Statin Therapy and Risk of Incident Diabetes Mellitus in Adults With Cardiovascular Risk Factors

Journal Pre-proof

Statin Therapy and Risk of Incident Diabetes Mellitus in Adults with Cardiovascular Risk Factors Alan S. Go MD , Andrew P. Ambrosy MD , Kevin Kheder MD , Dongjie Fan MSPH , Sue Hee Sung MPH , Alda I. Inveiss MPH , Victoria Romo-LeTourneau PharmD , Sheila M. Thomas PharmD , Andrew Koren MD , Joan C. Lo MD , for the Kaiser Permanente Cholesterol-Lowering Therapy in High-Risk Adults: Management and Patient Risks (KP CHAMP) Study PII: DOI: Reference:

S0002-9149(19)31305-0 https://doi.org/10.1016/j.amjcard.2019.11.011 AJC 24301

To appear in:

The American Journal of Cardiology

Received date: Revised date: Accepted date:

24 August 2019 11 November 2019 13 November 2019

Please cite this article as: Alan S. Go MD , Andrew P. Ambrosy MD , Kevin Kheder MD , Dongjie Fan MSPH , Sue Hee Sung MPH , Alda I. Inveiss MPH , Victoria Romo-LeTourneau PharmD , Sheila M. Thomas PharmD , Andrew Koren MD , Joan C. Lo MD , for the Kaiser Permanente Cholesterol-Lowering Therapy in High-Risk Adults: Management and Patient Risks (KP CHAMP) Study, Statin Therapy and Risk of Incident Diabetes Mellitus in Adults with Cardiovascular Risk Factors, The American Journal of Cardiology (2019), doi: https://doi.org/10.1016/j.amjcard.2019.11.011

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Inc.

1

Statin Therapy and Risk of Incident Diabetes Mellitus in Adults with Cardiovascular Risk Factors Alan S. Go, MDa,b,c, Andrew P. Ambrosy, MDa,d, Kevin Kheder, MDd, Dongjie Fan, MSPHa, Sue Hee Sung, MPHa, Alda I. Inveiss, MPHa, Victoria Romo-LeTourneau, PharmDe, Sheila M. Thomas, PharmDe, Andrew Koren, MDf, and Joan C. Lo, MDa,g for the Kaiser Permanente Cholesterol-Lowering Therapy in High-Risk Adults: Management and Patient Risks (KP CHAMP) Study a

Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA; bDepartments of Epidemiology, Biostatistics and

Medicine, University of California, San Francisco, San Francisco, CA, USA; cDepartments of Medicine, Health Research and Policy, Stanford University School of Medicine, Stanford, CA, USA; dDivision of Cardiology, Kaiser Permanente San Francisco Medical Center, San Francisco, CA; eUS Health Economics and Value Assessment, Sanofi Aventis Group, Bridgewater, NJ, USA, fUS Medical Affairs, Sanofi Aventis Group, Bridgewater, NJ, USA, gKaiser Permanente Oakland Medical Center, Oakland, CA, USA

Corresponding Author: Alan S. Go, M.D. Kaiser Permanente Northern California Division of Research 2000 Broadway, Oakland, CA 94612-2304 Tel: 510-891-3422/Fax: 510-891-3508

2

Email: [email protected] ABSTRACT The association between statins and diabetes mellitus (DM) remains controversial. The Kaiser Permanente CHAMP Study identified adults without DM who had CV risk factors and no prior lipid lowering therapy (LLT) between 2008 and 2010. The CV risk factors included known atherosclerotic CV disease (ASCVD), elevated low-density lipoprotein cholesterol (LDL-C) ≥190 mg/dL, or an LDLC between 70-189 mg/dL and an estimated 10-year ASCVD risk ≥7.5%. Incident DM was defined as ≥2 abnormal tests (i.e., A1C ≥6.5% or a fasting blood glucose ≥126 mg/dL) or ≥1 abnormal test result plus a new diagnostic code or medication for DM. Among 213,289 eligible adults, 28,149 patients initiating statins were carefully matched to an equal number of patients who remained off LLT during follow-up. Compared with matched patients not receiving statins, those initiating statin therapy had the same mean age (67.9±9.4 years) and gender (42.8% women). The crude rate (per 100 person-years) of incident DM was low (0.55, 95% CI 0.52 to 0.59) but was marginally higher in patients who were treated with a statin (0.69, 95% CI 0.64 to 0.74) vs. no LLT (0.42, 95% CI 0.38 to 0.46). After additional adjustment, statin therapy was associated with a modestly increased risk of incident DM (adjusted hazard ratio [aHR] 1.17, 95% CI 1.02 to 1.34). In conclusion, among adults without DM at increased ASCVD risk, initiation of statin therapy was independently associated with a modestly higher risk of incident DM.

