An alternative approach to deal with the absence of clinical trials: a proportional meta-analysis of case series studies
Bibliographic record
Abstract
PURPOSE: Systematic reviews are criticized for frequently offering inconsistent evidences and absence of straightforward recommendations. Their value seems to be depreciated when the conclusions are uncertain. To describe an alternative approach of evaluating case series studies in health care when there is absence of clinical trials. METHODS: We provide illustrations from recent experiences. Proportional meta-analysis was performed on surgical outcomes: (a) case series studies, (b) use of cryoablation or radiofrequency ablation, and (c) patients with small renal cell carcinoma. The statistically significant difference between both interventions studied was defined if their combined 95% confidential interval (CI) did not overlap. RESULTS: As demonstrated by the example, this analysis is an alternative approach to provide some evidence of the intervention's effects under evaluation and plotting all available case series in the absence of clinical trials for the health field. CONCLUSIONS: Although we are leading to a low level of evidence to determine efficacy, effectiveness and safety of interventions this alternative approach can help surgeons, physicians and health professionals for a provisionally decision in health care along with their clinical expertise and the patient's wishes and circumstances in the absence of high-quality primary studies. It's not a replacement for the gold standard randomized clinical trial, but an alternative analysis for clinical research.
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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 | 0.383 | 0.609 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.029 |
| Bibliometrics | 0.027 | 0.021 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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, 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".