Liu Yanhe, Feenan Katie, Chapple Vincent, Matson Phillip
a Fertility North , Joondalup , Australia.
b School of Medical and Health Sciences, Edith Cowan University , Joondalup , Australia.
Hum Fertil (Camb). 2019 Sep;22(3):182-190. doi: 10.1080/14647273.2018.1425919. Epub 2018 Jan 16.
This study investigated the efficacy of four published day 3 embryo time-lapse algorithms based on different types of datasets (known implantation data [KID] and single embryo transfer [SET]), and the confounding effect of female age and conventional embryo morphology. Four algorithms were retrospectively applied to three types of datasets generated at Fertility North between February 2013 and December 2014: (a) KID dataset ( = 270), (b) a subset of SET ( = 144, end-point = implantation), and (c) SET ( = 144, end-point = live birth), respectively. All four algorithms showed progressively reduced predictive power (expressed as area under the receiver operating characteristics curve and 95% confidence interval [CI]) after application to the three datasets (a-c): Liu (0.762 [0.701-0.824] vs. 0.724 [0.641-0.807] vs. 0.707 [0.620-0.793]), KIDScore (0.614 [0.539-0.688] vs. 0.548 [0.451-0.645] vs. 0.536 [0.434-0.637]), Meseguer (0.585 [0.508-0.663] vs. 0.56 [0.462-0.658] vs. 0.549 [0.445-0.652]), and Basile (0.582 [0.505-0.659] vs. 0.519 [0.421-0.618] vs. 0.509 [0.406-0.612]). Furthermore, using KID dataset, the association (expressed as odds ratio and 95% CI) between time-lapse algorithms and implantation outcomes lost statistical significance after adjusting for conventional embryo morphology and female age in 3 of the 4 algorithms (KIDScore 1.832 [1.118-3.004] vs. 1.063 [0.659-1.715], Meseguer 1.150 [1.021-1.295] vs. 1.122 [0.981-1.284] and Basile 1.122 [1.008-1.249] vs. 1.038 [0.919-1.172]). In conclusion, SET is a preferred dataset to KID when developing or validating time-lapse algorithms, and day 3 conventional embryo morphology and female age should be considered as confounding factors.
本研究调查了基于不同类型数据集（已知着床数据[KID]和单胚胎移植[SET]）的四种已发表的第3天胚胎延时算法的效能，以及女性年龄和传统胚胎形态的混杂效应。将四种算法回顾性应用于2013年2月至2014年12月在北方生育中心生成的三种类型的数据集：(a) KID数据集（n = 270），(b) SET的一个子集（n = 144，终点 = 着床），以及(c) SET（n = 144，终点 = 活产）。将这四种算法应用于三个数据集（a - c）后，所有四种算法的预测能力（以受试者操作特征曲线下面积和95%置信区间[CI]表示）均逐渐降低：Liu算法（0.762 [0.701 - 0.824]对0.724 [0.641 - 0.807]对0.707 [0.620 - 0.793]）、KIDScore算法（0.614 [0.539 - 0.688]对0.548 [0.451 - 0.645]对0.536 [0.434 - 0.637]）、Meseguer算法（0.585 [0.508 - 0.663]对0.56 [0.462 - 0.658]对0.549 [0.445 - 0.652]）和Basile算法（0.582 [0.505 - 0.659]对0.519 [0.421 - 0.618]对0.509 [0.406 - 0.612]）。此外，使用KID数据集时，在4种算法中的3种算法中，在调整了传统胚胎形态和女性年龄后，延时算法与着床结局之间的关联（以优势比和95% CI表示）失去了统计学意义（KIDScore算法：1.832 [1.118 - 3.004]对1.063 [0.659 - 1.715]；Meseguer算法：1.150 [1.021 - 1.295]对1.122 [0.981 - 1.284]；Basile算法：1.122 [1.008 - 1.249]对1.038 [0.919 - 1.172]）。总之，在开发或验证延时算法时，SET是比KID更优的数据集，并且第3天的传统胚胎形态和女性年龄应被视为混杂因素。