KEY WORDS: Statin, diabetes mellitus, pharmacoepidemiology, side effect

3

INTRODUCTION It is well-established that patients with cardiovascular (CV) risk factors are at high risk for both atherosclerotic CV disease (ASCVD) events and development of incident diabetes mellitus (DM).1-3 Statins are widely used for both primary and secondary prevention of ASCVD events based on strong randomized trial evidence for their efficacy and perceived short- and long-term safety.4,5 Based on the recently released national guidelines,6 a substantial fraction of U.S. adults are likely to be recommended to consider lifelong statin therapy. However, conflicting data exist from clinical trials and observational studies about the potentially increased risk of developing DM with statin therapy that could impact shared decision-making.7-8 Adding to the confusion, previously published observational studies have yielded mixed results7-9 but suffer from various methodological weaknesses and limitations in terms of generalizability. To address this controversy and to provide real-world data for assisting in shared decision-making for patients and providers, we examined the independent association of initiation of statin therapy and the risk of incident DM within an ethnically diverse, contemporary cohort of non-diabetic adults with CV risk factors.

METHODS The source population was based in Kaiser Permanente Northern California, a large integrated healthcare delivery system currently providing care to >4 million persons supported by a comprehensive electronic health records system. The Kaiser Permanente

4

membership is highly representative of the local and statewide population with regards to age, gender, race/ethnicity, and socioeconomic status.10 As previously described,10 the Kaiser Permanente Cholesterol-lowering Therapy in High-Risk Adults: Management and Patient Risks (KP CHAMP) study adult health plan members without DM who had CV risk factors. We included all adult health plan members ≥21 years of age who met eligibility criteria between January 1, 2008 and December 31, 2010. The date the patient met eligibility criteria was considered their index date. The following CV risk factors were identified using validated algorithms based on data extracted from electronic health records that included relevant diagnoses, procedures, laboratory tests, ambulatory vital signs, and outpatient pharmacy dispensings:11-15 known ASCVD [i.e., defined as prior acute myocardial infarction (MI), coronary revascularization, ischemic stroke or transient ischemia attack (TIA), or peripheral artery disease]; low-density lipoprotein cholesterol (LDL–C) ≥190 mg/dL; or LDL–C 70-189 mg/dL and estimated 10-year ASCVD risk ≥7.5% using the 2013 American College of Cardiology/American Heart Association Pooled Cohort ASCVD risk equation.16,17 We excluded patients who had received any prior lipid-lowering therapy (LLT) during the 4 years before their index date and those with <12 months of continuous membership and pharmacy benefit before index date. We also excluded patients who had prevalent DM based on inclusion in our regional health plan DM registry18 or who met diagnostic criteria.20 The study was approved by the Kaiser Permanente Northern California institutional review board.

5

We employed a ―new user‖ design to avoid important biases related to including prevalent users when studying outcomes associated with a therapy.19 Given this, we defined new statin exposure as an initial receipt of statin during the study period from a patient’s index date through December 31, 2013. Receipt of statin therapy was based on dispensed prescriptions found in outpatient health plan pharmacy databases. We note that results from surveys among members of Kaiser Permanente have shown that the vast majority with a drug co-pay choose to obtain chronic medications such as statins from health plan pharmacies.20 All statins were examined as a single drug class, with further classification of statin potency (i.e., high-potency = simvastatin ≥80 mg/day, atorvastatin ≥40 mg/day, or rosuvastatin ≥10 mg/day) as previously described and consistent with statins available during the study period.10 Longitudinal exposure to statin therapy was estimated from drug refill patterns using the calculated days’ supply for each prescription.12 Briefly, for any 2 consecutive prescriptions, the patient was classified as continually receiving the medication if the second prescription was filled within 14 days of the projected end date of the first prescription. In addition, if a non-fatal hospitalization occurred during follow-up, the length of stay (i.e., in days) was added to the end of the estimated day supply for any prescription crossing that hospitalization because patients were unlikely to take their own medications while still hospitalized. For each patient initiating statin therapy, we identified a carefully-matched non-user group (1:1 matching ratio) from among initially eligible patients to minimize several potential biases in this observational study. We individually matched patients who did or did not receive a new statin prescription based on age ± 2 years, difference in follow-up time of ≤30 days from treatment date through censoring date, the same number of days between statin initiation date and original index date, and having a high-dimensional

6

propensity score (hd-PS) difference for initiating statin therapy of ≤0.001. We developed the hd-PS using techniques by Schneeweiss et al.21 Briefly, the hd-PS algorithm (1) required the identification of the different data dimensions (i.e., demographics, hospitalization data, procedures, outpatient care, laboratory, and medication data) in the database, (2) identified the most prevalent variables in each data dimension as candidate covariates (3) ranked covariates across all data dimensions by their occurrence (i.e., the frequency that the codes are recorded for each individual during the baseline period) and their potential for control of confounding based on the bivariate associations of each covariate with the treatment and with the outcome, (4) selected covariates from step 3 (e.g., 200) for PS modeling, and (5) estimated the PS with multivariable logistic regression using the selected covariates. Finally, matched patients all had to have at least one screening test for diabetes (i.e., blood glucose or glycosylated hemoglobin) during follow-up to reduce ascertainment bias. Based on these criteria, we successfully matched 28,149 unique patients with newly prescribed statins with 28,149 patients who did not receive any type of lipid-lowering therapy. Follow-up occurred through December 31, 2013, and patients were censored at the time of death, disenrollment from the health plan, or end of study follow-up. Deaths were identified from health plan administrative databases (i.e., including member proxy reporting), hospitalization and billing claims databases, state death certificates, and Social Security Administration vital status files. We identified the occurrence of incident DM if a patient met any of the following criteria that were designed to enhance validity for clinically-recognized DM consistent with American Diabetes Association guidelines22 as follows: (1) two or more abnormal outpatient laboratory test results (i.e., A1C ≥6.5% or fasting blood glucose ≥126 mg/dl)23 on separate days over any period

