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Imputation of Baseline LDL Cholesterol Concentration in Patients with Familial Hypercholesterolemia on Statins or Ezetimibe.

Familial hypercholesterolemia (FH) [15] is characterized by increased circulating concentrations of LDL cholesterol (LDL-C) and is transmitted in an autosomal codominant fashion. FH is the most frequent monogenic disorder in clinical practice and is caused by mutations at the LDL receptor (LDLR) [16], apolipoprotein B (APOB), or proprotein convertase subtilisin/kexin type 9 (PCSK9) genes (1). Other genes have also been shown to be associated with the FH phenotype, but these are rare. Some patients with the FH phenotype may have multiple single-nucleotide polymorphisms in genes that have been shown to exert an effect on LDL-C (2).

The prevalence of FH, once considered to be 1 in 500, has been adjusted in light of more precise diagnostic criteria and is now estimated to be 1 in 250 worldwide (3), with a higher prevalence in populations with founder effects, such as that seen in the French-Canadian population.

There are 2 widely used and internationally accepted definitions for FH, namely, those from the Dutch Lipid Clinics Network and the Simon Broome Registry criteria. Each relies on documenting an increased LDL-C in an adult (usually >200 mg/dL or >5.0 mmol/L), together with a family history of increased LDL-C in first-degree relatives, or premature atherosclerotic cardiovascular disease (ASCVD) in a first-degree relative, plus the presence of xanthomas, xanthelasmas, or premature corneal arcus (4-9). A DNA diagnosis may confirm the diagnosis unambiguously but is not required for a clinical diagnosis. Other definitions include that from the Japanese Atherosclerosis Society, which has adapted the Simon-Broome Registry criteria, and also the MedPed definition, which is used infrequently because it relies on strict LDL-C cutpoints imposed on first-, second-, and third-degree relatives, making it impractical in a clinical setting (10, 11). A new Canadian definition for FH has also adapted the Simon Broome Registry criteria, but it offers these in a simplified version (6).

FH is frequently undiagnosed worldwide, except for in countries such as the Netherlands, Norway, Switzerland, Iceland, and the UK (1), where national registries have been implemented. The experience from the Netherlands has shown that if recognized and treated early, patients with FH can have a similar rate of coronary heart disease as the general population (12). A precise diagnosis of FH is important. Two recent studies have shown that the risk of ASCVD in patients with an LDL-C >200 mg/dL (>5.0 mmol/L) is increased approximately 6-fold compared with an individual with an LDL-C of 130 mg/dL (3.4 mmol/L). However, if a patient has a mutation in the LDLR, APOB, or PCSK9 genes known to cause FH, this risk is increased 10- to 22-fold (13, 14). Once a subject is diagnosed with FH, cascade screening, consisting of screening all first-degree relatives, proves to be a cost-efficient way to identify additional affected individuals (15-19). Many international groups have made awareness, screening, and treatment of FH a priority (7, 8, 20-22).

Often, the baseline pretreatment LDL-C is not available because the patient has initiated and continues to receive lipid-lowering therapy, especially statins. Further, the original baseline LDL-C may predate the current assessment by many years and cannot be easily retrieved. Most guidelines consider that a definite diagnosis of FH mandates lipid-lowering therapy and family screening (1,6,21,23,24). Access to inhibitors of PCSK9 and more costly medications, such as mipomersen or lomitapide, may depend on a diagnosis of FH in some countries (25-28).

We have provided an application for computers and smartphones to make the diagnosis of FH based on the Simon Broome Registry criteria, the Dutch Lipid Clinics Network criteria, and the new Canadian FH definition (6) that uses an imputed baseline LDL-C if the patient is on lipid-lowering therapy with either statins and/or ezetimibe. This application can be accessed online (http:// www.circl.ubc.ca/english/web_fh.html) (29). We used a metaanalysis that provides the average LDL-C reduction for each statin at indicated prescribed doses. We used the same data for the fixed 10-mg/day dose of ezetimibe as monotherapy or in combination with statins (30). In the present analysis, we present the validation of the imputation of a baseline LDL-C based on the observed impact of current lipid-lowering therapies with statins and/or ezetimibe in FH patients. Access to this algorithm is also available through the website of FH Canada (www. FHCanada.net) (31).

