Evaluation of C-reactive protein as a predictor of benefit from atorvastatin: Nested case control study from ASCOT

1. Peter S. Sever*, Neil R Poulter, Choon L Chang, Aroon Hingorani, Simon McG Thom, Alun D Hughes, Paul Welsh, Naveed Sattar, on behalf of the ASCOT Investigators *Imperial College London . Evaluation of C-reactive protein, prior to and on-treatment, as a predictor of benefit from atorvastatin: Nested case control study from ASCOT

2. ASCOT CRP Analysis Background • Lowering C-reactive protein (CRP) by statins has been shown to independently predict cardiovascular (CV) outcomes • The ASCOT database was used to explore the relationship between circulating CRP prior to, and on-treatment, with statins and their association with CV events

3. ASCOT Study Design 19342 hypertensive patients randomized to antihypertensive treatment ASCOT-BPLA stopped after 5.5 yrs Atenolol ± bendrofluazide Amlodipine ± perindopril 10305 patients eligible and randomized in lipid-lowering arm TC ≤ 6.5 mmol/L (250 mg/dL) ASCOT-LLA stopped after 3.3 yrs Atorvastatin 10 mg Placebo Investigator-led, multinational randomised controlled trial conducted in hypertensive patients, 40 -79 yrs, with no prior history of CHD, but with 3 additional cardiovascular risk factors (male sex, > 55 yrs, smoking etc )

4. Nested Case-control Trial Profile ASCOT – Subjects in the UK & Ireland (n = 9098) On-treatment Analysis Population (ASCOT-LLA) • LDL-C: 156 cases & 498 controls • CRP: 166 cases & 522 controls • LDL-C & CRP: 155 cases & 488 controls 14 cases & 37 controls were excluded because event occurred before blood samples were obtained. 66 cases & 252 controls did not have both baseline and on-treatment CRP & LDL-C or with missing values in covariates White European (n = 8217) 6549 subjects met entry criteria as potential cases/controls 235 cases & 777 controls participating in ASCOT-LLA Baseline CRP Analysis Population (ASCOT-BPLA) 452 cases & 1269 controls 485 cases matched with 1367 controls (ASCOT-BPLA case-control population) 490 cases & 5750 controls with valid lab data 33 cases & 98 controls with missing values in covariates No controls available for 5 cases

5. Study Subjects & Blood Samples • 485 cases (355 CHD & 130 stroke) matched with 1367 controls • Up to 3 controls from the same risk-set were matched to each case by age±1 year, sex and study entry time±90 days. • Fasting serum HDL-C, triglycerides and total cholesterol • Routinely measured at study visits • CRP at baseline and 6 months • Measured at the same time using stored serum samples • By a high sensitivity method (Dade-Behring, the lower limit of sensitivity was 0.1 mg/L)

6. Statistical Methods • t-test or Χ2 test for baseline characteristics comparison between cases and controls • Odd ratio obtained from a conditional logistic regression model for the association between CRP and the risk of CV events (CHD or stroke) • Loge CRP (baseline) as a continuous variable • Categorizing CRP into tertiles with the lowest as reference • Conditional logistic regression model • Model 1: unadjusted • Model 2 (Framingham CV risk factors + randomised treatment ) • Model 3 (extended CV risk factors): as in Model 2 plus • Body mass index (BMI) ,Loge transformed fasting glucose, Family history of coronary heart disease (FHCHD) ,Creatinine and Educational attainment

7. Baseline Characteristics Values are mean (SD) or n (%) Missing: LDL-C:121, triglycerides: 79, fasting glucose: 84, CRP: 4, creatinine: 45 *235 cases and 777 controls participated in ASCOT-LLA

8. Baseline CRP and Risk of CV Events (CHD or Stroke) Unadjusted Adjusted as for in Model 2 plus BMI, loge-glucose, family history of CHD, creatinine and educational attainment Odd ratio (95% CI) *Model 2: Adjusted for current smoking status, diabetes mellitus, randomized BP treatment (atenolol/amlodipine), randomized atorvastatin/placebo/not in LLA, left ventricular hypertrophy, baseline SBP, total cholesterol and HDL-C

9. Predictive Ability of Baseline CRP in CVD Prediction Beyond Classical Risk Factors - 1 Adjusted for age, sex, smoking status, diabetic mellitus, baseline SBP, total cholesterol, HDL-C, randomized BP treatment, randomized statin/placebo/not in LLA and LVH Full model: as for reduced model plus loge glucose, family history of CHD, educational attainment, creatinine and BMI

