Background: It is unknown whether statin use among people living with HIV results in a reduction in all-cause mortality. We aimed to evaluate the effect of statin use on all-cause mortality among people living with HIV. Methods: We conducted comprehensive literature searches of Medline, Embase, CINAHL, the Cochrane Library, and cross-references up to April 2018. We included randomised, quasi-randomised trials and prospective cohort studies that examined the association between statin use and cardio-protective and mortality outcomes among people living with HIV. Two reviewers independently abstracted the data. Hazard ratios (HRs) were pooled using empirical Bayesian random-effect meta-analysis. A number of sensitivity analyses were conducted. Results: We included seven studies with a total of 35,708 participants. The percentage of participants on statins across the studies ranged from 8 to 35%. Where reported, the percentage of participants with hypertension ranged from 14 to 35% and 7 to 10% had been diagnosed with diabetes mellitus. Statin use was associated with a 33% reduction in all-cause mortality (pooled HR = 0.67, 95% Credible Interval 0.39 to 0.96). The probability that statin use conferred a moderate mortality benefit (i.e. decreased risk of mortality of at least 25%, HR ≤ 0.75) was 71.5%. Down- weighting and excluding the lower quality studies resulted in a more conservative estimate of the pooled HR. Conclusion: Statin use appears to confer moderate mortality benefits in people living with HIV. Keywords: Statin, HIV, Mortality Background to hypothesise that statins are effective in reducing Although life expectancy for people living with HIV has cardiovascular events in people living with HIV. First, improved dramatically over the past two decades follow- they are effective in many groups and among high-risk ing the introduction of highly active antiretroviral people who do not have HIV [5–17]. Second, they have therapy, mortality rates remain higher than in the gen- been shown to reduce dyslipidaemia in HIV-infected eral population [1, 2]. As life expectancy has increased, people . Third, they have been shown to act the incidence of non-communicable diseases (NCDs) anti-inflammatory agent [19, 20] and improve surrogate including cardio-metabolic disorders has also dispropor- markers for cardiovascular events, such as carotid tionately increased along with risky behaviours such as intima-media thickness  and coronary artery plaque smoking, and has been identified as a major cause of ex- volume in people living with HIV . cess mortality . Dyslipidaemias are perhaps the most Although studies of statins in HIV have evaluated common and most studied cardio-metabolic disorders subclinical CVD, none has evaluated associations affecting people with HIV . There are strong reasons between statin use and hard CVD endpoints. This includes nonfatal CVD events such as MI and stroke as well as CVD mortality. Thus, the logical next step would * Correspondence: email@example.com be to evaluate statin use and hard CVD endpoints for Warwick-Centre for Applied Health Research and Delivery (WCAHRD), Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK HIV+ persons. To date, no randomised trials have been Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Uthman et al. BMC Infectious Diseases (2018) 18:258 Page 2 of 8 published on this topic. However, analyses of hard CVD through discussion and involving a third author. Two endpoints, including CVD mortality, may be underpow- authors (OU and NC) independently extracted data. ered due to insufficient data on hard CVD endpoints and/or cause-specific mortality in HIV+ cohorts and Risk of bias assessment trial registries where statin use was assessed. As a result, We used the Cochrane tool Risk Of Bias In Non-rando- this study sought to leverage the best currently available mised Studies - of Interventions (ROBINS-I) to assess data and primarily evaluate overall mortality among HIV the risk of bias of included studies (see Additional file 1: + persons taking vs. not taking statins, with the evalu- Appendix S2) . We assessed risks of bias in the ation of CVD mortality as an exploratory analysis. following seven domains, facilitated by consideration of Evidence regarding the potential benefits of a particular pertinent “signalling” questions, bias due to: confound- intervention is often available from a variety of disparate ing, selection of participants, measurement of interven- sources. When considering the benefit of an intervention tions, departures from intended interventions, missing - particularly in the absence of any RCTs addressing the data, measurement of outcomes, selection of reported relevant question - that ‘real-world’ evidence from results. Within each domain, we rated risk of bias as non-randomized studies should also be