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Yao MWM, Nguyen ET, Retzloff MG, Gago LA, Copland S, Nichols JE, Payne JF, Opsahl M, Cadesky K, Meriano J, Donesky BW, Bird J, Peavey M, Beesley R, Neal G, Bird JS, Swanson T, Chen X, Walmer DK. Improving IVF Utilization with Patient-Centric Artificial Intelligence-Machine Learning (AI/ML): A Retrospective Multicenter Experience. J Clin Med 2024; 13:3560. [PMID: 38930089 PMCID: PMC11204457 DOI: 10.3390/jcm13123560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2024] [Revised: 06/07/2024] [Accepted: 06/14/2024] [Indexed: 06/28/2024] Open
Abstract
Objectives: In vitro fertilization (IVF) has the potential to give babies to millions more people globally, yet it continues to be underutilized. We established a globally applicable and locally adaptable IVF prognostics report and framework to support patient-provider counseling and enable validated, data-driven treatment decisions. This study investigates the IVF utilization rates associated with the usage of machine learning, center-specific (MLCS) prognostic reports (the Univfy® report) in provider-patient pre-treatment and IVF counseling. Methods: We used a retrospective cohort comprising 24,238 patients with new patient visits (NPV) from 2016 to 2022 across seven fertility centers in 17 locations in seven US states and Ontario, Canada. We tested the association of Univfy report usage and first intra-uterine insemination (IUI) and/or first IVF usage (a.k.a. conversion) within 180 days, 360 days, and "Ever" of NPV as primary outcomes. Results: Univfy report usage was associated with higher direct IVF conversion (without prior IUI), with odds ratios (OR) 3.13 (95% CI 2.83, 3.46), 2.89 (95% CI 2.63, 3.17), and 2.04 (95% CI 1.90, 2.20) and total IVF conversion (with or without prior IUI), OR 3.41 (95% CI 3.09, 3.75), 3.81 (95% CI 3.49, 4.16), and 2.78 (95% CI 2.59, 2.98) in 180-day, 360-day, and Ever analyses, respectively; p < 0.05. Among patients with Univfy report usage, after accounting for center as a factor, older age was a small yet independent predictor of IVF conversion. Conclusions: Usage of a patient-centric, MLCS-based prognostics report was associated with increased IVF conversion among new fertility patients. Further research to study factors influencing treatment decision making and real-world optimization of patient-centric workflows utilizing the MLCS reports is warranted.
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Affiliation(s)
- Mylene W. M. Yao
- Department of R&D, Univfy Inc., 117 Main Street, #139, Los Altos, CA 94022, USA
| | - Elizabeth T. Nguyen
- Department of R&D, Univfy Inc., 117 Main Street, #139, Los Altos, CA 94022, USA
| | | | | | | | - John E. Nichols
- Piedmont Reproductive Endocrinology Group, Greenville, SC 29615, USA (J.F.P.)
| | - John F. Payne
- Piedmont Reproductive Endocrinology Group, Greenville, SC 29615, USA (J.F.P.)
| | | | - Ken Cadesky
- TRIO Fertility Partners, Toronto, ON M5G 2K4, Canada
| | - Jim Meriano
- TRIO Fertility Partners, Toronto, ON M5G 2K4, Canada
| | | | - Joseph Bird
- My Fertility Center, Chattanooga, TN 37421, USA
| | - Mary Peavey
- Atlantic Reproductive Medicine, Raleigh, NC 27617, USA
| | | | - Gregory Neal
- Fertility Center of San Antonio, San Antonio, TX 78229, USA
| | | | - Trevor Swanson
- Department of R&D, Univfy Inc., 117 Main Street, #139, Los Altos, CA 94022, USA
| | - Xiaocong Chen
- Department of R&D, Univfy Inc., 117 Main Street, #139, Los Altos, CA 94022, USA
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Shingshetty L, Cameron NJ, Mclernon DJ, Bhattacharya S. Predictors of success after in vitro fertilization. Fertil Steril 2024; 121:742-751. [PMID: 38492930 DOI: 10.1016/j.fertnstert.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/01/2024] [Accepted: 03/04/2024] [Indexed: 03/18/2024]
Abstract
The last few decades have witnessed a rise in the global uptake of in vitro fertilization (IVF) treatment. To ensure optimal use of this technology, it is important for patients and clinicians to have access to tools that can provide accurate estimates of treatment success and understand the contribution of key clinical and laboratory parameters that influence the chance of conception after IVF treatment. The focus of this review was to identify key predictors of IVF treatment success and assess their impact in terms of live birth rates. We have identified 11 predictors that consistently feature in currently available prediction models, including age, duration of infertility, ethnicity, body mass index, antral follicle count, previous pregnancy history, cause of infertility, sperm parameters, number of oocytes collected, morphology of transferred embryos, and day of embryo transfer.
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Affiliation(s)
- Laxmi Shingshetty
- Aberdeen Centre for Reproductive Medicine, NHS Grampian, Aberdeen, Aberdeenshire, United Kingdom; School of Medicine, Nutrition Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, Aberdeenshire, United Kingdom.
| | - Natalie J Cameron
- School of Medicine, Nutrition Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, Aberdeenshire, United Kingdom; Aberdeen Maternity Hospital, NHS Grampian and University of Aberdeen, Aberdeen, Aberdeenshire, United Kingdom
| | - David J Mclernon
- Medical Statistics Team, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, Aberdeenshire, United Kingdom
| | - Siladitya Bhattacharya
- School of Medicine, Nutrition Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, Aberdeenshire, United Kingdom
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Early prediction of live birth for assisted reproductive technology patients: a convenient and practical prediction model. Sci Rep 2021; 11:331. [PMID: 33431900 PMCID: PMC7801433 DOI: 10.1038/s41598-020-79308-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 12/07/2020] [Indexed: 11/08/2022] Open
Abstract
Live birth is the most important concern for assisted reproductive technology (ART) patients. Therefore, in the medical reproductive centre, obstetricians often need to answer the following question: "What are the chances that I will have a healthy baby after ART treatment?" To date, our obstetricians have no reference on which to base the answer to this question. Our research aimed to solve this problem by establishing prediction models of live birth for ART patients. Between January 1, 2010, and May 1, 2017, we conducted a retrospective cohort study of women undergoing ART treatment at the Reproductive Medicine Centre, Xiangya Hospital of Central South University, Hunan, China. The birth of at least one live-born baby per initiated cycle or embryo transfer procedure was defined as a live birth, and all other pregnancy outcomes were classified as no live birth. A live birth prediction model was established by stepwise multivariate logistic regression. All eligible subjects were randomly allocated to two groups: group 1 (80% of subjects) for the establishment of the prediction models and group 2 (20% of subjects) for the validation of the established prediction models. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each prediction model at different cut-off values were calculated. The prediction model of live birth included nine variables. The area under the ROC curve was 0.743 in the validation group. The sensitivity, specificity, PPV, and NPV of the established model ranged from 97.9-24.8%, 7.2-96.3%, 44.8-83.8% and 81.7-62.5%, respectively, at different cut-off values. A stable, reliable, convenient, and satisfactory prediction model for live birth by ART patients was established and validated, and this model could be a useful tool for obstetricians to predict the live rate of ART patients. Meanwhile, it is also a reference for obstetricians to create good conditions for infertility patients in preparation for pregnancy.
