Studies have associated statin use with increased risk of diabetes and diabetic complications. These studies often ensure comparability of statin users and non-users at baseline; however, most studies neglect to consider confounders that occur during follow-up. Failure to consider these confounders, such as new medications or procedures, may result in identification of a spurious association between statins and outcomes. The objective of this study was to examine the association of statins with diabetes mellitus and diabetic complications; and to examine potential confounders during the follow-up period that might affect this relationship. We conducted a retrospective cohort study using Tricare data (from October 1, 2003 to March 31, 2012). We propensity score-matched statin users and non-users on 115 baseline characteristics before starting statins; these characteristics would be potentially associated with the use of statins or the outcomes of interest. Outcomes included the risk of diabetes mellitus and diabetic complications. Out of 60,455 patients (10,910 statin users and 49,545 non-users), we propensity score-matched 6728 statin users to 6728 non-users. Statin users had higher ORs for diabetes (OR 1.34, 95% CI 1.24 to 1.44) and diabetes with complications (OR 1.28, 95% CI 1.16 to 1.42). Adjustment for potential confounders that occurred during the follow-up period did not explain or diminish the association between statins and adverse outcomes. Statin users in comparison to similar non-users were more commonly diagnosed with diabetes and diabetic complications, even after adjustment for potential confounders that occurred during the follow-up period.
Get full access to this article
View all access options for this article.
References
1.
NakataM, NagasakaS, KusakaI, . Effects of statins on the adipocyte maturation and expression of glucose transporter 4 (SLC2A4): implications in glycaemic control. Diabetologia2006;49:1881–92. doi:10.1007/s00125-006-0269-5
2.
SattarN, PreissD, MurrayHM, . Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet2010;375:735–42. doi:10.1016/S0140-6736(09)61965-6
3.
PreissD, SeshasaiSR, WelshP, . Risk of incident diabetes with intensive-dose compared with moderate-dose statin therapy: a meta-analysis. JAMA2011;305:2556–64. doi:10.1001/jama.2011.860
4.
SwerdlowDI, PreissD, KuchenbaeckerKB, . HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials. Lancet2015;385:351–61. doi:10.1016/S0140-6736(14)61183-1
5.
ChenCW, ChenTC, HuangKY, . Differential impact of statin on new-onset diabetes in different age groups: a population-based case-control study in women from an Asian country. PLoS ONE2013;8:e71817. doi:10.1371/journal.pone.0071817
6.
CurrieO, ManginD, WillimanJ, . The comparative risk of new-onset diabetes after prescription of drugs for cardiovascular risk prevention in primary care: a national cohort study. BMJ Open2013;3:e003475. doi:10.1136/bmjopen-2013-003475
7.
MansiI, FreiCR, WangCP, . Statins and new-onset diabetes mellitus and diabetic complications: a retrospective cohort study of US healthy adults. J Gen Intern Med2015;30:1599–610. doi:10.1007/s11606-015-3335-1
8.
LiewSM, LeePY, HanafiNS, . Statins use is associated with poorer glycaemic control in a cohort of hypertensive patients with diabetes and without diabetes. Diabetol Metab Syndr2014;6:53. doi:10.1186/1758-5996-6-53
9.
SukhijaR, PrayagaS, MarashdehM, . Effect of statins on fasting plasma glucose in diabetic and nondiabetic patients. J Investig Med2009;57:495–9. doi:10.231/JIM.0b013e318197ec8b
10.
MansiIA, EnglishJ, ZhangS, . Long-term outcomes of short-term statin use in healthy adults: a retrospective cohort study. Drug Saf2016;39:543–59. doi:10.1007/s40264-016-0412-2
11.
NielsenSF, NordestgaardBG. Statin use before diabetes diagnosis and risk of microvascular disease: a nationwide nested matched study. Lancet Diabetes Endocrinol2014;2:894–900. doi:10.1016/S2213-8587(14)70173-1
12.
SenK, MisraA, KumarA, . Simvastatin retards progression of retinopathy in diabetic patients with hypercholesterolemia. Diabetes Res Clin Pract2002;56:1–11. doi:10.1016/S0168-8227(01)00341-2
13.
AguirreL, HijonaE, MacarullaMT, . Several statins increase body and liver fat accumulation in a model of metabolic syndrome. J Physiol Pharmacol2013;64:281–8.
14.
LeeDS, MarkwardtS, GoeresL, . Statins and physical activity in older men: the osteoporotic fractures in men study. JAMA Intern Med2014;174:1263–70. doi:10.1001/jamainternmed.2014.2266
15.
SugiyamaT, TsugawaY, TsengCH, . Different time trends of caloric and fat intake between statin users and nonusers among US adults: gluttony in the time of statins?JAMA Intern Med2014;174:1038–45. doi:10.1001/jamainternmed.2014.1927
16.