considered . “low” (comparable to a well performed randomised trial), We aimed to examine whether statin use is associated “moderate” (sound for an observational study), “high” with all-cause mortality using a systematic review and (there are important problems), or “very high” (the study meta-analysis of prospective cohort studies. is too problematic to provide useful evidence). The judge- ments within each domain were carried forward to an Methods overall risk of bias judgement across bias domains. Eligibility criteria To be included, studies had to meet the following Statistical analysis selection criteria: For the main analysis, we performed Bayesian random- effects meta-analysis  with a prior based on expected Types of studies: Randomised, quasi-randomised trials heterogeneity to pool the hazard ratio (HR) estimates for and prospective cohort studies. the association between statin use and all-cause mortal- Types of participants: adult (> 18 years) people living ity among studies . We selected random-effects with HIV (PLHIV) of either sex. meta-analysis on account of anticipated heterogeneity in Types of intervention: Any form of statin use regardless study population and methodology . Treatment of indication, including but not limited to primary or effect measures, the hazard ratio and odds ratio were log secondary prevention of cardiovascular disease. transformed to reduce skewness. We combined hazard Types of comparator: no statin or placebo ratio (HR) and odds ratio (OR) in the meta-analysis. HR Types of outcome measures: All-cause mortality. and OR can be interpreted similarly if the underlying as- sumption of a generally low event risk (< 20%) is true . Information sources and search strategy We performed a meta-regression analysis to explore We conducted a thorough literature search to identify the relationship between the following study-level factors relevant studies. We searched electronic databases of and reported treatment effects: sample size, publication Medline, CINAHL and Web of Science from 1980 to year, cohort follow-up period, percentage of statin use, April 2018 without applying any language restriction. We percentage male, mean age and study location (Europe searched for abstracts of relevant conference proceedings vs. North America). Given the low number of studies from the National Library of Medicine Gateway. In identified in the study univariate meta-regressions were addition, the bibliographies of retrieved articles were estimated as opposed to multivariate. All models were examined for pertinent studies. The full Medline search estimated using STAN and R . strategy is shown in Additional file 1:Appendix S1. Sensitivity analyses Study selection and data extraction A number of sensitivity analyses were conducted to Two authors (OU and NC) evaluated the eligibility of examine the robustness of the results to study quality and studies obtained from the literature search using a modelling assumptions. First, we assigned ‘quality weights’ predefined protocol and worked independently to scan to the studies on the basis of the risk of bias assessment all abstracts and obtain the full texts of each selected . The quality weights can be interpreted as the propor- article. For each included study, details on design, tion of variance of a studies results not attributable to bias. population characteristics, intervention and outcome Two sets of weights were used: (i) studies at high risk of measures were extracted, and risk of bias was evaluated. bias were assigned a weight of 20% and studies at a Any discrepancies between the authors were resolved moderate/low risk were assigned a weight of 70%; (ii) the Uthman et al. BMC Infectious Diseases (2018) 18:258 Page 3 of 8 respective weights for high risk and low/moderate risk articles. After review of abstracts and titles, 11 articles were 50 and 80%. Second, we re-estimated the model were selected for critical reading. Four studies did not excluding studies deemed as being at high risk of bias (a meet the inclusion criteria [32–35] as no relevant quality weight of zero). Third, we examined the sensitivity outcomes were reported. Seven studies with a total of of the results to the choice of prior distribution. We used 35,708 participants were included [36–42]. The charac- an informative ‘sceptical’ prior distribution based on the teristics of the included studies are shown in Table 1. principle that ‘Most clinically important interventions are The studies were conducted between 1995 and 2015 and likely to reduce the relative risk of all-cause mortality by published between 2011 and 2015. Five were reported as about 10-20%.’ The sceptical prior specifies that there was full-text journal articles [38–42], and two were presented only a 5% probability that the HR was less than 0.75 . as conference abstracts [36, 37]. All the studies were This systematic review was reported according to the from high-income countries; four from the USA. The Preferred Reporting Items for Systematic Reviews and other studies were conducted in Denmark, France and Meta-analyses (PRISMA) guidelines (Additional file 1: Spain. The median number of participants was 1738 and Appendix S3). ranged from 438 to 25,884. All the seven studies were cohort studies [36–42]. The mean age at entry of the Results participants ranged from 39 to 51 years and the propor- Study selection and characteristics tions of males included in the studies ranged from 67% The process of study selection is shown in Fig. 1. Over- to as much as 98% (from US Veterans Affairs’ Clincial all, the literature searches of databases yielded 615 Case Registry). The percentage of participants on statins Fig. 1 PRISMA Flow for study selection Uthman et al. BMC Infectious Diseases (2018) 18:258 Page 4 of 8 Table 1 Summary Characteristics of the included studies Study Study Study Country Setting/ Indication CVD risk Male Age Sample Statin Multivariate analysis (adjusted) period design population (%) (mean/median) size therapy Moore et al., 1998 to Cohort USA Johns Hopkins Primary Antihypertensive use: 67.2 43 (36–49) 1538 Atorvastatin. CD4, HIV-1 RNA, haemoglobin and cholesterol  2011 2009 HIV Clinical prevention 29.3%, total cholesterol: Pravastatin, levels at the start of HAART, age, race, HIV risk Cohort 166 (141–194) mg/dL rosuvastatin group, prior use of ART, year of HAART start, [15.5%] NNRTI vs. PI-based ART, prior AIDS-defining illness, and viral hepatitis coinfection Drechsler 1995 to Cohort USA Veteran Affairs’ Primary Smokers: 50% 98 46.8 (40.6–52.9) 25,884 Atorvastatin, Age, gender, race, HCV-co-infection, et al.,  2009 Clinical Case prevention rosuvastatin hypertension, smoking, BMI, CD4 strata, 2013 Registry [35%] LDL-strata Knobel 2002– Cohort Spain HIV clinic in Primary Framingham score 72.2 42.09 (9.29) 733 Not reported Baseline CD4 cell count, baseline viral load, et al.,  2013 Barcelona prevention > 20%: 8.5%, ever [21%] undetectable viral load at follow-up, Framingham 2013 smokers: 67% risk score, age, HIV transmission group, chronic liver disease, and smoking status Overton 2000– Cohort USA Adult AIDS Clinical Primary Framingham score 83 39 (33–46) 3601 Not reported Age, sex, race/ethnicity, intravenous drug history, et al.,  2013 Trials Group prevention > 10%: 10%, current [13%] history of coronary artery disease (CAD), hepatitis 2013 Longitudinal smokers: 38% B coinfection, systolic BP, eGFR, glucose, current Linked use of lipid-lowering drugs other than statins, Randomized HIV-1 RNA, CD4 count, current smoking, and Trials (ALLRT) waist-to-hip ratio. Rasmussen 1998– Cohort Denmark Danish HIV Cohort Primary Total cholesterol > 73.1 39.3 (33.0–46.3) 1738 Not reported Age intervals (time-updated), gender, race, et al.,  2009 Study (DHCS) prevention 5 mmol/L: 28.3% [10%] HIV-transmission group, hepatitis C status, 2015 calendar year of HAART initiation, AIDS defining illnesses prior to HAART, ART use before initiating HAART, CD4 cell count, viral load and cholesterol at HAART initiation. Krask et al., 2000– Cohort USA Nutrition For Primary Framingham score: 68 44.3 (7.7) 438 Not reported Race, HBV, HCV, LDL, CD4 cell count, age,  2015 2015 Healthy Living prevention 6.5, hypertensive: 35%, [15%] smoking, statin duration (NFHL) diabetic: 7%, smokers: 47%, metabolic syndrome: 23% Lang et al., 2000– Cohort France French Hospital Primary Current smokers: 88.9 50.5 (10) 1776 Not reported Stepwise multivariable model using age, gender,  2015 2009 Database on HIV prevention 42.1%, hypertensive [8%] HIV transmission group, current CD4 and CD8 T (FHDH-ANRS CO4) 13.7%, diabetics: 10.1% cell counts, CD4 T cell nadir, CD4/CD8 T cell ratio, CD4 T cell nadir/CD8 T cell ratio, plasma HIV-1 RNA level, AIDS status, the haemoglobin level, body mass index (BMI), smoking status, hypertension or use of antihypertensive treatment, diabetes or use of antidiabetic treatment, anti-HCV antibodies and HBs antigen status, non-AIDS malignancy (CIM-10 definition), liver failure, chronic kidney disease, cirrhosis, and pulmonary embolism. *Conference abstracts Uthman et al. BMC Infectious Diseases (2018) 18:258 Page 5 of 8 across the studies ranged from 8 to 35%. None of the Effects of statins on all-cause mortality study reported statin type. When reported, the percent- The Bayesian random-effects meta-analysis yielded a age of participants with hypertension ranged from 14 to pooled HR of 0.67 (95% CrI 0.39 to 0.96) in the risk of 35% and 7 to 10% had been diagnosed with diabetes all-cause mortality; a 33% reduction in absolute risk mellitus. None of the studies reported rates of adherence (Fig. 2). However, 95% prediction interval for the pooled to statins use. HR contains values