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

Antonio Bernabe-Ortiz, Pablo Perel, Juan Jaime Miranda, Liam Smeeth, Antonio Bernabe-Ortiz, Pablo Perel, Juan Jaime Miranda, Liam Smeeth

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.

Keywords: Diabetes mellitus, type 2; Diagnostic test; Glucose tolerance test; Risk assessment; Screening.

Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Figures

Fig. 1
Fig. 1
Comparison of area under the ROC curves using the FINDRISC, LA-FINDRISC, the Peruvian Risk Score and the simplified risk scores.

References

    1. NCD Risk Factor Collaboration (N.C.D-RisC) Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants. Lancet. 2016;387:1513–1530.
    1. GBD 2016 Causes of Death Collaborators Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390:1151–1210.
    1. Global Burden of Metabolic Risk Factors for Chronic Diseases Collaboration Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factorsfrom 1980 to 2010: a comparative risk assessment. Lancet Diabetes Endocrinol. 2014;2:634–647.
    1. International Diabetes Federation . 8th edition. IDF; Brussels, Belgium: 2017. IDF Diabetes Atlas.
    1. Selph S., Dana T., Blazina I., Bougatsos C., Patel H., Chou R. Screening for type 2 diabetes mellitus: a systematic review for the U.S. Preventive Services Task Force. Ann. Intern. Med. 2015;162:765–776.
    1. Ali M.K., Siegel K.R., Chandrasekar E., Tandon N., Montoya P.A., Mbanya J.C., Chan J., Zhang P., Venkat Narayan K.M. 3rd edition. vol. 5. World Bank; Washington DC,US: 2017. Disease control priorities. (Cardiovascular, Respiratory and Related Disorders).
    1. American Diabetes Association 2. Classification and diagnosis of diabetes: standards of medical care in diabetes — 2018. Diabetes Care. 2018;41:S13–s27.
    1. Brown N., Critchley J., Bogowicz P., Mayige M., Unwin N. Risk scores based on self-reported or available clinical data to detect undiagnosed type 2 diabetes: a systematic review. Diabetes Res. Clin. Pract. 2012;98:369–385.
    1. Khunti K., Mani H., Achana F., Cooper N., Gray L.J., Davies M.J. Systematic review and meta-analysis of response rates and diagnostic yield of screening for type 2 diabetes and those at high risk of diabetes. PloS One. 2015;10
    1. Noble D., Mathur R., Dent T., Meads C., Greenhalgh T. Risk models and scores for type 2 diabetes: systematic review. BMJ. 2011;343:d7163.
    1. Lindstrom J., Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care. 2003;26:725–731.
    1. Schwarz P.E., Li J., Lindstrom J., Tuomilehto J. Tools for predicting the risk of type 2 diabetes in daily practice. Horm. Metab. Res. 2009;41:86–97.
    1. Saaristo T., Peltonen M., Lindstrom J., Saarikoski L., Sundvall J., Eriksson J.G., Tuomilehto J. Cross-sectional evaluation of the Finnish Diabetes Risk Score: a tool to identify undetected type 2 diabetes, abnormal glucose tolerance and metabolic syndrome. Diab. Vasc. Dis. Res. 2005;2:67–72.
    1. Schwarz P.E., Li J., Reimann M., Schutte A.E., Bergmann A., Hanefeld M., Bornstein S.R., Schulze J., Tuomilehto J., Lindstrom J. The Finnish Diabetes Risk Score is associated with insulin resistance and progression towards type 2 diabetes. J. Clin. Endocrinol. Metab. 2009;94:920–926.
    1. Zhang L., Zhang Z., Zhang Y., Hu G., Chen L. Evaluation of Finnish Diabetes Risk Score in screening undiagnosed diabetes and prediabetes among U.S. adults by gender and race: NHANES 1999–2010. PloS One. 2014;9
