Predicting Live Birth, Preterm Delivery, and Low Birth Weight in Infants Born from In Vitro Fertilisation: A Prospective Study of 144,018 Treatment Cycles
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{"title"=>"Predicting live birth, preterm delivery, and low birth weight in infants born from in vitro fertilisation: A prospective study of 144,018 treatment cycles", "type"=>"journal", "authors"=>[{"first_name"=>"Scott M.", "last_name"=>"Nelson", "scopus_author_id"=>"12776474100"}, {"first_name"=>"Debbie A.", "last_name"=>"Lawlor", "scopus_author_id"=>"7102452820"}], "year"=>2011, "source"=>"PLoS Medicine", "identifiers"=>{"issn"=>"15491277", "isbn"=>"1549-1676", "sgr"=>"79951596286", "pmid"=>"21245905", "pui"=>"361278287", "doi"=>"10.1371/journal.pmed.1000386", "scopus"=>"2-s2.0-79951596286"}, "id"=>"6cb1ead6-ad56-3438-a2bb-25998bee6204", "abstract"=>"BACKGROUND: The extent to which baseline couple characteristics affect the probability of live birth and adverse perinatal outcomes after assisted conception is unknown.\\n\\nMETHODS AND FINDINGS: We utilised the Human Fertilisation and Embryology Authority database to examine the predictors of live birth in all in vitro fertilisation (IVF) cycles undertaken in the UK between 2003 and 2007 (n = 144,018). We examined the potential clinical utility of a validated model that pre-dated the introduction of intracytoplasmic sperm injection (ICSI) as compared to a novel model. For those treatment cycles that resulted in a live singleton birth (n = 24,226), we determined the associates of potential risk factors with preterm birth, low birth weight, and macrosomia. The overall rate of at least one live birth was 23.4 per 100 cycles (95% confidence interval [CI] 23.2-23.7). In multivariable models the odds of at least one live birth decreased with increasing maternal age, increasing duration of infertility, a greater number of previously unsuccessful IVF treatments, use of own oocytes, necessity for a second or third treatment cycle, or if it was not unexplained infertility. The association of own versus donor oocyte with reduced odds of live birth strengthened with increasing age of the mother. A previous IVF live birth increased the odds of future success (OR 1.58, 95% CI 1.46-1.71) more than that of a previous spontaneous live birth (OR 1.19, 95% CI 0.99-1.24); p-value for difference in estimate <0.001. Use of ICSI increased the odds of live birth, and male causes of infertility were associated with reduced odds of live birth only in couples who had not received ICSI. Prediction of live birth was feasible with moderate discrimination and excellent calibration; calibration was markedly improved in the novel compared to the established model. Preterm birth and low birth weight were increased if oocyte donation was required and ICSI was not used. Risk of macrosomia increased with advancing maternal age and a history of previous live births. Infertility due to cervical problems was associated with increased odds of all three outcomes-preterm birth, low birth weight, and macrosomia.\\n\\nCONCLUSIONS: Pending external validation, our results show that couple- and treatment-specific factors can be used to provide infertile couples with an accurate assessment of whether they have low or high risk of a successful outcome following IVF.", "link"=>"http://www.mendeley.com/research/predicting-live-birth-preterm-delivery-low-birth-weight-infants-born-vitro-fertilisation-prospective", "reader_count"=>69, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>2, "Librarian"=>1, "Student > Doctoral Student"=>3, "Researcher"=>13, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>3, "Student > Master"=>16, "Other"=>5, "Student > Bachelor"=>4, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>3}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>2, "Librarian"=>1, "Student > Doctoral Student"=>3, "Researcher"=>13, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>3, "Student > Master"=>16, "Other"=>5, "Student > Bachelor"=>4, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>3}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>3, "Mathematics"=>2, "Medicine and Dentistry"=>37, "Agricultural and Biological Sciences"=>6, "Chemistry"=>1, "Psychology"=>3, "Social Sciences"=>8, "Computer Science"=>5, "Economics, Econometrics and Finance"=>3, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>37}, "Chemistry"=>{"Chemistry"=>1}, "Social Sciences"=>{"Social Sciences"=>8}, "Psychology"=>{"Psychology"=>3}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>3}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>6}, "Computer Science"=>{"Computer Science"=>5}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Mathematics"=>{"Mathematics"=>2}}, "reader_count_by_country"=>{"Canada"=>2, "Norway"=>1, "Brazil"=>1, "Italy"=>1, "United Kingdom"=>1, "Nigeria"=>1}, "group_count"=>6}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/808227"], "description"=>"<p>Cycles included in analyses are from couples for whom data were complete on all variables and who experienced a singleton birth after IVF. For associations with low birth weight, those with macrosomia as an outcome are removed so that low birth weight is compared with normal birth weight, and similarly for macrosomia, those with low birth weight are removed so that macrosomia is compared with normal birth weight. The results are with mutual adjustment for all variables in the first column. In addition, for preterm birth, results are adjusted for mean birth weight and for low birth weight and macrosomia for mean gestational age. <i>p</i>-Values are likelihood ratio tests of null hypothesis that the odds are the same for each category (i.e., they do not assume linearity).