greater than 1 (0.21 to 1.76), which suggests that although on average statins seem to be effective in reducing all-cause mortality, not all future Quality assessment of included studies individual studies can be expected to show all-cause A summary of the risk of bias assessment in the mortality benefits of statins. included studies is shown in Additional file 1: Table S1. Table 2 and Additional file 1: Table S2 reports the The risk of bias due to confounding was moderate all estimated pooled HRs from the sensitivity analyses. the seven studies. The bias in selection of participants Down-weighting the lower quality studies resulted in a was moderate in four studies [36, 38, 41, 42] and serious more conservative estimate of the pooled HR. The in three studies [37, 39, 40] For Knobel and colleagues pooled HRs from the two weighting schemes were 0.82 study , the Framingham cardiovascular risk score (0.49, 1.35) and 0.76 (0.50, 1.13). Excluding low quality above 20% was significantly higher among those on also resulted in a more conservative estimate of the statin compared with those not on statins (21.4% versus pooled HR. The ‘sceptical’ prior resulted in a posterior 5.0%, RR = 2.95, 95% CI 2.22 to 3.92) and those on statin mean estimate of the pooled HR of 0.88 (0.69, 1.14). had significantly higher median total cholesterol (231 In a series of meta-regression analyses, none of the versus 178 mg/dL). Similarly, for Lang et al. , the study level factors were associated with treatment effect proportion of participants with hypertension (29.7% estimates (Table 3). versus 12.4%) and type 2 diabetes mellitus (21.7% versus Only two studies [37, 40] reported cardiovascular 9.1%) was significantly higher among those exposed to disease mortality as an outcome. The pooled HR from statins compared with those not on statins at baseline. these two studies was 1.23 (0.52, 2.61). Only two studies For Moore and colleagues study , the proportion of [36, 41] reported cardiovascular disease event rates as participants on antihypertensive medications was signifi- on outcome. The pooled HR was 0.69 (0.37, 1.62). cantly higher among those on statin compared with those not on statins (46.3% versus 25.6%). The bias in Discussion measurement of interventions due to departures from Main findings intended interventions and due to missing data were To our knowledge, this systematic review and meta-ana- moderate all the seven studies. The bias in measurement lysis, comprising seven observational studies with more of outcomes was low in all studies, because the outcome than 35,000 HIV-infected participants, is the first to of study was death ascertained via adequate record examine the effect of statin therapy on all-cause linkages [36–42]. The bias in selection of reported mortality in people living with HIV. Overall, the findings studies was rated serious in the two studies published as support the expectation that statins confer mortality conference abstracts [36, 37] and moderate in the benefit. However, due to the limited evidence currently remaining five studies. Overall risk of bias was moderate available, we can draw no conclusions as to effectiveness in three studies and serious in four studies. of statins on cardiovascular disease mortality and Fig. 2 Forest plot of association between statins use and all-cause mortality Uthman et al. BMC Infectious Diseases (2018) 18:258 Page 6 of 8 Table 2 Estimated pooled HRs from the sensitivity analyses Posterior mean (95% CrI) Number of studies I Probability HR < 1 Main analysis 0.67 (0.39, 0.96) 7 63% 97% Down-weight low quality studies (20%/70%) 0.82 (0.49, 1.35) 7 49% 80% Down-weight low quality studies (50%/80%) 0.76 (0.50, 1.13) 7 43% 92% Exclude low quality studies 0.81(0.49, 1.37) 4 45% 81% ‘Sceptical’ prior 0.88 (0.69, 1.14) 7 62% 85% cardiovascular events. Nevertheless, the results of our cardiovascular disease . It has now been documented meta-analysis usefully extend previously published in the literature that PLHIV are at increased risk of meta-analyses of statin use in other high-risk groups developing CVD than non-HIV patients [43–45]. In such as the recent pivotal collaborative meta-analysis of addition, there is disparities in the quality of CVD care individual participants’ data by the Cholesterol Treat- between PLHIV and uninfected adults . Ladapo and ment Trialists’ (CTT)  based on 174, 000 individuals, colleagues found that “Physicians generally underused that reported reductions of approximately 10% in guideline-recommended cardiovascular care and were all-cause mortality for both women (risk ratio, 0.91; 99% less likely to prescribe aspirin and statins to HIV-infected CI 0.84–0.99) and men (risk ratio, 0.90, 99% 0.86–0.95). patients at increased risk-findings that may partially However, there has been conflicting literature about the explain