International Natural Procreative Technology Evaluation and Surveillance of Treatment for Subfertility (iNEST): enrollment and methods
Bibliographic record
Abstract
STUDY QUESTION: What is the feasibility of a prospective protocol to follow subfertile couples being treated with natural procreative technology for up to 3 years at multiple clinical sites? SUMMARY ANSWER: Overall, clinical sites had missing data for about one-third of participants, the proportion of participants responding to follow-up questionnaires during time periods when participant compensation was available (about two-thirds) was double that of time periods when participant compensation was not available (about one-third) and follow-up information was most complete for pregnancies and births (obtained from both clinics and participants). WHAT IS KNOWN ALREADY: Several retrospective single-clinic studies from Canada, Ireland and the USA, with subfertile couples receiving restorative reproductive medicine, mostly natural procreative technology, have reported adjusted cumulative live birth rates ranging from 29% to 66%, for treatment for up to 2 years, with a mean women's age of about 35 years. STUDY DESIGN SIZE DURATION: The international Natural Procreative Technology Evaluation and Surveillance of Treatment for Subfertility (iNEST) was designed as a multicenter, prospective cohort study, to enroll subfertile couples seeking treatment for live birth, assess baseline characteristics and follow them up for up to 3 years to report diagnoses, treatments and outcomes of pregnancy and live birth. In addition to obtaining data from medical record abstraction, we sent follow-up questionnaires to participants (both women and men) to obtain information about treatments and pregnancy outcomes, including whether they obtained treatment elsewhere. The study was conducted from 2006 to 2016, with a total of 10 clinics participating for at least some of the study period across four countries (Canada, Poland, UK and USA). PARTICIPANTS/MATERIALS SETTING METHODS: conception. MAIN RESULTS AND THE ROLE OF CHANCE: The mean age of women starting treatment was 34.0 years; among those with additional demographic data, 382/478 (80%) had 16 or more years of education, and 199/659 (30%) had a prior live birth. Across 10 clinical sites in four countries (mostly private clinical practices) with family physicians or obstetrician-gynecologists, data about clinic visits were submitted for 60% of participants, and diagnostic data for 77%. For data obtained directly from the couple, 59% of couples had at least one follow-up questionnaire, and the proportion of women and men responding to fill out the follow-up questionnaires was 69% and 67%, respectively, when participant financial compensation was available, compared to 38% and 33% when compensation was not available. Among all couples, 57% had at least one pregnancy and 44% at least one live birth during the follow-up time period, based on data obtained from clinic and/or participant questionnaires. All sites reported on female pelvic surgical procedures, and among all participants, 22% of females underwent a pelvic diagnostic and/or therapeutic procedure, predominantly laparoscopy and hysterosalpingography. Among the 643 (77%) of participants with diagnostic information, ovulation-related disorders were diagnosed in 87%, endometriosis in 31%, nutritional disorders in 47% and abnormalities of semen analysis in 24%. The mean number of diagnoses per couple was 4.7. LIMITATIONS REASONS FOR CAUTION: The level of missing data was higher than anticipated, which limits both generalizability and the ability to study different components of treatment and prognosis. Loss to follow-up may also be differential and introduce bias for outcomes. Most of the participating clinicians were not surgeons, which limits the opportunity to study the impact of surgical interventions. Participants were geographically dispersed but relatively homogeneous with regard to socioeconomic status, which may limit the generalizability of current and future findings. WIDER IMPLICATIONS OF THE FINDINGS: Multicenter studies are key to understanding the outcomes of subfertility treatments beyond IVF or IUI in broader populations, and the association of different prognostic factors with outcomes. We anticipate that the iNEST study will provide insight for clinical and treatment factors associated with outcomes of pregnancy and live birth, with appropriate attention to potential biases (including adjustment for potential confounders, multiple imputation for missing data, sensitivity analysis and inverse probability weighting for potential differential loss to follow-up, and assessments for clinical site heterogeneity). Future studies will need to either have: adequate funding to compensate clinics and participants for robust data collection, including targeted randomized trials; or a scaled-down, registry-based approach with targeted data points, similar to the multiple national and regional ART registries. STUDY FUNDING/COMPETING INTERESTS: Funding for the study came from the International Institute for Restorative Reproductive Medicine, the University of Utah, Department of Family and Preventive Medicine, Health Studies Fund, the Primary Children's Medical Foundation, the Mary Cross Tippmann Foundation, the Atlas Foundation, the St. Augustine Foundation and the Women's Reproductive Health Foundation. The authors declare no competing interests. TRIAL REGISTRATION NUMBER: The iNEST study is registered at clinicaltrials.gov, NCT01363596.
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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 | 0.037 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".