7

of time from outpatient visits only; (2) one abnormal outpatient laboratory test result and at least one diagnostic code for DM from any inpatient or outpatient encounter; or (3) one abnormal laboratory test result and at least one DM medication prescription. The date of the incident DM diagnosis was the earliest date meeting any of the 3 criteria. We validated this approach based on a series of manual chart review efforts by a board-certified endocrinologist using random samples of statin users and non-users and found a positive predictive value >99% for incident DM as well as in assigning the proper onset date of incident DM using this approach. Age, sex, and self-reported race/ethnicity were identified from health plan databases. Residential block-level socioeconomic status was estimated from 2010 US Census data. Low education was defined as living in a census block where more than 25% of those aged 25 years or older had less than a 12th-grade education; low income was defined as living in a block where annual household income is less than $35,000 per year. We ascertained information on coexisting illnesses based on diagnoses and/or procedures using ICD-9 codes, laboratory results, and specific therapies from health plan hospitalization discharge, ambulatory visit, laboratory, and pharmacy databases, as well as the regional cancer registry. We also identified outpatient measurements of total cholesterol, LDL-C, high density lipoprotein cholesterol (HDL-C), and hemoglobin12 from health plan laboratory databases during the 36 months before study entry and throughout follow-up. We estimated glomerular filtration rate using the CKD-EPI estimating equation based on outpatient serum creatinine measurements, along with identifying receipt of chronic renal replacement therapy.

8

We conducted a matched parallel cohort analysis to examine the association between new statin initiation and subsequent incidence of DM. Characteristics of matched patients were compared using the t test or Wilcoxon rank sum test for continuous variables and chi-square tests for categorical variables as appropriate. Given the large sample size, standard differences in each variable were compared between matched groups by computing a difference in means of the 2 groups divided by the pooled standard deviation, with Cohen’s d values >0.10 considered potentially meaningful. Time-varying statin exposure analyses were employed to provide unadjusted rates of incident DM in the matched cohort. We next used multivariable extended Cox regression models to examine the association between receipt of new statin therapy vs. no LLT and risk of DM with time-updated adjustment for demographic characteristics, medical history, medication use, and selected outpatient vital signs and laboratory results. Finally, we conducted a sensitivity analysis by applying the same statistical methods to determine if there is a difference in results for low-potency statin therapy compared to no LLT. All analyses were performed using SAS software version 9.3 (SAS Institute Inc, Cary, NC).

RESULTS Among 213,289 non-diabetic adults initially identified with CV risk factors and no prior LLT, we identified 68,085 patients who initiated statin therapy during follow-up. We next matched 28,149 patients considered at increased CV risk initiating statin therapy to an equal number of patients from the source cohort who were not exposed to LLT through follow-up. Among matched

9

patients, those who did or did not initiate statin therapy were similar in terms of age, gender, race/ethnicity, smoking status, educational attainment, and household income at entry (Table 1). However, statin initiators were more likely than those who did not receive statin therapy to have a history of acute MI, unstable angina, ischemic stroke/TIA, peripheral artery disease, heart failure, and dementia, but they were less likely to have chronic liver disease. Among 28,149 incident statin users and 28,149 highly matched patients with no LLT exposure, the unadjusted annual rate of incident DM was low (0.55 per 100 person-years, 95% confidence interval [CI] 0.52-0.59) but was higher in statin initiators vs. matched patients with no LLT exposure (0.69 per 100 person-years [95% CI:0.64-0.74] vs. 0.42 per 100 person-years [95% CI:0.380.46], respectively) (Figure 1). In multivariable models with adjustment for time-updated confounders, statin therapy was associated with a modestly increased risk of incident DM compared with no LLT (adjusted hazard ratio [aHR]1.17, 95% CI 1.02-1.34). Results were similar in a sensitivity analysis comparing exposure to low-potency statin therapy (N=25,999) versus no LLT (N=25,999) (aHR 1.22, 95% CI 1.06-1.40) (Figure 2). There was not adequate statistical power to address whether the risk of incident DM differed between exposure to high-potency statin therapy and no LLT.