higher rates of adverse cardiovascular events association of statin use with all-cause mortality in other among patients with HIV”.Implementation of population [11, 13]. Ray and colleagues conducted a intensive lifestyle modification in PLHIV may help reduce meta-analysis of 11 RCTs involving 65,2229 participants CVD mortality and morbidity . The frequency and to examine the effect of statin use on all-cause mortality consistency of clinical encounters with PLHIV may among intermediate to high-risk individuals without a provide a unique opportunity to provide them with con- history of CVD . They found that the use of statins tinuous assistance to help behaviour changes to prevent in this high-risk primary prevention setting was not CVD risk . Given the crucial need for prevention of associated with a statistically significant reduction (risk cardiovascular disease in PLHIV, there is a need for a ratio, 0.91; 95% confidence interval, 0.83–1.01) in the multi-morbidity trials to definitively assess the efficacy of risk of all-cause mortality . Taylor and colleagues statins as a primary prevention strategy for cardiovascular conducted Cochrane review to assess the effects, both disease in this at-risk population [47, 48], especially in harms and benefits, of statins in in adults with no resource-limited settings that bear the highest burden of restrictions on total, low density lipoprotein (LDL) or HIV. Furthermore, low income settings are now experien- high-density lipoprotein (HDL) cholesterol levels, and cing an epidemiological transition from infectious diseases where 10% or less had a history of CVD . They to chronic diseases,  as a result of dramatic changes in included 18 RCTs involving 56,934 participants and found diet and lifestyle. The epidemiological transition in LMICs that all-cause mortality was reduced by statins (odds ratio is happening over a shorter time frame than that experi- 0.86, 95% confidence interval, 0.79 to 0.94) . enced historically by high-income countries . PLHIV are now living longer than because of effective treatment with antiretroviral therapy . However, the Study limitations and strengths increased life expectancy is now associated with in- Strengths of this study include the comprehensive creased prevalence of chronic conditions such as searches of databases to ensure that all relevant, published studies were identified. We used a Bayesian approach that Table 3 Study level factors associated with treatment effect allows us to utilize informative prior information. The estimates, meta-regression analyses main limitation of our study is that the nature of the Factor Ratio of Hazard Ratio literature is entirely observational. Statistical adjustment (95% Credible Interval) cannot exclude existing confounding, such as confounding Sample size (per 1000 people) 1.02 (0.97 to 1.06) by indication or variations in other patient or clinician Publication year 1.20 (0.85 to 1.71) level variability that might be independently associated Cohort follow-up period 1.16 (0.93 to 1.38) with the outcome. Counter-intuitively, there is some evidence that statin may increase risk of CVD mortality, Statin use (%) 1.01 (0.95 to 1.06) but perhaps not surprising because it likely reflects some Male (%) 1.02 (0.98 to 1.05) confounding by therapy indication - people prescribed Age (mean, years) 1.08 (0.98 to 1.18) statins may be more likely to have pre-existing CVD or be Europe vs. North America studies 0.94 (0.31 to 2.27) at greater risk for CVD, and this risk is unlikely to be fully Uthman et al. BMC Infectious Diseases (2018) 18:258 Page 7 of 8 accounted for through multivariable adjustment. Thus, Availability of data and materials All data generated or analysed during this study are included in this factors leading to these people being prescribed statins published article and its additional file. may be responsible for their apparently elevated CVD- related mortality rather than their actual use of statins. Authors’ contributions Statins are a large constellation with different results OAU led protocol design, study design, the literature review, data extraction, statistical analysis, data interpretation, article preparation, article review, and depending upon the type and dose of statin therapy. As correspondence. CN, SIW, RL contributed to protocol design, study design, the these data were not reported, it was not possible to literature review, data extraction, statistical analysis, data interpretation, article conduct sensitivity analyses to stratify by different types preparation, article review, and correspondence. EJM, APK, SSJ, AC, TM, AME contributed to data interpretation, article preparation, article review, and and doses of statins. In addition, the pooled association correspondence. All authors have read and approved the final manuscript. should be interpreted