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. 2015 Nov;104(5):1236-43.e1-2.
doi: 10.1016/j.fertnstert.2015.08.001. Epub 2015 Sep 3.

Predictors of participant retention in infertility treatment trials

Hongying Kuang  1 , Susan Jin  2 , Tracey Thomas  2 , Lawrence Engmann  3 , Karl R Hansen  4 , Christos Coutifaris  5 , Peter Casson  6 , Gregory Christman  7 , Ruben Alvero  8 , Nanette Santoro  8 , Esther Eisenberg  9 , Michael P Diamond  10 , Richard S Legro  11 , Heping Zhang  12 ; Reproductive Medicine Network
Collaborators, Affiliations

Predictors of participant retention in infertility treatment trials

Hongying Kuang et al. Fertil Steril. 2015 Nov.

Abstract

Objective: To identify variables associated with retention (or dropout) in infertility clinical trials. Retention of subjects in randomized controlled clinical trials (RCTs) has received considerable attention, but there have been few consistent findings.

Design: Secondary analysis of data from RCTs.

Setting: Academic medical centers.

Patient(s): Women with polycystic ovary syndrome (PCOS) or couples with unexplained infertility, aged 18-40 years.

Intervention(s): This study is not an intervention study, but the patients in the original RCTs were treated with any or combination of metformin, clomiphene citrate (CC), letrozole, and gonadotropins.

Main outcome measure(s): Successful retention versus dropout during the RCTs.

Result(s): Race, ethnicity, body mass index (BMI), insurance coverage, history of smoking, and history of alcohol use were significantly associated with retention whether they were considered in bivariate analyses or a multivariable logistic model. Specifically, white race, higher income, having graduate degrees, normal weight, better insurance coverage, nonsmokers, and those who reported current use of alcohol at the start of the trial, had higher retention rates.

Conclusion(s): We identified several additive and persistent predictors of retention that can be used to guide the conduct of RCTs and improve the retention rate. Given the limitation of our association analysis, methodologically sound and theoretically grounded research are warranted so that high quality data can be collected to improve our understanding on the causes of dropout.

Clinical trial registration number: NCT00068861 (PPCOS-I), NCT00719186 (PPCOS-II), and NCT01044862 (AMIGOS).

Keywords: Randomized controlled clinical trial; dropout; logistic regression; retention.

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Figures

Figure 1
Figure 1
Calibration between predicted and observed probabilities of retention. Predicted probabilities were calculated by averaged the probabilities estimated from the logistic model within each decile while the observed probabilities were the proportion of retained participants within each decile. The circles are the 10 points, the solid line is the regression line for the 10 points, and the dashed line is the perfect diagonal line.
See this image and copyright information in PMC

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