Is there an advantage in scoring early embryos on more than one day?

BACKGROUND This study was undertaken to determine what characteristics should be recorded on which days to build a predictive model for selection of Day 3 embryos. METHODS Embryos failing to form a clinical sac or that formed a viable fetus (to > or =12 weeks), and transferred singly (n = 269) or in pairs (n = 1326) were scored for early cleavage and pronuclear status on Day 1, and cell number, fragmentation, and symmetry on Days 2 and 3, with number of nuclei per blastomere also recorded on Day 2. Seven candidate models were identified using a priori clinical knowledge and univariate analyses. Each model was fit on a training-set and evaluated on a test-set with resampling, with discrimination assessed using the area under the ROC curve (AUC) and calibration assessed using the Hosmer-Lemeshow statistics. RESULTS Models built using Day 1, 2 or 3 scores independently on the 30 resampled data sets showed that Day 1 evaluations provided the poorest predictive value (median AUC = 0.683 versus 0.729 and 0.725, for Day 2 and 3). Combining information from Day 1, 2 and 3 marginally improved discrimination (median AUC = 0.737). Using the final Day 3 model fitted on the whole dataset, the median AUC was 0.732 (95% CI, 0.700-0.764), and 68.6% of embryos would be correctly classified with a cutoff probability equal to 0.3. CONCLUSIONS Day 2 or Day 3 evaluations alone are sufficient for morphological selection of cleavage stage embryos. The derived regression coefficients can be used prospectively in an algorithm to rank embryos for selection.

[1]  R. Edwards,et al.  The growth of human preimplantation embryos in vitro. , 1981, American journal of obstetrics and gynecology.

[2]  P Barlow,et al.  Embryo scoring as a prognostic tool in IVF treatment. , 1987, Human reproduction.

[3]  G. Bettendorf,et al.  Endocrine profiles and luteal function during GnRH-analogue/HMG therapy. , 1989, Human reproduction.

[4]  D. Hosmer,et al.  Applied Logistic Regression , 1991 .

[5]  P. Devroey,et al.  The relationship between embryo quality and the occurrence of multiple pregnancies , 1992, Fertility and sterility.

[6]  S. Campbell,et al.  The cumulative embryo score: a predictive embryo scoring technique to select the optimal number of embryos to transfer in an in-vitro fertilization and embryo transfer programme. , 1992, Human reproduction.

[7]  J. Grifo,et al.  Embryo morphology, developmental rates, and maternal age are correlated with chromosome abnormalities. , 1995, Fertility and sterility.

[8]  J. Shaffer Multiple Hypothesis Testing , 1995 .

[9]  C. Giorgetti,et al.  Implantation: Embryo score to predict implantation after in-vitro fertilization: based on 957 single embryo transfers , 1995 .

[10]  L. Gianaroli,et al.  Preimplantation genetic diagnosis increases the implantation rate in human in vitro fertilization by avoiding the transfer of chromosomally abnormal embryos. , 1997, Fertility and sterility.

[11]  John Mylopoulos,et al.  Case-based reasoning in IVF: prediction and knowledge mining , 1998, Artif. Intell. Medicine.

[12]  R. Saith,et al.  Relationships between the developmental potential of human in-vitro fertilization embryos and features describing the embryo, oocyte and follicle. , 1998, Human reproduction update.

[13]  D. De Neubourg,et al.  Characterization of a top quality embryo, a step towards single-embryo transfer. , 1999, Human reproduction.

[14]  Stanley Lemeshow,et al.  Applied Logistic Regression, Second Edition , 1989 .

[15]  N. Desai,et al.  Morphological evaluation of human embryos and derivation of an embryo quality scoring system specific for day 3 embryos: a preliminary study. , 2000, Human reproduction.

[16]  C. Giorgetti,et al.  Embryo score is a better predictor of pregnancy than the number of transferred embryos or female age. , 2001, Fertility and sterility.

[17]  D. De Neubourg,et al.  Calculating the implantation potential of day 3 embryos in women younger than 38 years of age: a new model. , 2001, Human reproduction.

[18]  M. Pepe The Statistical Evaluation of Medical Tests for Classification and Prediction , 2003 .

