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Development and Validation of a Patient Self-assessment Score for Diabetes Risk
- Heejung Bang, PhD;
- Alison M. Edwards, MStat;
- Andrew S. Bomback, MD, MPH;
- Christie M. Ballantyne, MD;
- David Brillon, MD;
- Mark A. Callahan, MD;
- Steven M. Teutsch, MD, MPH;
- Alvin I. Mushlin, MD, ScM; and
- Lisa M. Kern, MD, MPH
- From Weill Medical College of Cornell University, Columbia University College of Physicians and Surgeons, and FOJP Service Corporation, New York, New York; Baylor College of Medicine, and Center for Cardiovascular Disease Prevention, Methodist DeBakey Heart Center, Houston, Texas; and Los Angeles County Department of Public Health, Los Angeles, California.
Abstract
Background: National guidelines disagree on who should be screened for undiagnosed diabetes. No existing diabetes risk score is highly generalizable or widely followed.
Objective: To develop a new diabetes screening score and compare it with other available screening instruments (Centers for Disease Control and Prevention, American Diabetes Association, and U.S. Preventive Services Task Force guidelines; 2 American Diabetes Association risk questionnaires; and the Rotterdam model).
Design: Cross-sectional data.
Setting: NHANES (National Health and Nutrition Examination Survey) 1999 to 2004 for model development and 2005 to 2006, plus a combined cohort of 2 community studies, ARIC (Atherosclerosis Risk in Communities) Study and CHS (Cardiovascular Health Study), for validation.
Participants: U.S. adults aged 20 years or older.
Measurements: A risk-scoring algorithm for undiagnosed diabetes, defined as fasting plasma glucose level of 7.0 mmol/L (126 mg/dL) or greater without known diabetes, was developed in the development data set. Logistic regression was used to determine which participant characteristics were independently associated with undiagnosed diabetes. The new algorithm and other methods were evaluated by standard diagnostic and feasibility measures.
Results: Age, sex, family history of diabetes, history of hypertension, obesity, and physical activity were associated with undiagnosed diabetes. In NHANES (ARIC/CHS), the cut-point of 5 or more points selected 35% (40%) of persons for diabetes screening and yielded a sensitivity of 79% (72%), specificity of 67% (62%), positive predictive value of 10% (10%), and positive likelihood ratio of 2.39 (1.89). In contrast, the comparison scores yielded a sensitivity of 44% to 100%, specificity of 10% to 73%, positive predictive value of 5% to 8%, and positive likelihood ratio of 1.11 to 1.98.
Limitation: Data during pregnancy were not available.
Conclusion: This easy-to-implement diabetes screening score seems to demonstrate improvements over existing methods. Studies are needed to evaluate it in diverse populations in real-world settings.
Primary Funding Source: Clinical and Translational Science Center at Weill Cornell Medical College.
Article and Author Information
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Disclaimer: The NHANES were supported by the Centers for Disease Control and Prevention. The ARIC and CHS studies were supported by the National Heart, Lung and Blood Institute. This manuscript was prepared by using public-use data sets (for NHANES) and limited-access data sets (for ARIC and CHS) and does not necessarily reflect the opinions or views of these studies or agencies.
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Acknowledgment: The authors thank the staff and participants of NHANES, ARIC, and CHS for their important contributions to research and data sharing.
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Grant Support: By the Clinical and Translational Science Center at Weill Cornell Medical College (UL1-RR024996).
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Potential Conflicts of Interest: Employment: S.M. Teutsch (Merck & Co.). Honoraria: L.M. Kern (Lifetime Healthcare). Stock ownership or options (other than mutual funds): S.M. Teutsch (Merck & Co.).
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Reproducible Research Statement: Study protocol: Not available. Statistical code: Available from Dr. Bang (e-mail, heb2013{at}med.cornell.edu). Data set: Data for NHANES are publicly available (www.cdc.gov/nchs/nhanes.htm), and data for ARIC and CHS are available through a limited-access distribution agreement (www.nhlbi.nih.gov/resources/deca/datasets_obv.htm).
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Requests for Single Reprints: Heejung Bang, PhD, Department of Public Health, Weill Cornell Medical College, 402 East 67th Street, New York, NY 10065; e-mail, heb2013{at}med.cornell.edu.
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Current Author Addresses: Drs. Bang, Mushlin, and Kern and Ms. Edwards: Department of Public Health, Weill Cornell Medical College, 402 East 67th Street, New York, NY 10065.
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Dr. Bomback: Division of Nephrology, Department of Medicine, Columbia University Medical Center, 622 West 168th Street, PH 4-124, New York, NY 10032.
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Dr. Ballantyne: Section of Atherosclerosis and Lipoprotein Research, Department of Medicine, Baylor College of Medicine, 6565 Fannin, M.S. A-60, Houston, TX 77030.
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Dr. Brillon: Department of Medicine, Weill Cornell Medical College, Baker Pavilion, 20th Floor, 525 East 68th Street, New York, NY 10065.
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Dr. Callahan: FOJP Service Corporation, 28 East 28th Street, New York, NY 10016.
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Dr. Teutsch: Los Angeles County Public Health, 313 North Figueroa Street, Room 708, Los Angeles, CA 90012.
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Author Contributions: Conception and design: H. Bang, D. Brillon, M.A. Callahan, S.M. Teutsch, A.I. Mushlin, L.M. Kern.
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Analysis and interpretation of the data: H. Bang, A.S. Bomback, D. Brillon, M.A. Callahan, S.M. Teutsch, A.I. Mushlin, L.M. Kern.
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Drafting of the article: H. Bang, A.M. Edwards, A.S. Bomback, D. Brillon, A.I. Mushlin.
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Critical revision of the article for important intellectual content: H. Bang, A.S. Bomback, C.M. Ballantyne, D. Brillon, A.I. Mushlin, L.M. Kern.
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Final approval of the article: H. Bang, A.M. Edwards, A.S. Bomback, C.M. Ballantyne, M.A. Callahan, S.M. Teutsch, A.I. Mushlin, L.M. Kern.
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Statistical expertise: H. Bang, A.M. Edwards, S.M. Teutsch.
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Obtaining of funding: H. Bang, M.A. Callahan, S.M. Teutsch, A.I. Mushlin.
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Collection and assembly of data: A.M. Edwards.
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