Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study

Abstract

Objective To develop and validate a risk score model for recognizing prediabetes among Indonesian adults in primary care. Methods This was a cross-sectional diagnostic study. After excluding subjects with diabetes from Indonesian National Basic Health Survey (INBHS) data set, 21,720 subjects who have completed fasting plasma glucose test and aged >18 years were selected for development stage. About 6,933 subjects were selected randomly from INBHS for validation stage in different diagnostic criteria of prediabetes-based random plasma glucose. Logistic regression was used to determine significant diagnostic variable and the receiver operating characteristic analysis was used to calculate area under the curve (AUC), cutoff point, sensitivity, specificity, and predictive values. Results Age, sex, education level, family history of diabetes, smoking habit, physical activity, body mass index, and hypertension were significant variables for Indonesian Prediabetes Risk Score (INA-PRISC). The scoring range from 0 to 24, the AUC was 0.623 (95% CI 0.616–0.631) and cutoff point of 12 yielded sensitivity/specificity (50.03%/67.19%, respectively). The validation study showed the AUC was 0.646 (95% CI 0.623–0.669) and cutoff point of 12 yielded sensitivity/specificity (55.11%/65.81%, respectively). Conclusion INA-PRISC, which consists of eight demographical and clinical variables, is a valid and a simple prediabetes risk score in primary care.

Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study (Preprint)

“…However, in comparable reports on the risk assessment of diabetes, the area under the curves was 0.67 to 0.882. [5][6][7]16] A similar trend was seen in our study. The highest area under the curve was 0.77 for pre-diabetes risk assessment, while the highest area under the curve for diabetes risk assessment was 0.93.…”

“…[22] As far as we know, all previous diabetes risk assessment tools were based on information obtained from questionnaires, such as family history and lifestyle habits. [4][5][6][7]16] Because of this, our results could not be easily compared with previous reports. A previous study showed that combining the results of blood tests and questionnaire information improved the prediction accuracy of diabetes risk assessment.…”

“…[1][2][3] We used the diabetes risk assessed from noninvasive questionnaire information, such as physique and age, as a first screening test to select subjects to have their plasma glucose measured. [4][5][6][7] However, we believe that the classification abilities of noninvasive diabetes screening tools are lacking in accuracy and reproducibility, having area under the curve values based on receiver operating characteristic curves between 0.617 to 0.85. A 75-g oral glucose tolerance test (OGTT) provides information regarding the diagnosis of diabetes and the pathological condition called glucose metabolism disorder.…”

Simple risk score to screen for prediabetes: A cross‐sectional study from the Qatar Biobank cohort

“…Compared with other LR‐based prediabetes risk scores developed in other countries for adult populations, the discrimination capability of the PRISQ risk score, as measured by the AUC of the receiver operating characteristic curve, was 80%, higher than many other scores developed in other countries, such as Indonesia (AUC 62.3%) 38 , China (two scores: AUC 74% and AUC 70%) 36,39 and the USA (AUC 74%) 40 . According to our risk score, a person with a score between 17 and 27 would be considered as being at moderate risk of prediabetes, whereas a score >27 would be considered high risk.…”

Prediabetes and Their Contributed Factors: A Study in Semarang

“…The prevalence of prediabetes in Indonesia is very high, reaching 10% (Manaf, 2014). A Previous study stated that one-third of people diagnosed with prediabetes will develop diabetes (Fujiati, Damanik, Bachtiar, Nurdin, & Ward, 2017). Moreover, another study also stated that, at one year of follow-up, 3.7% of those with prediabetes had progressed to have diabetes and, by five years of follow-up, 17.1% had progressed to have diabetes (DeJesus et al, 2017).…”