Temporal validation and updating of a prediction model for the diagnosis of gestational diabetes mellitus.

Autor: Cooray SD; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria 3168, Australia; Diabetes and Endocrinology Units, Monash Health, Clayton, Victoria 3168, Australia., De Silva K; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria 3168, Australia; Department of Radiation Sciences, Umeå University, Umeå, Sweden., Enticott JC; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria 3168, Australia., Dawadi S; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria 3168, Australia., Boyle JA; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria 3168, Australia; Department of Obstetrics and Gynaecology, Monash University, Clayton, Victoria 3168, Australia; Eastern Health Clinical School, Monash University, Box Hill, Victoria 3128, Australia., Soldatos G; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria 3168, Australia; Diabetes and Endocrinology Units, Monash Health, Clayton, Victoria 3168, Australia., Paul E; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria 3168, Australia., Versace VL; Deakin Rural Health, School of Medicine, Deakin University, Warrnambool, Victoria 3280, Australia., Teede HJ; Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria 3168, Australia; Diabetes and Endocrinology Units, Monash Health, Clayton, Victoria 3168, Australia. Electronic address: Helena.Teede@monash.edu.
Jazyk: angličtina
Zdroj: Journal of clinical epidemiology [J Clin Epidemiol] 2023 Dec; Vol. 164, pp. 54-64. Date of Electronic Publication: 2023 Sep 01.
DOI: 10.1016/j.jclinepi.2023.08.020
Abstrakt: Objective: The original Monash gestational diabetes mellitus (GDM) risk prediction in early pregnancy model is internationally externally validated and clinically implemented. We temporally validate and update this model in a contemporary population with a universal screening context and revised diagnostic criteria and ethnicity categories, thereby improving model performance and generalizability.
Study Design and Setting: The updating dataset comprised of routinely collected health data for singleton pregnancies delivered in Melbourne, Australia from 2016 to 2018. Model predictors included age, body mass index, ethnicity, diabetes family history, GDM history, and poor obstetric outcome history. Model updating methods were recalibration-in-the-large (Model A), intercept and slope re-estimation (Model B), and coefficient revision using logistic regression (Model C1, original ethnicity categories; Model C2, revised ethnicity categories). Analysis included 10-fold cross-validation, assessment of performance measures (c-statistic, calibration-in-the-large, calibration slope, and expected-observed ratio), and a closed-loop testing procedure to compare models' log-likelihood and akaike information criterion scores.
Results: In 26,474 singleton pregnancies (4,756, 18% with GDM), the original model demonstrated reasonable temporal validation (c-statistic = 0.698) but suboptimal calibration (expected-observed ratio = 0.485). Updated model C2 was preferred, with a high c-statistic (0.732) and significantly better performance in closed testing.
Conclusion: We demonstrated updating methods to sustain predictive performance in a contemporary population, highlighting the value and versatility of prediction models for guiding risk-stratified GDM care.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023. Published by Elsevier Inc.)
Databáze: MEDLINE
Externí odkaz: