La Marca · Human reproduction (Oxford, England) 2014 · cross-sectional comparative modeling study · n=4220

The ovarian response to controlled stimulation in IVF cycles may be predictive of the age at menopause.

Cited 6 times in the scientific literature.

Level 4 - case-series / case-control

Cross-sectional study comparing two separate cohorts using mathematical modeling

PubMed 25267784 · doi:10.1093/humrep/deu234 · record verified 2026-08-26

What was done

A cross-sectional study compared 1,585 infertile women undergoing controlled ovarian stimulation with gonadotrophins at an IVF clinic to 2,635 menopausal women sampled from a general population. Researchers modeled the relationship between patient age and the mean number of retrieved oocytes using a cubic function. From the residual distribution around this curve, they mathematically estimated the distribution of the age at which zero oocytes would be retrieved and compared this derived distribution directly to the actual distribution of menopausal ages in the comparison cohort.

What was found

The relationship between age and mean retrieved oocytes was described by a cubic function with statistically significant terms. The derived distribution for the age of zero oocyte retrieval showed similarity to the empirical menopausal age distribution, with actual menopause occurring approximately one year later than the predicted zero-oocyte age. Specific numerical values, regression coefficients, and variance measures were not reported in the abstract.

Why it matters

This study provides theoretical support for using ovarian response during IVF as an indirect indicator of the remaining reproductive lifespan and the timeline to natural menopause.

Limits

The study is limited by its cross-sectional and indirect design; women were not followed longitudinally from IVF to menopause. The analysis compares two distinct populations (infertile clinic attendees versus a general menopausal cohort), which introduces potential confounding. The abstract reports no numerical precision metrics, prediction intervals, or individual-level predictive validation.

Cited by