Literature DB >> 26385210

Impact of statin therapy on coronary plaque composition: a systematic review and meta-analysis of virtual histology intravascular ultrasound studies.

Maciej Banach1, Corina Serban2, Amirhossein Sahebkar3,4, Dimitri P Mikhailidis5, Sorin Ursoniu6, Kausik K Ray7, Jacek Rysz8, Peter P Toth9,10, Paul Muntner11, Svetlana Mosteoru12, Hector M García-García13,14, G Kees Hovingh15, John J P Kastelein16, Patrick W Serruys17,18.   

Abstract

BACKGROUND: Virtual histology intravascular ultrasound (VH-IVUS) imaging is an innovative tool for the morphological evaluation of coronary atherosclerosis. Evidence for the effects of statin therapy on VH-IVUS parameters have been inconclusive. Consequently, we performed a systematic review and meta-analysis to investigate the impact of statin therapy on plaque volume and its composition using VH-IVUS.
METHODS: The search included PubMed, Cochrane Library, Scopus and Embase (through 30 November 2014) to identify prospective studies investigating the effects of statin therapy on plaque volume and its composition using VH-IVUS.
RESULTS: We identified nine studies with 16 statin treatment arms and 830 participants. There was a significant effect of statin therapy in reducing plaque volume (standardized mean difference (SMD): -0.137, 95 % confidence interval (CI): -0.255, -0.019; P = 0.023), external elastic membrane volume (SMD: -0.097, 95 % CI: -0.183, -0.011; P = 0.027) but not lumen volume (SMD: -0.025, 95 % CI: -0.110, +0.061; P = 0.574). There was a significant reduction in fibrous plaque volume (SMD: -0.129, 95 % CI: -0.255, -0.003; P = 0.045) and an increase of dense calcium volume (SMD: +0.229, 95 % CI: +0.008, +0.450; P = 0.043), while changes in fibro-fatty (SMD: -0.247, 95 % CI: -0.592, +0.098; P = 0.16) and necrotic core (SMD: +0.011, 95 % CI: -0.144, +0.165; P = 0.892) tissue volumes were not statistically significant.
CONCLUSIONS: This meta-analysis indicates a significant effect of statin therapy on plaque and external elastic membrane volumes and fibrous and dense calcium volumes. There was no effect on lumen volume, fibro-fatty and necrotic tissue volumes.

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Year:  2015        PMID: 26385210      PMCID: PMC4575433          DOI: 10.1186/s12916-015-0459-4

Source DB:  PubMed          Journal:  BMC Med        ISSN: 1741-7015            Impact factor:   8.775


Background

Despite continuously improving therapies used for acute coronary syndromes (ACS), cardiovascular disease (CVD) and its complications remain the leading causes of mortality and morbidity [1]. The most important mechanism leading to ACS is the rupture of a vulnerable plaque and subsequent thrombus formation [2-4]. The lesion most frequently prone to rupture is represented by the thin-cap fibroatheroma (TCFA), which contains a large necrotic core with an overlying thin fibrous cap [5]. The recently introduced technique of virtual histology intravascular ultrasound (VH-IVUS) utilizes spectral analysis of the radiofrequency ultrasound backscatter signals, which allows in vivo differentiation of four distinct atherosclerotic plaque phenotypes: fibrous; fibro-fatty; dense calcium; and necrotic core [6]. In vivo studies of coronary [7] and carotid plaques [8] have demonstrated the accuracy of VH-IVUS for histological characterization of atherosclerotic plaques. The Providing Regional Observations to Study Predictors of Events in the Coronary Tree (PROSPECT), the VH-IVUS in Vulnerable Atherosclerosis (VIVA) and the European Collaborative Project on Inflammation and Vascular Wall Remodeling in Atherosclerosis (ATHEROREMO-IVUS) substudy are three important prospective studies that have demonstrated that the presence of VH-IVUS-derived TCFA lesions is strongly and independently predictive for the occurrence of major adverse cardiovascular events (MACE) [9-11]. Extensive research has focused on preventing CVD events, including therapies that may stabilize atherosclerotic plaques [12]. There is a well-established association between therapy with high doses of statins and regression of coronary atherosclerosis [13]. Also, there have been studies that have investigated the efficiency of statin therapy on coronary plaque composition evaluated with the VH-IVUS method [14, 15]. However, these studies were conducted in relatively small study cohorts and are not conclusive. It is not established whether and to what extent statins have an effect on coronary plaque composition. The purpose of this meta-analysis was therefore to investigate the impact of statin therapy on coronary plaque composition.

Methods

Data sources

This study was designed according to the guidelines of the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [16]. Our search included Scopus, Medline, Web of Science and Cochrane Library databases. It was limited to prospective studies carried out up to 30 November 2014, investigating the potential effects of statin therapy on plaque volume and its composition. The databases were searched using the following search terms in titles and abstracts (also in combination with Medical Subject Headings (MeSH) terms): ‘virtual histology intravascular ultrasound’ OR ‘virtual histology IVUS’ OR ‘VH IVUS’ OR ‘VH-IVUS’ AND ‘statins’ (all fields) OR ‘statin’ (all fields) OR ‘statin therapy’ (all fields) OR ‘rosuvastatin’ OR ‘pravastatin’ OR ‘fluvastatin’ OR ‘simvastatin’ OR ‘atorvastatin’ OR ‘pitavastatin’ OR ‘lovastatin’ OR ‘cerivastatin’ AND ‘virtual histology intravascular ultrasound’ (all fields) OR ‘virtual histology IVUS’ (all fields) OR ‘VH IVUS’ (all fields) OR ‘VH-IVUS’ (all fields). The wild-card term ‘*’ was used to increase the sensitivity of the search strategy. No language restriction was used in the literature search. The search was limited to studies in humans. References of all obtained articles were additionally explored for supplemental publications. Two reviewers (CS and AS) examined every article separately to minimize the possibility of duplication, investigating reviews, case studies and experimental studies. Disagreements were managed by discussion with a third party (MB).

