The Table shows comparisons of c-statistics with and without CRP included in the multivariable model, from studies that have reported these data (27, 29, 31, 36, 38–40). None of these studies showed substantial improvements in risk discrimination when CRP was considered in the context of the full range of traditional risk factors for CVD. The largest improvement in c-statistic with addition of CRP to the Framingham risk score was observed in a cohort of 3435 men from southern Germany, age 45 to 74 years (40). In that study, the c-statistic increased only 1.5% when CRP was added to the Framingham risk score, from 0.735 to 0.750. In the Women's Health Study (a prospective study of 27939 healthy women, of whom only approximately 2% had CVD events over 8 years), CRP alone yielded a c-statistic of 0.64 for prediction of CVD (38). This level of c-statistic is similar to that seen for most risk factors when considered alone. When CRP was included in a multivariable model that did not include low-density lipoprotein cholesterol for predicting 8-year risk for CVD, the c-statistic of 0.81 indicated a relatively high degree of discrimination for risk estimation. However, when low-density lipoprotein cholesterol was substituted for CRP in the multivariable model, the c-statistic also was 0.81 (38). In the Rotterdam Study, involving 7983 healthy men and women, 157 participants had incident myocardial infarctions during follow-up. These 157 participants were compared with 500 randomly selected controls in a nested case–control study. When CRP was added to the Framingham risk function, using the upper 20% of the CRP distribution as the cutoff for a positive test result, sensitivity of prediction increased modestly from 31.2% to 39.5% and specificity increased from 84.4% to 87.0%. However, as shown in the Table, addition of CRP did not significantly improve the c-statistics of the Framingham risk function alone in this study (39) or most others (27, 29, 31, 36).