How to diagnose and treat male subfertility

Open Access
Authors
  • M. Cissen
Supervisors
  • S. Repping
  • D.D.M. Braat
Cosupervisors
  • M. van Wely
  • J.P. de Bruin
Award date 12-04-2017
ISBN
  • 9789462334557
Number of pages 208
Organisations
  • Faculty of Medicine (AMC-UvA)
Abstract
Approximately 80% of subfertile couples still have a chance to conceive naturally and the most important thing is to assess whether any form of medical assistance will increase their chance of pregnancy over continuing natural conception.
In couples with male subfertility, IUI, IVF and ICSI are frequently used fertility treatments. Evidence-based guidelines on male subfertility are limited and the use of medically assisted reproduction is generally experience-based.
In roughly 1% of subfertile couples the male partner is diagnosed with non-obstructive azoospermia. Men with NOA are able to father their own genetic child by using testicular sperm extraction (TESE) in combination with ICSI. Since both TESE and TESE-ICSI are invasive and costly procedures, patients should be well informed about their chances of successful TESE and their likelihood to conceive after TESE-ICSI before undergoing treatment.
In this thesis, we performed several studies on male subfertility and MAR. We concluded that categorizing couples with male subfertility based on the TMSC allows for better classification in terms of chance of spontaneous ongoing pregnancy rate than categorization using the WHO classification system. We also concluded that there is insufficient evidence to determine whether there is any difference in safety and effectiveness between different treatment strategies for male subfertility. Furthermore, we developed a prediction model for obtaining sperm after testicular sperm extraction (TESE) in men suffering from NOA, as well as a prediction model for live birth in TESE-ICSI. Finally, we concluded that the current sperm DNA fragmentation tests have limited capacity to predict the chance of pregnancy in context of MAR.
Document type PhD thesis
Language English
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