Study selection

Inclusion criteria

Original studies were included if they met the following inclusion criteria: a) being a prospective clinical study; b) investigating the impact of statin therapy on plaque volume and/or its composition using VH-IVUS (in comparison to placebo group or high-intensity versus moderate/low-intensity statin therapy); c) presentation of sufficient information on VH-IVUS findings at baseline and at the end of study; and d) statin therapy for at least 2 weeks.

Exclusion criteria

Exclusion criteria were: a) non-clinical studies (experimental and basic studies); b) observational or retrospective studies; c) duplicate reports or secondary or post hoc analyses of the same study population; and d) lack of sufficient information on baseline or follow-up VH-IVUS data. Exclusion of an article for this reason was also done if no feedback was received after contacting the author(s).

Data extraction

Eligible studies were reviewed and the following data were abstracted: 1) first author’s name; 2) year of publication; 3) study location; 4) number of participants; 5) age, gender and body mass index (BMI) of study participants; 6) baseline levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), high-sensitivity C-reactive protein (hs-CRP) and glucose; 7) systolic (SBP) and diastolic blood pressure (DBP); 8) statin type, statin dose and duration of treatment (both in research and control groups); and 9) data regarding baseline and follow-up VH-IVUS findings including plaque volume (PV), lumen volume (LV), external elastic membrane volume (EEMV), as well as atheroma compositional data (comprising volumes of fibrous, fibro-fatty, dense calcium and necrotic core tissues).

Quality assessment and quantitative data synthesis

The quality of included studies was assessed using the Cochrane scale. Meta-analysis was conducted using Review Manager, version 5.2 (Cochrane Collaboration, Oxford, UK), and Comprehensive Meta-Analysis (CMA) V2 software (Biostat, NJ, USA) [17]. Standard deviations (SD) of the mean difference were calculated using the following formula: SD = square root ((SDpre-treatment)2 + (SDpost-treatment)2 − (2R × SDpre-treatment × SDpost-treatment)), assuming a correlation coefficient (R) = 0.5. In case of reporting SEM, SD was estimated using the following formula: SD = SEM × sqrt (n), where n is the number of subjects. In case levels were reported as the median and interquartile range, the mean and SD were estimated using the recommendations of Hozo et al. [18]. Net changes in measurements (change scores) were calculated for parallel and crossover trials, as follows: measure at end of follow-up − measure at baseline. A random-effects model (using DerSimonian–Laird method) and the generic inverse variance method were used to compensate for the heterogeneity of studies in terms of statin type, statin dose, study design, treatment duration and the characteristics of populations being studied [19]. Effect sizes were expressed as weighed standardized mean difference (SMD) and 95 % confidence intervals (CI). In order to evaluate the influence of each study on the overall effect size, sensitivity analysis was conducted using the one-study remove (leave-one-out) approach.

Meta-regression

Meta-regression was performed using a random-effects model (using unrestricted maximum likelihood method) to evaluate the association between calculated SMD in plaque volume with duration of statin therapy and changes in LDL-C concentrations.

Publication bias

Potential publication bias was explored using visual inspection of Begg’s funnel plot asymmetry, and Begg’s rank correlation and Egger’s weighted regression tests. The Duval and Tweedie ‘trim and fill’ and ‘fail-safe N’ methods were used to adjust the analysis for the effects of publication bias [20].

Results

Search results and trial flow

A total of nine eligible studies comprising 16 treatment arms met the inclusion criteria and were included for the final meta-analysis [14, 21–28]. An overview of the study selection process is presented in Fig. 1.
Fig. 1

Flow diagram for study selection. VH-IVUS, virtual histology intravascular ultrasound

Flow diagram for study selection. VH-IVUS, virtual histology intravascular ultrasound

Characteristics of included studies

Among 830 participants in the included studies, 737 were allocated to statin intervention groups (with different statin preparations and different doses) and 93 to placebo group. The number of participants in these studies ranged from 20 to 228. The studies were published between 2009 and 2014, and were conducted in USA (two studies), South Korea (two studies), China, Hong Kong and Japan (three studies). The following statin doses were administered in the included trials: 10 to 80 mg/day atorvastatin; 10 to 40 mg/day pravastatin; 20 mg/day simvastatin; 10 to 40 mg/day rosuvastatin; 60 mg/day fluvastatin; and 2 to 4 mg/day pitavastatin. One study did not mention statin preparation or dosage [24]. Duration of statin intervention ranged from 6 to 24 months. Only two studies were placebo-controlled, the other seven included only statin intervention groups. Demographic and baseline parameters of the included studies are shown in Table 1.
Table 1

