Methodological quality of systematic reviews in subfertility: a comparison of Cochrane and non-Cochrane systematic reviews in assisted reproductive technologies
Bibliographic record
Abstract
STUDY QUESTION: Are there differences in the methodological quality of Cochrane systematic reviews (CRs) and non-Cochrane systematic reviews (NCRs) of assisted reproductive technologies? SUMMARY ANSWER: CRs on assisted reproduction are of higher methodological quality than similar reviews published in other journals. WHAT IS KNOWN ALREADY: The quality of systematic reviews varies. STUDY DESIGN, SIZE AND DURATION: This was a cross-sectional study of 30 CR and 30 NCR systematic reviews that were randomly selected from the eligible reviews identified from a literature search for the years 2007-2011. MATERIALS, SETTING AND METHODS: We extracted data on the reporting and methodological characteristics of the included systematic reviews. We assessed the methodological quality of the reviews using the 11-domain Measurement Tool to Assess the Methodological Quality of Systematic Reviews (AMSTAR) tool and subsequently compared CR and NCR systematic reviews. MAIN RESULTS AND THE ROLE OF CHANCE: The AMSTAR quality assessment found that CRs were superior to NCRs. For 10 of 11 AMSTAR domains, the requirements were met in >50% of CRs, but only 4 of 11 domains showed requirements being met in >50% of NCRs. The strengths of CRs are the a priori study design, comprehensive literature search, explicit lists of included and excluded studies and assessments of internal validity. Significant failings in the CRs were found in duplicate study selection and data extraction (67% meeting requirements), assessment for publication bias (53% meeting requirements) and reporting of conflicts of interest (47% meeting requirements). NCRs were more likely to contain methodological weaknesses as the majority of the domains showed <40% of reviews meeting requirements, e.g. a priori study design (17%), duplicate study selection and data extraction (17%), assessment of study quality (27%), study quality in the formulation of conclusions (23%) and reporting of conflict of interests (10%). LIMITATIONS, REASONS FOR CAUTION: The AMSTAR assessment can only judge what is reported by authors. Although two of the five authors are involved in the production of CRs, the risk of bias was reduced by not involving these authors in the assessment of the systematic review quality. WIDER IMPLICATIONS OF THE FINDINGS: Not all systematic reviews are equal. The reader needs to consider the quality of the systematic review when they consider the results and the conclusions of a systematic review. STUDY FUNDING/COMPETING INTEREST(S): There are no conflicts with any commercial organization. Funding was provided for the students by the summer studentship programme of the Faculty of Medical and Health Sciences of the University of Auckland.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.443 | 0.768 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.024 | 0.037 |
| Bibliometrics | 0.043 | 0.041 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".