Evidence map›Paper›PMID 34028549›Full record

ArticleJAMA network open2021

Evaluation of Oncology Trial Results Reporting Over a 10-Year Period.

Xu Liu, Yuan Zhang, Wen-Fei Li, Everett Vokes, Ying Sun, Quynh-Thu Le, Jun Ma

Abstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Xu LiuDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, Guangdong, China.
Yuan ZhangDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, Guangdong, China.
Wen-Fei LiDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, Guangdong, China.
Everett VokesDepartment of Medicine, University of Chicago Medicine and Biological Sciences, Chicago, Illinois.
Ying SunDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, Guangdong, China.
Quynh-Thu LeDepartment of Radiation Oncology, Stanford University, Stanford, California.
Jun MaDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Unreported clinical trial results represent a violation of human rights. Oncology trials account for nearly 30% of interventional biopharmaceutical clinical studies registered on ClinicalTrials.gov and are the most numerous among all disciplines. Objective: To analyze the reporting of results among all interventional oncology trials registered on ClinicalTrials.gov from 2007 through 2017. Design, Setting, and Participants: This cohort study analyzed all clinical studies registered between June 1, 2007, and May 8, 2017, on ClinicalTrials.gov, the largest public clinical trial registry in the world. Trials with a recruitment status of completed or terminated and a primary completion date of on or before September 30, 2017, were selected. Data were analyzed between February 20, 2021, and February 26, 2021. Main Outcomes and Measures: The main outcome was the percentage of trials that reported results either on ClinicalTrials.gov or in journal publications within 24 months of the primary completion date. Journal publication was ascertained by searching ClinicalTrials.gov for a link to the publication, PubMed using national clinical trial number, and Embase using national clinical trial number and filters. Results: Of the 12 240 clinical trials registered in ClinicalTrials.gov, 7425 trials (60.7%; 95% CI, 60.0%-61.5%) reported results, with a 34.0% (95% CI, 30.3%-37.7%) increase in 24-month reporting rate from 2007 to 2017. Multivariable analyses confirmed that more recent trials (adjusted hazard ratio [HR], 1.11 per year increase; 95% CI, 1.10-1.13) and trials with larger sample sizes (51-100 patients: adjusted HR, 1.17 [95% CI, 1.09-1.24]; >100 patients: adjusted HR, 1.43 [95% CI, 1.33-1.54]) were more likely to report results. Terminated trials were less likely to report results compared with completed trials (adjusted HR, 0.88; 95% CI, 0.83-0.93). Compared with trials funded by industry, those funded by the National Institutes of Health were more likely to report results (adjusted HR, 1.39; 95% CI, 1.29-1.49), whereas those funded by other academic or nonprofit organizations were less likely to report results (adjusted HR, 0.66; 95% CI, 0.62-0.70). Among all 7425 trials, the results of 2807 trials (37.8%; 95% CI, 36.7%-38.9%) were posted only on ClinicalTrials.gov. These trials tended to be terminated early and to have small sample sizes (≤50 patients) compared with trials that published results in journals. Conclusions and Relevance: This study found a gradual improvement in results reporting among oncology trials over a 10-year period. Trial registries could serve as a results reporting platform for unpublished trials and as a data source of trial outcomes for future studies.

Indexed as

Clinical Trials as TopicCohort StudiesForecastingHumansMedical OncologyResearch ReportUnited States

Identifiers

PMID34028549
PMCPMC8144925

What OpenQuestion holds

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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.