</p>", "links"=>[], "tags"=>["associations", "factors", "preterm", "macrosomia", "amongst", "singleton", "births"], "article_id"=>478594, "categories"=>["Immunology", "Medicine"], "users"=>["Scott M. Nelson", "Debbie A. Lawlor"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000386.t005", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multivariable_associations_of_potential_risk_factors_with_preterm_birth_low_birth_weight_and_macrosomia_amongst_singleton_births_following_IVF_/478594", "title"=>"Multivariable associations of potential risk factors with preterm birth, low birth weight and macrosomia amongst singleton births following IVF.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-01-04 02:23:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/403461", "https://ndownloader.figshare.com/files/403476", "https://ndownloader.figshare.com/files/403493", "https://ndownloader.figshare.com/files/403509", "https://ndownloader.figshare.com/files/403529", "https://ndownloader.figshare.com/files/403547", "https://ndownloader.figshare.com/files/403572", "https://ndownloader.figshare.com/files/403611", "https://ndownloader.figshare.com/files/403634", "https://ndownloader.figshare.com/files/403652"], "description"=>"<div><h3>Background</h3><p>The extent to which baseline couple characteristics affect the probability of live birth and adverse perinatal outcomes after assisted conception is unknown.</p><h3>Methods and Findings</h3><p>We utilised the Human Fertilisation and Embryology Authority database to examine the predictors of live birth in all in vitro fertilisation (IVF) cycles undertaken in the UK between 2003 and 2007 (<em>n</em> = 144,018). We examined the potential clinical utility of a validated model that pre-dated the introduction of intracytoplasmic sperm injection (ICSI) as compared to a novel model. For those treatment cycles that resulted in a live singleton birth (<em>n</em> = 24,226), we determined the associates of potential risk factors with preterm birth, low birth weight, and macrosomia. The overall rate of at least one live birth was 23.4 per 100 cycles (95% confidence interval [CI] 23.2–23.7). In multivariable models the odds of at least one live birth decreased with increasing maternal age, increasing duration of infertility, a greater number of previously unsuccessful IVF treatments, use of own oocytes, necessity for a second or third treatment cycle, or if it was not unexplained infertility. The association of own versus donor oocyte with reduced odds of live birth strengthened with increasing age of the mother. A previous IVF live birth increased the odds of future success (OR 1.58, 95% CI 1.46–1.71) more than that of a previous spontaneous live birth (OR 1.19, 95% CI 0.99–1.24); <em>p</em>-value for difference in estimate <0.001. Use of ICSI increased the odds of live birth, and male causes of infertility were associated with reduced odds of live birth only in couples who had not received ICSI. Prediction of live birth was feasible with moderate discrimination and excellent calibration; calibration was markedly improved in the novel compared to the established model. Preterm birth and low birth weight were increased if oocyte donation was required and ICSI was not used. Risk of macrosomia increased with advancing maternal age and a history of previous live births. Infertility due to cervical problems was associated with increased odds of all three outcomes—preterm birth, low birth weight, and macrosomia.</p><h3>Conclusions</h3><p>Pending external validation, our results show that couple- and treatment-specific factors can be used to provide infertile couples with an accurate assessment of whether they have low or high risk of a successful outcome following IVF.</p><h3></h3><p><em>Please see later in the article for the Editors' Summary</em></p></div>", "links"=>[], "tags"=>["predicting", "preterm", "infants", "vitro", "prospective", "cycles"], "article_id"=>139715, "categories"=>["Immunology", "Medicine"], "users"=>["Scott M. Nelson", "Debbie A. Lawlor"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1000386.s001", "https://dx.doi.org/10.1371/journal.pmed.1000386.s002", "https://dx.doi.org/10.1371/journal.pmed.1000386.s003", "https://dx.doi.org/10.1371/journal.pmed.1000386.s004", "https://dx.doi.org/10.1371/journal.pmed.1000386.s005", "https://dx.doi.org/10.1371/journal.pmed.1000386.s006", "https://dx.doi.org/10.1371/journal.pmed.1000386.s007", "https://dx.doi.org/10.1371/journal.pmed.1000386.s008", "https://dx.doi.org/10.1371/journal.pmed.1000386.s009", "https://dx.doi.org/10.1371/journal.pmed.1000386.s010"], "stats"=>{"downloads"=>27, "page_views"=>65, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Predicting_Live_Birth_Preterm_Delivery_and_Low_Birth_Weight_in_Infants_Born_from_In_Vitro_Fertilisation_A_Prospective_Study_of_144_018_Treatment_Cycles/139715", "title"=>"Predicting Live Birth, Preterm Delivery, and Low Birth Weight in Infants Born from In Vitro Fertilisation: A Prospective Study of 144,018 Treatment Cycles", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-01-04 02:41:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/808197"], "description"=>"<p>These examples are plausible in terms of the types of patients regularly seen in IVF clinics, and they show the influence of couple characteristics (compare A to C and B to D) and of treatment effects (compare B to A and D to C), and of both of these combined (compare D to A).</p>", "links"=>[], "tags"=>["diabetes and endocrinology/reproductive endocrinology", "obstetrics/growth retardation", "obstetrics/pregnancy", "women's health/female subfertility and gynecological endocrinology"], "article_id"=>478565, "categories"=>["Immunology", "Medicine"], "users"=>["Scott M. Nelson", "Debbie A. Lawlor"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000386.t004", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Examples_of_risk_prediction_in_women_/478565", "title"=>"Examples of risk prediction in women.