Background: Gestational diabetes (GDM) is usually diagnosed late in pregnancy, precluding early preventive interventions. This study aims to develop a predictive model based on clinical factors and selected biochemical markers for the early risk assessment of GDM.
Methods: Based on a prospective cohort of 7929 pregnant women from the Quebec City metropolitan area, a nested case-control study was performed including 264 women who developed GDM. Each woman who developed GDM was matched with two women with normal glycemic profile. Risk prediction models for GDM and GDM requiring insulin therapy were developed using multivariable logistic regression analyses, based on clinical characteristics and the measurement of three clinically validated biomarkers: glycated hemoglobin (HbA1c), sex hormone binding globulin (SHBG) and high-sensitivity C-reactive protein (hsCRP) measured between 14 and 17 weeks of gestation.
Results: HbA1c and hsCRP were higher and SHBG was lower in women who developed GDM (p<0.001). The selected model for the prediction of GDM, based on HbA1c, SHBG, BMI, past history of GDM, family history of diabetes and soft drink intake before pregnancy yielded an area under the ROC curve (AUC) of 0.79 (0.75–0.83). For the prediction of GDM requiring insulin therapy, the selected model including the same six variables yielded an AUC of 0.88 (0.84–0.92) and a sensitivity of 68.9% at a false-positive rate of 10%.
Conclusions: A simple model based on clinical characteristics and biomarkers available early in pregnancy could allow the identification of women at risk of developing GDM, especially GDM requiring insulin therapy.
The authors thank Nathalie Bernard, Mylène Badeau and Véronique Goulet for their professional assistance with the project, and the research nurses for the recruitment of participants and retrieval of data from the medical records.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. ST assisted with the design of the study, interpreted the data and wrote the manuscript. YG assisted with the design of the study and writing and edition of the manuscript. JM analyzed the data and assisted with the interpretation of the data and writing and edition of the manuscript. JG contributed to the biomarkers measurements and assisted with writing and edition of the manuscript. JCF designed the study and assisted with the interpretation of the data and writing and edition of the manuscript.
Research funding: This work was supported by the Canadian Institutes of Health Research (CIHR, Healthy Pregnancy Initiative from the Institute for Human Development, Child and Youth Health, Grant number: NRF-HPG-78880). YG is a research scholar from the Fonds de la recherche du Québec – Santé (FRQ-S).
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
1. Landon MB, Gabbe SG. Gestational diabetes mellitus. Obstet Gynecol 2011;118:1379–93. Search in Google Scholar
2. Schneider S, Bock C, Wetzel M, Maul H, Loerbroks A. The prevalence of gestational diabetes in advanced economies. J Perinat Med 2012;40:511–20. Search in Google Scholar
3. Donovan L, Hartling L, Muise M, Guthrie A, Vandermeer B, Dryden DM. Screening tests for gestational diabetes: a systematic review for the U.S. Preventive Services Task Force. Ann Intern Med 2013;159:115–22. Search in Google Scholar
4. Metzger BE, Gabbe SG, Persson B, Buchanan TA, Catalano PA, Damm P, et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care 2010;33:676–82. Search in Google Scholar
5. National Institutes of Health consensus development conference statement: diagnosing gestational diabetes mellitus, March 4–6, 2013. Obstetr Gynecol 2013;122:358–69. Search in Google Scholar
6. Thompson D, Berger H, Feig D, Gagnon R, Kader T, Keely E, et al. Diabetes and pregnancy. Can J Diabetes 2013;37(Suppl 1):S168–83. Search in Google Scholar
7. American Diabetes Association. Standards of medical care in diabetes – 2014. Diabetes Care 2014;37(Suppl 1):S14–80. Search in Google Scholar
8. Diagnostic criteria and classification of hyperglycaemia first detected in pregnancy: a World Health Organization Guideline. Diabetes Res Clin Pract 2014;103:341–63. Search in Google Scholar
9. Beucher G, Viaris de Lesegno B, Dreyfus M. Maternal outcome of gestational diabetes mellitus. Diabetes Metab 2010;36:522–37. Search in Google Scholar
