Interpreting meta-analysis according to the adequacy of sample size. An example using isoniazid chemoprophylaxis for tuberculosis in purified protein derivative negative HIV-infected individuals
Bibliographic record
Abstract
Kristian Thorlund1,2, Aranka Anema3, Edward Mills41Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada; 2The Copenhagen Trial Unit, Centre for Clinical Intervention Research, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; 3British Columbia Centre for Excellence in HIV/AIDS, University of British Columbia, Vancouver, British Columbia, Canada; 4Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, CanadaObjective: To illustrate the utility of statistical monitoring boundaries in meta-analysis, and provide a framework in which meta-analysis can be interpreted according to the adequacy of sample size. To propose a simple method for determining how many patients need to be randomized in a future trial before a meta-analysis can be deemed conclusive.Study design and setting: Prospective meta-analysis of randomized clinical trials (RCTs) that evaluated the effectiveness of isoniazid chemoprophylaxis versus placebo for preventing the incidence of tuberculosis disease among human immunodeficiency virus (HIV)-positive individuals testing purified protein derivative negative. Assessment of meta-analysis precision using trial sequential analysis (TSA) with LanDeMets monitoring boundaries. Sample size determination for a future trials to make the meta-analysis conclusive according to the thresholds set by the monitoring boundaries.Results: The meta-analysis included nine trials comprising 2,911 trial participants and yielded a relative risk of 0.74 (95% CI, 0.53–1.04, P = 0.082, I2 = 0%). To deem the meta-analysis conclusive according to the thresholds set by the monitoring boundaries, a future RCT would need to randomize 3,800 participants.Conclusion: Statistical monitoring boundaries provide a framework for interpreting meta-analysis according to the adequacy of sample size and project the required sample size for a future RCT to make a meta-analysis conclusive.Keywords: meta-analysis, trial sequential analysis (TSA), randomized clinical trials (RCTs), isoniazid chemoprophylaxis, adequacy of sample size, human immunodeficiency virus (HIV), tuberculosis, purified protein derivative negative
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".