Materials and Methods

We performed a retrospective analysis on data from 1297 patients with FH from 6 clinics across Canada (Coauthor involved: RAH; LB; JB, PC; RD, AB, JG, IR; DG, DB) in whom a baseline LDL-C was available before the initiation of statins or ezetimibe and in whom an LDL-C was available within 18 months after the initiation of therapy [mean 7.2 (3.8) months]. We selected the 18-month time point to ensure the patients were on a stable dose of medication. We eliminated patients with missing data or noncompliance to treatment (n = 45), patients with an on-treatment LDL-C determined >18 months after initiation of therapy (n = 120), patients on lipid-lowering drugs other than statins or ezetimibe (n = 128), and patients on nonstandard dose of medication (e.g., rosuvastatin, 5 mg 3 times/week; simvastatin, 30 mg/day) (n = 53) (Fig. 1). All data were deidentified. The protocol for the Canadian FH registry was reviewed and accepted by the Research Ethics Board of the McGill University Health Center.

We used the metaanalysis of Hou et al. (30) to determine the mean percent change from baseline for lovastatin (10, 20, 40, and 80 mg), pravastatin (10, 20, and 40 mg), simvastatin (5, 10, 20, 40, and 80 mg), atorvastatin (10, 20, 40, and 80 mg), fluvastatin (20 and 40 mg), rosuvastatin (5, 10, 20, and 40 mg), and ezetimibe (10 mg; all daily doses). The selection criteria were a diagnosis of FH based on the Dutch Lipid Clinics Network (definite or probable) or the Simon Broome Registry criteria (definite or probable), a baseline LDL-C calculated by the Friedewald formula in a patient naive to lipid-lowering therapies and a follow-up evaluation, and on-treatment LDL-C obtained within 18 months. In all cases, secondary causes of severe hypercholesterolemia (e.g., hypothyroidism, liver disease, nephrotic syndrome, or medications) were ruled out. For ezetimibe, most patients were taking an optimal dose of statin, and the follow-up LDL-C was then taken as the new baseline. Some patients were started on statin and ezetimibe simultaneously, and the validation of the imputed LDL-C compared with baseline LDL-C was examined separately. We examined the effects of a patient's sex in the comparison of baseline vs imputed baseline LDL-C.

STATISTICAL ANALYSIS

Data are expressed as mean [+ or -] SE (see figures) or mean [+ or -] SD (see tables). The imputation of the LDL-C was performed by dividing the on-treatment LDL-C by the reciprocal of the expected percent change (Table 1). Patients were then grouped according to the dose and type of statin prescribed. The expected percent change was compared with the observed percent ([+ or -]SE) change for each dose and type of statin or ezetimibe. Because the expected percent change from baseline is based on a metaanalysis of multiple studies, no SE is provided. Therefore, we used a single-sided i-test to determine statistical significance. For each dose of each medication, the mean baseline LDL-C was compared with the mean of imputed baseline LDL-C by 2-tailed paired i-tests. A Bonferroni adjustment for multiple i-tests was made with the level of significance set at P < 0.002 (0.05/23 tests). A correlation between baseline and imputed LDL-C was performed for each dose of each medication by Pearson linear regression, and a correlation coefficient (r) and P value were determined. When available, the association between effect of sex on baseline and imputed LDL-C was determined (n = 788). All statistical analyses were performed using the IBM SPSS Statistics version 22.0.

Results

We obtained data on 1297 patients, and after eliminating those with missing data, nonstandard doses of statins, or medications other than statins or ezetimibe, 951 patients with FH were included in the final analysis (Fig. 1). The mean [+ or -] SD age was 43 (14) years (range, 9-80 years; 50% female). The number of patients on each dose of statin is shown in Table 2. The mean baseline LDL-C for all patients receiving a specific dose of a statin, the on-treatment LDL-C, the observed reduction in LDL-C, and the predicted percent reduction [derived from Table 1 of Hou et al. (30)] are shown in Table 2. We first compared the predicted percent reduction with the observed reduction: Fig. 2 shows the differences between the observed vs expected percent LDL-C reduction for each dose of individual statins. There was a statistically significant difference (P < 0.002) between observed and expected percent LDL-C reduction for ezetimibe only.