Demographic characteristics of the included studies

StudyEshtehardi et al. [21]Guo et al. [22]Hong et al. [23]Hwang et al. [24]Lee et al. [14]Nasu et al. [25]Nozue et al. [26]Puri et al. [27]Taguchi et al. [28]
Year201220122009201320122009201220142013
LocationUSAChinaKoreaKoreaHong KongJapanJapanUSAJapan
DesignPilot study on consecutive patients treated with atorvastatinRandomized placebo-controlled parallel group trialRandomized parallel group trialProspective study on patients treated with statinProspective randomized double-blind parallel group trialProspective and multicenter study with non-randomized and no blinded designProspective, open-labeled, randomized, multicenter studyRandomized parallel-group trialProspective, non-randomized, non-controlled and open-label trial
Duration of study6 months6 months12 months6 months6 months12 months8 months24 months8–10 months
Inclusion criteriaPatients with an abnormal non-invasive stress test, stable angina or stabilized acute coronary syndrome who were found to have moderate lesions requiring invasive physiologic evaluationCoronary heart disease patients with stable atherosclerotic plaquesPatients with de novo non-culprit/non-target lesions without significant stenosis by coronary angiogram (diameter stenosis <50 %), lesions with a plaque burden <0.75 by gray-scale IVUS, and lesions located in 1 of 3 major epicardial arteries in which stent implantation was not performedPatients with acute coronary syndromeStatin-naive patients free from unstable angina >8 weeks before intervention or acute coronary syndrome and with angiographic critical coronary stenosis requiring percutaneous coronary interventionPatients older than 30 years of age with symptomatic stable angina pectoris. Angiographic inclusion criteria: 1) target vessel for VH-IVUS interrogation must not have undergone angioplasty or have more than 50 % luminal narrowing throughout a target segment with a minimum length of 30 mm; 2) target vessel for VH-IVUS interrogation had mild-to-moderate vessel tortuosity and calcification for safe and accurate examination; and 3) left ventricular ejection fraction >30 %Patients with stable and unstable angina after successful percutaneous coronary interventionPatients with angiographically demonstrable coronary disease and LDL-C <116 mg/dL, following a 2-week treatment period with atorvastatin (40 mg) or rosuvastatin (20 mg) dailyPatients with acute coronary syndrome defined as unstable angina of Braunwald class IIIB (angina at rest without increased levels of the creatine kinase-MB fraction within 24 hours before coronary angiography), non-ST-segment elevation myocardial infarction, or ST-segment elevation myocardial infarction
Statin formAtorvastatinAtorvastatinSimvastatin or rosuvastatinNSAtorvastatinFluvastatinPitavastatin or pravastatinRosuvastatin or atorvastatinAtorvastatin or pitavastatin
Statin intervention80 mg/day10–80 mg/day20 mg/day or 10 mg/dayNS10–40 mg/day60 mg/day4 mg/day or 20 mg/day40 mg/day or 80 mg/day10 mg/day or 2 mg/day
ParticipantsIntervention2047a 50e 5419a 4058g 36i 60a
45b
43c 50f 20c 61h 35d 60j
39d
Control-54---39--
Age (years)Intervention54 (46–68)62.64 ± 12.0a 58 ± 10e 59 ± 1065.05 ± 9.99a 63 ± 1066 ± 9g 57.6 ± 9.0**65.8 ± 16.2#
59.18 ± 8.48b
58.91 ± 12.90c 59 ± 9f 63.70 ± 9.80c 67 ± 11h 63.7 ± 16.5##
58.95 ± 9.68d
Control-62.07 ± 8.51---62 ± 12---
Male (%)Intervention65.088.88a 80.0e 70.3773.68a 80.089.65g 80.3**76.6#
85.10b
80.0c 74.0f 90.0c 77.05h 69.2##
95.35d
Control-87.18---77.5---
BMI (kg/m2)Intervention30 (27–36)NSa NSe NS26.83 ± 6.85a NS24.4 ± 3.5g 28.6 ± 4.5**24.0 ± 2.5#
NSb
NSc NSf 26.58 ± 5.44c 24.5 ± 3.3h 24.2 ± 2.7##
NSd
Control-NS---NS---
hs-CRP (mg/L)InterventionNS6.04 ± 2.52a 0.17 ± 0.22e 3.18 ± 5.29NSa 2.05 ± 2.203.76 (1.22–9.22)g 1.4 (0.7–2.7)**NS#
5.09 ± 1.94b
5.67 ± 2.22c 0.21 ± 0.20f NSc 4.23 (1.21–9.26)h NS##
6.10 ± 2.12d
Control-5.07 ± 1.80---1.19 ± 1.03---
Total cholesterol (mg/dL)Intervention186.0 (168.0–212.5)NSa 191 ± 34e 195.0 ± 35.9200.58 ± 41.54a 239.1 ± 32.8199 ± 34g 203.1 ± 38**NS#
NSb
NSc 189 ± 27f 184.17 ± 29.27c 210 ± 38h NS##
NSd
Control-NS---199.5 ± 22.8---
LDL-C (mg/dL)Intervention118.5 (105.3–140.5)116.96 ± 27.02a 119 ± 30e 119.7 ± 31.4122.39 ± 39.54a 144.9 ± 31.5126 ± 28g 128.6 ± 30.7**117.3 ± 34.7#
112.71 ± 23.93b
111.94 ± 13.12c 116 ± 28f 112.35 ± 27.14c 137 ± 35h 116.2 ± 26.7##
109.24 ± 25.48d
Control-113.48 ± 27.79---122.3 ± 18.9---
HDL-C (mg/dL)Intervention39.5 (33.3–52.8)34.74 ± 6.56a 43 ± 10e 38.9 ± 8.541.47 ± 9.46a 52.7 ± 12.446 ± 11g 44.7 ± 11.0**46.8 ± 10.9#
35.90 ± 7.72b
37.44 ± 9.26c 43 ± 11f 42.82 ± 17.45c 47 ± 11h 46.5 ± 11.4##
34.74 ± 5.02d
Control-37.06 ± 6.95---54.3 ± 17.8---
Triglycerides (mg/dL)Intervention115.5 (83.5–158.8)NSa 149 ± 69e 178.5 ± 126.1168.58 ± 96.19a 200.6 ± 125.4129 ± 73g 130 (99–191)**115.6 ± 22.6#
NSb
NSc 152 ± 75f 154.42 ± 1.02c 134 ± 58h 119.9 ± 35.2##
NSd
Control-NS---122.8 ± 50.1--
Glucose (mg/dL)InterventionNS103.14 ± 18.0a NSe NSNSa NSNSg NS**NS#
102.96 ± 14.76b
90.0 ± 14.94c NSf NSc NSh NS##
101.34 ± 17.46d
Control-94.68 ± 17.64-NS-NS---
SBP (mmHg)Intervention129 (114–145)NSa NSe NSNSa NSNSg NS**NS#
NSb
NSc NSf NSc NSh NS##
NSd
Control-NS---NS---
DBP (mmHg)Intervention72 (68–83)NSa NSe NSNSa NSNSg NS**NS#
NSb
NSc NSf NSc NSh NS##
NSd
Control-NS---NS---
Plaque volume (mm3)Intervention308.8 (236.8–432.6)38.07 ± 13.94a 88.3 ± 26.9e 76.1 ± 32.198.47 ± 70.84a 440.2 ± 220.39.06 ± 2.90g*146.0 ± 55.6**10.2 ± 3.0#*
33.83 ± 10.56b
37.06 ± 12.01c 91.5 ± 27.5f 144.17 ± 154.46c 8.83 ± 3.67h*9.9 ± 2.9##*
36.47 ± 14.68d
Control-34.83 ± 13.76---432.9 ± 247.5---
Lumen volume (mm3)Intervention427.3 (310.9–703.7)NSa 85.2 ± 20.4e 70.5 ± 24.1NSa 373.7 ± 188.47.40 ± 2.55g*214.9 ± 71.5**6.6#*§
NSb
NSc 87.6 ± 26.2f NSc 7.42 ± 2.66h*8.0 ± 2.8##*
NSd
Control-NS---444.7 ± 233.5---
External elastic membrane volume (mm3)Intervention830.9 (606.8–1,080.1)NSa 173.5 ± 37.1e 146.6 ± 52.3NSa 813.9 ± 398.516.46 ± 4.98g*360.9 ± 108.8**16.8 ± 4.6#*
NSb
NSc 179.1 ± 46.6f NSc 16.25 ± 5.63h*17.9 ± 5.0##*
NSd
Control-NS---877.6 ± 458.3---
Fibrous volume (mm3)Intervention89.9 (67.1–123.9)NSa 25.6 ± 12.7e 27.7 ± 15.637.04 ± 30.41a 146.5 ± 85.63.46 ± 1.65g*18.5 (9.8–29.3)**5.9 ± 2.6#*
NSb
NSc 28.2 ± 14.4f 54.90 ± 58.05c 3.13 ± 1.98h*5.8 ± 2.3##*
NSd
Control-NS---142.9 ± 113.3---
Fibro-fatty volume (mm3)Intervention10.6 (6.4–27.9)NSa 4.1 ± 2.9e 4.5 ± 3.99.76 ± 9.80a 80.1 ± 57.91.09 ± 0.88g*23.1 (8.8–36.3)**1.5 ± 1.1#*
NSb
NSc 4.5 ± 4.0f 19.39 ± 36.04c 1.05 ± 1.03h*0.7 ± 0.6##*
NSd
Control-NS---50.7 ± 32.9---
Dense calcium volume (mm3)Intervention10.5 (4.0–20.9)NSa 6.5 ± 6.3e 4.2 ± 3.23.18 ± 3.44a 9.4 ± 9.90.42 ± 0.35g*1.2 (0.2–3.8)**0.6#*§
NSb
NSc 6.8 ± 6.4f 4.85 ± 7.68c 0.44 ± 0.47h*0.6##*§
NSd
Control-NS---13.7 ± 12.7---
Necrotic core volume (mm3)Intervention30.8 (13.9–48.2)NSa 15.8 ± 11.3e 8.7 ± 6.47.91 ± 7.47a 21.4 ± 24.90.68 ± 0.42g*5.9 (2.6–12.3)**1.6 ± 0.9#*
NSb
NSc 15.5 ± 8.4f 11.89 ± 18.72c 0.80 ± 0.66h*2.1 ± 1.4##*
NSd
Control-NS---22.1 ± 17.4---