10. Mitanchez D. Foetal and neonatal complications in gestational diabetes: perinatal mortality, congenital malformations, macrosomia, shoulder dystocia, birth injuries, neonatal complications. Diabetes Metab 2010;36:617–27. Search in Google Scholar
11. Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, Coustan DR, et al. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med 2008;358:1991–2002. Search in Google Scholar
12. Burguet A. Long-term outcome in children of mothers with gestational diabetes. Diabetes Metab 2010;36:682–94. Search in Google Scholar
13. Verier-Mine O. Outcomes in women with a history of gestational diabetes. Screening and prevention of type 2 diabetes. Literature review. Diabetes Metab 2010;36:595–616. Search in Google Scholar
14. Crowther CA, Hiller JE, Moss JR, McPhee AJ, Jeffries WS, Robinson JS. Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. N Engl J Med 2005;352:2477–86. Search in Google Scholar
15. Landon MB, Spong CY, Thom E, Carpenter MW, Ramin SM, Casey B, et al. A multicenter, randomized trial of treatment for mild gestational diabetes. N Engl J Med 2009;361:1339–48. Search in Google Scholar
16. Maher N, McAuliffe F, Foley M. The benefit of early treatment without rescreening in women with a history of gestational diabetes. J Matern Fetal Neonatal Med 2013;26:318–20. Search in Google Scholar
17. Thangaratinam S, Rogozinska E, Jolly K, Glinkowski S, Roseboom T, Tomlinson JW, et al. Effects of interventions in pregnancy on maternal weight and obstetric outcomes: meta-analysis of randomised evidence. Br Med J 2012;344:e2088. Search in Google Scholar
18. Oostdam N, van Poppel MN, Wouters MG, van Mechelen W. Interventions for preventing gestational diabetes mellitus: a systematic review and meta-analysis. J Women Health 2011;20:1551–63. Search in Google Scholar
19. Caliskan E, Kayikcioglu F, Ozturk N, Koc S, Haberal A. A population-based risk factor scoring will decrease unnecessary testing for the diagnosis of gestational diabetes mellitus. Acta Obstet Gynecol Scand 2004;83:524–30. Search in Google Scholar
20. Naylor CD, Sermer M, Chen E, Farine D. Selective screening for gestational diabetes mellitus. Toronto Trihospital Gestational Diabetes Project Investigators. N Engl J Med 1997;337:1591–6. Search in Google Scholar
21. Teede HJ, Harrison CL, Teh WT, Paul E, Allan CA. Gestational diabetes: development of an early risk prediction tool to facilitate opportunities for prevention. Aust N Z J Obstet Gynaecol 2011;51:499–504. Search in Google Scholar
22. van Leeuwen M, Opmeer BC, Zweers EJ, van Ballegooie E, ter Brugge HG, de Valk HW, et al. Estimating the risk of gestational diabetes mellitus: a clinical prediction model based on patient characteristics and medical history. Br J Obstet Gynaecol 2010;117:69–75. Search in Google Scholar
23. Theriault S, Forest JC, Masse J, Giguere Y. Validation of early risk-prediction models for gestational diabetes based on clinical characteristics. Diabetes Res Clin Pract 2014;103:419–25. Search in Google Scholar
24. Blachier A, Alberti C, Korb D, Schmitz T, Patrick V, Christine B, et al. Diet or medically treated gestational diabetes: is there any difference for obstetrical and neonatal complications? A French cohort study. J Perinat Med 2014;42:315–9. Search in Google Scholar
25. Ferreira AF, Rezende JC, Vaikousi E, Akolekar R, Nicolaides KH. Maternal serum visfatin at 11–13 weeks of gestation in gestational diabetes mellitus. Clin Chem 2011;57:609–13. Search in Google Scholar
26. Nanda S, Savvidou M, Syngelaki A, Akolekar R, Nicolaides KH. Prediction of gestational diabetes mellitus by maternal factors and biomarkers at 11 to 13 weeks. Prenatal Diagn 2011;31: 135–41. Search in Google Scholar
27. Savvidou M, Nelson SM, Makgoba M, Messow CM, Sattar N, Nicolaides K. First-trimester prediction of gestational diabetes mellitus: examining the potential of combining maternal characteristics and laboratory measures. Diabetes 2010;59:3017–22. Search in Google Scholar
28. Lovati E, Beneventi F, Simonetta M, Laneri M, Quarleri L, Scudeller L, et al. Gestational diabetes mellitus: including serum pregnancy-associated plasma protein-A testing in the clinical management of primiparous women? A case-control study. Diabetes Res Clin Pract 2013;100:340–7. Search in Google Scholar
