Impact of maternal depression and anxiety-related disorders on live birth rate in women with recurrent pregnancy loss

The propensity score is defined as a subject's probability of treatment selection, conditional on observed baseline covariates. Weighting subjects by the inverse probability of treatment received creates a synthetic sample in which treatment assignment is independent of measured baseline covariates. Inverse probability of treatment weighting (IPTW) using the propensity score allows one to obtain unbiased estimates of average treatment effects. However, these estimates are only valid if there are no residual systematic differences in observed baseline characteristics between treated and control subjects in the sample weighted by the estimated inverse probability of treatment. We report on a systematic literature review, in which we found that the use of IPTW has increased rapidly in recent years, but that in the most recent year, a majority of studies did not formally examine whether weighting balanced measured covariates between treatment groups. We then proceed to describe a suite of quantitative and qualitative methods that allow one to assess whether measured baseline covariates are balanced between treatment groups in the weighted sample. The quantitative methods use the weighted standardized difference to compare means, prevalences, higher‐order moments, and interactions. The qualitative methods employ graphical methods to compare the distribution of continuous baseline covariates between treated and control subjects in the weighted sample. Finally, we illustrate the application of these methods in an empirical case study. We propose a formal set of balance diagnostics that contribute towards an evolving concept of ‘best practice’ when using IPTW to estimate causal treatment effects using observational data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

In a study comparing the effects of two treatments, the propensity score is the probability of assignment to one treatment conditional on a subject's measured baseline covariates. Propensity-score matching is increasingly being used to estimate the effects of exposures using observational data. In the most common implementation of propensity-score matching, pairs of treated and untreated subjects are formed whose propensity scores differ by at most a pre-specified amount (the caliper width). There has been a little research into the optimal caliper width. We conducted an extensive series of Monte Carlo simulations to determine the optimal caliper width for estimating differences in means (for continuous outcomes) and risk differences (for binary outcomes). When estimating differences in means or risk differences, we recommend that researchers match on the logit of the propensity score using calipers of width equal to 0.2 of the standard deviation of the logit of the propensity score. When at least some of the covariates were continuous, then either this value, or one close to it, minimized the mean square error of the resultant estimated treatment effect. It also eliminated at least 98% of the bias in the crude estimator, and it resulted in confidence intervals with approximately the correct coverage rates. Furthermore, the empirical type I error rate was approximately correct. When all of the covariates were binary, then the choice of caliper width had a much smaller impact on the performance of estimation of risk differences and differences in means. Copyright © 2010 John Wiley & Sons, Ltd.

Abstract STUDY QUESTION What is the recommended management of women with recurrent pregnancy loss (RPL) based on the best available evidence in the literature? SUMMARY ANSWER The guideline development group formulated 77 recommendations answering 18 key questions on investigations and treatments for RPL, and on how care should be organized. WHAT IS KNOWN ALREADY A previous guideline for the investigation and medical treatment of recurrent miscarriage was published in 2006 and is in need of an update. STUDY DESIGN, SIZE, DURATION The guideline was developed according to the structured methodology for development of ESHRE guidelines. After formulation of key questions by a group of experts, literature searches and assessments were performed. Papers published up to 31 March 2017 and written in English were included. Cumulative live birth rate, live birth rate and pregnancy loss rate (or miscarriage rate) were considered the critical outcomes. PARTICIPANTS/MATERIALS, SETTING, METHODS Based on the collected evidence, recommendations were formulated and discussed until consensus was reached within the guideline group. A stakeholder review was organized after finalization of the draft. The final version was approved by the guideline group and the ESHRE Executive Committee. MAIN RESULTS AND THE ROLE OF CHANCE The guideline provides 38 recommendations on risk factors, prevention and investigations in couples with RPL, and 39 recommendations on treatments. These include 60 evidence-based recommendations – of which 31 were formulated as strong recommendations and 29 as conditional – and 17 good practice points. The evidence supporting investigations and treatment of couples with RPL is limited and of moderate quality. Of the evidence-based recommendations, only 10 (16.3%) were supported by moderate quality evidence. The remaining recommendations were supported by low (35 recommendations: 57.4%), or very low quality evidence (16 recommendations: 26.2%). There were no recommendations based on high quality evidence. Owing to the lack of evidence-based investigations and treatments in RPL care, the guideline also clearly mentions investigations and treatments that should not be used for couples with RPL. LIMITATIONS, REASONS FOR CAUTION Several investigations and treatments are offered to couples with RPL, but most of them are not well studied. For most of these investigations and treatments, a recommendation against the intervention or treatment was formulated based on insufficient evidence. Future studies may require these recommendations to be revised. WIDER IMPLICATIONS OF THE FINDINGS The guideline provides clinicians with clear advice on best practice in RPL, based on the best evidence available. In addition, a list of research recommendations is provided to stimulate further studies in RPL. One of the most important consequences of the limited evidence is the absence of evidence for a definition of RPL. STUDY FUNDING/COMPETING INTEREST(S) The guideline was developed and funded by ESHRE, covering expenses associated with the guideline meetings, with the literature searches and with the dissemination of the guideline. The guideline group members did not receive payment. J.E. reports position funding from CARE Fertility. S.L. reports position funding from SpermComet Ltd. S.M. reports research grants, consulting and speaker’s fees from GSK, BMS/Pfizer, Sanquin, Aspen, Bayer and Daiichi Sankyo. S.Q. reports speaker’s fees from Ferring. The other authors report no conflicts of interest. ESHRE Pages are not externally peer reviewed. This article has been approved by the Executive Committee of ESHRE.