Values are expressed as mean ± SD or median (25–75 percentiles). a10 mg/day atorvastatin arm; b20 mg/day atorvastatin arm; c40 mg/day atorvastatin arm; d80 mg/day atorvastatin arm; e20 mg/day simvastatin arm; f10 mg/day rosuvastatin arm; g4 mg/day pitavastatin arm; h20 mg/day pravastatin arm; i40 mg/day rosuvastatin arm; j2 mg/day pitavastatin arm; *the value was provided as volume index defined as the volume divided by the segment length (mm3/mm); **the value was provided for rosuvastatin and atorvastatin arms together; #patients belonging to plaque regression group (n = 94); ##patients belonging to plaque progression (n = 26) group; §SD not shown. BMI, body mass index; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; hs-CRP, high-sensitivity C-reactive protein; IVUS, intravascular ultrasound; LDL-C, low-density lipoprotein cholesterol; MB, myocardial band; NS, not stated; SBP, systolic blood pressure; VH-IVUS, virtual histology intravascular ultrasound

Demographic characteristics of the included studies Values are expressed as mean ± SD or median (25–75 percentiles). a10 mg/day atorvastatin arm; b20 mg/day atorvastatin arm; c40 mg/day atorvastatin arm; d80 mg/day atorvastatin arm; e20 mg/day simvastatin arm; f10 mg/day rosuvastatin arm; g4 mg/day pitavastatin arm; h20 mg/day pravastatin arm; i40 mg/day rosuvastatin arm; j2 mg/day pitavastatin arm; *the value was provided as volume index defined as the volume divided by the segment length (mm3/mm); **the value was provided for rosuvastatin and atorvastatin arms together; #patients belonging to plaque regression group (n = 94); ##patients belonging to plaque progression (n = 26) group; §SD not shown. BMI, body mass index; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; hs-CRP, high-sensitivity C-reactive protein; IVUS, intravascular ultrasound; LDL-C, low-density lipoprotein cholesterol; MB, myocardial band; NS, not stated; SBP, systolic blood pressure; VH-IVUS, virtual histology intravascular ultrasound

Risk of bias assessment

According to the Cochrane Collaboration [29], a specific tool for assessing risk of bias in every study involved consists of selection of particular characteristics of the study. This involves assessing the risk of bias as ‘low risk’, ‘high risk or ‘unclear risk’. The last category reveals either lack of detail or concern over the potential for bias. There are seven examined fields including: sequence generation (selection bias); allocation sequence concealment (selection bias); blinding of participants and personnel (performance bias); blinding of outcome assessment (detection bias); incomplete outcome data (attrition bias); selective outcome reporting (reporting bias); and other potential sources of bias (Table 2).
Table 2

Assessment of risk of bias in the included studies using Cochrane criteria

StudyReferenceSequence generationAllocation concealmentBlinding of participants and personnelBlinding of outcome assessmentIncomplete outcome dataSelective outcome reportingOther potential threats to validity
Eshtehardi et al. 2012[21]HHHHLLL
Guo et al. 2012[22]UUHHLLL
Hong et al. 2009[23]UUHHLLL
Hwang et al. 2013[24]HHHLLLH
Lee et al. 2012[14]LLLLLLL
Nasu et al. 2009[25]HHHHLLL
Nozue et al. 2012[26]LLHLLLL
Puri et al. 2014[27]UUHHLLL
Taguchi et al. 2013[28]HHHHLLL

H, high risk of bias; L, low risk of bias; U, unclear risk of bias

Assessment of risk of bias in the included studies using Cochrane criteria H, high risk of bias; L, low risk of bias; U, unclear risk of bias