29. Leipold H, Worda C, Ozbal A, Husslein P, Krampl E. First-trimester nuchal translucency screening in pregnant women who subsequently developed gestational diabetes. J Soc Gynecol Invest 2005;12:529–32. Search in Google Scholar
30. Qiu C, Sorensen TK, Luthy DA, Williams MA. A prospective study of maternal serum C-reactive protein (CRP) concentrations and risk of gestational diabetes mellitus. Paediatr Perinat Epidemiol 2004;18:377–84. Search in Google Scholar
31. Caglar GS, Ozdemir ED, Cengiz SD, Demirtas S. Sex-hormone-binding globulin early in pregnancy for the prediction of severe gestational diabetes mellitus and related complications. J Obstetr Gynaecol Res 2012;38:1286–93. Search in Google Scholar
32. Fong A, Serra AE, Gabby L, Wing DA, Berkowitz KM. Use of hemoglobin A1c as an early predictor of gestational diabetes mellitus. Am J Obstet Gynecol 2014;211:641.e1–7. Search in Google Scholar
33. Canadian Diabetes Association Clinical Practice Guidelines Expert Committee. Canadian Diabetes Association 2008 Clinical Practice Guidelines for the prevention and management of diabetes in Canada. Can J Diabetes 2008;32(Suppl 1):S1–201. Search in Google Scholar
34. Chen L, Hu FB, Yeung E, Willett W, Zhang C. Prospective study of pre-gravid sugar-sweetened beverage consumption and the risk of gestational diabetes mellitus. Diabetes Care 2009;32: 2236–41. Search in Google Scholar
35. Zhang C, Solomon CG, Manson JE, Hu FB. A prospective study of pregravid physical activity and sedentary behaviors in relation to the risk for gestational diabetes mellitus. Arch Intern Med 2006;166:543–8. Search in Google Scholar
36. Sauerbrei W. The use of resampling methods to simplify regression models in medical statistics. J Royal Stat Soc Series C 1999;48:313–29. Search in Google Scholar
37. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44:837–45. Search in Google Scholar
38. Savona-Ventura C, Vassallo J, Marre M, Karamanos BG. A composite risk assessment model to screen for gestational diabetes mellitus among Mediterranean women. Int J Gynaecol Obstet 2013;120:240–4. Search in Google Scholar
39. Walker JD. NICE guidance on diabetes in pregnancy: management of diabetes and its complications from preconception to the postnatal period. NICE clinical guideline 63. London, March 2008. Diabet Med 2008;25:1025–7. Search in Google Scholar
40. Avalos GE, Owens LA, Dunne F. Applying current screening tools for gestational diabetes mellitus to a European population: is it time for change? Diabetes Care 2013;36:3040–4. Search in Google Scholar
41. Mosca A, Paleari R, Dalfra MG, Di Cianni G, Cuccuru I, Pellegrini G, et al. Reference intervals for hemoglobin A1c in pregnant women: data from an Italian multicenter study. Clin Chem 2006;52:1138–43. Search in Google Scholar
42. Hughes RC, Moore MP, Gullam JE, Mohamed K, Rowan J. An early pregnancy HbA1c >/=5.9% (41 mmol/mol) is optimal for detecting diabetes and identifies women at increased risk of adverse pregnancy outcomes. Diabetes Care 2014;37:2953–9. Search in Google Scholar
43. Peter A, Kantartzis K, Machann J, Schick F, Staiger H, Machicao F, et al. Relationships of circulating sex hormone-binding globulin with metabolic traits in humans. Diabetes 2010;59:3167–73. Search in Google Scholar
44. Watanabe N, Morimoto S, Fujiwara T, Suzuki T, Taniguchi K, Mori F, et al. Prediction of gestational diabetes mellitus by soluble (pro)renin receptor during the first trimester. J Clin Endocrinol Metab 2013;98:2528–35. Search in Google Scholar
45. Rasanen JP, Snyder CK, Rao PV, Mihalache R, Heinonen S, Gravett MG, et al. Glycosylated fibronectin as a first-trimester biomarker for prediction of gestational diabetes. Obstetr Gynecol 2013;122:586–94. Search in Google Scholar
46. Maitland RA, Seed PT, Briley AL, Homsy M, Thomas S, Pasupathy D, et al. Prediction of gestational diabetes in obese pregnant women from the UK Pregnancies Better Eating and Activity (UPBEAT) pilot trial. Diabet Med 2014;31:963–70. Search in Google Scholar
47. Wong VW, Jalaludin B. Gestational diabetes mellitus: who requires insulin therapy? Aust N Z J Obstet Gynaecol 2011;51:432–6. Search in Google Scholar
48. Halperin IJ, Feig DS. The role of lifestyle interventions in the prevention of gestational diabetes. Curr Diabetes Rep 2014;14:452. Search in Google Scholar
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