Predicting the outcomes of assisted reproductive technology treatments: a systematic review and quality assessment of prediction models

Ian Henderson M.Sc. , Michael P. Rimmer M.Sc. , Stephen D. Keay M.D. , Paul Sutcliffe Ph.D. , Khalid S. Khan M.Sc. , Ephia Yasmin Ph.D. , Bassel H. Al Wattar Ph.D.
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引用次数: 1

Abstract

Objective

Predicting the outcomes of assisted reproductive technology (ART) treatments is desirable, but adopting prediction models into clinical practice remains limited. We aimed to review available prediction models for ART treatments by conducting a systematic review of the literature to identify the best-performing models for their accuracy, generalizability, and applicability.

Evidence review

We searched electronic databases (MEDLINE, EMBASE, and CENTRAL) until June 2020. We included studies reporting on the development or evaluation of models predicting the reproductive outcomes before (pre-ART) or after (intra-ART) starting treatment in couples undergoing any ART treatment. We evaluated the models’ discrimination, calibration, type of validation, and any implementation tools for clinical practice.

Results

We included 69 cohort studies reporting on 120 unique prediction models. Half of the studies reported on pre-ART (48%) and half on intra-ART (56%) prediction models. The commonest predictors used were maternal age (90%), tubal factor subfertility (50%), and embryo quality (60%). Only 14 models were externally validated (14/120, 12%), including 8 pre-ART models (Templeton, Nelson, LaMarca, McLernon, Arvis, and the Stolwijk A/I, C, II models) and 5 intra-ART models (Cai, Hunault, van Loendersloot, Meijerink, Stolwijk B, and the McLernon posttreatment model), with a reported c-statistic ranging from 0.50 to 0.78. Ten of these models provided implementation tools for clinical practice, with only 2 reporting online calculators.

Conclusion

We identified externally validated prediction models that could be used to advise couples undergoing ART treatments on their reproductive outcomes. The quality of the available models remains limited and more research is needed to improve their generalizability and applicability into clinical practice.

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预测辅助生殖技术治疗的结果:预测模型的系统回顾和质量评估
目的预测辅助生殖技术(ART)治疗的结果是可取的,但将预测模型应用于临床实践仍然有限。我们的目的是通过对文献进行系统的回顾来回顾现有的ART治疗预测模型,以确定其准确性、概括性和适用性的最佳模型。我们检索了电子数据库(MEDLINE, EMBASE和CENTRAL),直到2020年6月。我们纳入了报告在接受任何ART治疗的夫妇开始治疗前(ART前)或治疗后(ART内)预测生殖结果模型的开发或评估的研究。我们评估了模型的鉴别、校准、验证类型和任何临床实践的实施工具。结果我们纳入了69项队列研究,报告了120种独特的预测模型。一半的研究报告了抗逆转录病毒治疗前(48%)和一半的研究报告了抗逆转录病毒治疗期间(56%)的预测模型。最常见的预测因素是母亲年龄(90%)、输卵管因素不孕(50%)和胚胎质量(60%)。只有14个模型进行了外部验证(14/ 120,12%),包括8个art前模型(Templeton, Nelson, LaMarca, McLernon, Arvis和Stolwijk A/I, C, II模型)和5个art内模型(Cai, Hunault, van Loendersloot, Meijerink, Stolwijk B和McLernon治疗后模型),报告的C统计量范围为0.50至0.78。其中10个模型为临床实践提供了实施工具,只有2个报告在线计算器。结论:我们确定了外部验证的预测模型,可用于建议接受ART治疗的夫妇的生殖结果。现有模型的质量仍然有限,需要更多的研究来提高其在临床实践中的普遍性和适用性。
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来源期刊
F&S reviews
F&S reviews Endocrinology, Diabetes and Metabolism, Obstetrics, Gynecology and Women's Health, Urology
CiteScore
3.70
自引率
0.00%
发文量
0
审稿时长
61 days
期刊最新文献
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