- 作者：Laura C. Rosella ; Michael Lebenbaum ; Ye Li ; Jun Wang ; Douglas G. Manuel
- 关键词：ARR ; absolute risk reduction ; CCHS ; Canadian Community Health Survey ; DPoRT ; Diabetes Population Risk Tool
- 刊名：Preventive Medicine
- 出版年：January, 2014
- 年：2014
- 卷：58
- 期：Complete
- 页码：17-21
- 全文大小：291 K
Objective
To quantify the influence of type 2 diabetes risk distribution on prevention benefit and apply a method to optimally identify population targets.Methods
We used data from the 2011 Canadian Community Health Survey (N = 45,040) and the validated Diabetes Population Risk Tool to calculate 10-year diabetes risk. We calculated the Gini coefficient as a measure of risk dispersion. Intervention benefit was estimated using absolute risk reduction (ARR), number-needed-to-treat (NNT), and number of cases prevented.
Results
There is a wide variation of diabetes risk in Canada (Gini = 0.48) and with an inverse relation to risk (r = 鈭?#xA0;0.99). Risk dispersion is lower among individuals meeting an empirically derived risk cut-off (Gini = 0.18). Targeting prevention based on a risk cut-off (10-year risk 鈮?#xA0;16.5%) resulted in a greater number of cases prevented (340 thousand), higher ARR (7.7%) and lower NNT (13) compared to targeting individuals based on risk factor targets.
Conclusions
This study provides empirical evidence to demonstrate that risk variability is an important consideration for estimating the prevention benefit. Prioritizing target populations using an empirically derived cut-off based on a multivariate risk score will result in greater benefit and efficiency compared to risk factor targets.