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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...

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Autores principales: Brateanu, Andrei, Barwacz, Thomas, Kou, Lei, Wang, Sihe, Misra-Hebert, Anita D., Hu, Bo, Deshpande, Abhishek, Kobaivanova, Nana, Rothberg, Michael B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
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.
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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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