with caution because it is derived from observational studies. Our study found high I values Ethics approval and consent to participate as measures of heterogeneity. However, it is worth noting Not applicable. that the I measurement offers inflated estimates when Competing interests dealing with non-comparative studies. Meta-regression The authors declare that they have no competing interests. analyses are prone to ecological fallacy (aggregate bias) and may have low power to detect an association [51–53]. Publisher’sNote We did not conduct tests for publication bias because we Springer Nature remains neutral with regard to jurisdictional claims in included observational studies and we are aware that published maps and institutional affiliations. many patients outside these studies receive statin Author details treatment, so there is, by definition, publication bias. Warwick-Centre for Applied Health Research and Delivery (WCAHRD), Finally, the fact that most included studies were Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK. observational may explain a larger treatment effect Division of Health Sciences, Warwick Medical School, University of Warwick, 3 4 Coventry, UK. McMaster University, Hamilton, Canada. Non-Communicable observed in our analysis than that observed among Diseases Research Unit, South African Medical Research Council, Cape Town, RCTs in non-HIV patients . South Africa. Department of Medicine, University of Cape Town, Cape Town, South Africa. Liverpool School of Tropical Medicine, Dept of International Public Health, Liverpool, UK. Institute of Environmental Medicine, Division of Epidemiology, Karolinska Institutet Stockholm, Stockholm, Sweden. Conclusions Department of Public Health (IHCAR), Karolinska Institutet, Stockholm, In summary, based on pooled data on 35,708 HIV-infected 9 Sweden. Department of Infectious Diseases, Karolinska University Hospital, participants from seven observational studies, we observed Stockholm, Sweden. that statin therapy may have an important mortality benefit Received: 3 October 2017 Accepted: 23 May 2018 in people living with HIV, accounting for an estimated 33% reduction in all-cause mortality. While awaiting a definitive answer from on-going trials and long-term observational References 1. Global, regional, and national life expectancy, all-cause mortality, and cause- studies about the benefits of statin as a primary prevention specific mortality for 249 causes of death, 1980–2015: a systematic analysis for cardiovascular disease and all-cause mortality, our for the Global Burden of Disease Study 2015. Lancet (London, England). findings are timely and reassuring. They reinforce the 2016;388(10053):1459–544. 2. Wandeler G, Johnson LF, Egger M. Trends in life expectancy of HIV-positive notion that lowering lipid levels is likely to be associated adults on antiretroviral therapy across the globe: comparisons with general with a reduction in all-cause mortality in people living with population. Curr Opin HIV AIDS. 2016;11(5):492–500. HIVas itisinother high-riskgroups. 3. Hooshyar D, Hanson DL, Wolfe M, Selik RM, Buskin SE, McNaghten AD. Trends in perimortal conditions and mortality rates among HIV-infected patients. AIDS (London, England). 2007;21(15):2093–100. 4. Nduka C, Sarki A, Uthman O, Stranges S. Impact of antiretroviral therapy on Additional file serum lipoprotein levels and dyslipidemias: a systematic review and meta-analysis. Int J Cardiol. 2015;199:307–18. 5. Baigent C, Keech A, Kearney PM, Blackwell L, Buck G, Pollicino C, Kirby A, Additional file 1: Appendix S1. Medline Search Strategy. Appendix Sourjina T, Peto R, Collins R, et al. Efficacy and safety of cholesterol-lowering S2. Risk bias assessment. Appendix S3. PRISMA checklist. Table S1. Risk- treatment: prospective meta-analysis of data from 90,056 participants in 14 of-bias assessment of included studies. Table S2. Estimated pooled HRs randomised trials of statins. Lancet (London, England). 2005;366(9493):1267–78. from the sensitivity analyses. (DOCX 41 kb) 6. de Vries FM, Denig P, Pouwels KB, Postma MJ, Hak E. Primary prevention of major cardiovascular and cerebrovascular events with statins in diabetic patients: a meta-analysis. Drugs. 2012;72(18):2365–73. Acknowledgements 7. Fulcher J, O'Connell R, Voysey M, Emberson J, Blackwell L, Mihaylova B, Samuel Watson, Aileen Clarke and Richard Lilford are supported by the NIHR Simes J, Collins R, Kirby A, Colhoun H, et al. Efficacy and safety of LDL- CLAHRC West Midlands initiative. Olalekan Uthman, Samuel Watson, and lowering therapy among men and women: meta-analysis of individual data Richard Lilford are supported by the National Institute for Health Research from 174,000 participants in 27 randomised trials. Lancet (London, England). using Official Development Assistance (ODA) funding. The views expressed 2015;385(9976):1397–405. in this publication are those of the author(s) and not necessarily those of the 8. Jia M, Huang W, Li L, Xu Z, Wu L. Statins reduce mortality after non-severe NHS, the National Institute for Health Research or the Department of but not after severe pneumonia: a systematic review and meta-analysis. Health and Social Care. J Pharm Pharm Sci. 2015;18(3):286–302. Uthman et al. BMC Infectious Diseases (2018) 18:258 Page 8 of 8 9. Jung JM, Choi JY, Kim HJ, Seo WK. Statin use in spontaneous intracerebral 31. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for hemorrhage: a systematic review and meta-analysis. Int J Stroke. systematic reviews and meta-analyses: the PRISMA statement. Ann Intern 2015;10(Suppl A100):10–7. Med. 2009;151(4):264–9. w264 10. Minder CM, Blumenthal RS, Blaha MJ. Statins for primary prevention of 32. Elsamadisi P, Cha A, Kim E, Latif S. Statin Use With the ATP III Guidelines cardiovascular disease: the benefits outweigh the risks. Curr Opin Cardiol. Compared to the 2013 ACC/AHA Guidelines in HIV Primary Care Patients. 2013;28(5):554–60. J Pharm Pract. 2017;30(1):64–69. 33. Eckard AR, Meissner EG, Singh I, McComsey GA. Cardiovascular Disease, 11. Ray KK, Seshasai SR, Erqou S, Sever P, Jukema JW, Ford I, Sattar N. Statins Statins, and HIV. J Infect Dis. 2016;214(Suppl 2):S83–92. and all-cause mortality in high-risk primary prevention: a meta-analysis of 11 34. Ou HT, Chang KC, Li CY, Yang CY, Ko NY. Intensive statin regimens for randomized controlled trials involving 65,229 participants. Arch Intern Med. reducing risk of cardiovascular diseases among human immunodeficiency 2010;170(12):1024–31. virus-infected population: A nation-wide longitudinal cohort study 2000- 12. Tapia Perez JH, Yildiz OC, Schneider T, Nimsky C. Meta-analysis of statin use 2011. Int J Cardiol. 2017;230:592–98. for the acute therapy of spontaneous intracerebral hemorrhage. J Stroke 35. Lichtenstein KA, Hart RL, Wood KC, Bozzette S, Buchacz K, Brooks JT, Cerebrovasc Dis. 2015;24(11):2521–6. Investigators HIVOS. Statin use is associated with incident diabetes mellitus 13. Taylor F, Huffman MD, Macedo AF, Moore TH, Burke M, Davey Smith G, among patients in the HIV outpatient study. J Acquir Immune Defic Syndr. Ward K, Ebrahim S. Statins for the primary prevention of cardiovascular 2015;69(3):306–11. disease. Cochrane Database Syst Rev. 2013;1:Cd004816. 36. Drechsler H, Zhang S, Maalouf N, Cutrell J, Tebas P, Bedimo R: Impact of 14. Taylor F, Huffman MD, Macedo AF, Moore THM, Burke M, Davey Smith G, statin exposure on mortality and non-AIDS complications in HIV patients on Ward K, Ebrahim S. Statins for the primary prevention of cardiovascular HAART. Abstract 765. In: 20th conference on retroviruses and opportunistic disease. Cochrane Database Syst Rev. 2013;(1):CD004816. https://doi.org/10. infections march 3–6, 2013. Atlanta: Conference on Retroviruses and 1002/14651858.CD004816.pub5. Opportunistic Infections (CROI); 2013. 15. Teng M, Lin L, Zhao YJ, Khoo AL, Davis BR, Yong QW, Yeo TC, Lim BP. 37. Knobel H, Fratchez V, Montero M, Villar J, Lerma E, Gonzalez E, Molas E, Sorli Statins for primary prevention of cardiovascular disease in elderly patients: L, Guerri R, Guelar A: The use of statins was associated with reduced systematic review and meta-analysis. Drugs Aging. 2015;32(8):649–61. mortality in HIV-infected patients. Abstract PE12/7. In: 14th European AIDS 16. Vrecer M, Turk S, Drinovec J, Mrhar A. Use of statins in primary and Conference October 16–19. Brussels; 2013. secondary prevention of coronary heart disease and ischemic stroke. Meta- 38. Krsak M, Kent DM, Terrin N, Holcroft C, Skinner SC, Wanke C. Myocardial analysis of randomized trials. Int J Clin Pharmacol Ther. 2003;41(12):567–77. infarction, stroke, and mortality in cART-treated HIV patients on statins. AIDS 17. Yang M, Xie XS, Yuan WJ. A meta-analysis of the effects of statin treatment Patient Care STDs. 2015;29(6):307–13. on cardiovascular events and all-cause mortality in diabetic dialysis patients. 39. Lang S, Lacombe JM, Mary-Krause M, Partisani M, Bidegain F, Cotte L, Int J Clin Exp Med. 2015;8(6):8415–24. Aslangul E, Cheret A, Boccara F, Meynard JL, et al. Is impact of statin therapy 18. Feinstein MJ, Achenbach CJ, Stone NJ, Lloyd-Jones DM. A systematic review on all-cause mortality different in HIV-infected individuals compared to of the usefulness of statin therapy in HIV-infected patients. Am J Cardiol. general population? Results from the FHDH-ANRS CO4 cohort. PLoS One. 2015;115(12):1760–6. 2015;10(7):e0133358. 19. Feinstein MJ, Bahiru E, Achenbach C, Longenecker CT, Hsue P, So-Armah 40. Moore RD, Bartlett JG, Gallant JE. Association between use of HMG CoA K, Freiberg MS, Lloyd-Jones DM. Patterns of cardiovascular mortality for reductase inhibitors and mortality in HIV-infected patients. PLoS One. HIV-infected adults in the United States: 1999 to 2013. Am J Cardiol. 