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Alonso A, Van der Elst W, Sanchez L, Luaces P, Molenberghs G. Identifying individual predictive factors for treatment efficacy. Biometrics 2020; 78:35-45. [PMID: 33128231 DOI: 10.1111/biom.13398] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2019] [Accepted: 10/12/2020] [Indexed: 11/29/2022]
Abstract
Given the heterogeneous responses to therapy and the high cost of treatments, there is an increasing interest in identifying pretreatment predictors of therapeutic effect. Clearly, the success of such an endeavor will depend on the amount of information that the patient-specific variables convey about the individual causal treatment effect on the response of interest. In the present work, using causal inference and information theory, a strategy is proposed to evaluate individual predictive factors for cancer immunotherapy efficacy. In a first step, the methodology proposes a causal inference model to describe the joint distribution of the pretreatment predictors and the individual causal treatment effect. Further, in a second step, the so-called predictive causal information (PCI), a metric that quantifies the amount of information the pretreatment predictors convey on the individual causal treatment effects, is introduced and its properties are studied. The methodology is applied to identify predictors of therapeutic success for a therapeutic vaccine in advanced lung cancer. A user-friendly R library EffectTreat is provided to carry out the necessary calculations.
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Affiliation(s)
- Ariel Alonso
- I-BioStat, Catholic University of Leuven, Leuven, Belgium
| | | | | | | | - Geert Molenberghs
- I-BioStat, Catholic University of Leuven, Leuven, Belgium.,I-BioStat, Hasselt University, Diepenbeek, Belgium
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5
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Jenkins J, van der Poel S, Krüssel J, Bosch E, Nelson SM, Pinborg A, Yao MM. Empathetic application of machine learning may address appropriate utilization of ART. Reprod Biomed Online 2020; 41:573-577. [DOI: 10.1016/j.rbmo.2020.07.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Revised: 04/27/2020] [Accepted: 07/09/2020] [Indexed: 01/10/2023]
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Tajalli S, Mashayekhi F, Salehi Z, Arefi S, Sasani ST. Association of hTERT SNP (rs2736100) with implantation failure after in vitro fertilization and embryo transfer (IVF-ET). Br J Biomed Sci 2020; 78:41-43. [PMID: 32401182 DOI: 10.1080/09674845.2020.1769332] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- S Tajalli
- Department of Biology, Faculty of Sciences, University of Guilan , Rasht, Iran
| | - F Mashayekhi
- Department of Biology, Faculty of Sciences, University of Guilan , Rasht, Iran
| | - Z Salehi
- Department of Biology, Faculty of Sciences, University of Guilan , Rasht, Iran
| | - S Arefi
- Department of Biology, Faculty of Sciences, University of Guilan , Rasht, Iran
| | - S T Sasani
- Department of Biology, Faculty of Sciences, University of Guilan , Rasht, Iran
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Schaeffer E, Porchia LM, Neumann A, Luna A, Rojas T, López-Bayghen E. Embryos derived from donor or patient oocytes are not different for in vitro fertilization outcomes when PGT allows euploid embryo selection: a retrospective study. Clin Transl Med 2020; 9:14. [PMID: 32030567 PMCID: PMC7005195 DOI: 10.1186/s40169-020-0266-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Accepted: 01/24/2020] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND At our facilities, patients that received embryos using donor oocyte during in vitro fertilization (IVF), usually have had at least one failed attempt to produce at least one euploid embryo with their own oocytes; however, the current debate between using donor over patient oocytes remains inconclusive. We examined the aneuploidy rate and IVF clinical outcomes from embryos derived from either donor or patient oocytes. METHODS Retrospectively, 973 cycles were examined of patients who underwent a standard IVF protocol. Chromosomal content was determined using Pre-implantation Genetic Testing (PGT) by either microarray-comparative genomic hybridization or Next-generation sequencing from either Day 3 (blastocysts) or Day 5 (trophectoderm) embryo biopsies, respectively. Embryo implantation was confirmed by serum β-hCG (> 10 m IU/mL/Day 14), whereas clinical pregnancy by a fetal heartbeat (Week 6.5-8). RESULTS Embryos derived from donor oocytes presented with more monosomies than embryos derived from patient oocytes (41.2% vs. 25.4%, p < 0.05, respectively); however, only Trisomy 7 (0.4% vs. 2.3%, p < 0.05) and Trisomy in X (0.7% vs. 2.3%, p < 0.05) were significantly less present when compared to patient oocyte derived embryos. Interestingly, rates for embryo implantation (46.7% vs. 50.8%, p = 0.35), clinical pregnancy (38.5% vs. 43.1%, p = 0.30), and live birth (30.5% vs. 30.5%, p = 0.99) were similar for embryos derived from donor and patient oocytes. These results did not change when adjusted for the number of embryos implanted. CONCLUSION Here, we show no significant differences in achieving pregnancy when using donor oocytes. Taking into consideration that aneuploidy rates are > 30% in embryos, independent of the oocyte origin, PGT should be recommended with donor oocytes as well.
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Affiliation(s)
- Elizabeth Schaeffer
- Laboratorio de Investigación y Diagnóstico Molecular, Instituto de Infertilidad y Genética, Ingenes, México City, Mexico
- Departamento de Toxicología, Centro de Investigación de Estudios Avanzados del Instituto Politécnico Nacional, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, CP 07360, México City, Distrito Federal, Mexico
| | - Leonardo M Porchia
- Departamento de Toxicología, Centro de Investigación de Estudios Avanzados del Instituto Politécnico Nacional, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, CP 07360, México City, Distrito Federal, Mexico
| | - Adina Neumann
- Laboratorio de Investigación y Diagnóstico Molecular, Instituto de Infertilidad y Genética, Ingenes, México City, Mexico
| | - Almena Luna
- Laboratorio de Investigación y Diagnóstico Molecular, Instituto de Infertilidad y Genética, Ingenes, México City, Mexico
| | - Tania Rojas
- Laboratorio de Investigación y Diagnóstico Molecular, Instituto de Infertilidad y Genética, Ingenes, México City, Mexico
| | - Esther López-Bayghen
- Departamento de Toxicología, Centro de Investigación de Estudios Avanzados del Instituto Politécnico Nacional, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, CP 07360, México City, Distrito Federal, Mexico.
