A suggestion for quality assessment in systematic reviews of observational studies in nutritional epidemiology
Bibliographic record
Abstract
OBJECTIVES: It is important to control the quality level of the observational studies in conducting meta-analyses. The Newcastle-Ottawa Scale (NOS) is a representative tool used for this purpose. We investigated the relationship between high-quality (HQ) defined using NOS and the results of subgroup analysis according to study design. METHODS: We selected systematic review studies with meta-analysis which performed a quality evaluation on observational studies of diet and cancer by NOS. HQ determinations and the distribution of study designs were examined. Subgroup analyses according to quality level as defined by the NOS were also extracted. Equivalence was evaluated based on the summary effect size (sES) and 95% confidence intervals computed in the subgroup analysis. RESULTS: The meta-analysis results of the HQ and cohort groups were identical. The overall sES, which was obtained by combining the sES when equivalence was observed between the cohort and case-control groups, also showed equivalence. CONCLUSIONS: The results of this study suggest that it is more reasonable to control for quality level by performing subgroup analysis according to study design rather than by using HQ based on the NOS quality assessment tool.
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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 | 0.606 | 0.806 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.012 | 0.026 |
| Bibliometrics | 0.033 | 0.029 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.015 | 0.023 |
| Open science | 0.015 | 0.012 |
| Research integrity | 0.039 | 0.037 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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".