MakiKC, RidkerPM, BrownWV, . An assessment by the Statin Diabetes Safety Task Force: 2014 update. J Clin Lipidol2014;8:S17–29. doi:10.1016/j.jacl.2014.02.012
17.
MansiI, MortensenE. The controversy of a wider statin utilization: why?Expert Opin Drug Saf2013;12:327–37. doi:10.1517/14740338.2013.779667
18.
MansiI. Statin adverse events in primary prevention: between randomized trials and observational studies. Am J Med Sci2015;350:330–7. doi:10.1097/MAJ.0000000000000527
19.
ShenL, ShahBR, ReyesEM, . Role of diuretics, beta blockers, and statins in increasing the risk of diabetes in patients with impaired glucose tolerance: reanalysis of data from the NAVIGATOR study. BMJ2013;347:f6745. doi:10.1136/bmj.f6745
20.
EaglesCJ, KendallMJ. The effects of combined treatment with beta 1-selective receptor antagonists and lipid-lowering drugs on fat metabolism and measures of fatigue during moderate intensity exercise: a placebo-controlled study in healthy subjects. Br J Clin Pharmacol1997;43:291–300. doi:10.1111/j.1365-2125.1997.00554.x
LuhrmanS, LehrE, HefflinC, . Interface Control Document describing the case management exchange from BEA to MDR and M2 Baseline. DHSS Program Management. Falls Church, VA: DHSS, Report number: ICD-1300-6220-01; 18 August 2008.
23.
EnewoldL, BrintonLA, McGlynnKA, . Oral contraceptive use among women in the military and the general U.S. population. J Womens Health (Larchmt)2010;19:839–45. doi:10.1089/jwh.2009.1706
24.
GanttCJ, NeelyJA, VillafanaIA, . Analysis of weight and associated health consequences of the active duty staff at a major Naval medical center. Mil Med2008;173:434–40. doi:10.7205/MILMED.173.5.434
25.
GeorgeSZ, ChildsJD, TeyhenDS, . Brief psychosocial education, not core stabilization, reduced incidence of low back pain: results from the Prevention of Low Back Pain in the Military (POLM) cluster randomized trial. BMC Med2011;9:128. doi:10.1186/1741-7015-9-128
26.
SuissaS. Immortal time bias in pharmaco-epidemiology. Am J Epidemiol2008;167:492–9. doi:10.1093/aje/kwm324
27.
DanaeiG, RodriguezLA, CanteroOF, . Observational data for comparative effectiveness research: an emulation of randomised trials of statins and primary prevention of coronary heart disease. Stat Methods Med Res2013;22:70–96. doi:10.1177/0962280211403603
28.
JeeSH, SullJW, ParkJ, . Body-mass index and mortality in Korean men and women. N Engl J Med2006;355:779–87. doi:10.1056/NEJMoa054017
29.
AllisonDB, FaithMS, HeoM, . Meta-analysis of the effect of excluding early deaths on the estimated relationship between body mass index and mortality. Obes Res1999;7:342–54. doi:10.1002/j.1550-8528.1999.tb00417.x
30.
ElixhauserA, SteinerC, PalmerL. Clinical Classifications Software (CCS) for ICD-9-CM. Databases and Related Tools from the Healthcare Cost and Utilization Project (HCUP). Agency for Healthcare Research and Quality, 2012. Appendix A.
31.
CowenME, DusseauDJ, TothBG, . Casemix adjustment of managed care claims data using the clinical classification for health policy research method. Med Care1998;36:1108–13. doi:10.1097/00005650-199807000-00016
32.
DuffyS, ElixhauserA, SommersJ. Diagnosis and procedure combinations in hospital inpatient data. Healthcare Cost and Utilization Project (HCUP 3) Research Note 5. Rockville, MD: Agency for Health Care Policy and Research, 1996. AHCPR Pub. No. 96-0047.
33.
ElixhauserA, McCarthyE. Clinical classifications for health policy research, version 2: hospital inpatient statistics. Healthcare Cost and Utilization Project (HCUP 3) Research Note 1. Rockville, MD: Agency for Health Care Policy and Research, 1996. AHCPR Pub. No. 96 0017.
34.
ElixhauserA, SteinerC, WhittingtonC. Clinical classifications for health policy research: Hospital inpatient statistics, 1995. Healthcare Cost and Utilization Project, HCUP 3 Research Note. Rockville, MD: Agency for Health Care Policy and Research, 1998. AHCPR Pub. No. 98-0049.
35.
ElixhauserA, SteinerC. Healthcare Cost and Utilization Project (HCUP) Research Note. Rockville, MD: Agency for Health Care Policy and Research, 1999. AHCPR Pub. No. 99-0034.
36.
