Risk of bias tools in systematic reviews of health interventions: an analysis of PROSPERO-registered protocols
Bibliographic record
Abstract
Abstract Background Systematic reviews of health interventions are increasingly incorporating evidence outside of randomized controlled trials (RCT). While non-randomized study (NRS) types may be more prone to bias compared to RCT, the tools used to evaluate risk of bias (RoB) in NRS are less straightforward and no gold standard tool exists. The objective of this study was to evaluate the planned use of RoB tools in systematic reviews of health interventions, specifically for reviews that planned to incorporate evidence from RCT and/or NRS. Methods We evaluated a random sample of non-Cochrane protocols for systematic reviews of interventions registered in PROSPERO between January 1 and October 12, 2018. For each protocol, we extracted data on the types of studies to be included (RCT and/or NRS) as well as the name and number of RoB tools planned to be used according to study design. We then conducted a longitudinal analysis of the most commonly reported tools in the random sample. Using keywords and name variants for each tool, we searched PROSPERO records by year since the inception of the database (2011 to December 7, 2018), restricting the keyword search to the “Risk of bias (quality) assessment” field. Results In total, 471 randomly sampled PROSPERO protocols from 2018 were included in the analysis. About two-thirds (63%) of these planned to include NRS, while 37% restricted study design to RCT or quasi-RCT. Over half of the protocols that planned to include NRS listed only a single RoB tool, most frequently the Cochrane RoB Tool. The Newcastle-Ottawa Scale and ROBINS-I were the most commonly reported tools for NRS (39% and 33% respectively) for systematic reviews that planned to use multiple RoB tools. Looking at trends over time, the planned use of the Cochrane RoB Tool and ROBINS-I seems to be increasing. Conclusions While RoB tool selection for RCT was consistent, with the Cochrane RoB Tool being the most frequently reported in PROSPERO protocols, RoB tools for NRS varied widely. Results suggest a need for more education and awareness on the appropriate use of RoB tools for NRS. Given the heterogeneity of study designs comprising NRS, multiple RoB tools tailored to specific designs may be required.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".