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Regression Toward the Mean

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...

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Clarifying Contradictions: Transportability in 17OHP-C Trials and Preterm Birth Outcomes Using Doubly Debiased

Arti V Virkud¹, Eric Tchetgen Tchetgen¹, Enrique F Schisterman¹

¹University of Pennsylvania, Perelman School of Medicine, Department of Biostatistics Epidemiology and Informatics.

American Journal of Epidemiology

|September 24, 2025

Summary

This summary is machine-generated.

Conflicting trial results for 17-alpha-hydroxyprogesterone caproate (17OHP-C) in preventing recurrent preterm birth (PTB) may stem from population differences. Transportability methods did not fully reconcile the differing outcomes between the Meis and PROLONG trials.

Keywords:

17OHP-C Double Debiased Machine Learning Preterm Birth Transportability

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Area of Science:

Perinatal medicine
Clinical trial analysis
Causal inference

Background:

The Meis et al. trial suggested 17-alpha-hydroxyprogesterone caproate (17OHP-C) reduces recurrent preterm birth (PTB).
The PROLONG trial, however, found no significant benefit of 17OHP-C for PTB prevention.
Discrepancies between trials are hypothesized to be due to heterogeneity in PTB risk within trial populations.

Purpose of the Study:

To investigate if measured differences between the Meis and PROLONG trial populations explain the conflicting results regarding 17OHP-C efficacy.
To apply doubly debiased machine learning for transportability analysis.

Main Methods:

Utilized doubly debiased machine learning for causal transportability analysis.
Estimated the treatment effect of 17OHP-C by transporting findings between the Meis and PROLONG trial populations.
Assessed the impact of population differences on treatment effect estimates.

Main Results:

Transporting the Meis trial's effect to the PROLONG population yielded an RD of -18.6% (95% CI: -55.9%, 8.8%).
Transporting the PROLONG trial's effect to the Meis population yielded an RD of 5.2% (95% CI: -17.3%, 18.1%).
Neither transport direction fully reconciled the conflicting trial results, suggesting unmeasured factors may influence 17OHP-C efficacy.

Conclusions:

Measured population differences alone do not fully explain the divergent trial outcomes for 17OHP-C in PTB prevention.
Unmeasured effect modifiers or violations of causal assumptions might underlie the observed discrepancies.
Future research should focus on understanding effect heterogeneity in PTB to clarify 17OHP-C's role.