DISCUSSION To our knowledge, this is the largest observational analysis of statin initiation and subsequent risk of incident DM in patents with established or at increased risk for ASCVD. We studied 28,149 non-diabetic patients with a new statin prescription who were

10

carefully matched to similar patients who did not receive any LLT during follow-up. Additionally, although the unadjusted annual incidence of DM was low, it was marginally higher among patients who were initiated statin therapy compared to no LLT. Finally, after additional adjustment for potential confounders, statin therapy remained independently associated with a modestly increased risk of incident DM overall and among the subgroup of patients treated with low-potency statin therapy. The KP CHAMP cohort is unique compared to prior meta-analyses of clinical trials and observational studies for several clinically important reasons. First, approximately 25% of patients were ≥75 years of age. This is distinctly different from previously conducted clinical trials and meta-analyses.24 In fact, among older adults with CV risk factors, the net clinical benefit of statins for primary prevention is not well-established25-27 and geriatric patient populations may be more vulnerable to adverse events including muscle symptoms, functional limitations, and detrimental effects on cognition. Second, it is worth noting that more than 40% of KP CHAMP patients were women and/or minorities, groups which have also traditionally been underrepresented in clinical trials, may respond differently to statins in terms of efficacy, safety, and tolerability, and have a differential underlying risk of DM.28,29 Finally, the rate of known ASCVD was low at study entry, and >90% of study patients qualified based on a primary elevation of LDL-C or increased predicted ASCVD risk, suggesting this study provides an accurate, real-world estimate of the risk of incident DM associated with statin use for primary prevention. In addition, although all 3 subsets of patients included in the KP CHAMP study correspond to one of the statin benefit groups outlined in the 2013 and 2018 ACC/AHA cholesterol treatment guidelines16,17 for whom high-intensity statin therapy is recommended,

11

the vast majority of patients received low-intensity statin therapy. In this context, it is important to remember that this was a historical cohort of non-diabetic adults with CV risk factors who met eligibility criteria between 2008-2010 and followed through 2013, which thus predated the 2013 and 2018 ACC/AHA cholesterol treatment guidelines. The approach to cholesterol management has generally shifted from targeting specific LDL-C goals to making a global assessment of risk and treating established statin benefit groups with the appropriate intensity of LLT.16 Thus, given that approximately 45% of the KP CHAMP patients had an LDL-C <130 mg/dL, the rate of statin prescription in this study population is likely commensurate with contemporaneous guideline recommendations and expert opinion. Finally, the most clinically important finding from this study is that initiation of statin therapy was independently associated with a marginally increased risk of incident DM in non-diabetic adults with known ASCVD or risk factors for ASCVD. However, given the well-established and sizable benefits of statin therapy across the spectrum of ASCVD risk in terms of total survival and reduction in major adverse CV events,24 it is important to frame the magnitude of a relative increase of 17% associated with statin therapy in the context of an absolute crude annual incidence in patients with no LLT exposure of 0.42% (95% CI:0.38-0.46%). There were an insufficient number of patients to evaluate the relationship between high-potency statin therapy and risk of incident DM. Given that the effects of statins on cholesterol lowering, clinical outcomes, and some side effects (e.g., muscle symptoms) are known to be related to the potency of LLT, the possibility that the risk of incident DM is greater with high-intensity statin therapy cannot be

12

excluded. Regardless, these real-world data have clinical relevance and can inform patient-provider conversations regarding the riskbenefit ratio of statin therapy for primary and secondary prevention in patients with CV risk factors. We acknowledge several limitations of our study. Although patients were matched on demographic characteristics, follow-up time, time since study entry, a high-dimensional propensity score for initiating statins and all matched patients having received laboratory screening for DM, there remained a difference in the prevalence of ASCVD at baseline, which may partially explain the higher crude rate of incident DM in statin-treated patients. In addition, although this study employed a comprehensive, validated algorithm for ascertaining incident DM incorporating diagnostic codes, laboratory values, and pharmacy dispensing data—as well as all patients having had at least one screening test during follow-up—the results may still have some residual confounding from differential frequency of testing for detection of DM (i.e., providers may test for DM more frequently in statin-treated patients versus in those not receiving LLT). In conclusion, in this real-world observational study of non-diabetic patients with CV risk factors including a high proportion of older adults, women, and ethnic/racial minorities, we found that initiation of statin therapy was independently associated with a modestly higher adjusted rate of incident DM, overall and among those treated with low-potency statin therapy.

AUTHOR CONTRIBUTIONS All authors have been involved in the study design, analysis, and manuscript revision.

13

All authors read and approved the final manuscript. AS Go: Dr. Go is the guarantor, had full access to all of the data in the study, and takes responsibility for the integrity of the data and the accuracy of the analyses. Dr. Go contributed to the conception and design of the study, the data analysis, the data interpretation, the manuscript drafting, and the critical revision of the manuscript. AP Ambrosy: Dr. Ambrosy contributed to the data interpretation, the manuscript drafting, and the critical revision of the manuscript. K Kheder: Dr. Kheder contributed to the data interpretation, the manuscript drafting, and the critical revision of the manuscript. D Fan: Ms. Fan had full access to all of the data in the study, and takes responsibility for the integrity of the data and the accuracy of the analyses. Ms. Fan contributed to the conception and design of the study, the data analysis, the data interpretation, the manuscript drafting, and the critical revision of the manuscript. SH Sung: Ms. Sung contributed to the conception and design of the study, the data analysis, the data interpretation, the manuscript drafting, and the critical revision of the manuscript. V Romo-LeTourneau: Dr. Romo-LeTourneau contributed to the conception and design of the study, the data interpretation, and the critical revision of the manuscript. S Thomas: Dr. Thomas contributed to the conception and design of the study, the data interpretation, and the critical revision of the manuscript. A Koren: Dr. Koren contributed to the conception and design of the study, the data interpretation, and the critical revision of the manuscript. JC Lo: Dr. Lo contributed to the conception and design of the study, the data interpretation, and the critical revision of the manuscript.

