Anzeige
Erschienen in:
14.06.2016 | Review
Preimplantation genetic testing for aneuploidy: what technology should you use and what are the differences?
Erschienen in: Journal of Assisted Reproduction and Genetics | Ausgabe 7/2016
Einloggen, um Zugang zu erhaltenAbstract
Purpose
The purpose of the review was to define the various diagnostic platforms currently available to perform preimplantation genetic testing for aneuploidy and describe in a clear and balanced manner the various strengths and weaknesses of these technologies.
Methods
A systematic literature review was conducted. We used the terms “preimplantation genetic testing,” “preimplantation genetic diagnosis,” “preimplantation genetic screening,” “preimplantation genetic diagnosis for aneuploidy,” “PGD,” “PGS,” and “PGD-A” to search through PubMed, ScienceDirect, and Google Scholar from the year 2000 to April 2016. Bibliographies of articles were also searched for relevant studies. When possible, larger randomized controlled trials were used. However, for some emerging data, only data from meeting abstracts were available.
Results
PGS is emerging as one of the most valuable tools to enhance pregnancy success with assisted reproductive technologies. While all of the current diagnostic platforms currently available have various advantages and disadvantages, some platforms, such as next-generation sequencing (NGS), are capable of evaluating far more data points than has been previously possible. The emerging complexity of different technologies, especially with the utilization of more sophisticated tools such as NGS, requires an understanding by clinicians in order to request the best test for their patients..
Conclusion
Ultimately, the choice of which diagnostic platform is utilized should be individualized to the needs of both the clinic and the patient. Such a decision must incorporate the risk tolerance of both the patient and provider, fiscal considerations, and other factors such as the ability to counsel patients on their testing results and how these may or may not impact clinical outcomes.