Evidence map›Paper›PMID 33764385›Full record

Trial reportJAMA oncology2021

Evolution of the Randomized Clinical Trial in the Era of Precision Oncology.

Joseph C Del Paggio, John S Berry, Wilma M Hopman, Elizabeth A Eisenhauer, Vinay Prasad, Bishal Gyawali, Christopher M Booth

Open access · bronzeAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JAMA oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 8 pooled it
44.3field-weighted citation impact, top 1% 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

100 citing papers in PubMed, 8 syntheses or guidelines pooled it, 190 citations in OpenAlex.

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  9. Using CA1 rather than the whole hippocampus to capture tau-PET Braak stage II.European journal of nuclear medicine and molecular imaging · 2026
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  13. An overview of clinical trials in anal cancer 1999-2024.ESMO gastrointestinal oncology · 2026
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40 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Joseph C Del PaggioDepartment of Medical Oncology, Thunder Bay Regional Health Sciences Centre and Northern Ontario School of Medicine, Thunder Bay, Canada.
John S BerryDivision of Cancer Care and Epidemiology, Queen's Cancer Research Institute, Queen's University, Kingston, Canada.
Wilma M HopmanKingston General Health Research Institute, Kingston, Canada.
Elizabeth A EisenhauerDepartment of Oncology, Queen's University, Kingston, Canada.
Vinay PrasadDepartment of Epidemiology and Biostatistics, University of California at San Francisco.
Bishal GyawaliDivision of Cancer Care and Epidemiology, Queen's Cancer Research Institute, Queen's University, Kingston, Canada.
Christopher M BoothDivision of Cancer Care and Epidemiology, Queen's Cancer Research Institute, Queen's University, Kingston, Canada.
Queen's University · CAThunder Bay Regional Health Sciences Centre · CAUniversity of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

importanceThe randomized clinical trial (RCT) in oncology has evolved since its widespread adoption in the 1970s. In recent years, concerns have emerged regarding the use of putative surrogate end points, such as progression-free survival (PFS), and marginal effect sizes.

objectiveTo describe contemporary trends in oncology RCTs and compare these findings with earlier eras of RCT design and output. DESIGN, SETTING, AND

participantsRetrospective cohort study of systemic therapy RCTs in breast, colorectal, and non-small cell lung cancer published in 7 major journals between 2010 and 2020. This strategy replicates prior work and allows for comparison of trends with RCTs published between 1995 to 2004 and 2005 to 2009. MAIN OUTCOMES AND MEASURES: Data on RCT design, funding, results, and reporting were extracted from the published RCT report. Findings from the current period (2010-2020) were compared with data from RCTs published from 1995 to 2004 and 2005 to 2009. Descriptive and bivariate statistics were used to analyze temporal trends.

resultsThe cohort included 298 RCTs (132 [44%] breast, 111 [37%] non-small cell lung cancer, 55 [19%] colorectal cancer). Experimental treatment included molecular inhibitor (171 of 298 [57%]), cytotoxic (83 of 298 [28%]), hormone (15 of 298 [5%]), and immune (24 of 298 [8%]) therapies. Sixty-nine percent (206 of 298) of RCTs were of palliative intent. The most common primary end point is now PFS; this has increased substantially over time (from 0% [0 of 167] to 18% [25 of 137] to 42% [125 of 298]; P < .001). Of 298 RCTs, 265 (89%) are now funded by industry (previously 95 of 167 [57%] and 107 of 137 [78%]; P < .001). Fifty-eight percent (173 of 298) of trials met their primary end point. Among positive trials, median improvement in overall survival and PFS was 3.4 and 2.9 months, respectively. More than one-third (117 of 298 [39%]) of reports used a professional medical writer; this increased substantially during the study period (from 3 of 27 [11%] in 2010 to 12 of 18 [67%] in 2020; P < .001). CONCLUSIONS AND RELEVANCE: This cohort study suggests that contemporary oncology RCTs now largely measure putative surrogate end points and are almost exclusively funded by the pharmaceutical industry. The increasing role of medical writers warrants attention. To demonstrate that new cancer treatments are high value, the oncology community needs to consider the extent to which study end points and target effect size provide meaningful benefit to patients.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsDrug IndustryHumansMedical OncologyProgression-Free Survival

Identifiers

PMID33764385
PMCPMC7995135
OpenAlexW3137427440

What OpenQuestion holds

Textmetadata
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.