Quantitative data synthesis

Meta-analysis of data from 16 statin-treated arms showed a significant effect of statin therapy in reducing plaque volume (SMD: −0.137, 95 % CI: −0.255, −0.019; P = 0.023) (Fig. 2). This effect size was robust in the sensitivity analysis and remained at a significant or borderline significant levels following omission of each single study (Fig. 3). Statin therapy was also associated with a significant decrease in EEMV (SMD: −0.097, 95 % CI: −0.183, −0.011; P = 0.027) but not LV (SMD: −0.025, 95 % CI: −0.110, +0.061; P = 0.574) (Fig. 2).
Fig. 2

Forest plot detailing weighted mean difference and 95 % confidence intervals for the impact of statin therapy on plaque, lumen and external elastic membrane volumes according to virtual histology intravascular ultrasound (VH-IVUS). Meta-analysis was performed using a random-effects model with inverse variance weighting

Fig. 3

Leave-one-out sensitivity analysis of the impact of statin therapy on plaque volume

Forest plot detailing weighted mean difference and 95 % confidence intervals for the impact of statin therapy on plaque, lumen and external elastic membrane volumes according to virtual histology intravascular ultrasound (VH-IVUS). Meta-analysis was performed using a random-effects model with inverse variance weighting Leave-one-out sensitivity analysis of the impact of statin therapy on plaque volume The analysis of plaque composition data indicated significant reduction in fibrous (SMD: −0.129, 95 % CI: −0.255, −0.003; P = 0.045) and increase in dense calcium (SMD: 0.229, 95 % CI: 0.008, 0.450; P = 0.043) volumes, while fibro-fatty (SMD: −0.247, 95 % CI: −0.592, +0.098; P = 0.160) and necrotic core (SMD: 0.011, 95 % CI: −0.144, +0.165; P = 0.892) tissue volumes remained statistically unaltered (Fig. 4).
Fig. 4

Forest plot detailing weighted mean difference and 95 % confidence intervals for the impact of statin therapy on plaque composition parameters according to virtual histology intravascular ultrasound (VH-IVUS). Meta-analysis was performed using a random-effects model with inverse variance weighting

Forest plot detailing weighted mean difference and 95 % confidence intervals for the impact of statin therapy on plaque composition parameters according to virtual histology intravascular ultrasound (VH-IVUS). Meta-analysis was performed using a random-effects model with inverse variance weighting A subgroup analysis was performed to compare the impact of high-intensity versus moderate/low-intensity statin therapy on coronary atherosclerosis according to American College of Cardiology (ACC)/American Heart Association (AHA) lipid guidelines [30]. High-intensity statin therapy had a greater effect in reducing plaque volume (SMD: −0.338, 95 % CI: −0.637, −0.040; P = 0.026) compared with moderate/low-intensity treatment (SMD: −0.071, 95 % CI: −0.167, +0.026; P = 0.152) (Fig. 5). However, no significant difference between the subgroups was observed in terms of effects on LV and EEMV (Fig. 5). With respect to plaque composition parameters, significant changes in dense calcium (SMD: 0.091, 95 % CI: 0.011, 0.171; P = 0.025) and fibrous (SMD: −0.399, 95 % CI: −0.722, −0.076; P = 0.015) volumes were observed in the moderate/low-intensity and high-intensity subgroups, respectively (Fig. 6). The effects of both treatment regimens on fibro-fatty and necrotic core tissue volumes were statistically comparable (Fig. 6).
Fig. 5

Forest plot detailing weighted mean difference and 95 % confidence intervals for the impact of high-intensity versus moderate/low-intensity statin therapy on plaque, lumen and external elastic membrane volumes according to virtual histology intravascular ultrasound (VH-IVUS). Meta-analysis was performed using a random-effects model with inverse variance weighting

Fig. 6

Forest plot detailing weighted mean difference and 95 % confidence intervals for the impact of high-intensity versus moderate/low-intensity statin therapy on plaque composition parameters according to virtual histology intravascular ultrasound (VH-IVUS). Meta-analysis was performed using a random-effects model with inverse variance weighting

Forest plot detailing weighted mean difference and 95 % confidence intervals for the impact of high-intensity versus moderate/low-intensity statin therapy on plaque, lumen and external elastic membrane volumes according to virtual histology intravascular ultrasound (VH-IVUS). Meta-analysis was performed using a random-effects model with inverse variance weighting Forest plot detailing weighted mean difference and 95 % confidence intervals for the impact of high-intensity versus moderate/low-intensity statin therapy on plaque composition parameters according to virtual histology intravascular ultrasound (VH-IVUS). Meta-analysis was performed using a random-effects model with inverse variance weighting Another subgroup analysis was performed to compare the effects of statin therapy on coronary atherosclerosis in the subgroups of trials with and without ACS patients. PV was reduced only in the subset of trials not recruiting ACS patients (SMD: −0.175, 95 % CI: −0.334, −0.015; P = 0.032). The impact of statin therapy on other indices in ACS+ and ACS− subgroups are summarized in Table 3.
Table 3

Comparison of the effects of statin therapy on coronary atherosclerosis indices in subgroups of trials recruiting subjects with and without ACS

Without ACSWith ACS
SMD95 % CI P valueSMD95 % CI P value
Plaque volume−0.175−0.334, −0.0150.032−0.080−0.258, 0.0990.382
Lumen volume−0.033−0.121, 0.0560.469−0.007−0.148, 0.1340.919
External elastic membrane volume (mm3)−0.065−0.154, 0.0240.150−0.121−0.263, 0.0200.093
Fibrous volume (mm3)−0.010−0.053, 0.1330.8880.027−0.243, 0.2970.844
Fibro-fatty volume−0.395−0.824, 0.0340.0710.008−0.312, 0.3280.961
Dense calcium volume−0.119−0.304, 0.0650.206−0.137−0.266, −0.0070.038
Necrotic core volume0.271−0.013, 0.5550.0620.074−0.055, 0.2030.261

ACS, acute coronary syndrome; CI, confidence interval; SMD, standardized mean difference

Comparison of the effects of statin therapy on coronary atherosclerosis indices in subgroups of trials recruiting subjects with and without ACS ACS, acute coronary syndrome; CI, confidence interval; SMD, standardized mean difference

