Design and rationale of a prospective, collaborative meta-analysis of all randomized controlled trials of angiotensin receptor antagonists in Marfan syndrome, based on individual patient data: A report from the Marfan Treatment Trialists' Collaboration
Bibliographic record
Abstract
RATIONALE: A number of randomized trials are underway, which will address the effects of angiotensin receptor blockers (ARBs) on aortic root enlargement and a range of other end points in patients with Marfan syndrome. If individual participant data from these trials were to be combined, a meta-analysis of the resulting data, totaling approximately 2,300 patients, would allow estimation across a number of trials of the treatment effects both of ARB therapy and of β-blockade. Such an analysis would also allow estimation of treatment effects in particular subgroups of patients on a range of end points of interest and would allow a more powerful estimate of the effects of these treatments on a composite end point of several clinical outcomes than would be available from any individual trial. DESIGN: A prospective, collaborative meta-analysis based on individual patient data from all randomized trials in Marfan syndrome of (i) ARBs versus placebo (or open-label control) and (ii) ARBs versus β-blockers will be performed. A prospective study design, in which the principal hypotheses, trial eligibility criteria, analyses, and methods are specified in advance of the unblinding of the component trials, will help to limit bias owing to data-dependent emphasis on the results of particular trials. The use of individual patient data will allow for analysis of the effects of ARBs in particular patient subgroups and for time-to-event analysis for clinical outcomes. The meta-analysis protocol summarized in this report was written on behalf of the Marfan Treatment Trialists' Collaboration and finalized in late 2012, without foreknowledge of the results of any component trial, and will be made available online (http://www.ctsu.ox.ac.uk/research/meta-trials).
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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 | 0.198 | 0.277 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".