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1.  Preconception Low Dose Aspirin and Pregnancy Outcomes: Findings from the EAGeR (Effects of Aspirin in Gestation and Reproduction) Randomized Trial 
Lancet  2014;384(9937):29-36.
Our objective was to determine whether preconception-initiated low dose aspirin (LDA) improved live birth rates in women with one to two prior pregnancy losses.
This multi-center, block-randomized, double-blind, placebo-controlled trial recruited from four medical centers in the US (2006–2012). Women aged 18–40 years attempting pregnancy were stratified by eligibility criteria: “original”: women with one loss <20 weeks’ gestation during the past year; or “expanded”: women with one to two prior losses regardless of gestational length or time of loss. Women were block-randomized (615 LDA, 613 placebo) by center and eligibility stratum. Preconception-initiated daily LDA (81 mg/day) was compared with placebo for up to six menstrual cycles; for those who conceived, study treatment continued until 36 weeks’ gestation. The primary outcome was live birth rate. The trial was registered on (#NCT00467363).
Overall, 1078 women completed the trial (LDA 535, placebo 543). Live birth rates were 58% (309/535) in women assigned LDA vs. 53% placebo (286/543; risk difference [RD] 5%; 95% confidence interval [CI] −0·8, 11). Pregnancy loss rates were similar between groups (13% [68/535] LDA, 12% [65/543] placebo; p=0·7812). In the original stratum, live birth rates were 62% (151/242) LDA vs. 53% (133/250) placebo (RD 9%; 95% CI 0·5, 18), and in the expanded, 54% (158/293) LDA vs. 52% (153/293) placebo (RD 2%; 95% CI −6, 10). Major adverse events were similar between treatment arms. LDA was associated with increased bleeding per vaginam, but this was not associated with losses.
Preconception-initiated LDA was not significantly associated with live birth or pregnancy loss among women with one to two prior losses. However, higher live birth rates were observed among women with a single documented loss at <20 weeks’ gestation during the previous year. LDA is not recommended for the prevention of pregnancy loss.
PMCID: PMC4181666  PMID: 24702835
low dose aspirin; conception; pregnancy loss; fertility; live birth
2.  A randomised trial to evaluate the Effects of low dose Aspirin in Gestation and Reproduction (EAGeR): Design and baseline characteristics 
Paediatric and perinatal epidemiology  2013;27(6):10.1111/ppe.12088.
Low dose aspirin (LDA) has been proposed to improve pregnancy outcomes in couples experiencing recurrent pregnancy loss. However, results from studies of LDA on pregnancy outcomes have been inconsistent, perhaps because most studies evaluated LDA-initiated post-conception. The purpose of the Effects of Aspirin in Gestation and Reproduction (EAGeR) trial was to determine whether preconception-initiated LDA improves live-birth rates in women with 1–2 prior losses.
We performed a multicenter, block randomised, double-blind, placebo-controlled trial. Study participants were recruited using community-based advertisements and physician referral to four university medical centers in the US (2006–12). Eligible women were aged 18–40 years actively trying to conceive with 1–2 prior losses. Participants were randomised to receive daily LDA (81 mg/day) or a matching placebo, and all were provided with daily 400 mcg folic acid. Follow-up continued for ≤six menstrual cycles while attempting to conceive. For those that conceived, treatment was continued until 36 weeks gestation. The primary outcome was the cumulative live birth rate over the trial period.
1228 women were randomised (615 LDA, 613 placebo). Participants had a mean age of 28.7, were mostly white (95%), well educated (86% >high school education), and employed (75%) with a household income >$100,000 annually (40%). Characteristics of those in the treatment and placebo arms were well-balanced.
We describe the study design, recruitment, data collection, and baseline characteristics of participants enrolled in EAGeR, which aimed to determine the effect of LDA on live birth and other pregnancy outcomes in these women.
PMCID: PMC3821875  PMID: 24118062
Low-dose aspirin; conception; pregnancy; miscarriage; sub-fertility
3.  Estimation of the ROC Curve under Verification Bias 
The ROC (Receiver Operating Characteristic) curve is the most commonly used statistical tool for describing the discriminatory accuracy of a diagnostic test. Classical estimation of the ROC curve relies on data from a simple random sample from the target population. In practice, estimation is often complicated due to not all subjects undergoing a definitive assessment of disease status (verification). Estimation of the ROC curve based on data only from subjects with verified disease status may be badly biased. In this work we investigate the properties of the doubly robust (DR) method for estimating the ROC curve under verification bias originally developed by Rotnitzky et al. (2006) for estimating the area under the ROC curve. The DR method can be applied for continuous scaled tests and allows for a non ignorable process of selection to verification. We develop the estimator's asymptotic distribution and examine its finite sample properties via a simulation study. We exemplify the DR procedure for estimation of ROC curves with data collected on patients undergoing electron beam computer tomography, a diagnostic test for calcification of the arteries.
PMCID: PMC3475535  PMID: 19588455
Diagnostic test; Nonignorable; Semiparametric model; Sensitivity analysis; Sensitivity; Specificity
4.  Youden Index and the optimal threshold for markers with mass at zero‡ 
Statistics in medicine  2008;27(2):297-315.
The Youden Index is often used as a summary measure of the receiver operating characteristic curve. It measures the effectiveness of a diagnostic marker and permits the selection of an optimal threshold value or cutoff point for the biomarker of interest. Some markers, while basically continuous and positive, have a spike or positive mass of probability at the value zero. We provide a flexible modeling approach for estimating the Youden Index and its associated cutoff point for such spiked data and compare it with the standard empirical approach. We show how this modeling approach can be adjusted to take covariate information into account. This approach is applied to data on the Coronary Calcium Score, a marker for atherosclerosis. Published in 2007 by John Wiley & Sons, Ltd.
PMCID: PMC2749250  PMID: 17624866
Box–Cox power transformations; Coronary Calcium Score; diagnostic markers; mixture model; ROC curve; sensitivity; specificity

Results 1-4 (4)