The imputed baseline LDL-C was compared with the actual baseline LDL-C by paired 2-tailed i-test (Fig. 3). There were no statistically significant differences (P > 0.002) observed except for ezetimibe (P < 0.001). For lovastatin 80 mg, pravastatin 20 mg, and simvastatin 10, 20, and 40 mg, we observed marginal statistical significance. In the overall group, the mean [+ or -] SE baseline LDL-C was 243.0 (2.2) mg/dL [6.28 (0.06) mmol/L] and the mean [+ or -] SE imputed baseline LDL-C was 244.2 (2.6) mg/dL [6.31 (0.07) mmol/L] (P = 0.48) (Fig. 3, inset). There was no difference in response according to the patient's sex (see Figure 1 in the Data Supplement that accompanies the online version of this article at http://www.clinchem.org/content/vol64/issue2). A DNA mutation in the LDLR, APOB, or PCSK9 genes was identified in 429 of 951 (45%) individuals. Results were similar to those of the whole cohort.

The Pearson correlation coefficient for baseline observed and imputed baseline LDL-C was r = 0.76 (P < 0.001; Fig. 4). Histograms showing the comparison between observed vs expected percent LDL-C reduction (left panels), between baseline vs imputed LDL-C concentrations (middle panel), and the correlations between each dose of statins and ezetimibe (right panels) are shown Figs. 2--8 of the online Data Supplement. The data are presented for individual doses of each statin (lovastatin, 10, 20, 40, and 80 mg; pravastatin, 10, 20, and 40 mg; simvastatin, 5, 10, 20, 40, and 80 mg; atorvastatin, 10, 20, 40, and 80 mg; fluvastatin, 20 and 40 mg; rosuvastatin, 5, 10, 20, and 40 mg; and ezetimibe, 10 mg).

Discussion

The diagnosis of FH relies on various criteria, each of which includes the concentration of LDL-C before the initiation of lipid-lowering therapy. Clinicians are frequently faced with a patient on lipid-lowering therapy with an on-treatment LDL-C concentration without knowledge of the baseline LDL-C. The reasons for this vary considerably, but inaccessibility of past medical records, changes in care providers, and patients' lack of recall can make the determination of the baseline LDL-C difficult, if not impossible. Current guidelines for the management of increased cholesterol support the use of high-intensity statins (atorvastatin 40-80 mg or rosuvastatin 20-40 mg/day) in high-risk individuals, targeting either a 50% reduction from baseline LDL-C or <70 mg/dL (1.8 mmol/L) (21, 23, 24). In some cases, the LDL-C remains increased despite treatment. This can be because of lack of patient adherence to treatment, a decreased response to the prescribed dose, or an increased baseline LDL-C. Many patients who are compliant to prescribed high-dose statin and who have an on-treatment LDL-C that remains increased may, in fact, have FH.

Here, we provide validation for the calculation of an imputed baseline LDL-C that will help clinicians and raise awareness of the possibility that the patient may have FH, leading to more appropriate and intensive treatment. Importantly, an increased LDL-C should spur cascade screening in the family for the detection of affected individuals. To facilitate both the calculation of the imputed baseline LDL-C and the diagnosis of FH, we provide a web-based and smartphone application, the FH Calculator, part of the updated CardioRisk Calculator available online through either the FH Canada website (http://www.fhcanada.net) (31) or http://www.circl.ubc. ca/english/web_fh.html (29). The "app" is also downloadable from the web free of charge.

National guidelines for the identification and treatment of patients with FH strongly recommend the use of statin therapy and/or ezetimibe to lower LDL-C. This is especially important for patients bearing a mutation in LDLR, PCSK9, or APOB genes, in whom the risk of ASCVD is 10- to 20-fold that of a normolipidemic individual (13, 14).

LIMITATIONS

The data are largely derived from retrospective analyses performed in 6 large specialized lipid clinics across Canada. We used the average response to specific doses of medications, but there is considerable interindividual variability (32). The correlation between baseline and imputed LDL-C (r = 0.76) (Fig. 4) shows that our imputed LDL-C can be overestimated (or, in some cases, underestimated); this can be because of patient adherence to treatment, variability in response, and type of mutations in genes causing FH. These results reflect current clinical practice in specialized clinics. Thus, in our large cohort of well-characterized FH patients, each with directly reported untreated LDL-C concentrations, our algorithm provides an excellent estimate of baseline untreated LDL-C concentrations using current treated concentrations together with information on the type of treatment. In FH in particular, baseline LDL-C concentrations are important for diagnosis and monitoring of adequate patient response to treatment, especially in primary prevention.

Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.

Authors' Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest:

Employment or Leadership: None declared.

Consultant or Advisory Role: R.A. Hegele, Amgen, Sanofi, Aegerion; G.A. Francis, Akcea, Alexion, Amgen, Sanofi; G.B.J. Mancini, Sanofi. Stock Ownership: None declared.