    1. Barengo N.C., Acosta T., Arrieta A., Ricaurte C., Mayor D., Tuomilehto J.O. Screening for people with glucose metabolism disorders within the framework of the DEMOJUAN project (DEMOnstration area for primary prevention of type 2 diabetes, JUAN Mina and Barranquilla, Colombia) Diabetes Metab. Res. Rev. 2013
    1. Gomez-Arbelaez D., Alvarado-Jurado L., Ayala-Castillo M., Forero-Naranjo L., Camacho P.A., Lopez-Jaramillo P. Evaluation of the Finnish Diabetes Risk Score to predict type 2 diabetes mellitus in a Colombian population: a longitudinal observational study. World J. Diabetes. 2015;6:1337–1344.
    1. Nieto-Martinez R., Gonzalez-Rivas J.P., Aschner P., Barengo N.C., Mechanick J.I. Transculturalizing diabetes prevention in Latin America. Ann. Glob. Health. 2017;83:432–443.
    1. Instituto Nacional de Estadistica e Informatica . INEI; Lima, Peru: 2017. Peru en cifras.
    1. Bernabe-Ortiz A., Carrillo-Larco R.M., Gilman R.H., Checkley W., Smeeth L., Miranda J.J. Contribution of modifiable risk factors for hypertension and type-2 diabetes in Peruvian resource-limited settings. J. Epidemiol. Community Health. 2016;70:49–55.
    1. Bernabe-Ortiz A., Smeeth L., Gilman R.H., Sanchez-Abanto J.R., Checkley W., Miranda J.J., C.C. Study Group Development and validation of a simple risk score for undiagnosed type 2 diabetes in a resource-constrained setting. J. Diabetes Res. 2016;2016 8790235.
    1. Youden W.J. Index for rating diagnostic tests. Cancer. 1950;3:32–35.
    1. Bang H., Edwards A.M., Bomback A.S., Ballantyne C.M., Brillon D., Callahan M.A., Teutsch S.M., Mushlin A.I., Kern L.M. Development and validation of a patient self-assessment score for diabetes risk. Ann. Intern. Med. 2009;151:775–783.
    1. Baan C.A., Ruige J.B., Stolk R.P., Witteman J.C., Dekker J.M., Heine R.J., Feskens E.J. Performance of a predictive model to identify undiagnosed diabetes in a health care setting. Diabetes Care. 1999;22:213–219.
    1. Gray L.J., Taub N.A., Khunti K., Gardiner E., Hiles S., Webb D.R., Srinivasan B.T., Davies M.J. The Leicester Risk Assessment score for detecting undiagnosed type 2 diabetes and impaired glucose regulation for use in a multiethnic UK setting. Diabet Med. 2010;27:887–895.
    1. Gao W.G., Dong Y.H., Pang Z.C., Nan H.R., Wang S.J., Ren J., Zhang L., Tuomilehto J., Qiao Q. A simple Chinese risk score for undiagnosed diabetes. Diabet Med. 2010;27:274–281.
    1. Ramachandran A., Snehalatha C., Vijay V., Wareham N.J., Colagiuri S. Derivation and validation of diabetes risk score for urban Asian Indians. Diabetes Res. Clin. Pract. 2005;70:63–70.
    1. Xie J., Hu D., Yu D., Chen C.S., He J., Gu D. A quick self-assessment tool to identify individuals at high risk of type 2 diabetes in the Chinese general population. J. Epidemiol. Community Health. 2010;64:236–242.
    1. Glumer C., Vistisen D., Borch-Johnsen K., Colagiuri S. Risk scores for type 2 diabetes can be applied in some populations but not all. Diabetes Care. 2006;29:410–414.
    1. Barengo N.C., Tamayo D.C., Tono T., Tuomilehto J. A Colombian diabetes risk score for detecting undiagnosed diabetes and impaired glucose regulation. Prim. Care Diabetes. 2017;11:86–93.