2011;6(7):e21843. 2016;117(2):214–20. 41. Overton ET, Kitch D, Benson CA, Hunt PW, Stein JH, Smurzynski M, Ribaudo HJ, 20. Schoenfeld SR, Lu L, Rai SK, Seeger JD, Zhang Y, Choi HK. Statin use and Tebas P. Effect of statin therapy in reducing the risk of serious non-AIDS- mortality in rheumatoid arthritis: a general population-based cohort study. defining events and nonaccidental death. Clin Infect Dis. 2013;56(10):1471–9. Ann Rheum Dis. 2016;75(7):1315–20. 42. Rasmussen LD, Kronborg G, Larsen CS, Pedersen C, Gerstoft J, Obel N. Statin 21. Calza L, Manfredi R, Colangeli V, Trapani FF, Salvadori C, Magistrelli E, Danese I, therapy and mortality in HIV-infected individuals; a Danish nationwide Verucchi G, Serra C, Viale P. Two-year treatment with rosuvastatin reduces population-based cohort study. PLoS One. 2013;8(3):e52828. carotid intima-media thickness in HIV type 1-infected patients receiving highly 43. Bouvier G. Lifestyle modification and cardiovascular disease in HIV. HIV Clin. active antiretroviral therapy with asymptomatic atherosclerosis and moderate 2012;24(4):1. 5-6 cardiovascular risk. AIDS Res Hum Retrovir. 2013;29(3):547–56. 44. Triant VA. Cardiovascular disease and HIV infection. Curr HIV/AIDS Rep. 22. Lo J, Lu MT, Ihenachor EJ, Wei J, Looby SE, Fitch KV, Oh J, Zimmerman CO, 2013;10(3):199–206. Hwang J, Abbara S, et al. Effects of statin therapy on coronary artery plaque 45. Triant VA, Lee H, Hadigan C, Grinspoon SK. Increased acute myocardial volume and high-risk plaque morphology in HIV-infected patients with infarction rates and cardiovascular risk factors among patients with human subclinical atherosclerosis: a randomised, double-blind, placebo-controlled immunodeficiency virus disease. J Clin Endocrinol Metab. 2007;92(7):2506–12. trial. Lancet HIV. 2015;2(2):e52–63. 46. Ladapo JA, Richards AK, DeWitt CM, Harawa NT, Shoptaw S, Cunningham 23. Nallamothu BK, Hayward RA, Bates ER. Beyond the randomized clinical trial: WE, Mafi JN. Disparities in the quality of cardiovascular care between HIV- the role of effectiveness studies in evaluating cardiovascular therapies. infected versus HIV-uninfected adults in the United States: a cross-sectional Circulation. 2008;118(12):1294–303. study. J Am Heart Assoc. 2017;6(11):e007107. 24. Sterne JA, Hernan MA, Reeves BC, Savovic J, Berkman ND, Viswanathan M, 47. Gilbert JM, Fitch KV, Grinspoon SK. HIV-related cardiovascular disease, statins, Henry D, Altman DG, Ansari MT, Boutron I, et al. ROBINS-I: a tool for and the REPRIEVE Trial. Topics in antiviral medicine. 2015;23(4):146–9. assessing risk of bias in non-randomised studies of interventions. 48. Mitka M. Exploring statins to decrease HIV-related heart disease risk. Jama. BMJ (Clinical Res Ed). 2016;355:i4919. 2015;314(7):657–9. 25. Sutton AJ, Abrams KR. Bayesian methods in meta-analysis and evidence 49. Gaziano TA, Bitton A, Anand S, Abrahams-Gessel S, Murphy A. Growing synthesis. Stat Methods Med Res. 2001;10(4):277–303. epidemic of coronary heart disease in low- and middle-income countries. 26. Turner RM, Davey J, Clarke MJ, Thompson SG, Higgins JP. Predicting the Curr Probl Cardiol. 2010;35(2):72–115. extent of heterogeneity in meta-analysis, using empirical data from the 50. Miranda JJ, Kinra S, Casas JP, Davey Smith G, Ebrahim S. Non-communicable Cochrane database of systematic reviews. Int J Epidemiol. 2012;41(3):818–27. diseases in low- and middle-income countries: context, determinants and 27. Symons MJ, Moore DT. Hazard rate ratio and prospective epidemiological health policy. Tropical Med Int Health. 2008;13(10):1225–34. studies. J Clin Epidemiol. 2002;55(9):893–9. 51. Schmid CH, Stark PC, Berlin JA, Landais P, Lau J. Meta-regression detected 28. Stan Development Team: Stan Modeling Language User’s Guide and Reference associations between heterogeneous treatment effects and study-level, but Manual, Version 2.10.0. URL http://mc-stan.org/ [Accessed 10 Oct 2016]; 2015. not patient-level, factors. J Clin Epidemiol. 2004;57(7):683–97. 29. Thompson S, Ekelund U, Jebb S, Lindroos AK, Mander A, Sharp S, Turner R, 52. Mills EJ, Jansen JP, Kanters S. Heterogeneity in meta-analysis of FDG-PET Wilks D. A proposed method of bias adjustment for meta-analyses of studies to diagnose lung cancer. Jama. 2015;313(4):419. published observational studies. Int J Epidemiol. 2011;40(3):765–77. 53. Thompson SG, Higgins JP. How should meta-regression analyses be 30. Higgins JP, Spiegelhalter DJ. Being sceptical about meta-analyses: a undertaken and interpreted? Stat Med. 2002;21(11):1559–73. Bayesian perspective on magnesium trials in myocardial infarction. Int J Epidemiol. 2002;31(1):96–104.
BMC Infectious Diseases – Springer Journals
Published: Jun 5, 2018
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