Meta-regression

Meta-regression analysis was conducted to assess the association between statin-induced changes in PV with duration of statin therapy and respective changes in plasma LDL-C concentrations as potential confounders. In meta-regression analysis, the impact of statins on PV was found to be independent of treatment duration (slope: 0.00007; 95 % CI: −0.006, +0.006; P = 0.980). Likewise, statin-induced reduction in PV was not found to be significantly associated with LDL-C reductions (slope: −0.002; 95 % CI: −0.015, +0.011; P = 0.788) (Fig. 7). Further analyses did not reveal any significant association between statin-induced changes in PV and other potential confounders including age, dose (atorvastatin), age, proportion of males, proportion of diabetics, proportion of smokers and baseline LDL-C (Table 4).
Fig. 7

Random effects meta-regression plots of the association between mean changes in plaque volume with treatment duration, and changes in plasma low-density lipoprotein cholesterol (LDL-C) concentrations. The size of each circle is inversely proportional to the variance of change. Meta-regression was performed using unrestricted maximum likelihood method

Table 4

Impact of potential confounders on changes in plaque volume following statin therapy in random-effects meta-regression

ConfounderSlope95 % CI P value
Age (years)0.009−0.020, 0.0390.537
% Males−0.011−0.024, 0.0020.106
% Diabetics0.003−0.002, 0.0080.255
% Smokers−0.004−0.009, 0.00040.075
Dose (mg/day)a −0.007−0.015, 0.0010.091
Baseline LDL-C (mg/dL)0.004−0.007, 0.0160.435

aRestricted to atorvastatin trials. CI, confidence interval; LDL-C, low-density lipoprotein cholesterol

Random effects meta-regression plots of the association between mean changes in plaque volume with treatment duration, and changes in plasma low-density lipoprotein cholesterol (LDL-C) concentrations. The size of each circle is inversely proportional to the variance of change. Meta-regression was performed using unrestricted maximum likelihood method Impact of potential confounders on changes in plaque volume following statin therapy in random-effects meta-regression aRestricted to atorvastatin trials. CI, confidence interval; LDL-C, low-density lipoprotein cholesterol

Publication bias

The results of Egger’s linear regression (intercept = 0.860, standard error = 1.866; 95 % CI: −3.142, +4.861, t = 0.461, df = 14.00; two-tailed P = 0.652) and Begg’s rank correlation (Kendall’s tau with continuity correction = 0.025, Z = 0.135; two-tailed P = 0.893) tests did not provide any proof of significant publication bias for the decreasing effect of statin therapy on PV. However, the funnel plot of precision (1/standard error) by effect size (SMD) was found to be asymmetric and suggestive of potential publication bias. The observed publication bias was imputed using trim-and-fill correction. This correction suggested no asymmetry on the right of the mean, while five potentially missing studies were imputed on the left of the mean leading to a corrected effect size that was significant: SMD: −0.232 (95 % CI: −0.351, −0.114). The ‘fail-safe N’ method indicated that 38 theoretically missing studies would need to be added to the analysis before the overall effect size becomes trivial. Funnel plot of the impact of statins on plaque volume is illustrated in Fig. 8.
Fig. 8

Funnel plot detailing publication bias in the studies reporting the impact of statin therapy on plaque volume. Open circles represent observed published studies; closed circles represent imputed unpublished studies

Funnel plot detailing publication bias in the studies reporting the impact of statin therapy on plaque volume. Open circles represent observed published studies; closed circles represent imputed unpublished studies

Discussion

The present systematic review and meta-analysis provides a comprehensive assessment of the impact of statin therapy on coronary plaque composition assessed with VH-IVUS. We observed a significant effect of statin therapy on plaque volume (however with no significant changes in lumen volume), external elastic membrane, fibrous and dense calcium volumes, while fibro-fatty and necrotic core tissue volumes remained statistically unchanged. The potential reason for obtaining these results may lie in the fact that foam cells function as a substrate for the progression of necrosis [31]. The existence of foam cells and non-load-bearing lipid pools enzymatic together with destruction of collagen by matrix metalloproteinases, and microcalcifications might produce a TCFA, increasing the risk of plaque rupture and MACE [32]. However, statins have been associated with increase in fibrous cap thickness in optical coherence tomography (OCT) studies [33]. In these OCT studies, only assessment of the near field can be achieved due to the poor penetration of the technology and therefore the quantification of fibrous tissue in the total plaque cannot be obtained. In our meta-analysis that included only VH-IVUS studies, we observed a global decrease in fibrous tissue associated with statin treatment. In other words, there may be two differential effects of statin treatment, on the one hand a focal increase in cap thickness and on the other hand a global decrease in fibrous tissue. This hypothesis needs further investigation. Increased quantities of calcium in coronary plaques have been linked to negative remodeling [34, 35], in contrast to increased lipid and fibro-fatty elements usually seen in positively remodeled lesions [36, 37]. Moreover, ACS and histological features of plaque vulnerability such as a large lipid core and high macrophage content seems to be associated with a positive coronary arterial remodeling [38]. Many studies such as the Myocardial Ischemia Reduction with Aggressive Cholesterol Lowering (MIRACL) [39] and the Pravastatin or Atorvastatin Evaluation and Infection Therapy–Thrombolysis in Myocardial Infarction 22 (PROVE IT-TIMI 22) [40] have reported that intensive statin therapy reduces MACE in patients with coronary heart disease. Significant plaque burden, extensive remodeling and calcification have been regarded as fundamental morphologies of high-risk plaques leading to MACE [41]. It has been shown that statin therapy improves plaque hyperechogenicity without a considerable decrease in plaque volume, suggesting that statins might influence coronary artery plaque composition [42]. Moreover, in non-culprit, high-risk coronary lesions after the onset of ACS, statins proved to be beneficial for regression and stabilization of vulnerable plaques [41]. However, the effect of statin therapy on plaque volume and composition might essentially differ by statin preparations, doses, duration of therapy, methods of imaging, as well as plaque localization. In the Reversal of Atherosclerosis with Aggressive Lipid Lowering (REVERSAL) trial [43], moderate lipid-lowering therapy with 40 mg of pravastatin did not stop plaque progression, while treatment with 80 mg of atorvastatin did. The first study showing reduction on plaque size was the a Study to Evaluate the Effect of Rosuvastatin on Intravascular Ultrasound-Derived Coronary Atheroma Burden (ASTEROID) trial with 40 mg of rosuvastatin [44]. However, these trials have only evaluated quantitative changes of coronary artery plaque using gray-scale IVUS and did not study plaque composition changes. Our meta-analysis showed that statin therapy reduces atheroma plaque volume, however with no significant changes in lumen volume. It also influences plaque composition reducing fibrous volume, however with no significant changes in fibro-fatty and necrotic core tissue volumes. Although these results differed between available studies [14, 21–28], these observations confirm the changes in plaque composition affecting lesion size and plaque stability (changes the composition of plaques from fatty to fibrous). On the other hand, the lack of effect on necrotic material is highly concerning for the field, given that the outcome studies in this field have largely supported the findings that TCFA is associated with adverse outcomes [45]. Statin therapy induced a significant regression of IVUS-measured coronary plaque volume, especially when reaching the target LDL-C level, as shown in a meta-analysis of gray-scale IVUS studies investigating temporal modifications in coronary plaque volume [46]. However, conventional gray-scale IVUS compared with VH-IVUS method has many limitations in the evaluation of atheromatous plaque composition and identification of a vulnerable plaque prior to rupture [47-49]. Another study indicated that VH-IVUS may potentially allow the best detection of features associated with future plaque rupture, increasing the probability of superior risk stratification at the moment of percutaneous coronary intervention [50]. The present meta-analysis has several limitations. Most importantly, there were few eligible prospective trials, and most had small numbers of patients. Furthermore, the included studies were heterogeneous regarding factors such as population characteristics (different statins, doses and duration of treatment), study design and VH-IVUS methodology (for example, in some of the included studies VH-IVUS was not performed in all patients and there were different IVUS catheters used in the included studies). There were only two studies controlled with placebo, and others compared high-intensity versus moderate/low-intensity statin therapy. Furthermore, VH-IVUS was only performed in one coronary vessel, which might not reflect changes in plaque features sampled from other regions of the coronary tree. Plaque volume might be also very variable when measured in mm3 across studies. Finally, the use of serial VH-IVUS imaging might be problematic, as it is ECG gated, so there is limited ability to precisely match segments.