WashingtonR, AndrewsR, MutterR. Emergency department visits for adults with diabetes, 2010. HCUP Statistical Brief #167.Rockville, MD: Agency for Healthcare Research and Quality, 2013. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb167.pdf (accessed 16 Mar 2015).
37.
WierL, WittE, BurgessJ, . Hospitalizations related to diabetes in pregnancy, 2008. HCUP Statistical Brief #102.Rockville, MD: Agency for Healthcare Research and Quality, 2010. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb102.pdf (accessed 16 Mar 2015).
FrazeT, JiangH, BurgessJ. Hospital stays for patients with diabetes, 2008. HCUP Statistical Brief #93. Rockville, MD: Agency for Healthcare Research and Quality, 2010. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb93.pdf (accessed 16 Mar 2015).
CookCB, TsuiC, ZiemerDC, . Common reasons for hospitalization among adult patients with diabetes. Endocr Pract2006;12:363–70. doi:10.4158/EP.12.4.363
42.
FogertyMD, AbumradNN, NanneyL, . Risk factors for pressure ulcers in acute care hospitals. Wound Repair Regen2008;16:11–18. doi:10.1111/j.1524-475X.2007.00327.x
43.
DeyoRA, CherkinDC, CiolMA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol1992;45:613–19. doi:10.1016/0895-4356(92)90133-8
44.
ElixhauserA, SteinerC, HarrisDR, . Comorbidity measures for use with administrative data. Med Care1998;36:8–27. doi:10.1097/00005650-199801000-00004
45.
LiB, EvansD, FarisP, . Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases. BMC Health Serv Res2008;8:12. doi:10.1186/1472-6963-8-12
46.
MillerDR, SaffordMM, PogachLM. Who has diabetes? Best estimates of diabetes prevalence in the Department of Veterans Affairs based on computerized patient data. Diabetes Care2004;27(Suppl 2):B10–21.
47.
QuanH, LiB, SaundersLD, . Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database. Health Serv Res2008;43:1424–41. doi:10.1111/j.1475-6773.2007.00822.x
48.
HoD, ImaiK, KingG, . Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Polit Anal2007;15:199–236. doi:10.1093/pan/mpl013
49.
HoD, ImaiK, KingG, . MatchIt: nonparametric preprocessing for parametric causal inference. J Stat Software2011;42:1–28.
50.
HansenBB. Full matching in an observational study of coaching for the SAT. J Am Stat Assoc2004;99:609–18. doi:10.1198/016214504000000647
51.
HansenBB, BowersJ. Covariate balance in simple, stratified and clustered comparative studies. Stat Sci2008;23:219–36. doi:10.1214/08-STS254
52.
ThoemmesF. An SPSS R menu for propensity score matching. 2011. http://www.arxiv.org (accessed 21 May 2015).
53.
FDA Drug Safety Communication: new restrictions, contraindications, and dose limitations for Zocor (simvastatin) to reduce the risk of muscle injury. U.S. Food and Drug Administration; U.S. Department of Health and Human Services, 2011. http://www.fda.gov/Drugs/DrugSafety/ucm256581.htm (accessed 16 Mar 2015).
54.
StoneNJ, RobinsonJG, LichtensteinAH, . 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. Circulation2014;129:S1–45. doi:10.1161/01.cir.0000437738.63853.7a
MitchellP, MaretteA. Statin-induced insulin resistance through inflammasome activation: sailing between Scylla and Charybdis. Diabetes2014;63:3569–71. doi:10.2337/db14-1059
57.
KilpatrickES, RigbyAS, AtkinSL. Insulin resistance, the metabolic syndrome, and complication risk in type 1 diabetes: “double diabetes” in the Diabetes Control and Complications Trial. Diabetes Care2007;30:707–12. doi:10.2337/dc06-1982
58.
BuseMG. Hexosamines, insulin resistance, and the complications of diabetes: current status. Am J Physiol Endocrinol Metab2006;290:E1–8. doi:10.1152/ajpendo.00329.2005
59.
MenkeA, CasagrandeS, GeissL, . Prevalence of and trends in diabetes among adults in the United States, 1988–2012. JAMA2015;314:1021–9. doi:10.1001/jama.2015.10029
60.
FraylingTM. Statins and type 2 diabetes: genetic studies on target. Lancet2015;385:310–12.
61.
GordonB, ChangS, KavanaghM, . The effects of lipid lowering on diabetic retinopathy. Am J Ophthalmol1991;112:385–91. doi:10.1016/S0002-9394(14)76244-0
62.
National Diabetes Statistics Report: estimates of diabetes and its burden in the United States, 2014. Atlanta, GA: US Department of Health and Human Services; Centers for Disease Control and Prevention, 2014. http://www.cdc.gov/diabetes/pubs/statsreport14.htm (accessed 16 Mar 2015).