14

Declaration of Interest We wish to draw the attention of the Editor to the following facts which may be considered as potential conflicts of interest and to significant financial contributions to this work. We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us. We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property. We understand that the Corresponding Author is the sole contact for the Editorial process (including Editorial Manager and direct communications with the office). He/she is responsible for communicating with the other authors about progress, submissions of revisions and final approval of proofs. We confirm that we have provided a current, correct email address which is accessible by the Corresponding Author. Declaration of interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: funding for Dr. Go, Ms. Fan, Ms. Sung and Dr. Lo from a research grant through their institution from Sanofi Aventis and Regeneron; Dr. Romo-LeTourneau, Dr. Thomas and Dr. Koren are employees of Sanofi Aventis. The remaining co-authors have no financial relationships with any organizations that might have an interest in the submitted work in the previous 3 years. There are no other relationships or activities that could appear to have influenced the submitted work.

15

Funding: This study was supported by a research grant from Sanofi and Regeneron Pharmaceuticals. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication beyond the description of the roles of Drs. Thomas, Koren, and Romo-LeTourneau.

Ethical Approval: The study was approved by the Kaiser Permanente Northern California institutional review board. A waiver of informed consent was obtained due to the nature of the study.

1. Dawber TR, Kannel WB. The Framingham study. An epidemiological approach to coronary heart disease. Circulation 1966;34:553-555. 2. Mozumdar A, Liguori G. Persistent increase of prevalence of metabolic syndrome among U.S. adults: NHANES III to NHANES 1999-2006. Diabetes Care 2011;34:216-219. 3. Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, Chiuve SE, Cushman M, Delling FN, Deo R, de Ferranti SD, Ferguson JF, Fornage M, Gillespie C, Isasi CR, Jimenez MC, Jordan LC, Judd SE, Lackland D, Lichtman JH, Lisabeth L, Liu S, Longenecker CT, Lutsey PL, Mackey JS, Matchar DB, Matsushita K, Mussolino ME, Nasir K, O'Flaherty M, Palaniappan LP, Pandey A, Pandey DK, Reeves MJ, Ritchey MD, Rodriguez CJ, Roth GA, Rosamond WD, Sampson UKA, Satou GM, Shah SH, Spartano NL, Tirschwell DL, Tsao CW, Voeks JH, Willey JZ, Wilkins JT, Wu JH, Alger HM, Wong SS, Muntner P, American Heart

16

Association Council on E, Prevention Statistics C, Stroke Statistics S. Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association. Circulation 2018;137:e67-e492. 4. Last AR, Ference JD, Menzel ER. Hyperlipidemia: Drugs for Cardiovascular Risk Reduction in Adults. Am Fam Physician 2017;95:78-87. 5. Jacobson TA. Statin safety: lessons from new drug applications for marketed statins. Am J Cardiol 2006;97:44C-51C. 6. Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Jr., Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2018. 7. Carter AA, Gomes T, Camacho X, Juurlink DN, Shah BR, Mamdani MM. Risk of incident diabetes among patients treated with statins: population based study. Bmj 2013;346:f2610. 8. Ma T, Tien L, Fang CL, Liou YS, Jong GP. Statins and new-onset diabetes: a retrospective longitudinal cohort study. Clinical therapeutics 2012;34:1977-1983. 9. Wang KL, Liu CJ, Chao TF, Huang CM, Wu CH, Chen SJ, Chen TJ, Lin SJ, Chiang CE. Statins, risk of diabetes, and implications on outcomes in the general population. Journal of the American College of Cardiology 2012;60:1231-1238. 10. Go AS, Fan D, Sung SH, Inveiss AI, Romo-LeTourneau V, Mallaya UG, Boklage S, Lo JC. Contemporary rates and correlates of statin use and adherence in non-diabetic adults with cardiovascular risk factors: The KP CHAMP study. Am Heart J 2017;(Epub ahead of print) DOI: http://dx.doi.org/10.1016/j.ahj.2017.08.013.

17

11. Go AS, Lee WY, Yang J, Lo JC, Gurwitz JH. Statin therapy and risks for death and hospitalization in chronic heart failure. JAMA 2006;296:2105-2111. 12. Go AS, Yang J, Ackerson LM, Lepper K, Robbins S, Massie BM, Shlipak MG. Hemoglobin level, chronic kidney disease, and the risks of death and hospitalization in adults with chronic heart failure: the Anemia in Chronic Heart Failure: Outcomes and Resource Utilization (ANCHOR) Study. Circulation 2006;113:2713-2723. 13. Go AS CG, Fan D et al. Chronic Kidney Disease and the Risks of Death, Cardiovascular Events and Hospitalization. NEJM 2004;351:12961305.