10. Predictive Ability of Baseline CRP in CVD Prediction Beyond Classical Risk Factors - 2 Net Reclassification Improvement (NRI) for model including CRP over model without CRP • Of 485 cases the Framingham model with CRP improved risk classification in 54 but worsened classification in 39 • In 1367 controls CRP improved classification in 116 and worsened classification in 131 • In Model 2, NRI=0.021 (p=0.32) • In Model 3, NRI=0.03 (p=0.17) Estimation of Integrated Discrimination Improvement (IDI) • When CRP was included • In Model 2, IDI increased 0.38% (P=0.015) • In Model 3, the increase in IDI was 0.49% (P=0.013) • It suggests that the addition of CRP to the model with established risk factors very modestly improved the discriminatory property of the model for risk prediction.

11. Effect of Atorvastatin on CVD events by Tertile of Baseline CRP Adjusted for current smoking status, diabetes mellitus, randomized BP treatment (atenolol/amlodipine), randomized atorvastatin/placebo/not in ASCOT-LLA. Left ventricular hypertrophy, baseline SBP, total cholesterol, HDL-C, BMI, loge-glucose, family history of CHD, creatinine and educational attainment and baseline LDL-C. * Interaction between statin treatment and tertile baseline CRP

12. Effects of Atorvastatin on LDL-C and CRP(median and interquartile range) • On-treatment change in CRP was independent of baseline classical risk factors, baseline CRP and change in LDL-C (P=0.02) • In ASCOT-LLA, in those assigned atorvastatin, age-adjusted Spearman’s correlation between percentage change in CRP and percentage change in LDL-C was modest (r=0.19 P=0.0006) 3.55 40.3% reduction 2.52 2.12 27.4% reduction 1.83

13. Baseline Profiles by 6 Month Median CRP Values are mean (SD) or n (%) Missing: fasting glucose: 24; creatinine: 12; LDL-C: 27; triglyceride: 22

14. On-treatment LDL-C (6 Month in Trial) and Risk of CV Events (CHD or Stroke) Unadjusted Adjusted for baseline LDL-C and loge baseline CRP Odd ratio (95% CI) *Model 3: Current smoking status, diabetes mellitus, randomized BP treatment (atenolol/amlodipine), left ventricular hypertrophy, baseline SBP, HDL-C, BMI, loge-glucose, family history of CHD, creatinine, educational attainment, baseline LDL-C or total cholesterol and loge baseline CRP

15. On-treatment CRP (6 Month in Trial) and Risk of CV Events (CHD or Stroke) Unadjusted Adjusted for baseline LDL-C and loge baseline CRP Odd ratio (95% CI) *Model 3: Current smoking status, diabetes mellitus, randomized BP treatment (atenolol/amlodipine), left ventricular hypertrophy, baseline SBP, HDL-C, BMI, loge-glucose, family history of CHD, creatinine, educational attainment, baseline LDL-C or total cholesterol and loge baseline CRP

16. Risk of CV Events (CHD or Stroke) by On-treatment (6 Month in Trial) LDL-C and CRP* *LDL-C in mmol/L and CRP in mg/L Odd ratio (95% CI) Adjusted for current smoking status, diabetes mellitus, randomised BP treatment (atenolol/amlodipine), , left ventricular hypertrophy, baseline SBP, total cholesterol, HDL-cholesterol, BMI, loge-glucose, family history of CHD, creatinine, educational attainment, and baseline LDL or total cholesterol and loge baseline CRP

17. Summary • Baseline LDL-C and loge transformed CRP were correlated and predicted CV events respectively • Inclusion of baseline CRP into a modified Framingham risk model in the whole cohort very modestly improved risk prediction • Baseline CRP was not an indicator of the magnitude of the effect of atorvastatin on CV outcome of those assigned atorvastatin • At 6 months, atorvastatin reduced median LDL-C by 40.3% and median CRP by 27.4% • In those randomized to atorvastatin • Lower on-treatment LDL-C at 6 months was associated with a highly significant reduction in subsequent CV events • By contrast, lower CRP at 6 months was not associated with CV events • Consequently, addition of on-treatment CRP to on-treatment LDL-C did not improve prediction of statin efficacy

18. Conclusion • In ASCOT-LLA, neither baseline nor on-treatment CRP provide useful information about the efficacy of statin treatment to reduce CV events beyond LDL-C reduction • The results do not support current proposals to measure CRP in the clinical setting either to assign statins to individuals on the basis of an elevated CRP alone, or to monitor CRP levels as an indicator of the efficacy of statin treatment