Systematic reviews of prognosis studies: a critical appraisal of five core clinical journals
Bibliographic record
Abstract
BACKGROUND: Prognosis research refers to the investigation of association between a baseline health state, patient characteristic and future outcomes. The findings of several prognostic studies can be summarized in systematic reviews (SRs), but some characteristics of prognostic studies may result in difficulties when performing the analyses. This study aimed to investigate trends in the volume and quality of SRs of prognostic studies in the literature. METHODS: We conducted a systematic review in five high-impact clinical journals (Annals of Internal Medicine, BMJ, Circulation, JAMA, and Stroke) to identify SRs of prognosis studies focused on fundamental prognosis research and prognostic factor research published between 2000 and 2012. We excluded studies of clinical prediction guides or implementation studies. The quality of the SRs was rated based on the Meta-analysis of Observational Studies in Epidemiology (MOOSE) and the PRISMA checklists. RESULTS: Over the 13-year period, 1065 SRs were published. Of these, 198 were SRs of prognosis studies. The proportion of all SRs to published articles increased from 0.86% in 2000 to 4.2% in 2012. Likewise, the proportion of prognosis SRs to all SRs increased from 10.3% in 2000 to 17.7% in 2012. MOOSE and PRISMA mean summary scores consistently increased over time for all journals, indicating that the quality of reporting in these SRs has steadily improved. However, several items were not consistently well reported by investigators. CONCLUSIONS: This study shows that there is a growing number of SRs of prognosis studies. However, the quality is suboptimal when assessed with the generic reporting guidelines for observational studies. New reporting guidelines and risk of bias tools for prognosis studies are needed to improve the quality of future research in this field.
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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: Evaluation · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
| gpt | Metaresearch Domain: Reporting · 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 | 0.362 | 0.689 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.020 | 0.021 |
| Bibliometrics | 0.082 | 0.056 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".