Developing a core outcome set for future infertility research: an international consensus development study
Bibliographic record
Abstract
Study Question Can a core outcome set to standardize outcome selection, collection, and reporting across future infertility research be developed? Summary Answer A minimum data set, known as a core outcome set, has been developed for randomized controlled trials (RCT) and systematic reviews evaluating potential treatments for infertility. What is Known Already Complex issues, including a failure to consider the perspectives of people with fertility problems when selecting outcomes, variations in outcome definitions, and the selective reporting of outcomes on the basis of statistical analysis, make the results of infertility research difficult to interpret. Study Design, Size, Duration A three-round Delphi survey (372 participants from 41 countries) and consensus development workshop (30 participants from 27 countries). Participants/Materials, Setting, Methods Healthcare professionals, researchers, and people with fertility problems were brought together in an open and transparent process using formal consensus science methods. Main Results and the Role of Chance The core outcome set consists of: viable intrauterine pregnancy confirmed by ultrasound (accounting for singleton, twin, and higher multiple pregnancy); pregnancy loss (accounting for ectopic pregnancy, miscarriage, stillbirth, and termination of pregnancy); live birth; gestational age at delivery; birthweight; neonatal mortality; and major congenital anomaly. Time to pregnancy leading to live birth should be reported when applicable. Limitations, Reasons for Caution We used consensus development methods which have inherent limitations, including the representativeness of the participant sample, Delphi survey attrition, and an arbitrary consensus threshold. Wider Implications of the Findings Embedding the core outcome set within RCTs and systematic reviews should ensure the comprehensive selection, collection, and reporting of core outcomes. Research funding bodies, the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) statement, and over 80 specialty journals, including the Cochrane Gynaecology and Fertility Group, Ferility and Sterility , and Human Reproduction , have committed to implementing this core outcome set. Study Funding/Competing Interest(S) This research was funded by the Catalyst Fund, Royal Society of New Zealand, Auckland Medical Research Fund, and Maurice and Phyllis Paykel Trust. Siladitya Bhattacharya reports being the Editor-in-Chief of Human Reproduction Open and an editor of the Cochrane Gynaecology and Fertility group. Hans Evers reports being the Editor Emeritus of Human Reproduction. José Knijnenburg reports research sponsorship from Ferring and Theramex. Richard Legro reports consultancy fees from Abbvie, Bayer, Ferring, Fractyl, Insud Pharma and Kindex and research sponsorship from Guerbet and Hass Avocado Board. Ben Mol reports consultancy fees from Guerbet, iGenomix, Merck, Merck KGaA and ObsEva. Craig Niederberger reports being the Co Editor-in-Chief of Fertility and Sterility and Section Editor of the Journal of Urology, research sponsorship from Ferring, and retains a financial interest in NexHand. Annika Strandell reports consultancy fees from Guerbet. Ernest Ng reports research sponsorship from Merck. Lan Vuong reports consultancy and conference fees from Ferring, Merck and Merck Sharp and Dohme. The remaining authors declare no competing interests in relation to the work presented. All authors have completed the disclosure form. Trial Registration Number Core Outcome Measures in Effectiveness Trials Initiative: 1023.
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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 | 0.353 | 0.337 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".