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-01-04 02:22:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/808322"], "description"=>"<p><i>N</i> = 144,018 analysis cohort with complete data on all variables included in any model.</p>a<p>Multivariable adjusted  =  mutual adjustment for all variables listed in column one.</p>b<p><i>p</i>-Value for multivariable association; all <i>p</i>-values are likelihood ratio tests of null hypothesis that the odds are the same for each category (i.e., they do not assume linearity).</p>", "links"=>[], "tags"=>["predictors"], "article_id"=>478695, "categories"=>["Immunology", "Medicine"], "users"=>["Scott M. Nelson", "Debbie A. Lawlor"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000386.t001", "stats"=>{"downloads"=>4, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Associations_of_potential_predictors_for_live_birth_following_IVF_/478695", "title"=>"Associations of potential predictors for live birth following IVF.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-01-04 02:24:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/808097"], "description"=>"<p>IVF, In-vitro fertilisation, GIFT, gamete intra-fallopian tube transfer, ZIFT, zygote intra-fallopian tube transfer.</p>", "links"=>[], "tags"=>["cohort"], "article_id"=>478474, "categories"=>["Immunology", "Medicine"], "users"=>["Scott M. Nelson", "Debbie A. Lawlor"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000386.g001", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Definition_of_eligible_cohort_and_analysis_sample_/478474", "title"=>"Definition of eligible cohort and analysis sample.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-01-04 02:21:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/808258"], "description"=>"<p><i>N</i> = 144,018 analysis cohort with complete data on all variables included in any model. Templeton: As in reference <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000386#pmed.1000386-Templeton1\" target=\"_blank\">[7]</a>, to date the only externally validated prediction model. Novel model: using the same variables as Templeton but allowing them to have different multivariable coefficients to those originally derived by Templeton and including terms for all causes of infertility (rather than just tubal versus other, as in the original Templeton) and four additional predictors: type of hormonal preparation, whether egg came from patient or donor, number of treatment cycles, and whether ICSI was used with the IVF.</p>", "links"=>[], "tags"=>["templeton", "predicting"], "article_id"=>478638, "categories"=>["Immunology", "Medicine"], "users"=>["Scott M. Nelson", "Debbie A. Lawlor"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000386.t002", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_AUROC_for_the_Templeton_and_novel_method_of_predicting_live_birth_with_IVF_/478638", "title"=>"AUROC for the Templeton and novel method of predicting live birth with IVF.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-01-04 02:23:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/808143"], "description"=>"<p><i>N</i> = 144,018 cycles of IVF treatment in the United Kingdom. Long dashed line, Templeton model; short dashed line, novel prediction model 2; red horizontal line, ratio of 1 (i.e., perfect prediction) for all levels of risk.</p>", "links"=>[], "tags"=>["observed"], "article_id"=>478518, "categories"=>["Immunology", "Medicine"], "users"=>["Scott M. Nelson", "Debbie A. Lawlor"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000386.g002", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Ratios_of_predicted_to_observed_live_birth_rate_using_two_prediction_models_/478518", "title"=>"Ratios of predicted to observed live birth rate using two prediction models.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-01-04 02:21:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/808291"], "description"=>"<p><i>N</i> = 144,018 analysis cohort with complete data on all variables included in any model. The cohort is split into 10ths of the distribution of the linear predictor for each of the two prediction models. For example, for the Templeton prediction model the observed and predicted are compared by 10<sup>th</sup> of the Templeton linear predictor.</p>a<p>Templeton: As in reference <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000386#pmed.1000386-Templeton1\" target=\"_blank\">[7]</a>, to date the only externally validated prediction model (<a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000386#pmed.1000386.s009\" target=\"_blank\">Text S1</a>).</p>b<p>Novel model: Using the same variables as Templeton but allowing them to have different multivariable coefficients to those originally derived by Templeton and including terms for all causes of infertility (rather than just tubal versus other as in the original Templeton) and four additional predictors: type of hormonal preparation, whether egg came from patient or donor, number of treatment cycles, and whether ICSI was used with the IVF (<a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000386#pmed.1000386.s010\" target=\"_blank\">Text S2</a>).</p>", "links"=>[], "tags"=>["diabetes and endocrinology/reproductive endocrinology", "obstetrics/growth retardation", "obstetrics/pregnancy", "women's health/female subfertility and gynecological endocrinology"], "article_id"=>478661, "categories"=>["Immunology", "Medicine"], "users"=>["Scott M. Nelson", "Debbie A. Lawlor"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000386.t003", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Calibration_of_the_two_prediction_models_/478661", "title"=>"Calibration of the two prediction models.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-01-04 02:24:21"}

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Relative Metric

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