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Gao H, Liu DE, Li Y, Tang J, Wu X, Tan H. Uterine size and volume are associated with higher live birth rate in patients undergoing assisted reproduction technology: A prospective cohort study. Medicine (Baltimore) 2019; 98:e17966. [PMID: 31764800 PMCID: PMC6882568 DOI: 10.1097/md.0000000000017966] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
To investigate how uterine size and volume are associated with live birth rate in patients undergoing assisted reproduction technology.This prospective cohort study was conducted at the Reproductive Medicine Centre from January 2010 to May 2017. Multivariate binary logistic regression was used to evaluate the relations between uterine size, total volume, and live birth outcomes, after they were adjusted for the main influencing factors.A total of 7320 women of clinical pregnancy were enrolled. Compared with uterine lengths of 50 to 59 mm (referent), women with uterine lengths ≥60 mm had a lower live birth rate (RR = 1.541). Compared with uterine widths of ≥50 mm (referent), women with uterine widths <30 mm had a lower live birth rate (RR = 1.430). Compared with uterine anteroposterior diameters of <30 mm (referent), women with uterine anteroposterior diameters ≥50 mm had a lower live birth rate (RR = 1.636). Compared with uterine volumes of 30 to 49 mL (referent), women with volumes <30 mL and ≥70 mL had lower live birth rates (RR = 1.368 and 1.742, respectively).Our findings indicate that uterine sizes and volumes that were too large or too small reduced the live birth rate.
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Affiliation(s)
- Hong Gao
- School of Nursing, University of South China, Hengyang
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha
| | - Dong-e Liu
- Reproductive Medicine Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yumei Li
- Reproductive Medicine Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jing Tang
- Reproductive Medicine Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xinrui Wu
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha
| | - Hongzhuan Tan
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha
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Vogiatzi P, Pouliakis A, Siristatidis C. An artificial neural network for the prediction of assisted reproduction outcome. J Assist Reprod Genet 2019; 36:1441-1448. [PMID: 31218565 PMCID: PMC6642243 DOI: 10.1007/s10815-019-01498-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 05/28/2019] [Indexed: 12/27/2022] Open
Abstract
PURPOSE To construct and validate an efficient artificial neural network (ANN) based on parameters with statistical correlation to live birth, to be used as a comprehensive tool for the prediction of the clinical outcome for patients undergoing ART. METHODS Data from 257 infertile couples that underwent a total of 426 IVF/ICSI cycles from 2010 to 2017 was collected on an ensemble of 118 parameters for each cycle. Statistical correlation of the parameters with the outcome of live birth was performed, using either t test or χ2 test, and the parameters that demonstrated statistical significance were used to construct the ANN. Cross-validation was performed by random separation of data and repeating the training-testing procedure by 10 times. RESULTS 12 statistically significant parameters out of the initial ensemble were used for the ANN construction, which exhibited a cumulative sensitivity and specificity of 76.7% and 73.4%, respectively. During cross-validation, the system exhibited the following: sensitivity 69.2% ± 2.36%, specificity 69.19% ± 2.8% (OR 5.21 ± 1.27), PPV 36.96 ± 3.44, NPV 89.61 ± 1.09, and OA 69.19% ± 2.69%. A rather small standard deviation in the performance indices between the training and test sets throughout the validation process indicated a stable performance of the constructed ANN. CONCLUSIONS The constructed ANN is based on statistically significant variables with the outcome of live birth and represents a stable and efficient system with increased performance indices. Validation of the system allowed an insight of its clinical value as a supportive tool in medical decisions, and overall provides a reliable approach in the routine practice of IVF units in a user-friendly environment.
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Affiliation(s)
- Paraskevi Vogiatzi
- Assisted Reproduction Unit, Third Department of Obstetrics and Gynecology, Medical School, "Attikon" University Hospital, National and Kapodistrian University of Athens, 1 Rimini Street, Chaidari, 12642, Athens, Greece
| | - Abraham Pouliakis
- Second Department of Pathology, Medical School, "Attikon" University Hospital, National and Kapodistrian University of Athens, 1 Rimini Street, Chaidari, 12642, Athens, Greece
| | - Charalampos Siristatidis
- Assisted Reproduction Unit, Third Department of Obstetrics and Gynecology, Medical School, "Attikon" University Hospital, National and Kapodistrian University of Athens, 1 Rimini Street, Chaidari, 12642, Athens, Greece.
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10
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Liu Y, Sakkas D, Afnan M, Matson P. Time-lapse videography for embryo selection/de-selection: a bright future or fading star? HUM FERTIL 2019; 23:76-82. [PMID: 30963781 DOI: 10.1080/14647273.2019.1598586] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
The recent clinical introduction of time-lapse videography into in vitro fertilization laboratories has offered a novel opportunity for embryologists to explore improved methods for embryo selection. While the concept of uninterrupted culture of embryos provided by such systems is welcomed, the current evidence does not support its full application in routine clinical practice. The issue of whether or not algorithms for embryo selection can be extrapolated between laboratories, which may represent a major hurdle to its wide application, is currently gaining increasing attention amongst embryologists worldwide. In this commentary issues identified in time-lapse embryo selection/de-selection algorithms, such as quantitative versus qualitative parameters, are discussed alongside the reference start point for the timing system, and types of datasets used for developing and validating time-lapse algorithms. Considering these factors, alternative future research directions which could potentially solve current issues are proposed.
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Affiliation(s)
- Yanhe Liu
- Reproductive Medicine Center, Tianjin United Family Hospital, Tianjin, China.,School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
| | | | - Masoud Afnan
- Reproductive Medicine Center, Tianjin United Family Hospital, Tianjin, China
| | - Phillip Matson
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia.,Joondalup Private Hospital, Fertility North, Joondalup, Australia
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11
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Are computational applications the "crystal ball" in the IVF laboratory? The evolution from mathematics to artificial intelligence. J Assist Reprod Genet 2018; 35:1545-1557. [PMID: 30054845 DOI: 10.1007/s10815-018-1266-6] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Accepted: 07/11/2018] [Indexed: 01/23/2023] Open
Abstract
Mathematics rules the world of science. Innovative technologies based on mathematics have paved the way for implementation of novel strategies in assisted reproduction. Ascertaining efficient embryo selection in order to secure optimal pregnancy rates remains the focus of the in vitro fertilization scientific community and the strongest driver behind innovative approaches. This scoping review aims to describe and analyze complex models based on mathematics for embryo selection, devices, and software most widely employed in the IVF laboratory and algorithms in the service of the cutting-edge technology of artificial intelligence. Despite their promising nature, the practicing embryologist is the one ultimately responsible for the success of the IVF laboratory and thus the one to approve embracing pioneering technologies in routine practice. Applied mathematics and computational biology have already provided significant insight into the selection of the most competent preimplantation embryo. This review describes the leap of evolution from basic mathematics to bioinformatics and investigates the possibility that computational applications may be the means to foretell a promising future for the IVF clinical practice.
