ArticleJournal of clinical epidemiology2024
A survey of experts to identify methods to detect problematic studies: stage 1 of the INveStigating ProblEmatic Clinical Trials in Systematic Reviews project.
Article in Journal of clinical epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review and meta-analysis evaluating the effect of exercise on the development of cancer-related lymphedema.JNCI cancer spectrum · 2026Pooled it
- Article
Corrections and comments
- Update of
Authors and funding
32 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveRandomized controlled trials (RCTs) inform health-care decisions. Unfortunately, some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesize all RCTs which have been conducted on a given topic. This means that any of these 'problematic studies' are likely to be included, but there are no agreed methods for identifying them. The INveStigating ProblEmatic Clinical Trials in Systematic Reviews (INSPECT-SR) project is developing a tool to identify problematic RCTs in systematic reviews of health care-related interventions. The tool will guide the user through a series of 'checks' to determine a study's authenticity. The first objective in the development process is to assemble a comprehensive list of checks to consider for inclusion.
methodsWe assembled an initial list of checks for assessing the authenticity of research studies, with no restriction to RCTs, and categorized these into five domains: Inspecting results in the paper; Inspecting the research team; Inspecting conduct, governance, and transparency; Inspecting text and publication details; Inspecting the individual participant data. We implemented this list as an online survey, and invited people with expertise and experience of assessing potentially problematic studies to participate through professional networks and online forums. Participants were invited to provide feedback on the checks on the list, and were asked to describe any additional checks they knew of, which were not featured in the list.
resultsExtensive feedback on an initial list of 102 checks was provided by 71 participants based in 16 countries across five continents. Fourteen new checks were proposed across the five domains, and suggestions were made to reword checks on the initial list. An updated list of checks was constructed, comprising 116 checks. Many participants expressed a lack of familiarity with statistical checks, and emphasized the importance of feasibility of the tool.
conclusionA comprehensive list of trustworthiness checks has been produced. The checks will be evaluated to determine which should be included in the INSPECT-SR tool.
Indexed as
Identifiers
39222724What OpenQuestion holds
Registered trials
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.