtain regulatory approval from the FDA.

Indexed as

Antineoplastic AgentsDrug ApprovalNeoplasmsResearch DesignClinical Trials, Phase III as TopicHumansUnited StatesUnited States Food and Drug AdministrationAntineoplastic Agentsclinical trialsdrug developmentoncologypharmaceutical medicineregulatory/scientific affairs

Identifiers

PMID39654374
PMCPMC12034908

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Registered trials

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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.