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12
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Tobias T, Sharara FI, Franasiak JM, Heiser PW, Pinckney-Clark E. Promoting the use of elective single embryo transfer in clinical practice. FERTILITY RESEARCH AND PRACTICE 2016; 2:1. [PMID: 28620526 PMCID: PMC5424309 DOI: 10.1186/s40738-016-0024-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2016] [Accepted: 08/02/2016] [Indexed: 11/12/2022]
Abstract
Background The transfer of multiple embryos after in vitro fertilization (IVF) increases the risk of twins and higher-order births. Multiple births are associated with significant health risks and maternal and neonatal complications, as well as physical, emotional, and financial stresses that can strain families and increase the incidence of depression and anxiety disorders in parents. Elective single embryo transfer (eSET) is among the most effective methods to reduce the risk of multiple births with IVF. Main body Current societal guidelines recommend eSET for patients <35 years of age with a good prognosis, yet even this approach is not widely applied. Many patients and clinicians have been reluctant to adopt eSET due to studies reporting higher live birth rates with the transfer of two or more embryos rather than eSET. Additional barriers to eSET include risk of treatment dropout after embryo transfer failure, patient preference for twins, a lack of knowledge about the risks and complications associated with multiple births, and the high costs of multiple IVF cycles. This review provides a comprehensive summary of strategies to increase the rate of eSET, including personalized counseling, access to educational information regarding the risks of multiple pregnancies and births, financial incentives, and tools to help predict the chances of IVF success. The use of comprehensive chromosomal screening to improve embryo selection has been shown to improve eSET outcomes and may increase acceptance of eSET. Conclusions eSET is an effective method for reducing multiple pregnancies resulting from IVF. Although several factors may impede the adoption of eSET, there are a number of strategies and tools that may encourage the more widespread adoption of eSET in clinical practice.
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Affiliation(s)
- Tamara Tobias
- Seattle Reproductive Medicine, 1505 Westlake Ave North, Suite 400, Seattle, WA 98109 USA
| | - Fady I Sharara
- Virginia Center for Reproductive Medicine, 11150 Sunset Hills Rd, Suite #100, Reston, VA 20190 USA.,Department of Obstetrics and Gynecology, George Washington University, 2150 Pennsylvania Ave NW, Suite 6A 4169, Washington, DC 20037 USA
| | - Jason M Franasiak
- Division of Reproductive Endocrinology, Department of Obstetrics, Gynecology and Reproductive Sciences, Robert Wood Johnson Medical School, Rutgers University, 125 Paterson St, New Brunswick, NJ 08901 USA.,Reproductive Medicine Associates of New Jersey, 140 Allen Road, Basking Ridge, NJ 07920 USA
| | - Patrick W Heiser
- Ferring Pharmaceuticals, Inc., 100 Interpace Parkway, Parsippany, NJ 07054 USA
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Abad AA, Elst WVD, Molenberghs G. Validating predictors of therapeutic success: A causal inference approach. STAT MODEL 2015. [DOI: 10.1177/1471082x15586286] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In personalized medicine medical decisions, practices and/or products are tailored to the individual patient. The idea is to provide the right patient with the right drug at the right dose at the right time. However, our current lack of ability to predict an individual patient's treatment success for most diseases and conditions is a major challenge to achieve the goal of personalized medicine. In the present work, we argue that many of the techniques often used to evaluate predictors of therapeutic success may not be able to answer the relevant scientific questions and we propose a new validation strategy based on causal inference. The methodology is illustrated using data from a clinical trial in opiate/heroin addiction. The user-friendly R library EffectTreat is provided to carry out the necessary calculations.
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14
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Nelson SM, Fleming R, Gaudoin M, Choi B, Santo-Domingo K, Yao M. Antimüllerian hormone levels and antral follicle count as prognostic indicators in a personalized prediction model of live birth. Fertil Steril 2015; 104:325-32. [PMID: 26003269 DOI: 10.1016/j.fertnstert.2015.04.032] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Revised: 04/16/2015] [Accepted: 04/20/2015] [Indexed: 01/08/2023]
Abstract
OBJECTIVE To compare antimüllerian hormone (AMH) and antral follicle count (AFC) separately and in combination with clinical characteristics for the prediction of live birth after controlled ovarian stimulation. DESIGN Retrospective development and temporal external validation of prediction model. SETTING Outpatient IVF clinic. PATIENT(S) We applied the boosted tree method to develop three prediction models incorporating clinical characteristics plus AMH or AFC or the combination on 2,124 linked IVF cycles from 2006 to 2010 and temporally externally validated predicted live-birth probabilities with an independent data set comprising 1,121 cycles from 2011 to 2012. INTERVENTION(S) None. MAIN OUTCOME MEASURE(S) Predictive power (posterior log of odds ratio compared to age, or PLORA), reclassification, receiver operator characteristic analysis, calibration, dynamic range. RESULT(S) Predictive power, was highest for the AMH model (PLORA = 29.1), followed by the AMH-AFC model (PLORA = 28.3) and AFC model (PLORA = 22.5). The prediction errors were 1% to <5% in each prognostic tier for all three models, except for the predicted live-birth probabilities of <10% in the AFC model, where the prediction error was 8%. The improvement in predictive power was highest for the AMH model: 76.2% improvement over age alone relative to 59% improvement for AFC and 73.3% for the combined model. Receiver operating characteristic analysis demonstrated that the AMH and the combined model had comparable discrimination (area under the curve = 0.716) and similar prediction error for high and low strata of live-birth prediction, with an improvement of 6.3% over age alone. CONCLUSION(S) The validated prediction model confirmed that AMH when combined with clinical characteristics can accurately identify the likelihood of live birth with a low prediction error. AFC provided no added predictive value beyond AMH.
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Affiliation(s)
- Scott M Nelson
- School of Medicine, University of Glasgow, Glasgow, United Kingdom.
| | - Richard Fleming
- School of Medicine, University of Glasgow, Glasgow, United Kingdom; Glasgow Centre for Reproductive Medicine, Glasgow, United Kingdom
| | - Marco Gaudoin
- Glasgow Centre for Reproductive Medicine, Glasgow, United Kingdom
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Predictors of in vitro fertilization outcomes in women with highest follicle-stimulating hormone levels ≥ 12 IU/L: a prospective cohort study. PLoS One 2015; 10:e0124789. [PMID: 25867175 PMCID: PMC4395083 DOI: 10.1371/journal.pone.0124789] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2015] [Accepted: 03/11/2015] [Indexed: 11/19/2022] Open
Abstract
Objective The purpose of this study is to evaluate factors predictive of outcomes in women with highest follicle-stimulating hormone (FSH) levels ≥12 IU/L on basal testing, undergoing in vitro fertilization (IVF). Methods A prospective cohort study was conducted at Stanford University Hospital in the Reproductive Endocrinology and Infertility Center for 12 months. Women age 21 to 43 undergoing IVF with highest FSH levels on baseline testing were included. Donor/Recipient and frozen embryo cycles were excluded from this study. Prognostic factors evaluated in association with clinical pregnancy rates were type of infertility diagnosis and IVF stimulation parameters. Results The current study found that factors associated with clinical pregnancy were: increased number of mature follicles on the day of triggering, number of oocytes retrieved, number of Metaphase II oocytes if intracytoplasmic sperm injection was done, and number of embryos developed 24 hours after retrieval. Conclusions Our findings suggest that it would be beneficial for women with increased FSH levels to attempt a cycle of IVF. Results of ovarian stimulation, especially embryo quantity appear to be the best predictors of IVF outcomes and those can only be obtained from a cycle of IVF. Therefore, increased basal FSH levels should not discourage women from attempting a cycle of IVF.
