Diabetes Care
30:e89
2007
DOI: 10.2337/dc07-0814
© 2007 by the American Diabetes Association
Online Letters: Comments and Responses
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An Accurate Risk Score Based on Anthropometric, Dietary, and Lifestyle Factors to Predict the Development of Type 2 DiabetesResponse to Schulze et al.
Kuo-Liong Chien, MD, PHD
From the Institute of Preventive Medicine, College of Public Health, National Taiwan University and the Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
Address correspondence to Kuo-Liong, Institute of Preventive Medicine, College of Public Health, National Taiwan University, Taipei, 100, Taiwan. E-mail: klchien{at}ntu.edu.tw
I read with interest the article by Schulze et al. (1). In this article, they provide a novel risk score algorithm for the risk of diabetes by allocating specific points from the regression coefficients in the Cox proportional hazards model. Developing a simple, reliable, and valid risk score method for predicting incident diabetes is useful for screening and management of diabetes risk (2–5). Schulze et al. constructed the score points from the Cox model and estimated the probability (P) of diabetes during the following 5 years based on the formula:
Unfortunately, the above formula was wrong because the sample mean point of the study population was not removed from the exponential term. The above formula should be modified into the following:
The sample mean point was a constant derived from the product of the regression coefficients and the means (or proportions) of the risk factors (6).
References
- Schulze MB, Hoffmann K, Boeing H, Linseisen J, Rohrmann S, Mohlig M, Pfeiffer AF, Spranger J, Thamer C, Haring HU, Fritsche A, Joost HG: An accurate risk score based on anthropometric, dietary, and lifestyle factors to predict the development of type 2 diabetes. Diabetes Care 30:510–515, 2007[Abstract/Free Full Text]
- Aekplakorn W, Bunnag P, Woodward M, Sritara P, Cheepudomwit S, Yamwong S, Yipintsoi T, Rajatanavin R: A risk score for predicting incident diabetes in the Thai population. Diabetes Care 29:1872–1877, 2006[Abstract/Free Full Text]
- Lindstrom J, Tuomilehto J: The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care 26:725–731, 2003[Abstract/Free Full Text]
- Ramachandran A, Snehalatha C, Vijay V, Wareham NJ, Colagiuri S: Derivation and validation of diabetes risk score for urban Asian Indians. Diabetes Res Clin Pract 70:63–70, 2005[Medline]
- Schmidt MI, Duncan BB, Bang H, Pankow JS, Ballantyne CM, Golden SH, Folsom AR, Chambless LE: Identifying individuals at high risk for diabetes: the Atherosclerosis Risk in Communities Study. Diabetes Care 28:2013–2018, 2005[Abstract/Free Full Text]
- Sullivan LM, Massaro JM, D'Agostino RB Sr: Presentation of multivariate data for clinical use: the Framingham Study risk score functions. Stat Med 23:1631–1660, 2004[Medline]
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