A prognosis-based approach to infertility: understanding the role of time

D. F. Albertini, R. Anderson, S. Bhattacharya, J. L. H. Evers, D. J. Mclernon, S. Repping, E. Somigliana, D. T. Baird, P. G. Crosignani*, K. Diedrich, R. G. Farquharson, K. Lundin, J. S. Tapanainen, A. Van Steirteghem, ESHRE Capri Workshop Grp

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The current definition of infertility acknowledges the importance of duration of pregnancy seeking but fails to recognize the prevalent negative impact of female age. In fact, the diagnosis of unexplained infertility increases with women's age because of our incapacity to discern between age-related infertility and real unexplained infertility. Physicians' response to the pressures of increased female age has been to take prompt refuge in assisted reproduction despite the lack of robust evidence and the inherent risks and costs of these procedures. Moreover, the prioritization of immediate health gains over those in the future, preference for accessing active treatment rapidly and reluctance to wait for spontaneous pregnancy expose patients to additional risks of overtreatment. Solutions are not simple to find but an alternative and innovative vision of infertility based on prognosis may be a valid solution. The availability of validated dynamic models based on real-life data that could predict both natural and ART-mediated conceptions may be of benefit. They could facilitate patients' counselling and could optimize the chances of success without exposing patients to unnecessary, expensive and demanding treatments.

Original languageEnglish
Pages (from-to)1556-1559
Number of pages4
JournalHuman Reproduction
Volume32
Issue number8
DOIs
Publication statusPublished - Aug 2017

Keywords

  • aging
  • subfertility
  • infertility
  • fecundity
  • age-related infertility
  • unexplained infertility
  • IN-VITRO FERTILIZATION
  • UNEXPLAINED INFERTILITY
  • SUBFERTILE COUPLES
  • PREDICTION MODELS
  • LIVE BIRTH
  • WOMEN
  • AGE
  • MEDICINE

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