Honoraria: R.A. Hegele, Amgen, Aegerion, Sanofi, Akcea, Valeant, Boston Heart; G.A. Francis, Alexion, Amgen, Sanofi; G.B.J. Mancini, Sanofi.

Research Funding: Funding from Amgen, Sanofi, and Pfizer to the institution.

Expert Testimony: None declared.

Patents: None declared.

Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or final approval of manuscript.

Acknowledgment: The authors thank all clinic personnel who helped with data collection.

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Isabelle Ruel, [1] Sumayah Aljenedil, [1] Iman Sadri, [1] Emilie de Varennes, [1] Robert A. Hegele, [2] Patrick Couture, [3] Jean Bergeron, [3] Eric Wanneh, [4] Alexis Baass, [4,5,6] Robert Dufour, [7] Daniel Gaudet, [8] Diane Brisson, [8] Liam R. Brunham, [9,10,11] Gordon A. Francis, [9,10,11] Lubomira Cermakova, [12] James M. Brophy, [13] Arnold Ryomoto, [14] G.B. John Mancini, [14] and Jacques Genest [1] *

[1] Research Institute of the McGill University Health Centre, Royal Victoria Hospital, Montreal, QC, Canada; [2] Departments of Medicine and Biochemistry, Schulich School of Medicine and Robarts Research Institute, Western University, London, ON, Canada; [3] Lipid Research Centre, CHU de Quebec-Universite Laval, Quebec City, QC, Canada; [4] Division of Experimental Medicine, Department of Medicine, McGill University, Montreal, QC, Canada; [5] Nutrition, Metabolism, and Atherosclerosis Clinic, Institut de recherches cliniques de Montreal, QC, Canada; [6] Division of Medical Biochemistry, Department of Med icine, McGill University, QC, Canada; [7] Department of Nutrition, Universite de Montreal, Montreal, QC, Canada; [8] Lipidology Unit, Community Genomic Medicine Centre and ECOGENE-21, Department of Medicine, Universite de Montreal, Saguenay, QC, Canada; [9] Healthy HeartProgram Prevention Clinic, St. Paul's Hospital, Vancouver, BC, Canada; [10] Department of Medicine, University of British Columbia, Vancouver, BC, Canada; [11] Centre for Heart Lung Innovation, Providence Health Care Research Institute, University of British Columbia, Vancouver, BC, Canada; [12] Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada; [13] McGill University, Royal Victoria Hospital, Montreal, QC, Canada; [14] Department of Medicine, Division of Cardiology, University of British Columbia, Vancouver, BC, Canada.

* Address correspondence to this author at: Institutde recherche du centre universitaire de sante McGill, 1001 boul. Decarie Bloc E, Office EM12212, Montreal, QC, H4A 3J1, Canada. Fax +514-933-6418; e-mail jacques.genest@mcgill.ca.

Received July 11,2017; accepted August 31,2017.

Previously published online at DOI: 10.1373/clinchem.2017.279422

[C] 2017 American Association for Clinical Chemistry

[15] Nonstandard abbreviations: FH, familial hypercholesterolemia; LDL-C, LDL cholesterol; ASCVD, atherosclerotic cardiovascular disease.

[16] Human genes: LDLR, LDL receptor gene; APOB, apolipoprotein B gene; PCSK9, proprotein convertase subtilisin/kexin type 9 gene.

Caption: Fig. 1. Study flow chart.

Caption: Fig. 2. Histogram of observed percent reduction ([+ or -] SE) vs expected percent reduction from Hou et al. (30) for all statins and all doses.

Caption: Fig. 3. Histogram of baseline vs imputed baseline LDL-C ([+ or -] SE) for all doses of statins and ezetimibe. Inset: overall comparison of observed baseline vs imputed baseline LDL-C.

Caption: Fig. 4. Scatterplot of all data (n = 951 patients), including ezetimibe, of observed baseline vs imputed baseline LDL-C. The dotted lines indicate the 95% CIs for the regression line.
Table 1. Expected percent reduction in LDL-C according to dose and
statin and ezetimibe. (a)

                    Mean reduction by dose: percent
                    change from baseline
                    (divide LDL-C by this factor)

Medication             5 mg        10 mg        20 mg

Rosuvastatin        -40 (0.60)   -46 (0.54)   -52 (0.48)
Atorvastatin            --       -37(0.63)    -43 (0.57)
Simvastatin         -26(0.74)    -30 (0.70)   -38 (0.62)
Lovastatin              --       -21 (0.79)   -27 (0.73)
Pravastatin             --       -20(0.80)    -24 (0.76)
Fluvastatin             --           --       -22 (0.78)
Ezetimibe alone         --       -20(0.80)        --
Ezetimibe 10 mg     -20(0.80)    -20 (0.80)   -20 (0.80)
added to a statin