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Smith ADAC, Tilling K, Lawlor DA, Nelson SM. External validation and calibration of IVFpredict: a national prospective cohort study of 130,960 in vitro fertilisation cycles. PLoS One 2015; 10:e0121357. [PMID: 25853703 PMCID: PMC4390202 DOI: 10.1371/journal.pone.0121357] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2014] [Accepted: 01/30/2015] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Accurately predicting the probability of a live birth after in vitro fertilisation (IVF) is important for patients, healthcare providers and policy makers. Two prediction models (Templeton and IVFpredict) have been previously developed from UK data and are widely used internationally. The more recent of these, IVFpredict, was shown to have greater predictive power in the development dataset. The aim of this study was external validation of the two models and comparison of their predictive ability. METHODS AND FINDINGS 130,960 IVF cycles undertaken in the UK in 2008-2010 were used to validate and compare the Templeton and IVFpredict models. Discriminatory power was calculated using the area under the receiver-operator curve and calibration assessed using a calibration plot and Hosmer-Lemeshow statistic. The scaled modified Brier score, with measures of reliability and resolution, were calculated to assess overall accuracy. Both models were compared after updating for current live birth rates to ensure that the average observed and predicted live birth rates were equal. The discriminative power of both methods was comparable: the area under the receiver-operator curve was 0.628 (95% confidence interval (CI): 0.625-0.631) for IVFpredict and 0.616 (95% CI: 0.613-0.620) for the Templeton model. IVFpredict had markedly better calibration and higher diagnostic accuracy, with calibration plot intercept of 0.040 (95% CI: 0.017-0.063) and slope of 0.932 (95% CI: 0.839-1.025) compared with 0.080 (95% CI: 0.044-0.117) and 1.419 (95% CI: 1.149-1.690) for the Templeton model. Both models underestimated the live birth rate, but this was particularly marked in the Templeton model. Updating the models to reflect improvements in live birth rates since the models were developed enhanced their performance, but IVFpredict remained superior. CONCLUSION External validation in a large population cohort confirms IVFpredict has superior discrimination and calibration for informing patients, clinicians and healthcare policy makers of the probability of live birth following IVF.
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Affiliation(s)
- Andrew D. A. C. Smith
- Medical Research Council Integrative Epidemiology Unit, the University of Bristol, Bristol, United Kingdom
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Kate Tilling
- Medical Research Council Integrative Epidemiology Unit, the University of Bristol, Bristol, United Kingdom
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Debbie A. Lawlor
- Medical Research Council Integrative Epidemiology Unit, the University of Bristol, Bristol, United Kingdom
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
- * E-mail: (DAL); (SMN)
| | - Scott M. Nelson
- School of Medicine, University of Glasgow, Glasgow, United Kingdom
- * E-mail: (DAL); (SMN)
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Liao C, Huang R, Scherer RW, Liang XY. Prognostic factors associated with clinical pregnancy in in vitro fertilization using pituitary down-regulation with depot and daily low-dose luteal phase gonadotropin releasing hormone agonists: A single center's experience. J Hum Reprod Sci 2015; 8:30-6. [PMID: 25838746 PMCID: PMC4381380 DOI: 10.4103/0974-1208.153124] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2014] [Revised: 01/15/2015] [Accepted: 02/27/2015] [Indexed: 11/29/2022] Open
Abstract
AIM: To review the experience on depot-dose, and daily low-dose gonadotropin releasing hormone agonist (GnRHa) long protocols and identify prognostic factors. SETTING AND DESIGN: A chart review was conducted on 2106 depot and 1299 daily low-dose cycles at a university hospital. METHODS: Clinical parameters were summarized, and prognostic factors of clinical pregnancy for each protocol were identified by logistic regressions. Missing data were imputed using multiple imputations (MI) and the regression models were rerun after MI. RESULTS: Clinical pregnancy rate was 57.5% and 46.9% in the depot and daily low-dose groups, respectively. Logistic regressions with MI identified age (odds ratio [OR]: 0.95, 95% confidence interval [CI]: 0.92–0.98), serum progesterone (OR: 0.62, 95% CI: 0.45–0.84) and endometrial thickness (OR: 1.06, 95% CI: 1.02–1.12) on human chorionic gonadotropin (hCG) day, number of oocytes retrieved (OR: 1.04, 95% CI: 1.01–1.06), fertilization rate (OR: 2.66, 95% CI: 1.46–4.87) and ratio of good-quality D3 embryos (OR: 4.31, 95% CI: 2.79–6.67) as prognostic factors in the depot group. Age (OR: 0.95, 95% CI: 0.92–0.98), endometrial thickness on hCG day (OR: 1.09, 95% CI: 1.03–1.15), ratio of good quality D3 embryos (OR: 2.56, 95% CI: 1.59–4.13) and the number of cryopreserved embryos (OR: 1.07, 95% CI: 1.003–1.15) are prognostic for the daily low-dose protocol. Some regression coefficients that are significant under model-wise deletion become nonsignificant after MI. CONCLUSIONS: Age, embryo quality and endometrial thickness on hCG day are important prognostic factors for both 1.0/1.3 mg depot and 0.05/0.1 mg daily low-dose luteal phase GnRHa long protocols. MI is a valuable tool to gauge and address bias caused by missing data in reproductive medicine.
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Affiliation(s)
- Caiyun Liao
- Reproductive Medicine Research Center of the Sixth Affiliated Hospital, Sun Yat Sen University, Tianhe District, Guangzhou, Guangdong 510620, China
| | - Rui Huang
- Reproductive Medicine Research Center of the Sixth Affiliated Hospital, Sun Yat Sen University, Tianhe District, Guangzhou, Guangdong 510620, China
| | - Roberta W Scherer
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
| | - Xiao-Yan Liang
- Reproductive Medicine Research Center of the Sixth Affiliated Hospital, Sun Yat Sen University, Tianhe District, Guangzhou, Guangdong 510620, China
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Dodd S, Berk M, Kelin K, Zhang Q, Eriksson E, Deberdt W, Craig Nelson J. Application of the Gradient Boosted method in randomised clinical trials: Participant variables that contribute to depression treatment efficacy of duloxetine, SSRIs or placebo. J Affect Disord 2014; 168:284-93. [PMID: 25080392 DOI: 10.1016/j.jad.2014.05.014] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2014] [Revised: 05/13/2014] [Accepted: 05/14/2014] [Indexed: 11/25/2022]
Abstract
BACKGROUND Randomised, placebo-controlled trials of treatments for depression typically collect outcomes data but traditionally only analyse data to demonstrate efficacy and safety. Additional post-hoc statistical techniques may reveal important insights about treatment variables useful when considering inter-individual differences amongst depressed patients. This paper aims to examine the Gradient Boosted Model (GBM), a statistical technique that uses regression tree analyses and can be applied to clinical trial data to identify and measure variables that may influence treatment outcomes. METHODS GBM was applied to pooled data from 12 randomised clinical trials of 4987 participants experiencing an acute depressive episode who were treated with duloxetine, an SSRI or placebo to predict treatment remission. Additional analyses were conducted on the same dataset using the logistic regression model for comparison between these two methods. RESULTS With GBM, there were noticeable differences between treatments when identifying which and to what extent variables were associated with remission. A single logistic regression only revealed a decreasing or increasing relationship between predictors and remission while GBM was able to reveal a complex relationship between predictors and remission. LIMITATIONS These analyses were conducted post-hoc utilising clinical trials databases. The criteria for constructing the analyses data were based on the characteristics of the clinical trials. CONCLUSIONS GBM can be used to identify and quantify patient variables that predict remission with specific treatments and has greater flexibility than the logistic regression model. GBM may provide new insights into inter-individual differences in treatment response that may be useful for selecting individualised treatments. TRIAL REGISTRATION IMPACT clinical trial number 3327; IMPACT clinical trial number 4091; IMPACT clinical trial number 4689; IMPACT clinical trial number 4298; NCT00071695; NCT00062673; NCT00036335; NCT00067912; NCT00073411; NCT00489775; NCT00536471; NCT00666757 (note that trials with IMPACT numbers predate mandatory clinical trial registration requirements).
