Optimizing strategies to identify high risk of developing type 2 diabetes

Front Endocrinol (Lausanne). 2023 Jun 28:14:1166147. doi: 10.3389/fendo.2023.1166147. eCollection 2023.

Abstract

Introduction: The success of diabetes prevention based on early treatment depends on high-quality screening. This study compared the diagnostic properties of currently recommended screening strategies against alternative score-based rules to identify those at high risk of developing diabetes.

Methods: The study used data from ELSA-Brasil, a contemporary cohort followed up for a mean (standard deviation) of 7.4 (0.54) years, to develop risk functions with logistic regression to predict incident diabetes based on socioeconomic, lifestyle, clinical, and laboratory variables. We compared the predictive capacity of these functions against traditional pre-diabetes cutoffs of fasting plasma glucose (FPG), 2-h plasma glucose (2hPG), and glycated hemoglobin (HbA1c) alone or combined with recommended screening questionnaires.

Results: Presenting FPG > 100 mg/dl predicted 76.6% of future cases of diabetes in the cohort at the cost of labeling 40.6% of the sample as high risk. If FPG testing was performed only in those with a positive American Diabetes Association (ADA) questionnaire, labeling was reduced to 12.2%, but only 33% of future cases were identified. Scores using continuously expressed clinical and laboratory variables produced a better balance between detecting more cases and labeling fewer false positives. They consistently outperformed strategies based on categorical cutoffs. For example, a score composed of both clinical and laboratory data, calibrated to detect a risk of future diabetes ≥20%, predicted 54% of future diabetes cases, labeled only 15.3% as high risk, and, compared to the FPG ≥ 100 mg/dl strategy, nearly doubled the probability of future diabetes among screen positives.

Discussion: Currently recommended screening strategies are inferior to alternatives based on continuous clinical and laboratory variables.

Keywords: mass screening; positive predictive value; prediction score; screening strategies; screening tool; sensitivity; type 2 diabetes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Blood Glucose
  • Diabetes Mellitus, Type 2* / diagnosis
  • Diabetes Mellitus, Type 2* / epidemiology
  • Diabetes Mellitus, Type 2* / etiology
  • Glucose Tolerance Test
  • Glycated Hemoglobin
  • Humans
  • Prediabetic State* / diagnosis
  • Prediabetic State* / epidemiology

Substances

  • Blood Glucose
  • Glycated Hemoglobin

Grants and funding

The study was supported by the Brazilian Ministry of Health (Department of Science and Technology); the Ministry of Science, Technology, and Innovation (FINEP, Financiadora de Estudos e Projetos), grant nos. 01 06 0010.00, 01 06 0212.00, 01 06 0300.00, 01 06 0278.00, 01 06 0115.00, and 01 06 0071.00; and the National Council for Scientific and Technological Development (CNPq). PB received a fellowship from CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior). The funders had no role in the study design; the collection, analysis, and interpretation of data; the writing of the report; or the decision to submit the article for publication.