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Epidemiology/Health Services Research
FINDRISC in Latin America: a systematic review of diagnosis and prognosis models
  1. Rodrigo M Carrillo-Larco1,2,3,
  2. Diego J Aparcana-Granda2,
  3. Jhonatan R Mejia4,
  4. Antonio Bernabé-Ortiz2,5
  1. 1Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
  2. 2CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru
  3. 3Instituto de Investigación, Universidad Católica Los Ángeles de Chimbote, Chimbote, Peru
  4. 4Facultad de Medicina Humana, Universidad Nacional del Centro del Perú, Huancayo, Peru
  5. 5Universidad Científica del Sur, Lima, Peru
  1. Correspondence to Dr Rodrigo M Carrillo-Larco; rcarrill{at}ic.ac.uk

Abstract

This review aimed to assess whether the FINDRISC, a risk score for type 2 diabetes mellitus (T2DM), has been externally validated in Latin America and the Caribbean (LAC). We conducted a systematic review following the CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) framework. Reports were included if they validated or re-estimated the FINDRISC in population-based samples, health facilities or administrative data. Reports were excluded if they only studied patients or at-risk individuals. The search was conducted in Medline, Embase, Global Health, Scopus and LILACS. Risk of bias was assessed with the PROBAST (Prediction model Risk of Bias ASsessment Tool) tool. From 1582 titles and abstracts, 4 (n=7502) reports were included for qualitative summary. All reports were from South America; there were slightly more women, and the mean age ranged from 29.5 to 49.7 years. Undiagnosed T2DM prevalence ranged from 2.6% to 5.1%. None of the studies conducted an independent external validation of the FINDRISC; conversely, they used the same (or very similar) predictors to fit a new model. None of the studies reported calibration metrics. The area under the receiver operating curve was consistently above 65.0%. All studies had high risk of bias. There has not been any external validation of the FINDRISC model in LAC. Selected reports re-estimated the FINDRISC, although they have several methodological limitations. There is a need for big data to develop—or improve—T2DM diagnostic and prognostic models in LAC. This could benefit T2DM screening and early diagnosis.

  • type 2 diabetes mellitus
  • prognostic models
  • diagnostic models
  • low- and middle-income countries
  • FINDRISC
https://creativecommons.org/licenses/by/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

https://doi.org/10.1136/bmjdrc-2019-001169

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    Footnotes

    • DJA-G and JRM contributed equally.

    • Contributors RMC-L and AB-O conceived the idea. RMC-L, DJA-G and JRM conducted the search and data extraction. DJA-G and JRM conducted the risk of bias. RMC-L wrote the manuscript with input from all coauthors. All authors approved the submitted version.

    • Funding The study received funding from Strategic Award, Wellcome Trust-Imperial College Centre for Global Health Research (100693/Z/12/Z), and Imperial College London Wellcome Trust Institutional Strategic Support Fund (Global Health Clinical Research Training Fellowship) (294834/Z/16/Z ISSF ICL). RMC-L is supported by a Wellcome Trust International Training Fellowship (214185/Z/18/Z). The funder had no role in the conception or conduct of this work, neither in the preparation of the results nor in manuscript writing. The authors alone are responsible for the results and opinions in this work.

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Ethics approval No human subjects were studied; thus, this review was classified as of low risk.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement Data sharing not applicable as no data sets generated and/or analyzed for this study. This is a systematic review of the scientific literature.