14. Solomon MD, Leong TK, Rana JS, Xu Y, Go AS. Community-Based Trends in Acute Myocardial Infarction From 2008 to 2014. J Am Coll Cardiol 2016;68:666-668. 15. Rana JS, Tabada GH, Solomon MD, Lo JC, Jaffe MG, Sung SH, Ballantyne CM, Go AS. Accuracy of the Atherosclerotic Cardiovascular Risk Equation in a Large Contemporary, Multiethnic Population. J Am Coll Cardiol 2016;67:2118-2130. 16. Stone NJ, Robinson JG, Lichtenstein AH, Bairey Merz CN, Blum CB, Eckel RH, Goldberg AC, Gordon D, Levy D, Lloyd-Jones DM, McBride P, Schwartz JS, Shero ST, Smith SC, Jr., Watson K, Wilson PW, American College of Cardiology/American Heart Association Task Force on Practice G. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2014;63:2889-2934. 17. Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, de Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R, Heidenreich PA, Hlatky MA, Jones DW, Lloyd-Jones D, Lopez-Pajares N, Ndumele CE, Orringer CE, Peralta CA, Saseen JJ, Smith SC, Jr., Sperling L, Virani SS, Yeboah J. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood

18

Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2019;73:e285-e350. 18. Karter AJ, Parker MM, Solomon MD, Lyles CR, Adams AS, Moffet HH, Reed ME. Effect of Out-of-Pocket Cost on Medication Initiation, Adherence, and Persistence among Patients with Type 2 Diabetes: The Diabetes Study of Northern California (DISTANCE). Health Serv Res 2017. 19. Ray WA. Evaluating medication effects outside of clinical trials: new-user designs. Am J Epidemiol 2003;158:915-920. 20. Karter AJ, Parker MM, Moffet HH, Ahmed AT, Schmittdiel JA, Selby JV. New prescription medication gaps: a comprehensive measure of adherence to new prescriptions. Health services research 2009;44:1640-1661. 21. Schneeweiss S, Rassen J. Re: Confounding adjustment via a semi-automated high-dimensional propensity score algorithm: an application to electronic medical records. Pharmacoepidemiol Drug Saf 2011;20:1110-1111; author reply 1112. 22. American Diabetes A. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2018. Diabetes Care 2018;41:S13-S27. 23. American Diabetes A. 2. Classification and Diagnosis of Diabetes. Diabetes Care 2017;40:S11-S24. 24. Cholesterol Treatment Trialists C, Mihaylova B, Emberson J, Blackwell L, Keech A, Simes J, Barnes EH, Voysey M, Gray A, Collins R, Baigent C. The effects of lowering LDL cholesterol with statin therapy in people at low risk of vascular disease: metaanalysis of individual data from 27 randomised trials. Lancet 2012;380:581-590. 25. Ridker PM, Danielson E, Fonseca FA, Genest J, Gotto AM, Jr., Kastelein JJ, Koenig W, Libby P, Lorenzatti AJ, MacFadyen JG, Nordestgaard BG, Shepherd J, Willerson JT, Glynn RJ, Group JS. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med 2008;359:2195-2207. 26. Ridker PM, Lonn E, Paynter NP, Glynn R, Yusuf S. Primary Prevention With Statin Therapy in the Elderly: New Meta-Analyses From the Contemporary JUPITER and HOPE-3 Randomized Trials. Circulation 2017;135:1979-1981.

19

27. Han BH, Sutin D, Williamson JD, Davis BR, Piller LB, Pervin H, Pressel SL, Blaum CS, Group ACR. Effect of Statin Treatment vs Usual Care on Primary Cardiovascular Prevention Among Older Adults: The ALLHAT-LLT Randomized Clinical Trial. JAMA internal medicine 2017;177:955-965. 28. Rosano GM, Lewis B, Agewall S, Wassmann S, Vitale C, Schmidt H, Drexel H, Patak A, Torp-Pedersen C, Kjeldsen KP, Tamargo J. Gender differences in the effect of cardiovascular drugs: a position document of the Working Group on Pharmacology and Drug Therapy of the ESC. Eur Heart J 2015;36:2677-2680. 29. Naito R, Miyauchi K, Daida H. Racial Differences in the Cholesterol-Lowering Effect of Statin. J Atheroscler Thromb 2017;24:19-25.

Figure Legends

20

Figure 1. Unadjusted rates of incident diabetes mellitus in a matched statin exposed-unexposed cohort (N=56,298).

21

Figure 2. Unadjusted rate of incident diabetes mellitus among matched low-potency statin exposed-unexposed cohort (N = 51,998). Table 1. Baseline characteristics for non-diabetic adults with cardiovascular risk factors initiating statin therapy and matched nonusers, 2008-2010.

