Development and multi-cohort validation of a clinical score for predicting type 2 diabetes mellitus.
- Kraege V Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland.
- Vollenweider P Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland.
- Waeber G Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland.
- Sharp SJ MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, England, United Kingdom.
- Vallejo M Tlalpan 2020 Study, Department of Socio-Medical Research, National Institute of Cardiology, Ignacio Chávez, Mexico City, Mexico.
- Infante O Tlalpan 2020 Study, Department of Socio-Medical Research, National Institute of Cardiology, Ignacio Chávez, Mexico City, Mexico.
- Mirjalili MR Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
- Ezoddini-Ardakani F Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
- Mozaffari-Khosravi H Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
- Lotfi MH Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
- Mirzaei M Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
- Méan M Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland.
- Marques-Vidal P Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland.
- 2019-10-10
Published in:
- PloS one. - 2019
Adult
Aged
Diabetes Mellitus, Type 2
Exercise
Female
Follow-Up Studies
Humans
Hypertension
Male
Middle Aged
Predictive Value of Tests
Prevalence
Prospective Studies
Waist Circumference
English
BACKGROUND AND AIMS
Many countries lack resources to identify patients at risk of developing Type 2 diabetes mellitus (diabetes). We aimed to develop and validate a diabetes risk score based on easily accessible clinical data.
METHODS
Prospective study including 5277 participants (55.0% women, 51.8±10.5 years) free of diabetes at baseline. Comparison with two other published diabetes risk scores (Balkau and Kahn clinical, respectively 5 and 8 variables) and validation on three cohorts (Europe, Iran and Mexico) was performed.
RESULTS
After a mean follow-up of 10.9 years, 405 participants (7.7%) developed diabetes. Our score was based on age, gender, waist circumference, diabetes family history, hypertension and physical activity. The area under the curve (AUC) was 0.772 for our score, vs. 0.748 (p<0.001) and 0.774 (p = 0.668) for the other two. Using a 13-point threshold, sensitivity, specificity, positive and negative predictive values (95% CI) of our score were 60.5 (55.5-65.3), 77.1 (75.8-78.2), 18.0 (16.0-20.1) and 95.9 (95.2-96.5) percent, respectively. Our score performed equally well or better than the other two in the Iranian [AUC 0.542 vs. 0.564 (p = 0.476) and 0.513 (p = 0.300)] and Mexican [AUC 0.791 vs. 0.672 (p<0.001) and 0.778 (p = 0.575)] cohorts. In the European cohort, it performed similarly to the Balkau score but worse than the Kahn clinical [AUC 0.788 vs. 0.793 (p = 0.091) and 0.816 (p<0.001)]. Diagnostic capacity of our score was better than the Balkau score and comparable to the Kahn clinical one.
CONCLUSION
Our clinically-based score shows encouraging results compared to other scores and can be used in populations with differing diabetes prevalence.
Many countries lack resources to identify patients at risk of developing Type 2 diabetes mellitus (diabetes). We aimed to develop and validate a diabetes risk score based on easily accessible clinical data.
METHODS
Prospective study including 5277 participants (55.0% women, 51.8±10.5 years) free of diabetes at baseline. Comparison with two other published diabetes risk scores (Balkau and Kahn clinical, respectively 5 and 8 variables) and validation on three cohorts (Europe, Iran and Mexico) was performed.
RESULTS
After a mean follow-up of 10.9 years, 405 participants (7.7%) developed diabetes. Our score was based on age, gender, waist circumference, diabetes family history, hypertension and physical activity. The area under the curve (AUC) was 0.772 for our score, vs. 0.748 (p<0.001) and 0.774 (p = 0.668) for the other two. Using a 13-point threshold, sensitivity, specificity, positive and negative predictive values (95% CI) of our score were 60.5 (55.5-65.3), 77.1 (75.8-78.2), 18.0 (16.0-20.1) and 95.9 (95.2-96.5) percent, respectively. Our score performed equally well or better than the other two in the Iranian [AUC 0.542 vs. 0.564 (p = 0.476) and 0.513 (p = 0.300)] and Mexican [AUC 0.791 vs. 0.672 (p<0.001) and 0.778 (p = 0.575)] cohorts. In the European cohort, it performed similarly to the Balkau score but worse than the Kahn clinical [AUC 0.788 vs. 0.793 (p = 0.091) and 0.816 (p<0.001)]. Diagnostic capacity of our score was better than the Balkau score and comparable to the Kahn clinical one.
CONCLUSION
Our clinically-based score shows encouraging results compared to other scores and can be used in populations with differing diabetes prevalence.
- Language
-
- English
- Open access status
- gold
- Identifiers
-
- DOI 10.1371/journal.pone.0218933
- PMID 31596852
- Persistent URL
- https://sonar.ch/global/documents/186161
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