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      Diagnostic accuracy of the Finnish Diabetes Risk Score (FINDRISC) for undiagnosed T2DM in Peruvian population

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          Highlights

          • Diagnostic accuracy of FINDRISC, LA-FINDRISC and Peruvian Risk Score was similar.

          • A simplified version of FINDRISC was created with only four variables.

          • The performance of the FINDRISC in Peruvian population was moderate.

          • Forty percent of individuals with T2DM are unaware of diagnosis.

          Abstract

          Aims

          To assess the diagnostic accuracy of the Finnish Diabetes Risk Score (FINDRISC) for undiagnosed T2DM and to compare its performance with the Latin-American FINDRISC (LA-FINDRISC) and the Peruvian Risk Score.

          Materials and methods

          A population-based study was conducted. T2DM and undiagnosed T2DM were defined using oral glucose tolerance test (OGTT). Risk scores assessed were FINDRISC, LA-FINDRISC and Peruvian Risk Score. Diagnostic accuracy of risk scores was estimated using the c-statistic and the area under the ROC curve (aROC). A simplified version of FINDRISC was also derived.

          Results

          Data from 1609 individuals, mean age 48.2 (SD: 10.6), 810 (50.3%) women, were collected. A total of 176 (11.0%; 95%CI: 9.4%–12.5%) were classified as having T2DM, and 71 (4.7%; 95%CI: 3.7%–5.8%) were classified as having undiagnosed T2DM. Diagnostic accuracy of the FINDRISC (aROC = 0.69), LA-FINDRISC (aROC = 0.68), and Peruvian Risk Score (aROC = 0.64) was similar (p = 0.15). The simplified FINDRISC, with 4 variables, had a slightly better performance (aROC = 0.71) than the other scores.

          Conclusion

          The performance of FINDRISC, LA-FINDRISC and Peruvian Risk Score for undiagnosed T2DM was similar. A simplified FINDRISC can perform as well or better for undiagnosed T2DM. The FINDRISC may be useful to detect cases of undiagnosed T2DM in resource-constrained settings.

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          Most cited references 27

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          Index for rating diagnostic tests.

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            Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study.

            Individuals with impaired glucose tolerance (IGT) have a high risk of developing NIDDM. The purpose of this study was to determine whether diet and exercise interventions in those with IGT may delay the development of NIDDM, i.e., reduce the incidence of NIDDM, and thereby reduce the overall incidence of diabetic complications, such as cardiovascular, renal, and retinal disease, and the excess mortality attributable to these complications. In 1986, 110,660 men and women from 33 health care clinics in the city of Da Qing, China, were screened for IGT and NIDDM. Of these individuals, 577 were classified (using World Health Organization criteria) as having IGT. Subjects were randomized by clinic into a clinical trial, either to a control group or to one of three active treatment groups: diet only, exercise only, or diet plus exercise. Follow-up evaluation examinations were conducted at 2-year intervals over a 6-year period to identify subjects who developed NIDDM. Cox's proportional hazard analysis was used to determine if the incidence of NIDDM varied by treatment assignment. The cumulative incidence of diabetes at 6 years was 67.7% (95% CI, 59.8-75.2) in the control group compared with 43.8% (95% CI, 35.5-52.3) in the diet group, 41.1% (95% CI, 33.4-49.4) in the exercise group, and 46.0% (95% CI, 37.3-54.7) in the diet-plus-exercise group (P or = 25 kg/m2). In a proportional hazards analysis adjusted for differences in baseline BMI and fasting glucose, the diet, exercise, and diet-plus-exercise interventions were associated with 31% (P < 0.03), 46% (P < 0.0005), and 42% (P < 0.005) reductions in risk of developing diabetes, respectively. Diet and/or exercise interventions led to a significant decrease in the incidence of diabetes over a 6-year period among those with IGT.
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              Risk models and scores for type 2 diabetes: systematic review

              Objective To evaluate current risk models and scores for type 2 diabetes and inform selection and implementation of these in practice. Design Systematic review using standard (quantitative) and realist (mainly qualitative) methodology. Inclusion criteria Papers in any language describing the development or external validation, or both, of models and scores to predict the risk of an adult developing type 2 diabetes. Data sources Medline, PreMedline, Embase, and Cochrane databases were searched. Included studies were citation tracked in Google Scholar to identify follow-on studies of usability or impact. Data extraction Data were extracted on statistical properties of models, details of internal or external validation, and use of risk scores beyond the studies that developed them. Quantitative data were tabulated to compare model components and statistical properties. Qualitative data were analysed thematically to identify mechanisms by which use of the risk model or score might improve patient outcomes. Results 8864 titles were scanned, 115 full text papers considered, and 43 papers included in the final sample. These described the prospective development or validation, or both, of 145 risk prediction models and scores, 94 of which were studied in detail here. They had been tested on 6.88 million participants followed for up to 28 years. Heterogeneity of primary studies precluded meta-analysis. Some but not all risk models or scores had robust statistical properties (for example, good discrimination and calibration) and had been externally validated on a different population. Genetic markers added nothing to models over clinical and sociodemographic factors. Most authors described their score as “simple” or “easily implemented,” although few were specific about the intended users and under what circumstances. Ten mechanisms were identified by which measuring diabetes risk might improve outcomes. Follow-on studies that applied a risk score as part of an intervention aimed at reducing actual risk in people were sparse. Conclusion Much work has been done to develop diabetes risk models and scores, but most are rarely used because they require tests not routinely available or they were developed without a specific user or clear use in mind. Encouragingly, recent research has begun to tackle usability and the impact of diabetes risk scores. Two promising areas for further research are interventions that prompt lay people to check their own diabetes risk and use of risk scores on population datasets to identify high risk “hotspots” for targeted public health interventions.
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                Author and article information

                Contributors
                Journal
                Prim Care Diabetes
                Prim Care Diabetes
                Primary Care Diabetes
                Elsevier
                1751-9918
                1878-0210
                1 December 2018
                December 2018
                : 12
                : 6
                : 517-525
                Affiliations
                [a ]CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima 18, Peru
                [b ]Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
                [c ]Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima 31, Peru
                Author notes
                [* ] Corresponding author at: CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Av. Armendáriz 497, Lima 18, Peru. Antonio.Bernabe@ 123456upch.pe
                Article
                S1751-9918(18)30244-4
                10.1016/j.pcd.2018.07.015
                6249987
                30131300
                © 2018 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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