    1. Salinero-Fort M.A., Burgos-Lunar C., Lahoz C., Mostaza J.M., Abanades-Herranz J.C., Laguna-Cuesta F., Estirado-de Cabo E., Garcia-Iglesias F., Gonzalez-Alegre T., Fernandez-Puntero B., Montesano-Sanchez L., Vicent-Lopez D., Cornejo-Del Rio V., Fernandez-Garcia P.J., Sanchez-Arroyo V., Sabin-Rodriguez C., Lopez-Lopez S., Patron-Barandio P., Gomez-Campelo P. Performance of the Finnish Diabetes Risk Score and a Simplified Finnish Diabetes Risk Score in a community-based, cross-sectional programme for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in Madrid, Spain: the SPREDIA-2 study. PloS One. 2016;11
    1. Stiglic G., Fijacko N., Stozer A., Sheikh A., Pajnkihar M. Validation of the Finnish Diabetes Risk Score (FINDRISC) questionnaire for undiagnosed type 2 diabetes screening in the Slovenian working population. Diabetes Res. Clin. Pract. 2016;120:194–197.
    1. Ministerio de Salud . MINSA; Lima Peru: 2006. Encuesta Nacional de Indicadores Nutricionales, Bioquimicos, Socioeconomicos y Culturales relacionados con las Enfermedades Cronicas Degenerativas.
    1. Seclen S.N., Rosas M.E., Arias A.J., Huayta E., Medina C.A. Prevalence of diabetes and impaired fasting glucose in Peru: report from PERUDIAB, a national urban population-based longitudinal study. BMJ Open Diabetes Res. Care. 2015;3
    1. Miranda J.J., Gilman R.H., Garcia H.H., Smeeth L. The effect on cardiovascular risk factors of migration from rural to urban areas in Peru: PERU MIGRANT Study. BMC Cardiovasc. Disord. 2009;9:23.
    1. Lerner A.G., Bernabe-Ortiz A., Gilman R.H., Smeeth L., Miranda J.J. The “rule of halves” does not apply in Peru: awareness, treatment, and control of hypertension and diabetes in rural, urban, and rural-to-urban migrants. Crit. Pathw. Cardiol. 2013;12:53–58.
    1. Knowler W.C., Barrett-Connor E., Fowler S.E., Hamman R.F., Lachin J.M., Walker E.A., Nathan D.M. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New Eng. J. Med. 2002;346:393–403.
    1. Pan X.R., Li G.W., Hu Y.H., Wang J.X., Yang W.Y., An Z.X., Hu Z.X., Lin J., Xiao J.Z., Cao H.B., Liu P.A., Jiang X.G., Jiang Y.Y., Wang J.P., Zheng H., Zhang H., Bennett P.H., Howard B.V. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance: the Da Qing IGT and diabetes study. Diabetes Care. 1997;20:537–544.
    1. Gill J.M., Bhopal R., Douglas A., Wallia S., Bhopal R., Sheikh A., Forbes J.F., McKnight J., Sattar N., Murray G., Lean M.E., Wild S.H. Sitting time and waist circumference are associated with glycemia in U.K. South Asians: data from 1228 adults screened for the PODOSA trial. Diabetes Care. 2011;34:1214–1218.
    1. Dhippayom T., Chaiyakunapruk N., Krass I. How diabetes risk assessment tools are implemented in practice: a systematic review. Diabetes Res. Clin. Pract. 2014;104:329–342.
    1. Ministerio de Salud . MINSA; Lima, Peru: 2016. Guia de Practica Clinica para el Diagnostico, Tratamiento y Control de la Diabetes Mellitus Tipo 2 en el Primer Nivel de Atencion.
    1. Pires de Sousa A.G., Pereira A.C., Marquezine G.F., Marques do Nascimento-Neto R., Freitas S.N., de Nicolato R.L.C., Machado-Coelho G.L., Rodrigues S.L., Mill J.G., Krieger J.E. Derivation and external validation of a simple prediction model for the diagnosis of type 2 diabetes mellitus in the Brazilian urban population. Eur. J. Epidemiol. 2009;24:101–109.
    1. Ta M.T., Nguyen K.T., Nguyen N.D., Campbell L.V., Nguyen T.V. Identification of undiagnosed type 2 diabetes by systolic blood pressure and waist-to-hip ratio. Diabetologia. 2010;53:2139–2146.

Source: PubMed

스폰서 및 공동 작업자

건강 상태

약물 개입

3
구독하다