Conclusions

In conclusion, this meta-analysis of nine prospective studies comprising 16 statin-treated arms indicates a significant effect of statin therapy on plaque, external elastic membrane, fibrous and dense calcium volumes, while fibro-fatty and necrotic core tissue volumes remained statistically unchanged. Further large-scale, well-designed head-to-head trials are warranted to fully address the differential effects on these parameters with different statins.
  44 in total

Review 1.  Tissue characterisation using intravascular radiofrequency data analysis: recommendations for acquisition, analysis, interpretation and reporting.

Authors:  Héctor M García-García; Gary S Mintz; Amir Lerman; D Geoffrey Vince; M Paulina Margolis; Gerrit-Anne van Es; Marie-Angèle M Morel; Anuja Nair; Renu Virmani; Allen P Burke; Gregg W Stone; Patrick W Serruys
Journal:  EuroIntervention       Date:  2009-06       Impact factor: 6.534

2.  Virtual histology findings and effects of varying doses of atorvastatin on coronary plaque volume and composition in statin-naive patients: the VENUS study.

Authors:  Stephen Wai Luen Lee; William Kong To Hau; Shun Ling Kong; Kelvin K W Chan; Pak-Hei Chan; Simon C C Lam; Frankie C C Tam; Michael K L Wong; Carmen W S Chan; Yui Ming Lam; Hung-Fat Tse; Raymond H W Chan
Journal:  Circ J       Date:  2012-08-02       Impact factor: 2.993

3.  Long-term effects of maximally intensive statin therapy on changes in coronary atheroma composition: insights from SATURN.

Authors:  Rishi Puri; Peter Libby; Steven E Nissen; Kathy Wolski; Christie M Ballantyne; Phillip J Barter; M John Chapman; Raimund Erbel; Joel S Raichlen; Kiyoko Uno; Yu Kataoka; E Murat Tuzcu; Stephen J Nicholls
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2014-01-20       Impact factor: 6.875

4.  Use of intravascular ultrasound to compare effects of different strategies of lipid-lowering therapy on plaque volume and composition in patients with coronary artery disease.

Authors:  M Schartl; W Bocksch; D H Koschyk; W Voelker; K R Karsch; J Kreuzer; D Hausmann; S Beckmann; M Gross
Journal:  Circulation       Date:  2001-07-24       Impact factor: 29.690

5.  In vivo detection of high-risk coronary plaques by radiofrequency intravascular ultrasound and cardiovascular outcome: results of the ATHEROREMO-IVUS study.

Authors:  Jin M Cheng; Hector M Garcia-Garcia; Sanneke P M de Boer; Isabella Kardys; Jung Ho Heo; K Martijn Akkerhuis; Rohit M Oemrawsingh; Ron T van Domburg; Jurgen Ligthart; Karen T Witberg; Evelyn Regar; Patrick W Serruys; Robert-Jan van Geuns; Eric Boersma
Journal:  Eur Heart J       Date:  2013-11-19       Impact factor: 29.983

6.  Virtual histology intravascular ultrasound assessment of carotid artery disease: the Carotid Artery Plaque Virtual Histology Evaluation (CAPITAL) study.

Authors:  Edward B Diethrich; M Pauliina Margolis; Donald B Reid; Allen Burke; Venkatesh Ramaiah; Julio A Rodriguez-Lopez; Grayson Wheatley; Dawn Olsen; Renu Virmani
Journal:  J Endovasc Ther       Date:  2007-10       Impact factor: 3.487

7.  Effect of intensive compared with moderate lipid-lowering therapy on progression of coronary atherosclerosis: a randomized controlled trial.

