Evidence map›Paper›PMID 30933235›Full record

ArticleJAMA internal medicine2019

Estimation of Study Time Reduction Using Surrogate End Points Rather Than Overall Survival in Oncology Clinical Trials.

Emerson Y Chen, Sunil K Joshi, Audrey Tran, Vinay Prasad

Abstract read
In one paragraph

Article in JAMA internal medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 9 pooled it
–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

73 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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  10. Fucoidan Improves Tumour Control and Liver Function in TACE for Unresectable Hepatocellular Carcinoma: A Randomised Trial.Liver international : official journal of the International Association for the Study of the Liver · 2025
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  16. Expedited regulatory approval pathways for novel oncology drugs.Medical oncology (Northwood, London, England) · 2026
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13 more citing papers are in PubMed but not listed here.

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

4 authors.

Emerson Y ChenDivision of Hematology Oncology, Knight Cancer Institute, Oregon Health & Science University, Portland.
Sunil K JoshiDivision of Hematology Oncology, Knight Cancer Institute, Oregon Health & Science University, Portland.
Audrey TranSchool of Medicine, Oregon Health & Science University, Portland.
Vinay PrasadDivision of Hematology Oncology, Knight Cancer Institute, Oregon Health & Science University, Portland.

Funding

Defining the stromal landscape that sustains AML drug resistanceF30CA239335 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI JOSHI, SUNIL KUMAR · 2019 to 2022
$187k
NCI NIH HHS F30 CA239335
6 · The paper itself

Abstract

Importance: Surrogate end points in oncology trade the advantage of reducing the time needed to conduct clinical trials for the disadvantage of greater uncertainty regarding the treatment effect on patient-centered end points, such as overall survival (OS) and quality of life. Objective: To quantify the amount of time saved through the acceptance of surrogate end points, including response rate (RR) and progression-free survival (PFS). Design, Setting, and Participants: This retrospective study of US Food and Drug Administration (FDA) oncology approvals and their drug registration trials based on actual publication analyzed the original and updated clinical trials data that led to FDA-approved drug indications in oncology from 2006 to 2017 by using existing publications, conference abstracts, and package inserts from the FDA. Data related to cancer type, line of therapy (first-line, second-line, and third- or later-line treatment of advanced or metastatic disease), FDA approval type, end point basis for approval (RR, PFS, or OS/quality of life), sample size, accrual rate, and drug RR were extracted by March 23, 2018. All data were analyzed by July 13, 2018. Main Outcomes and Measures: The main outcome was the study duration needed to complete the primary end point analysis used for each drug indication approval. This was estimated from reported enrollment dates, analysis cutoff dates, time to response, median duration of response, median PFS, and median OS. Results: In total, 188 distinct indications among 107 cancer drugs were identified. The RR was more often used for FDA approval in subsequent lines of therapy (17 of 71 drug indications [24%] in first-line therapy vs 34 of 77 drug indications [44%] in second-line therapy vs 19 of 24 drug indications [79%] in third- or later-line therapy, P < .001). Study duration for PFS (median, 31 [range, 10-104] months) was similar to that for OS (median, 33 [range, 12-117] months; P = .31), whereas study duration for RR (median, 25 [range, 11-54] months) was shorter than that for OS (P = .001). In multivariate analysis, compared with using OS, use of PFS as the end point was associated with study durations that were shorter by a mean of 11 months (95% CI, 5-17 months), and the use of RR as the end point was associated with study durations that were shorter by a mean of 19 months (95% CI, 13-25 months). Conclusions and Relevance: From the findings of this study, an estimated 11 months appeared to be needed (ie, approximately 12% longer in the drug development cycle) to assess the OS benefit of a cancer drug. This study's findings suggest that this must be weighed against the downside of increased uncertainty of clinical benefit arising from using surrogate end points.

Indexed as

Antineoplastic AgentsBiomarkersDisease-Free SurvivalDrug ApprovalEndpoint DeterminationHumansMedical OncologyNeoplasmsOutcome Assessment, Health CareResearch DesignRetrospective StudiesUnited StatesAntineoplastic AgentsBiomarkers

Identifiers

PMID30933235
PMCPMC6503556

What OpenQuestion holds

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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.