title: Prognostic models in obstetrics: available, but far from applicable.
abstract: Health care provision is increasingly focused on the prediction of patients' individual risk for developing a particular health outcome in planning further tests and treatments. There has been a steady increase in the development and publication of prognostic models for various maternal and fetal outcomes in obstetrics. We undertook a systematic review to give an overview of the current status of available prognostic models in obstetrics in the context of their potential advantages and the process of developing and validating models. Important aspects to consider when assessing a prognostic model are discussed and recommendations on how to proceed on this within the obstetric domain are given. We searched MEDLINE (up to July 2012) for articles developing prognostic models in obstetrics. We identified 177 papers that reported the development of 263 prognostic models for 40 different outcomes. The most frequently predicted outcomes were preeclampsia (n = 69), preterm delivery (n = 63), mode of delivery (n = 22), gestational hypertension (n = 11), and small-for-gestational-age infants (n = 10). The performance of newer models was generally not better than that of older models predicting the same outcome. The most important measures of predictive accuracy (ie, a model's discrimination and calibration) were often (82.9%, 218/263) not both assessed. Very few developed models were validated in data other than the development data (8.7%, 23/263). Only two-thirds of the papers (62.4%, 164/263) presented the model such that validation in other populations was possible, and the clinical applicability was discussed in only 11.0% (29/263). The impact of developed models on clinical practice was unknown. We identified a large number of prognostic models in obstetrics, but there is relatively little evidence about their performance, impact, and usefulness in clinical practice so that at this point, clinical implementation cannot be recommended. New efforts should be directed toward evaluating the performance and impact of the existing models.
authors.affiliation: Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam, The Netherlands. Electronic address: c.e.kleinrouweler@amc.uva.nl.
authors.forename: C Emily
authors.initials: CE
authors.lastname: Kleinrouweler
authors.affiliation: Women's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University London, London, United Kingdom.
authors.forename: Fiona M
authors.initials: FM
authors.lastname: Cheong-See
authors.affiliation: Center for Statistics in Medicine, University of Oxford, Oxford, United Kingdom.
authors.forename: Gary S
authors.initials: GS
authors.lastname: Collins
authors.affiliation: Department of Obstetrics and Gynecology, University Medical Center Utrecht, Utrecht, The Netherlands.
authors.forename: Anneke
authors.initials: A
authors.lastname: Kwee
authors.affiliation: Women's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University London, London, United Kingdom; Multidisciplinary Evidence Synthesis Hub, Barts and the London School of Medicine and Dentistry, Queen Mary University London, London, United Kingdom.
authors.forename: Shakila
authors.initials: S
authors.lastname: Thangaratinam
authors.affiliation: Women's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University London, London, United Kingdom; Multidisciplinary Evidence Synthesis Hub, Barts and the London School of Medicine and Dentistry, Queen Mary University London, London, United Kingdom.
authors.forename: Khalid S
authors.initials: KS
authors.lastname: Khan
authors.affiliation: Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam, The Netherlands.
authors.forename: Ben Willem J
authors.initials: BW
authors.lastname: Mol
authors.affiliation: Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam, The Netherlands.
authors.forename: Eva
authors.initials: E
authors.lastname: Pajkrt
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
authors.forename: Karel G M
authors.initials: KG
authors.lastname: Moons
authors.affiliation: Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam, The Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; Stanford Prevention Research Center, Stanford University, Stanford, CA.
authors.forename: Ewoud
authors.initials: E
authors.lastname: Schuit
mesh_terms: D005260:Female; D006801:Humans; D008954:Models, Biological; D009774:Obstetrics / Q000379:methods*; D011237:Predictive Value of Tests; D011247:Pregnancy; D011248:Pregnancy Complications / Q000175:diagnosis*
keywords: model; obstetrics; prediction; pregnancy