Literature DB >> 17061974

The Oxford Conception Study design and recruitment experience.

Cecilia Pyper1, Lise Bromhall, Sarah Dummett, Douglas G Altman, Pat Brownbill, Michael Murphy.   

Abstract

The Oxford Conception Study is a randomised controlled trial that aims to determine whether or not information about potential fertility from a device that monitors urinary hormones will increase the conception rate in women wishing to conceive. Three modified versions of a fertility monitor have been developed for the study. The monitor measures the levels of urinary oestrone-3-glucuronide (E3G) and luteinising hormone (LH), and the display indicates high or low fertility. The monitor requests all women to test their urine from day 6 to day 25 of the menstrual cycle inclusive. One-third of women are randomised to receive information from the fertility monitor about the early fertile time (from the first rise in E3G until the LH surge is detected), one-third receive information about the late fertile time (the onset of the LH surge and the following 2 days), and a third do not receive any information (control group). All the women are followed up for 6 months or until they are pregnant. A total of 1453 women have been recruited into the study, reaching the study recruitment goal for 80% power to detect a 10% difference in three-cycle pregnancy rate between the Late Fertile Time group (50%) and the Control group (40%), allowing for a 15% non-pregnancy drop-out rate. Follow-up of the women is currently ongoing. The primary analysis will compare the cumulative three-cycle pregnancy rate between each of the study arms. Time-specific conception probabilities will be estimated from coitus information recorded in 12-h intervals. The data from this study will also allow many additional questions to be addressed, including changes in intercourse patterns with feedback about the fertile days and other questions in relation to menstrual cycle function, sexual intercourse, stress, exposures to tobacco products, alcohol, caffeine and medications, fertility and pregnancy outcomes. In addition to presenting the study design, we review the recruitment experience for the Oxford Conception Study. We have achieved sustained and effective recruitment over time by primary use of recruiting via the Internet.

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Year:  2006        PMID: 17061974     DOI: 10.1111/j.1365-3016.2006.00771.x

Source DB:  PubMed          Journal:  Paediatr Perinat Epidemiol        ISSN: 0269-5022            Impact factor:   3.980


  12 in total

1.  Personal fertility monitors for contraception.

Authors:  Thomas P Bouchard; Stephen J Genuis
Journal:  CMAJ       Date:  2010-11-15       Impact factor: 8.262

2.  Recruitment for longitudinal, randomised pregnancy trials initiated preconception: lessons from the effects of aspirin in gestation and reproduction trial.

Authors:  Laurie L Lesher; Rebecca A Matyas; Lindsey A Sjaarda; Sarah L Newman; Robert M Silver; Noya Galai; Kathleen M Hovey; Jean Wactawski-Wende; Leah Emerick; Anne M Lynch; Betsy Mead; Janet M Townsend; Neil J Perkins; Sunni L Mumford; Joseph Stanford; Enrique F Schisterman
Journal:  Paediatr Perinat Epidemiol       Date:  2015-02-14       Impact factor: 3.980

3.  Stress reduces conception probabilities across the fertile window: evidence in support of relaxation.

Authors:  Germaine M Buck Louis; Kirsten J Lum; Rajeshwari Sundaram; Zhen Chen; Sungduk Kim; Courtney D Lynch; Enrique F Schisterman; Cecilia Pyper
Journal:  Fertil Steril       Date:  2010-08-05       Impact factor: 7.329

4.  Are increased levels of self-reported psychosocial stress, anxiety, and depression associated with fecundity?

Authors:  Courtney D Lynch; Rajeshwari Sundaram; Germaine M Buck Louis; Kirsten J Lum; Cecilia Pyper
Journal:  Fertil Steril       Date:  2012-06-13       Impact factor: 7.329

5.  Preconception stress and the secondary sex ratio: a prospective cohort study.

Authors:  Rebecca J Chason; Alexander C McLain; Rajeshwari Sundaram; Zhen Chen; James H Segars; Cecilia Pyper; Germaine M Buck Louis
Journal:  Fertil Steril       Date:  2012-08-09       Impact factor: 7.329

6.  Joint analysis of longitudinal and survival data measured on nested timescales by using shared parameter models: an application to fecundity data.

Authors:  Alexander C McLain; Rajeshwari Sundaram; Germaine M Buck Louis
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2014-09-24       Impact factor: 1.864

7.  [Pilot testing of an internet based pregnancy planning study "Snart-gravid.dk"].

Authors:  Ellen M Mikkelsen; Helle Terkildsen Maindal
Journal:  Klin Sygepleje       Date:  2011-01

8.  Flexible Bayesian Human Fecundity Models.

Authors:  Sungduk Kim; Rajeshwari Sundaram; Germaine M Buck Louis; Cecilia Pyper
Journal:  Bayesian Anal       Date:  2012-11-27       Impact factor: 3.728

9.  The role of social media in recruiting for clinical trials in pregnancy.

Authors:  Mahvash Shere; Xiu Yan Zhao; Gideon Koren
Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

10.  Pilot test and validation of the peak day method of prospective determination of ovulation against a handheld urine hormone monitor.

Authors:  Christina A Porucznik; Kyley J Cox; Karen C Schliep; Joseph B Stanford
Journal:  BMC Womens Health       Date:  2014-01-08       Impact factor: 2.809

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