                    Mean reduction by dose: percent
                    change from baseline
                    (divide LDL-C by this factor)

Medication            40 mg        80 mg

Rosuvastatin        -55 (0.45)       --
Atorvastatin        -48 (0.52)   -51 (0.49)
Simvastatin         -41 (0.59)   -47 (0.53)
Lovastatin          -31 (0.69)   -40 (0.60)
Pravastatin         -30 (0.70)   -36 (0.64)
Fluvastatin         -25 (0.75)   -35 (0.65)
Ezetimibe alone         --           --
Ezetimibe 10 mg     -20 (0.80)   -20 (0.80)
added to a statin

(a) Data derived from Hou et al. (30).

Table 2. Baseline and imputed baseline LDL-C. (a)

Statin,                          Baseline           On Rx LDL-C,
dose/mg            Number      LDL-C, mg/dL             mg/dL

Lovastatin, 10       9     265.6 [+ or -] 89.2   199.8 [+ or -] 81.7
Lovastatin, 20       97    255.0 [+ or -] 61.4   182.9 [+ or -] 48.7
Lovastatin, 40       63    258.9 [+ or -] 60.3   176.0 [+ or -] 41.9
Lovastatin, 80       17    317.1 [+ or -] 83.7   218.2 [+ or -] 50.3
Pravastatin, 10      18    229.2 [+ or -] 52.4   174.5 [+ or -] 42.5
Pravastatin, 20      28    258.4 [+ or -] 44.8   180.3 [+ or -] 37.9
Pravastatin, 40      22    279.1 [+ or -] 71.0   183.3 [+ or -] 56.9
Simvastatin, 5       7     271.5 [+ or -] 101.1  208.8 [+ or -] 93.7
Simvastatin, 10      72    246.2 [+ or -] 49.1   179.1 [+ or -] 44.9
Simvastatin, 20      97    267.6 [+ or -] 53.0   172.3 [+ or -] 38.8
Simvastatin, 40      42    280.1 [+ or -] 41.2   185.4 [+ or -] 40.6
Simvastatin, 80      6     282.2 [+ or -] 49.4   142.6 [+ or -] 20.2
Atorvastatin, 10     37    231.4 [+ or -] 51.0   154.3 [+ or -] 42.5
Atorvastatin, 20     58    252.6 [+ or -] 53.4   146.5 [+ or -] 34.0
Atorvastatin, 40     52    289.9 [+ or -] 68.1   157.4 [+ or -] 47.0
Atorvastatin, 80     23    290.8 [+ or -] 70.8   131.2 [+ or -] 31.9
Fluvastatin, 20      10    226.4 [+ or -] 51.0   171.9 [+ or -] 39.1
Fluvastatin, 40      7     234.8 [+ or -] 35.3   157.4 [+ or -] 32.9
Rosuvastatin, 5      34    221.4 [+ or -] 47.1   138.8 [+ or -] 37.0
Rosuvastatin, 10     46    236.9 [+ or -] 50.3   130.1 [+ or -] 41.1
Rosuvastatin, 20     26    273.6 [+ or -] 61.9   139.8 [+ or -] 44.8
Rosuvastatin, 40     6     274.7 [+ or -] 57.1   140.9 [+ or -] 35.0
Ezetimibe, 10       172    169.5 [+ or -] 43.6   123.5 [+ or -] 34.2

Statin,                 Observed         Expected
dose/mg               reduction, %       reduction
                                          (30), %