Variable Age (years) Mean (SD) Median (IQR) Gender Women Race

Overall

Incident Statin

(N=56,298)

(N=28,149)

No Lipid-Lowering Therapy (N=28,149)

67.9 (9.4) 68.0 (61.3-74.5)

67.9 (9.4) 68.0 (61.3-74.5)

67.9 (9.4) 68.1 (61.3-74.5)

24,103 (42.8%)

12,236 (43.5%)

11,867 (42.2%)

D-Value 0.00 0.00 0.03 0.01

22

Overall Variable White/European Black/African American Asian/Pacific Islander Other Unknown Hispanic Smoking status Non-smoker Current smoker Former smoker Unknown Educational attainment >25% with <12th grade education ≤25% with <12th grade education Missing Median annual household income status < $35,000 ≥ $35,000 Missing Baseline medical history Acute myocardial infarction Unstable angina Ischemic stroke Transient ischemic attack Peripheral artery disease Heart failure Hypertension Chronic liver disease

Incident Statin

(N=56,298) 37,350 (66.3%) 4539 (8.1%) 6185 (11.0%) 3546 (6.3%) 4678 (8.3%) 5483 (9.7%)

(N=28,149) 18,922 (67.2%) 1946 (6.9%) 3158 (11.2%) 1820 (6.5%) 2303 (8.2%) 2678 (9.5%)

No Lipid-Lowering Therapy (N=28,149) 18,428 (65.5%) 2593 (9.2%) 3027 (10.8%) 1726 (6.1%) 2375 (8.4%) 2805 (10.0%)

31,190 (55.4%) 6445 (11.4%) 17,708 (31.5%) 955 (1.7%)

15,249 (54.2%) 3292 (11.7%) 9232 (32.8%) 376 (1.3%)

15,941 (56.6%) 3153 (11.2%) 8476 (30.1%) 579 (2.1%)

8712 (15.5%) 47,449 (84.3%) 137 (0.2%)

4403 (15.6%) 23,679 (84.1%) 67 (0.2%)

4309 (15.3%) 23,770 (84.4%) 70 (0.2%)

4465 (7.9%) 51,700 (91.8%) 137 (0.2%)

2253 (8.0%) 25,832 (91.8%) 67 (0.2%)

2212 (7.9%) 25,868 (91.9%) 70 (0.2%)

1716 (3.0%) 215 (0.4%) 911 (1.6%) 971 (1.7%) 817 (1.5%) 1131 (2.0%) 33,908 (60.2%) 1455 (2.6%)

1696 (6.0%) 192 (0.7%) 892 (3.2%) 837 (3.0%) 577 (2.0%) 764 (2.7%) 17,159 (61.0%) 601 (2.1%)

20 (0.1%) 23 (0.1%) 19 (0.1%) 134 (0.5%) 240 (0.9%) 367 (1.3%) 16,749 (59.5%) 854 (3.0%)

D-Value

0.02 0.06

0.01

0.00

2.73 1.29 2.35 1.13 0.54 0.45 0.04 0.22

23

Overall Variable Chronic lung disease Hyperthyroidism Hypothyroidism Dementia Systemic cancer Baseline medication use Angiotensin-converting enzyme inhibitor Angiotensin II receptor blocker β-blocker Calcium channel blocker Diuretic Aldosterone receptor antagonist Hydralazine Vasodilators Alpha blocker Nitrates Non-aspirin antiplatelet agent Anticoagulant Digoxin Antiarrhythmic Body mass index (kg/m2) < 18.5 18.5-24.9 25.0-29.9 30.0-39.9 ≥ 40.0 Unknown Systolic blood pressure (mmHg)

Incident Statin

No Lipid-Lowering Therapy (N=28,149) 5748 (20.4%) 219 (0.8%) 3323 (11.8%) 438 (1.6%) 3244 (11.5%)

(N=56,298) 11,731 (20.8%) 424 (0.8%) 6784 (12.1%) 1004 (1.8%) 6497 (11.5%)

(N=28,149) 5983 (21.3%) 205 (0.7%) 3461 (12.3%) 566 (2.0%) 3253 (11.6%)

13,533 (24.0%) 3285 (5.8%) 12,769 (22.7%) 7206 (12.8%) 18,538 (32.9%) 221 (0.4%) 366 (0.7%) 393 (0.7%) 4539 (8.1%) 183 (0.3%) 312 (0.6%) 2132 (3.8%) 574 (1.0%) 346 (0.6%)

6997 (24.9%) 1671 (5.9%) 6575 (23.4%) 3602 (12.8%) 9214 (32.7%) 104 (0.4%) 184 (0.7%) 195 (0.7%) 2181 (7.7%) 135 (0.5%) 256 (0.9%) 1219 (4.3%) 316 (1.1%) 195 (0.7%)

6536 (23.2%) 1614 (5.7%) 6194 (22.0%) 3604 (12.8%) 9324 (33.1%) 117 (0.4%) 182 (0.6%) 198 (0.7%) 2358 (8.4%) 48 (0.2%) 56 (0.2%) 913 (3.2%) 258 (0.9%) 151 (0.5%)

621 (1.1%) 14,801 (26.3%) 21,161 (37.6%) 14,188 (25.2%) 1051 (1.9%) 4476 (8.0%)

277 (1.0%) 7476 (26.6%) 11,126 (39.5%) 7162 (25.4%) 465 (1.7%) 1643 (5.8%)

344 (1.2%) 7325 (26.0%) 10,035 (35.6%) 7026 (25.0%) 586 (2.1%) 2833 (10.1%)

D-Value 0.03 0.04 0.03 0.16 0.00 0.05 0.02 0.05 0.00 0.01 0.07 0.01 0.01 0.05 0.63 0.93 0.18 0.12 0.16 0.12