[19]  Lutz Hamel,et al.  Comparing data mining and logistic regression for predicting IVF outcome , 2003 .

[20]  G. Sher,et al.  The graduated embryo score predicts the outcome of assisted reproductive technologies better than a single day 3 evaluation and achieves results associated with blastocyst transfer from day 3 embryo transfer. , 2003, Fertility and sterility.

[21]  C. Racowsky,et al.  Day 3 and day 5 morphological predictors of embryo viability. , 2003, Reproductive biomedicine online.

[22]  Phillip I. Good,et al.  Common Errors in Statistics (and How to Avoid Them) , 2003 .

[23]  L. Nieddu,et al.  Pattern recognition methods in human‐assisted reproduction , 2004 .

[24]  Lucila Ohno-Machado,et al.  Discrimination and calibration of mortality risk prediction models in interventional cardiology , 2005, J. Biomed. Informatics.

[25]  J. Shaw,et al.  A formula for scoring human embryo growth rates in in vitro fertilization: Its value in predicting pregnancy and in comparison with visual estimates of embryo quality , 1986, Journal of in Vitro Fertilization and Embryo Transfer.

[26]  Bagyalakshmi Mathiyalagan,et al.  Prediction of embryo developmental potential and pregnancy based on early stage morphological characteristics. , 2006, Fertility and sterility.

[27]  D. Gardner,et al.  Proteomic analysis of individual human embryos to identify novel biomarkers of development and viability. , 2006, Fertility and sterility.

[28]  L. Ohno-Machado,et al.  Prognosis in critical care. , 2006, Annual review of biomedical engineering.

[29]  Santiago Munné,et al.  Chromosome abnormalities and their relationship to morphology and development of human embryos. , 2006, Reproductive biomedicine online.

[30]  C. Racowsky,et al.  Early compaction on day 3 may be associated with increased implantation potential. , 2006, Fertility and sterility.

[31]  Kay Elder,et al.  Human preimplantation embryo selection , 2007 .

[32]  B Giraudeau,et al.  Limited value of morphological assessment at days 1 and 2 to predict blastocyst development potential: a prospective study based on 4042 embryos. , 2007, Human reproduction.

[33]  Luca Gianaroli,et al.  Embryo morphology and development are dependent on the chromosomal complement. , 2007, Fertility and sterility.

[34]  A. Revelli,et al.  Construction of an evidence-based integrated morphology cleavage embryo score for implantation potential of embryos scored and transferred on day 2 after oocyte retrieval. , 2007, Human reproduction.

[35]  C. Racowsky,et al.  Development rate, cumulative scoring and embryonic viability , 2007 .

[36]  N. Cook Use and Misuse of the Receiver Operating Characteristic Curve in Risk Prediction , 2007, Circulation.

[37]  R. Goodacre,et al.  Predicting human embryo viability: the road to non-invasive analysis of the secretome using metabolic footprinting. , 2007, Reproductive biomedicine online.

[38]  Denny Sakkas,et al.  Noninvasive metabolomic profiling of embryo culture media using Raman and near-infrared spectroscopy correlates with reproductive potential of embryos in women undergoing in vitro fertilization. , 2007, Fertility and sterility.

[39]  C. Giorgetti,et al.  Relationship between even early cleavage and day 2 embryo score and assessment of their predictive value for pregnancy. , 2007, Reproductive biomedicine online.

[40]  H. Leese,et al.  Prediction of Porcine Blastocyst Formation Using Morphological, Kinetic, and Amino Acid Depletion and Appearance Criteria Determined During the Early Cleavage of In Vitro-Produced Embryos1 , 2007, Biology of reproduction.

[41]  C. Lambalk,et al.  Metabolomic profiling by near-infrared spectroscopy as a tool to assess embryo viability: a novel, non-invasive method for embryo selection. , 2008, Human reproduction.

[42]  C. Venetis,et al.  How to improve the probability of pregnancy in poor responders undergoing in vitro fertilization: a systematic review and meta-analysis. , 2009, Fertility and sterility.

[43]  F. Segal,et al.  A CHARACTERIZATION OF FIBRANT SEGAL CATEGORIES , 2006, math/0603400.