Authors:  Steven E Nissen; E Murat Tuzcu; Paul Schoenhagen; B Greg Brown; Peter Ganz; Robert A Vogel; Tim Crowe; Gail Howard; Christopher J Cooper; Bruce Brodie; Cindy L Grines; Anthony N DeMaria
Journal:  JAMA       Date:  2004-03-03       Impact factor: 56.272

8.  Antiatherosclerotic effects of long-term maximally intensive statin therapy after acute coronary syndrome: insights from Study of Coronary Atheroma by Intravascular Ultrasound: Effect of Rosuvastatin Versus Atorvastatin.

Authors:  Rishi Puri; Steven E Nissen; Mingyuan Shao; Christie M Ballantyne; Philip J Barter; M John Chapman; Raimund Erbel; Peter Libby; Joel S Raichlen; Kiyoko Uno; Yu Kataoka; Stephen J Nicholls
Journal:  Arterioscler Thromb Vasc Biol       Date:  2014-09-11       Impact factor: 8.311

Review 9.  From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: Part I.

Authors:  Morteza Naghavi; Peter Libby; Erling Falk; S Ward Casscells; Silvio Litovsky; John Rumberger; Juan Jose Badimon; Christodoulos Stefanadis; Pedro Moreno; Gerard Pasterkamp; Zahi Fayad; Peter H Stone; Sergio Waxman; Paolo Raggi; Mohammad Madjid; Alireza Zarrabi; Allen Burke; Chun Yuan; Peter J Fitzgerald; David S Siscovick; Chris L de Korte; Masanori Aikawa; K E Juhani Airaksinen; Gerd Assmann; Christoph R Becker; James H Chesebro; Andrew Farb; Zorina S Galis; Chris Jackson; Ik-Kyung Jang; Wolfgang Koenig; Robert A Lodder; Keith March; Jasenka Demirovic; Mohamad Navab; Silvia G Priori; Mark D Rekhter; Raymond Bahr; Scott M Grundy; Roxana Mehran; Antonio Colombo; Eric Boerwinkle; Christie Ballantyne; William Insull; Robert S Schwartz; Robert Vogel; Patrick W Serruys; Goran K Hansson; David P Faxon; Sanjay Kaul; Helmut Drexler; Philip Greenland; James E Muller; Renu Virmani; Paul M Ridker; Douglas P Zipes; Prediman K Shah; James T Willerson
Journal:  Circulation       Date:  2003-10-07       Impact factor: 29.690

Review 10.  Thin-cap fibroatheroma rupture is associated with a fine interplay of shear and wall stress.

Authors:  Ryan M Pedrigi; Ranil de Silva; Sandra M Bovens; Vikram V Mehta; Enrico Petretto; Rob Krams
Journal:  Arterioscler Thromb Vasc Biol       Date:  2014-07-24       Impact factor: 8.311

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  52 in total

1.  Psychometric Evaluation of Stress in 17,414 Critical Care Unit Nurses: Effects of Age, Gender, and Working Conditions.

Authors:  Mohammad Asghari Jafarabadi; Amir Vahedian-Azimi; Farshid Rahimibashar; Paul C Guest; Leila Karimi; Amirhossein Sahebkar
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

2.  Predicting Locations of High-Risk Plaques in Coronary Arteries in Patients Receiving Statin Therapy.

Authors:  Ling Zhang; Andreas Wahle; Zhi Chen; John J Lopez; Tomas Kovarnik; Milan Sonka
Journal:  IEEE Trans Med Imaging       Date:  2017-07-11       Impact factor: 10.048

Review 3.  Effect of ezetimibe on plasma adipokines: a systematic review and meta-analysis.

Authors:  Eva Dolezelova; Evan Stein; Giuseppe Derosa; Pamela Maffioli; Petr Nachtigal; Amirhossein Sahebkar
Journal:  Br J Clin Pharmacol       Date:  2017-03-10       Impact factor: 4.335

4.  PoLA/CFPiP/PCS Guidelines for the Management of Dyslipidaemias for Family Physicians 2016.

Authors:  Maciej Banach; Piotr Jankowski; Jacek Jóźwiak; Barbara Cybulska; Adam Windak; Tomasz Guzik; Artur Mamcarz; Marlena Broncel; Tomasz Tomasik; Jacek Rysz; Agnieszka Jankowska-Zduńczyk; Piotr Hoffman; Agnieszka Mastalerz-Migas
Journal:  Arch Med Sci       Date:  2016-12-19       Impact factor: 3.318

5.  Association between age and progression of carotid artery atherosclerosis: a serial high resolution magnetic resonance imaging study.

Authors:  Mingming Lu; Peng Peng; Huiyu Qiao; Yuanyuan Cui; Lu Ma; Bao Cui; Jianming Cai; Xihai Zhao
Journal:  Int J Cardiovasc Imaging       Date:  2019-02-09       Impact factor: 2.357

Review 6.  Impact of statin therapy on plasma leptin concentrations: a systematic review and meta-analysis of randomized placebo-controlled trials.

Authors:  Amirhossein Sahebkar; Renato Giua; Claudio Pedone
Journal:  Br J Clin Pharmacol       Date:  2016-10-04       Impact factor: 4.335

Review 7.  The evolving view of coronary artery calcium and cardiovascular disease risk.

Authors:  Isac C Thomas; Nketi I Forbang; Michael H Criqui
Journal:  Clin Cardiol       Date:  2018-01-22       Impact factor: 2.882

Review 8.  Interactive and Multifactorial Mechanisms of Calcific Vascular and Valvular Disease.

Authors:  Linda L Demer; Yin Tintut
Journal:  Trends Endocrinol Metab       Date:  2019-07-03       Impact factor: 12.015

Review 9.  Cardiovascular Immunotherapy and the Role of Imaging.

Authors:  Eva Zupančič; Zahi A Fayad; Willem J M Mulder
Journal:  Arterioscler Thromb Vasc Biol       Date:  2017-11       Impact factor: 8.311

10.  Statin Effects on Vascular Calcification: Microarchitectural Changes in Aortic Calcium Deposits in Aged Hyperlipidemic Mice.

Authors:  Joshua Zhaojun Xian; Mimi Lu; Felicia Fong; Rong Qiao; Nikhil Rajesh Patel; Dishan Abeydeera; Sidney Iriana; Linda L Demer; Yin Tintut
Journal:  Arterioscler Thromb Vasc Biol       Date:  2021-01-21       Impact factor: 8.311

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