Identifying systemic vulnerability phenotypes associated with programmed regimens in frozen embryo transfer: a...

Programmed endometrial preparation is widely used for frozen embryo transfer (FET) because it allows flexible scheduling. Recent randomized evidence has shown that programmed regimens increase the risk of hypertensive disorders of pregnancy, particularly pre-eclampsia, compared with natural ovulation regimens. However, it remains unclear whether this risk is distributed uniformly across patients or concentrated in women with specific baseline characteristics.

This study aimed to evaluate the heterogeneous treatment effects of programmed regimens versus natural ovulation regimens on pre-eclampsia after FET and to identify baseline phenotypes associated with increased vulnerability across multiple adverse obstetric outcomes.

We performed an exploratory secondary analysis of a multicentre, open-label randomized clinical trial comparing programmed and natural ovulation regimens for endometrial preparation before FET. The analysis was restricted to women with regular menstrual cycles who achieved clinical pregnancy after FET. The primary outcome was pre-eclampsia. Secondary outcomes included late-onset pre-eclampsia, placenta accreta spectrum, postpartum haemorrhage and caesarean delivery. Inverse probability of treatment weighting was used to improve covariate balance. Individualized treatment effects were estimated using causal forests. Restricted cubic spline models were used as a sensitivity analysis to examine statistical interactions between treatment regimen and key baseline variables.

Among 2,541 women included in the analytical cohort, 1,261 were assigned to natural ovulation and 1,280 to programmed treatment. Pre-eclampsia occurred in 38 women (3.01%) in the natural ovulation group and 60 women (4.69%) in the programmed group, corresponding to an unadjusted absolute risk difference of 1.67 percentage points. The causal forest estimated positive CATEs for all participants (100.0%), with a median estimated absolute risk increase of 1.51 percentage points (IQR, 1.37-1.83). BMI, AMH, and the retrieval-to-randomization interval were the leading contributors to model-estimated treatment-effect heterogeneity. Conventional regression analysis supported a statistically significant treatment interaction for BMI (P for interaction = 0.039), whereas interactions involving AMH and the retrieval-to-randomization interval were not statistically significant.

Programmed FET regimens were associated with a higher absolute risk of pre-eclampsia in the pregnancy-conditioned analytical cohort, although the estimated magnitude of this increase varied across participants. BMI showed the strongest support as a treatment-effect modifier in conventional regression analysis, whereas AMH and the retrieval-to-randomization interval should be interpreted as exploratory candidate modifiers identified by causal forest analysis. These findings require prospective validation before they can be used to guide individualized regimen selection.