Toggle Main Menu Toggle Search

Open Access padlockePrints

Reproductive outcome following pre-implantation genetic diagnosis (PGD) in the UK

Lookup NU author(s): Dr Abigail Sharpe, Dr Peter Avery, Dr Meenakshi Choudhary


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


© 2017 The British Fertility Society In 2013, the National Health Service Commissioning board centralized the funding in England for up to three cycles of pre-implantation genetic diagnosis (PGD) for couples who have, or are carriers of, a specific genetic disorder. This study presents the historical data of PGD cycles and their clinical outcomes in UK as extrapolated from the national data registry. Retrospective analysis of outcome of cycles undergoing pre-implantation genetic diagnosis in the UK over the past 20 years was performed from the Human Fertilisation and Embryology Authority database (n = 2974). Binary logistic regression was used to determine trends over time and adjusted for maternal age. Briefly, the number of PGD cycles has risen 127-fold from 1991 to 2012 with 3.6-fold increase (360% rise) from 2004 to 2012. A total of one in four embryos following pre-implantation genetic diagnosis did not reach embryo transfer and 92% of these were due to a failure to survive. The live birth rate has risen over 20 years and there has been a steady decline in reported incidence of congenital abnormalities (p < 0.07). PGD has thus emerged as a safe and effective alternative to prenatal diagnosis but with ever evolving technological advances, a robust system of data collection that incorporates techniques used and reporting of mutation-specific clinical outcomes is suggested.

Publication metadata

Author(s): Sharpe A, Avery P, Choudhary M

Publication type: Article

Publication status: Published

Journal: Human Fertility

Year: 2018

Volume: 21

Issue: 2

Pages: 120-127

Online publication date: 12/06/2017

Acceptance date: 15/11/2016

ISSN (print): 1464-7273

ISSN (electronic): 1742-8149

Publisher: Taylor and Francis Ltd


DOI: 10.1080/14647273.2017.1336259


Altmetrics provided by Altmetric