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Affiliation(s)
- Seetal Dodd
- Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia; IMPACT SRC (Innovation in Mental and Physical Health and Clinical Treatment), School of Medicine, Deakin University, Geelong, VIC, Australia.
| | - Michael Berk
- Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia; IMPACT SRC (Innovation in Mental and Physical Health and Clinical Treatment), School of Medicine, Deakin University, Geelong, VIC, Australia; Florey Institute for Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia; ORYGEN Research Centre, Parkville, VIC, Australia
| | - Katarina Kelin
- Eli Lilly Australia Pty Limited, West Ryde, NSW, Australia
| | | | - Elias Eriksson
- Department of Pharmacology and the Institute of Physiology and Neuroscience, Sahlgrenska, Academy, Goteborg University, Goteborg, Sweden
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Green MP, Mouat F, Miles HL, Pleasants AB, Henderson HV, Hofman PL, Peek JC, Cutfield WS. The phenotype of an IVF child is associated with peri-conception measures of follicular characteristics and embryo quality. Hum Reprod 2014; 29:2583-91. [PMID: 25217609 DOI: 10.1093/humrep/deu221] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
STUDY QUESTION Are childhood measures of phenotype associated with peri-conception parental, IVF treatment and/or embryonic characteristics of IVF children? SUMMARY ANSWER Birthweight, childhood body mass index (BMI) and height of pre-pubertal IVF children were strongly associated with peri-conception factors, including follicular and embryonic characteristics. WHAT IS KNOWN ALREADY A growing number of studies have identified a range of phenotypic differences between IVF and naturally conceived pre-pubertal children; for example, birthweights are lower following a fresh compared with a thawed embryo transfer. STUDY DESIGN, SIZE, DURATION This retrospective cohort study included IVF children (n = 96) born at term (>37 weeks) after a singleton pregnancy from the transfer of either fresh or thawed embryos in New Zealand. Between March 2004 and November 2008, these children were subjected to clinical assessment before puberty. PARTICIPANTS/MATERIALS, SETTING, METHODS Clinical assessment provided anthropometric measures of children aged 3.5-11 years old. Peri-conception factors (n = 36) derived retrospectively from parental, treatment, laboratory and embryonic variables (n = 69) were analysed using multiple stepwise regression with respect to standard deviation scores (SDSs) of the birthweight, mid-parental corrected BMI and height of the IVF children. Data from children conceived from fresh (n = 60) or thawed (n = 36) embryos, that met inclusion criteria and had high-quality data with >90% completeness, were analysed. MAIN RESULTS AND THE ROLE OF CHANCE Embryo treatment at transfer was identified as a predictor of birthweight with thawed embryos resulting in heavier birthweights than fresh embryos [P = 0.02, 95% confidence interval (CI) fresh minus thawed: -1.047 to -0.006]. Birthweight SDS was positively associated with mid-parental corrected BMI SDS (P = 0.003, slope 0.339 ± 0.100). Four factors were related (P < 0.05) to mid-parental corrected height SDS. In particular, child height was inversely associated with the diameter of lead follicles at oocyte retrieval (P < 0.0001, slope -0.144 ± 0.040) and with the quality score of embryos at transfer (P = 0.0008, slope -0.425 ± 0.157), and directly associated with the number of follicles retrieved (P = 0.05, slope 1.011 ± 0.497). Child height was also positively associated with the transfer of a fresh as opposed to thawed embryo (P < 0.001, 95% CI 0.275-0.750). LIMITATIONS, REASONS FOR CAUTION More than one embryo was transferred in most cycles so mean development and quality data were used. The large number of variables measured was on a relatively small sample size. Large cohorts from multiple clinics using a variety of treatment protocols and embryology methods are needed to confirm the associations identified and ultimately to test these factors as possible predictors of phenotype. WIDER IMPLICATIONS OF THE FINDINGS This is the first study to directly associate peri-conception measures of IVF treatment with a pre-pubertal child's phenotype. Demonstration that peri-conception measures relate to a pre-pubertal child's phenotype extends the range of factors that may influence growth and development. These findings, if corroborated by larger studies, would provide invaluable information for practitioners, who may want to consider the impact of ovarian stimulation protocols as well as the quality of the embryo transferred on a child's growth and development, in addition to their impact on pregnancy rate. STUDY FUNDING/COMPETING INTERESTS This work was supported by grants from the National Research Centre of Growth and Development New Zealand (grant 3682065) and the Australasian Paediatric Endocrine Group (APEG; grant 3621994), as well as a fellowship from Fertility Associates New Zealand awarded to M.P.G. In terms of competing interest, J.C.P is a shareholder of Fertility Associates. M.P.G. currently holds the position of Merck Serono Lecturer in Reproductive Biology. W.S.C. and P.L.H. have also received grants and non-financial support from Novo Nordisk, as well as personal fees from Pfizer that are unrelated to the current study. The other authors have no conflict of interest to declare.
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Affiliation(s)
- M P Green
- The Liggins Institute and Gravida (National Research Centre for Growth and Development), University of Auckland, Auckland 1023, New Zealand AgResearch Ltd., Ruakura Research Centre, Hamilton 3240, New Zealand
| | - F Mouat
- The Liggins Institute and Gravida (National Research Centre for Growth and Development), University of Auckland, Auckland 1023, New Zealand
| | - H L Miles
- The Liggins Institute and Gravida (National Research Centre for Growth and Development), University of Auckland, Auckland 1023, New Zealand
| | - A B Pleasants
- The Liggins Institute and Gravida (National Research Centre for Growth and Development), University of Auckland, Auckland 1023, New Zealand AgResearch Ltd., Ruakura Research Centre, Hamilton 3240, New Zealand
| | - H V Henderson
- AgResearch Ltd., Ruakura Research Centre, Hamilton 3240, New Zealand
| | - P L Hofman
- The Liggins Institute and Gravida (National Research Centre for Growth and Development), University of Auckland, Auckland 1023, New Zealand
| | - J C Peek
- Fertility Associates, Auckland 1051, New Zealand
| | - W S Cutfield
- The Liggins Institute and Gravida (National Research Centre for Growth and Development), University of Auckland, Auckland 1023, New Zealand
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Beim PY, Elashoff M, Hu-Seliger TT. Personalized reproductive medicine on the brink: progress, opportunities and challenges ahead. Reprod Biomed Online 2013; 27:611-23. [DOI: 10.1016/j.rbmo.2013.09.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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21
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Boland MR, Hripcsak G, Shen Y, Chung WK, Weng C. Defining a comprehensive verotype using electronic health records for personalized medicine. J Am Med Inform Assoc 2013; 20:e232-8. [PMID: 24001516 PMCID: PMC3861934 DOI: 10.1136/amiajnl-2013-001932] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2013] [Accepted: 08/12/2013] [Indexed: 11/04/2022] Open
Abstract
The burgeoning adoption of electronic health records (EHR) introduces a golden opportunity for studying individual manifestations of myriad diseases, which is called 'EHR phenotyping'. In this paper, we break down this concept by: relating it to phenotype definitions from Johannsen; comparing it to cohort identification and disease subtyping; introducing a new concept called 'verotype' (Latin: vere = true, actually) to represent the 'true' population of similar patients for treatment purposes through the integration of genotype, phenotype, and disease subtype (eg, specific glucose value pattern in patients with diabetes) information; analyzing the value of the 'verotype' concept for personalized medicine; and outlining the potential for using network-based approaches to reverse engineer clinical disease subtypes.