Lovastatin, 10     24.2 [+ or -] 14.6       21
Lovastatin, 20     27.6 [+ or -] 12.6       27
Lovastatin, 40     30.8 [+ or -] 13.8       31
Lovastatin, 80     28.9 [+ or -] 17.3       40
Pravastatin, 10    22.7 [+ or -] 13.4       20
Pravastatin, 20    29.4 [+ or -] 13.7       24
Pravastatin, 40    33.4 [+ or -] 16.8       30
Simvastatin, 5     24.1 [+ or -] 15.5       26
Simvastatin, 10    27.3 [+ or -] 11.3       30
Simvastatin, 20    34.9 [+ or -] 11.8       38
Simvastatin, 40    32.9 [+ or -] 15.7       41
Simvastatin, 80     48.9 [+ or -] 6.9       47
Atorvastatin, 10   32.7 [+ or -] 14.8       37
Atorvastatin, 20   40.5 [+ or -] 12.9       43
Atorvastatin, 40   45.3 [+ or -] 12.0       48
Atorvastatin, 80   53.0 [+ or -] 13.4       51
Fluvastatin, 20    21.8 [+ or -] 18.4       22
Fluvastatin, 40    32.8 [+ or -] 10.5       25
Rosuvastatin, 5    37.0 [+ or -] 11.6       40
Rosuvastatin, 10    45.4 [+ or -]11.7       46
Rosuvastatin, 20   48.9 [+ or -] 10.8       52
Rosuvastatin, 40   45.5 [+ or -] 23.1       55
Ezetimibe, 10      26.3 [+ or -] 13.7       20

                                                      Pearson
                                                      correlation
Statin,                  Imputed
dose/mg                LDL-C, mg/dL          P         r        P
                                          value (b)   value   value

Lovastatin, 10     252.9 [+ or -] 103.4     0.50      0.85    0.004
Lovastatin, 20     250.5 [+ or -] 66.7      0.32      0.76    <0.001
Lovastatin, 40     255.1 [+ or -] 60.7      0.59      0.58    <0.001
Lovastatin, 80     363.6 [+ or -] 83.8      0.05      0.40    0.107
Pravastatin, 10    218.1 [+ or -] 53.2      0.32      0.62    0.006
Pravastatin, 20    237.3 [+ or -] 49.9      0.03      0.49    0.007
Pravastatin, 40    261.8 [+ or -] 81.3      0.30      0.51    0.015
Simvastatin, 5     282.2 [+ or -] 126.7     0.56      0.94    0.002
Simvastatin, 10    255.8 [+ or -] 64.1      0.04      0.79    <0.001
Simvastatin, 20    277.9 [+ or -] 62.6      0.04      0.66    <0.001
Simvastatin, 40    314.3 [+ or -] 68.8      0.003     0.27     0.09
Simvastatin, 80    269.1 [+ or -] 38.2      0.43      0.67     0.15
Atorvastatin, 10   244.9 [+ or -] 67.5      0.10      0.70    <0.001
Atorvastatin, 20   257.1 [+ or -] 59.7      0.49      0.62    <0.001
Atorvastatin, 40   302.6 [+ or -] 90.4      0.16      0.71    <0.001
Atorvastatin, 80   267.7 [+ or -] 65.1      0.14      0.43     0.04
Fluvastatin, 20    220.4 [+ or -] 50.1      0.76      0.30     0.40
Fluvastatin, 40    209.9 [+ or -] 43.9      0.10      0.66     0.11
Rosuvastatin, 5    231.4 [+ or -] 61.6      0.20      0.70    <0.001
Rosuvastatin, 10   241.0 [+ or -] 76.1      0.58      0.76    <0.001
Rosuvastatin, 20   291.3 [+ or -] 93.3      0.18      0.71    <0.001
Rosuvastatin, 40   313.1 [+ or -] 77.9      0.45      -0.42    0.41
Ezetimibe, 10      154.3 [+ or -] 42.7     <0.001     0.69    <0.001

(a) For each statin (lovastatin, 10,20,40, and 80 mg-day),
pravastatin (10,20, and 40 mg-day), simvastatin (5,10,20,40, and 80
mg-day), atorvastatin (10,20,40, and 80 mg-day), fluvastatin (20 and
40 mg-day), rosuvastatin (5,10,20, and 40 mg-day), and ezetimibe (10
mg-day), the number of subjects, baseline and on-treatment, the
observed reduction for each dose of statins and ezetimibe, the
expeded redudion, and the imputed baseline LDL-C are shown.

(b) P value is for paired f-tests between observed baseline LDL-C and
imputed baseline LDL-C. The nominal level of significance for
multiple testing is set at P< 0.002. The Pearson linear correlation
coefficient (r) and P value for baseline LDL-C and imputed baseline
LDL-C are also shown. Results are expressed in mean [+ or -] SD.
For SI units, please see Table 1 in the online Data Supplement.
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Title Annotation:Lipids, Lipoproteins, and Cardiovascular Risk Factors
Author:Ruel, Isabelle; Aljenedil, Sumayah; Sadri, Iman; de Varennes, Emilie; Hegele, Robert A.; Couture, Pa
Publication:Clinical Chemistry
Date:Feb 1, 2018
Words:5024
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