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Models Predicting Success of Infertility Treatment: A Systematic Review



Zarinara A1 ; Zeraati H2 ; Kamali K1 ; Mohammad K2 ; Shahnazari P1 ; Akhondi MM1
Authors
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Authors Affiliations
  1. 1. Reproductive Biotechnology Research Center, Avicenna Research Institute, ACECR, P.O. Box: 19615-1177, Tehran, Iran
  2. 2. Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences, TUMS, Tehran, Iran

Source: Journal of Reproduction and Infertility Published:2016

Abstract

Background: Infertile couples are faced with problems that affect their marital life. Infertility treatment is expensive and time consuming and occasionally isn't simply possible. Prediction models for infertility treatment have been proposed and prediction of treatment success is a new field in infertility treatment. Because prediction of treatment success is a new need for infertile couples, this paper reviewed previous studies for catching a general concept in applicability of the models. Methods: This study was conducted as a systematic review at Avicenna Research Institute in 2015. Six data bases were searched based on WHO definitions and MESH key words. Papers about prediction models in infertility were evaluated. Results: Eighty one papers were eligible for the study. Papers covered years after 1986 and studies were designed retrospectively and prospectively. IVF prediction models have more shares in papers. Most common predictors were age, duration of infertility, ovarian and tubal problems. Conclusion: Prediction model can be clinically applied if the model can be statistically evaluated and has a good validation for treatment success. To achieve better results, the physician and the couples' needs estimation for treatment success rate were based on history, the examination and clinical tests. Models must be checked for theoretical approach and appropriate validation. The privileges for applying the prediction models are the decrease in the cost and time, avoiding painful treatment of patients, assessment of treatment approach for physicians and decision making for health managers. The selection of the approach for designing and using these models is inevitable.