Barrie Amy, Homburg Roy, McDowell Garry, Brown Jeremy, Kingsland Charles, Troup Stephen
Hewitt Fertility Centre, Liverpool Women's NHS Foundation Trust, Liverpool, United Kingdom.
Hewitt Fertility Centre, Liverpool Women's NHS Foundation Trust, Liverpool, United Kingdom.
Fertil Steril. 2017 Mar;107(3):613-621. doi: 10.1016/j.fertnstert.2016.11.014. Epub 2017 Jan 6.
To study the efficacy of six embryo-selection algorithms (ESAs) when applied to a large, exclusive set of known implantation embryos.
Retrospective, observational analysis.
Fertility treatment center.
PATIENT(S): Women undergoing a total of 884 in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) treatment cycles (977 embryos) between September 2014 and September 2015 with embryos cultured using G-TL (Vitrolife) at 5% O, 89% N, 6% CO, at 37°C in EmbryoScope instruments.
INTERVENTION(S): None.
MAIN OUTCOME MEASURE(S): Efficacy of each ESA to predict implantation defined using specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV), area under the receiver operating characteristic curve (AUC), and likelihood ratio (LR), with differences in implantation rates (IR) in the categories outlined by each ESA statistically analyzed (Fisher's exact and Kruskal-Wallis tests).
RESULT(S): When applied to an exclusive cohort of known implantation embryos, the PPVs of each ESA were 42.57%, 41.52%, 44.28%, 38.91%, 38.29%, and 40.45%. The NPVs were 62.12%, 68.26%, 71.35%, 76.19%, 61.10%, and 64.14%. The sensitivity was 16.70%, 75.33%, 72.94%, 98.67%, 51.19%, and 62.33% and the specificity was 85.83%, 33.33%, 42.33%, 2.67%, 48.17%, and 42.33%, The AUC were 0.584, 0.558, 0.573, 0.612, 0.543, and 0.629. Two of the ESAs resulted in statistically significant differences in the embryo classifications in terms of IR.
CONCLUSION(S): These results highlight the need for the development of in-house ESAs that are specific to the patient, treatment, and environment. These data suggest that currently available ESAs may not be clinically applicable and lose their diagnostic value when externally applied.
研究六种胚胎选择算法（ESA）应用于大量已知着床胚胎的专属集合时的效果。
回顾性观察分析。
生育治疗中心。
2014年9月至2015年9月期间共进行884个体外受精（IVF）或卵胞浆内单精子注射（ICSI）治疗周期（977个胚胎）的女性，胚胎在EmbryoScope仪器中于37°C、5%氧气、89%氮气、6%二氧化碳的条件下使用G-TL（Vitrolife）培养基培养。
无。
每种ESA预测着床的效果，用特异性、敏感性、阳性预测值（PPV）、阴性预测值（NPV）、受试者工作特征曲线下面积（AUC）和似然比（LR）来定义，对每种ESA所划分类别中的着床率（IR）差异进行统计学分析（Fisher精确检验和Kruskal-Wallis检验）。
当应用于已知着床胚胎的专属队列时，每种ESA的PPV分别为42.57%、41.52%、44.28%、38.91%、38.29%和40.45%。NPV分别为62.12%、68.26%、71.35%、76.19%、61.10%和64.14%。敏感性分别为16.70%、75.33%、72.94%、98.67%、51.19%和62.33%，特异性分别为85.83%、33.33%、42.33%、2.67%、48.17%和42.33%，AUC分别为0.584、0.558、0.573、0.612、0.543和0.629。其中两种ESA在胚胎分类的IR方面导致了统计学上的显著差异。
这些结果凸显了开发针对患者、治疗和环境的内部ESA的必要性。这些数据表明，目前可用的ESA可能在临床上不适用，并且在外部应用时会失去其诊断价值。