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Affiliation(s)
- Mary Regina Boland
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Yufeng Shen
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
- Department of Systems Biology, Columbia University, New York, New York, USA
| | - Wendy K Chung
- Department of Pediatrics, Columbia University, New York, New York, USA
- Department of Medicine, Columbia University, New York, New York, USA
- The Irving Institute for Clinical and Translational Research, Columbia University, New York, New York, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
- The Irving Institute for Clinical and Translational Research, Columbia University, New York, New York, USA
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Choi B, Bosch E, Lannon BM, Leveille MC, Wong WH, Leader A, Pellicer A, Penzias AS, Yao MW. Personalized prediction of first-cycle in vitro fertilization success. Fertil Steril 2013; 99:1905-11. [DOI: 10.1016/j.fertnstert.2013.02.016] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2012] [Revised: 02/08/2013] [Accepted: 02/08/2013] [Indexed: 10/27/2022]
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O'Leary T, Heindryckx B, Lierman S, Van der Jeught M, Duggal G, De Sutter P, Chuva de Sousa Lopes SM. Derivation of human embryonic stem cells using a post–inner cell mass intermediate. Nat Protoc 2013; 8:254-64. [DOI: 10.1038/nprot.2012.157] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Broer SL, van Disseldorp J, Broeze KA, Dolleman M, Opmeer BC, Bossuyt P, Eijkemans MJ, Mol BWJ, Broekmans FJ, Broer S, van Disseldorp J, Broeze K, Dolleman M, Opmeer B, Anderson R, Ashrafi M, Bancsi L, Caroppo LE, Copperman A, Ebner T, Eldar Geva M, Erdem M, Greenblatt E, Jayaprakasan K, Fenning R, Klinkert E, Kwee J, Lambalk C, La Marca A, McIlveen M, Merce L, Muttukrishna S, Nelson S, Ng H, Popovic-Todorovic B, Smeenk J, Tomás C, Van der Linden P, van Rooij I, Vladimirov I, Bossuyt P, Eijkemans M, Mol B, Frank B. Added value of ovarian reserve testing on patient characteristics in the prediction of ovarian response and ongoing pregnancy: an individual patient data approach. Hum Reprod Update 2013. [DOI: 10.1093/humupd/dms041] [Citation(s) in RCA: 302] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Simone L. Broer
- Department of Reproductive Medicine, University Medical Center Utrecht, Room F05.126, P.O. Box 85500, Utrecht 3508 GA, The Netherlands
- Department of Obstetrics and Gynaecology, Amsterdam Medical Center, Amsterdam, the Netherlands
| | - Jeroen van Disseldorp
- Department of Reproductive Medicine, University Medical Center Utrecht, Room F05.126, P.O. Box 85500, Utrecht 3508 GA, The Netherlands
- Department of Obstetrics and Gynaecology, Amsterdam Medical Center, Amsterdam, the Netherlands
| | - Kimiko A. Broeze
- Department of Reproductive Medicine, University Medical Center Utrecht, Room F05.126, P.O. Box 85500, Utrecht 3508 GA, The Netherlands
- Department of Obstetrics and Gynaecology, Amsterdam Medical Center, Amsterdam, the Netherlands
| | - Madeleine Dolleman
- Department of Reproductive Medicine, University Medical Center Utrecht, Room F05.126, P.O. Box 85500, Utrecht 3508 GA, The Netherlands
- Department of Obstetrics and Gynaecology, Amsterdam Medical Center, Amsterdam, the Netherlands
| | - Brent C. Opmeer
- Department of Reproductive Medicine, University Medical Center Utrecht, Room F05.126, P.O. Box 85500, Utrecht 3508 GA, The Netherlands
- Department of Obstetrics and Gynaecology, Amsterdam Medical Center, Amsterdam, the Netherlands
| | - Patrick Bossuyt
- Department of Reproductive Medicine, University Medical Center Utrecht, Room F05.126, P.O. Box 85500, Utrecht 3508 GA, The Netherlands
- Department of Obstetrics and Gynaecology, Amsterdam Medical Center, Amsterdam, the Netherlands
| | - Marinus J.C. Eijkemans
- Department of Reproductive Medicine, University Medical Center Utrecht, Room F05.126, P.O. Box 85500, Utrecht 3508 GA, The Netherlands
- Department of Obstetrics and Gynaecology, Amsterdam Medical Center, Amsterdam, the Netherlands
| | - Ben-Willem J. Mol
- Department of Reproductive Medicine, University Medical Center Utrecht, Room F05.126, P.O. Box 85500, Utrecht 3508 GA, The Netherlands
- Department of Obstetrics and Gynaecology, Amsterdam Medical Center, Amsterdam, the Netherlands
| | - Frank J.M. Broekmans
- Department of Reproductive Medicine, University Medical Center Utrecht, Room F05.126, P.O. Box 85500, Utrecht 3508 GA, The Netherlands
- Department of Obstetrics and Gynaecology, Amsterdam Medical Center, Amsterdam, the Netherlands
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Reducing multiples: a mathematical formula that accurately predicts rates of singletons, twins, and higher-order multiples in women undergoing in vitro fertilization. Fertil Steril 2012; 98:1474-80.e2. [PMID: 22985944 DOI: 10.1016/j.fertnstert.2012.08.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2011] [Revised: 08/08/2012] [Accepted: 08/08/2012] [Indexed: 11/21/2022]
Abstract
OBJECTIVE To develop a mathematical formula that accurately predicts the probability of a singleton, twin, and higher-order multiple pregnancy according to implantation rate and number of embryos transferred. DESIGN A total of 12,003 IVF cycles from a single center resulting in ET were analyzed. Using mathematical modeling we developed a formula, the Combined Formula, and tested for the ability of this formula to accurately predict outcomes. SETTING Academic hospital. PATIENT(S) Patients undergoing IVF. INTERVENTION(S) None. MAIN OUTCOME MEASURE(S) Goodness of fit of data from our center and previously published data to the Combined Formula and three previous mathematical models. RESULT(S) The Combined Formula predicted the probability of singleton, twin, and higher-order pregnancies more accurately than three previous formulas (1.4% vs. 2.88%, 4.02%, and 5%, respectively) and accurately predicted outcomes from five previously published studies from other centers. An online applet is provided (https://secure.ivf.org/ivf-calculator.html). CONCLUSION(S) The probability of pregnancy with singletons, twins, and higher-order multiples according to number of embryos transferred is predictable and not random and can be accurately modeled using the Combined Formula. The embryo itself is the major predictor of pregnancy outcomes, but there is an influence from "barriers," such as the endometrium and collaboration between embryos (embryo-embryo interaction). This model can be used to guide the decision regarding number of embryos to transfer after IVF.