0.11

24

Overall Variable < 120 120-129 130-139 140-159 160-179 ≥ 180 Unknown Diastolic blood pressure (mmHg) ≤ 80 81-84 85-89 90-99 100-109 ≥ 110 Unknown Baseline laboratory values Estimated glomerular filtration rate (ml/min/1.73m2) >150 90-150 60-89 45-59 30-44 15-29 < 15 Dialysis Transplant Unknown Total cholesterol (mg/dL)

Incident Statin

(N=56,298) 13,541 (24.1%) 12,473 (22.2%) 17,370 (30.9%) 8022 (14.2%) 1716 (3.0%) 384 (0.7%) 2792 (5.0%)

(N=28,149) 7171 (25.5%) 6316 (22.4%) 8502 (30.2%) 4069 (14.5%) 903 (3.2%) 203 (0.7%) 985 (3.5%)

No Lipid-Lowering Therapy (N=28,149) 6370 (22.6%) 6157 (21.9%) 8868 (31.5%) 3953 (14.0%) 813 (2.9%) 181 (0.6%) 1807 (6.4%)

39,261 (69.7%) 6111 (10.9%) 4739 (8.4%) 2766 (4.9%) 521 (0.9%) 108 (0.2%) 2792 (5.0%)

20,065 (71.3%) 3002 (10.7%) 2355 (8.4%) 1440 (5.1%) 248 (0.9%) 54 (0.2%) 985 (3.5%)

19,196 (68.2%) 3109 (11.0%) 2384 (8.5%) 1326 (4.7%) 273 (1.0%) 54 (0.2%) 1807 (6.4%)

1 10,853 (19.3%) 34,808 (61.8%) 6602 (11.7%) 1573 (2.8%) 211 (0.4%) 24 33 (0.1%) 18 2175 (3.9%)

0 5066 (18.0%) 16,939 (60.2%) 3719 (13.2%) 981 (3.5%) 133 (0.5%) 12 24 (0.1%) 11 1264 (4.5%)

1 5787 (20.6%) 17,869 (63.5%) 2883 (10.2%) 592 (2.1%) 78 (0.3%) 12 9 7 911 (3.2%)

D-Value

0.11

0.12

0.70

25

Overall Variable <200 200-240 > 240 Unknown High density lipoprotein cholesterol (mg/dL) <35 35-39 40-49 50-59 > 60 Unknown Low density lipoprotein cholesterol (mg/dL) < 70 70-99 100-129 130-159 160-199 > 200 Unknown Triglycerides (mg/dL) < 150 150-199 200-249 ≥ 250 Unknown Hemoglobin (g/dL) < 9.0 9.0-9.9

Incident Statin

No Lipid-Lowering Therapy (N=28,149) 13,862 (49.2%) 10,676 (37.9%) 3025 (10.7%) 586 (2.1%)

(N=56,298) 19,555 (34.7%) 21,007 (37.3%) 14,122 (25.1%) 1614 (2.9%)

(N=28,149) 5693 (20.2%) 10,331 (36.7%) 11,097 (39.4%) 1028 (3.7%)

3401 (6.0%) 5968 (10.6%) 16,189 (28.8%) 13,569 (24.1%) 15,463 (27.5%) 1708 (3.0%)

1478 (5.3%) 2879 (10.2%) 8139 (28.9%) 7116 (25.3%) 7455 (26.5%) 1082 (3.8%)

1923 (6.8%) 3089 (11.0%) 8050 (28.6%) 6453 (22.9%) 8008 (28.4%) 626 (2.2%)

435 (0.8%) 7299 (13.0%) 17,398 (30.9%) 17,094 (30.4%) 10,199 (18.1%) 2527 (4.5%) 1346 (2.4%)

181 (0.6%) 1673 (5.9%) 5360 (19.0%) 9572 (34.0%) 8281 (29.4%) 2158 (7.7%) 924 (3.3%)

254 (0.9%) 5626 (20.0%) 12,038 (42.8%) 7522 (26.7%) 1918 (6.8%) 369 (1.3%) 422 (1.5%)

34,844 (61.9%) 9646 (17.1%) 4530 (8.0%) 4031 (7.2%) 3247 (5.8%)

16,466 (58.5%) 5171 (18.4%) 2513 (8.9%) 2244 (8.0%) 1755 (6.2%)

18,378 (65.3%) 4475 (15.9%) 2017 (7.2%) 1787 (6.3%) 1492 (5.3%)

D-Value

0.02

0.71

0.10

0.01 71 (0.1%) 135 (0.2%)

34 (0.1%) 65 (0.2%)

37 (0.1%) 70 (0.2%)

26

Overall Variable 10.0-10.9 11.0-11.9 12.0-12.9 13.0-13.9 ≥14.0 Unknown

(N=56,298) 487 (0.9%) 1706 (3.0%) 5325 (9.5%) 11,771 (20.9%) 30,738 (54.6%) 6065 (10.8%)

Incident Statin (N=28,149) 231 (0.8%) 867 (3.1%) 2603 (9.2%) 5886 (20.9%) 15,371 (54.6%) 3092 (11.0%)

No Lipid-Lowering Therapy (N=28,149) 256 (0.9%) 839 (3.0%) 2722 (9.7%) 5885 (20.9%) 15,367 (54.6%) 2973 (10.6%)

D-Value