Dissemination Bias in Systematic Reviews of Animal Research: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Systematic reviews of preclinical studies, in vivo animal experiments in particular, can influence clinical research and thus even clinical care. Dissemination bias, selective dissemination of positive or significant results, is one of the major threats to validity in systematic reviews also in the realm of animal studies. We conducted a systematic review to determine the number of published systematic reviews of animal studies until present, to investigate their methodological features especially with respect to assessment of dissemination bias, and to investigate the citation of preclinical systematic reviews on clinical research. METHODS: Eligible studies for this systematic review constitute systematic reviews that summarize in vivo animal experiments whose results could be interpreted as applicable to clinical care. We systematically searched Ovid Medline, Embase, ToxNet, and ScienceDirect from 1st January 2009 to 9th January 2013 for eligible systematic reviews without language restrictions. Furthermore we included articles from two previous systematic reviews by Peters et al. and Korevaar et al. RESULTS: The literature search and screening process resulted in 512 included full text articles. We found an increasing number of published preclinical systematic reviews over time. The methodological quality of preclinical systematic reviews was low. The majority of preclinical systematic reviews did not assess methodological quality of the included studies (71%), nor did they assess heterogeneity (81%) or dissemination bias (87%). Statistics quantifying the importance of clinical research citing systematic reviews of animal studies showed that clinical studies referred to the preclinical research mainly to justify their study or a future study (76%). DISCUSSION: Preclinical systematic reviews may have an influence on clinical research but their methodological quality frequently remains low. Therefore, systematic reviews of animal research should be critically appraised before translating them to a clinical context.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.387 | 0.705 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.020 | 0.016 |
| Bibliometrics | 0.034 | 0.027 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".