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Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model
BACKGROUND: Progression to diabetes mellitus (DM) is variable and the screening time interval not well defined. The American Diabetes Association and US Preventive Services Task Force suggest screening every 3 years, but evidence is limited. The objective of the study was to develop a model to predi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5685604/ https://www.ncbi.nlm.nih.gov/pubmed/29135987 http://dx.doi.org/10.1371/journal.pone.0187695 |
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author | Brateanu, Andrei Barwacz, Thomas Kou, Lei Wang, Sihe Misra-Hebert, Anita D. Hu, Bo Deshpande, Abhishek Kobaivanova, Nana Rothberg, Michael B. |
author_facet | Brateanu, Andrei Barwacz, Thomas Kou, Lei Wang, Sihe Misra-Hebert, Anita D. Hu, Bo Deshpande, Abhishek Kobaivanova, Nana Rothberg, Michael B. |
author_sort | Brateanu, Andrei |
collection | PubMed |
description | BACKGROUND: Progression to diabetes mellitus (DM) is variable and the screening time interval not well defined. The American Diabetes Association and US Preventive Services Task Force suggest screening every 3 years, but evidence is limited. The objective of the study was to develop a model to predict the probability of developing DM and suggest a risk-based screening interval. METHODS: We included non-diabetic adult patients screened for DM in the Cleveland Clinic Health System if they had at least two measurements of glycated hemoglobin (HbA1c), an initial one less than 6.5% (48 mmol/mol) in 2008, and another between January, 2009 and December, 2013. Cox proportional hazards models were created. The primary outcome was DM defined as HbA1C greater than 6.4% (46 mmol/mol). The optimal rescreening interval was chosen based on the predicted probability of developing DM. RESULTS: Of 5084 participants, 100 (4.4%) of the 2281 patients with normal HbA1c and 772 (27.5%) of the 2803 patients with prediabetes developed DM within 5 years. Factors associated with developing DM included HbA1c (HR per 0.1 units increase 1.20; 95%CI, 1.13–1.27), family history (HR 1.31; 95%CI, 1.13–1.51), smoking (HR 1.18; 95%CI, 1.03–1.35), triglycerides (HR 1.01; 95%CI, 1.00–1.03), alanine aminotransferase (HR 1.07; 95%CI, 1.03–1.11), body mass index (HR 1.06; 95%CI, 1.01–1.11), age (HR 0.95; 95%CI, 0.91–0.99) and high-density lipoproteins (HR 0.93; 95% CI, 0.90–0.95). Five percent of patients in the highest risk tertile developed DM within 8 months, while it took 35 months for 5% of the middle tertile to develop DM. Only 2.4% percent of the patients in the lowest tertile developed DM within 5 years. CONCLUSION: A risk prediction model employing commonly available data can be used to guide screening intervals. Based on equal intervals for equal risk, patients in the highest risk category could be rescreened after 8 months, while those in the intermediate and lowest risk categories could be rescreened after 3 and 5 years respectively. |
format | Online Article Text |
id | pubmed-5685604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-56856042017-11-30 Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model Brateanu, Andrei Barwacz, Thomas Kou, Lei Wang, Sihe Misra-Hebert, Anita D. Hu, Bo Deshpande, Abhishek Kobaivanova, Nana Rothberg, Michael B. PLoS One Research Article BACKGROUND: Progression to diabetes mellitus (DM) is variable and the screening time interval not well defined. The American Diabetes Association and US Preventive Services Task Force suggest screening every 3 years, but evidence is limited. The objective of the study was to develop a model to predict the probability of developing DM and suggest a risk-based screening interval. METHODS: We included non-diabetic adult patients screened for DM in the Cleveland Clinic Health System if they had at least two measurements of glycated hemoglobin (HbA1c), an initial one less than 6.5% (48 mmol/mol) in 2008, and another between January, 2009 and December, 2013. Cox proportional hazards models were created. The primary outcome was DM defined as HbA1C greater than 6.4% (46 mmol/mol). The optimal rescreening interval was chosen based on the predicted probability of developing DM. RESULTS: Of 5084 participants, 100 (4.4%) of the 2281 patients with normal HbA1c and 772 (27.5%) of the 2803 patients with prediabetes developed DM within 5 years. Factors associated with developing DM included HbA1c (HR per 0.1 units increase 1.20; 95%CI, 1.13–1.27), family history (HR 1.31; 95%CI, 1.13–1.51), smoking (HR 1.18; 95%CI, 1.03–1.35), triglycerides (HR 1.01; 95%CI, 1.00–1.03), alanine aminotransferase (HR 1.07; 95%CI, 1.03–1.11), body mass index (HR 1.06; 95%CI, 1.01–1.11), age (HR 0.95; 95%CI, 0.91–0.99) and high-density lipoproteins (HR 0.93; 95% CI, 0.90–0.95). Five percent of patients in the highest risk tertile developed DM within 8 months, while it took 35 months for 5% of the middle tertile to develop DM. Only 2.4% percent of the patients in the lowest tertile developed DM within 5 years. CONCLUSION: A risk prediction model employing commonly available data can be used to guide screening intervals. Based on equal intervals for equal risk, patients in the highest risk category could be rescreened after 8 months, while those in the intermediate and lowest risk categories could be rescreened after 3 and 5 years respectively. Public Library of Science 2017-11-14 /pmc/articles/PMC5685604/ /pubmed/29135987 http://dx.doi.org/10.1371/journal.pone.0187695 Text en © 2017 Brateanu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Brateanu, Andrei Barwacz, Thomas Kou, Lei Wang, Sihe Misra-Hebert, Anita D. Hu, Bo Deshpande, Abhishek Kobaivanova, Nana Rothberg, Michael B. Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model |
title | Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model |
title_full | Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model |
title_fullStr | Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model |
title_full_unstemmed | Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model |
title_short | Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model |
title_sort | determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5685604/ https://www.ncbi.nlm.nih.gov/pubmed/29135987 http://dx.doi.org/10.1371/journal.pone.0187695 |
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