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Lannon BM, Choi B, Hacker MR, Dodge LE, Malizia BA, Barrett CB, Wong WH, Yao MWM, Penzias AS. Predicting personalized multiple birth risks after in vitro fertilization-double embryo transfer. Fertil Steril 2012; 98:69-76. [PMID: 22673597 DOI: 10.1016/j.fertnstert.2012.04.011] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2012] [Revised: 03/23/2012] [Accepted: 04/10/2012] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To report and evaluate the performance and utility of an approach to predicting IVF-double embryo transfer (DET) multiple birth risks that is evidence-based, clinic-specific, and considers each patient's clinical profile. DESIGN Retrospective prediction modeling. SETTING An outpatient university-affiliated IVF clinic. PATIENT(S) We used boosted tree methods to analyze 2,413 independent IVF-DET treatment cycles that resulted in live births. The IVF cycles were retrieved from a database that comprised more than 33,000 IVF cycles. INTERVENTION(S) None. MAIN OUTCOME MEASURE(S) The performance of this prediction model, MBP-BIVF, was validated by an independent data set, to evaluate predictive power, discrimination, dynamic range, and reclassification. RESULT(S) Multiple birth probabilities ranging from 11.8% to 54.8% were predicted by the model and were significantly different from control predictions in more than half of the patients. The prediction model showed an improvement of 146% in predictive power and 16.0% in discrimination over control. The population standard error was 1.8%. CONCLUSION(S) We showed that IVF patients have inherently different risks of multiple birth, even when DET is specified, and this risk can be predicted before ET. The use of clinic-specific prediction models provides an evidence-based and personalized method to counsel patients.
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O'Leary T, Duggal G, Lierman S, Van den Abbeel E, Heindryckx B, De Sutter P. The influence of patient and cohort parameters on the incidence and developmental potential of embryos with poor quality traits for use in human embryonic stem cell derivation. Hum Reprod 2012; 27:1581-9. [PMID: 22442247 DOI: 10.1093/humrep/des040] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Human embryonic stem cells (hESCs) are most commonly derived from the inner cell mass (ICM) of blastocyst stage embryos. While the majority of hESC lines originate from good-quality embryos donated after cryogenic storage, poor-quality embryos (PQEs) not suitable for clinical use have also been shown to generate hESC. This provides a newfound function for embryos that would otherwise be discarded following IVF or ICSI. Owing to their lack of clinical importance, however, data on the poorest embryos in a cohort go largely unreported in the literature. It is therefore of interest to better understand the availability of PQEs from IVF/ICSI cycles and to determine their ability to develop into blastocysts with good-quality ICMs for use in hESC derivation. In this study, we investigate the influence of patient parameters and embryo cohort on PQE incidence, blastocyst development, ICM quality and successful hESC derivation from donated PQEs. METHODS PQEs from 736 patient cycles that did not meet our clinical criteria for transfer or cryopreservation were cultured until Day 6 of development and assessed for blastocyst formation and ICM quality. A subset of blastocysts with good-quality ICMs were then used for hESC derivation attempts. Anonymous patient data such as maternal age, embryo history and cohort parameters were then retrospectively compiled and analysed. RESULTS PQEs made up 46.8% of two pronucleate embryos created from IVF/ICSI. Including embryos with abnormal fertilization, a mean of 3.6 ± 2.8 embryos were donated per cycle with 32.6% developing to the blastocyst stage. Good-quality ICM were produced in 13.9% of PQEs cultured. Of good-quality ICM, 15.4% of those used in hESC derivation attempts resulted in a novel line. The PQEs that originated from older patients (>37 year) or from cycles that did not result in pregnancy had significantly diminished blastocyst development and ICM quality. Maternal age was also shown to further influence the ability of good-quality ICMs to generate hESC. CONCLUSIONS PQEs are an abundant source of embryos capable of developing to blastocysts with good-quality ICMs and subsequently generating novel hESC. We have shown that prognostic variables used to predict IVF/ICSI outcome can also help predict which PQEs have the best hESC developmental potential. Owing to the diversity of PQE origin, experiments designed to compare hESC derivation techniques or efficiency using PQEs should consider clinical IVF/ICSI parameters to establish groups with equal developmental competence. Additional investigation is needed to determine if these results are applicable to hESC derivation using good-quality embryos.
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Affiliation(s)
- T O'Leary
- Department for Reproductive Medicine, Ghent University Hospital, De Pintelaan, Ghent, Belgium.
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Garrido N, Bellver J, Remohí J, Simón C, Pellicer A. Cumulative live-birth rates per total number of embryos needed to reach newborn in consecutive in vitro fertilization (IVF) cycles: a new approach to measuring the likelihood of IVF success. Fertil Steril 2011; 96:40-6. [PMID: 21621770 DOI: 10.1016/j.fertnstert.2011.05.008] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2011] [Revised: 04/15/2011] [Accepted: 05/02/2011] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To report the use of cumulative live-birth rates (CLBRs) per ovarian stimulation cycle to measure the success of IVF is proving to be the most accurate method for advising couples who failed to conceive, although the accuracy yielded is relatively low, and cycle outcome is highly dependent on the number of embryos replaced. Our aim with this work is to report the CLBRs of IVF as a function of the number of embryos required to reach a live birth (EmbR), considering age, day of ET, and infertility etiology. DESIGN Survival curves and Kaplan-Meier methods to analyze CLBR in a retrospective cohort with respect to the number of EmbR. SETTING University-affiliated infertility center. PATIENT(S) Infertile couples undergoing IVF using own oocytes. INTERVENTION(S) None. MAIN OUTCOME MEASURE(S) CLBR per embryo transferred. RESULT(S) CLBRs increase rapidly between 1 and 5 EmbR, moderately between 5 and 15, and slowly thereafter. Live-birth rates rise more slowly when embryos are transferred on days 2-3 rather than on days 5-6, with comparable long-term results. Women's age is a negative factor from 35 to 37 years old, with a dramatic decrease in live-birth rates beyond age 40 years. In addition, there are significant worse results in endometriosis patients. CONCLUSION(S) The relationship between CLBR and number of EmbR provides realistic and precise information regarding IVF success and can be used to guide couples and practitioners.
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Affiliation(s)
- Nicolás Garrido
- Instituto Universitario IVI Valencia, University of Valencia, Valencia, Spain.
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Affiliation(s)
- Michael LeBlanc
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
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