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News 15/07/2544


EFFICACY OF ATORVASTATIN IN ACHIEVING NATIONAL CHOLESTEROL EDUCATION PROGRAM LOW-DENSITY LIPOPROTEIN TARGETS IN WOMEN
Recent improvements have been made in the diagnosis and treatment of cardiovascular disease (CVD) in women, including recognition of the benefits of lipid lowering.

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Efficacy of Atorvastatin in Achieving National Cholesterol Education Program Low-Density Lipoprotein Targets in Women With Severe Dyslipidemia and Cardiovascular Disease or Risk Factors for Cardiovascular Disease: The Women's Atorvastatin Trial on Cholesterol (WATCH)

Ruth McPherson, MD, PhD, FRCPC,a Carmella Angus, MSc,b Peter Murray, BS,b and Jacques Genest, Jr, MD, FRACP,c for the WATCH Investigators Ottawa, Ontario, Canada, and Montreal, Quebec, Canada.

[Am Heart J 141(6):949-956, 2001. © 2001 Mosby-Year Book, Inc.]


Abstract

Background: Recent studies have demonstrated that women at high risk for cardiovascular disease (CVD) benefit from cholesterol lowering to an extent similar to that of men. The ability to achieve established treatment goals for low-density lipoprotein cholesterol (LDL-C) in women with clearly defined risk factors has not been examined in detail.
Methods and Results: We have determined the efficacy and frequency of achieving target levels for LDL-C with atorvastatin on the basis of National Cholesterol Education Program Adult Treatment Panel II recommendations in 318 women according to the presence of CVD (198 women) or risk factors for CVD (120 women) and the presence of mixed dyslipidemia with obesity with or without CVD (72 women). Mean baseline LDL-C concentrations for women with established CVD were in the upper 10% of the distribution for age-matched North American women and, for those without CVD, were also extremely elevated and were in the top 5% of the LDL-C distribution for age-matched women in this population. The majority of participants without CVD (63%) reached LDL-C targets (LDL-C 160 mg/dL [4.1 mmol/L] if <2 CHD risk factors and LDL-C 130 mg/dL [3.4 mmol/L] if 2 CVD risk factors) with 10 mg atorvastatin and 79% reached targets with up to 20 mg of atorvastatin. For women with established CVD, 34% achieved an LDL-C 100 mg/dL (2.6 mmol/L) with 10 mg and 60% reached this target with up to 20 mg of atorvastatin. With maximal titration to the LDL-C target, up to and including 80 mg atorvastatin, 87% of women without CVD and 80% of women with established CVD achieved LDL-C targets. The presence of mixed dyslipidemia with obesity did not affect the frequency of achieving LDL-C targets.
Conclusion: Atorvastatin is very effective in achieving National Cholesterol Education Program Adult Treatment Panel II target concentrations for LDL-C in the majority of women with established CVD or CVD risk factors.

Introduction

Recent improvements have been made in the diagnosis and treatment of cardiovascular disease (CVD) in women, including recognition of the benefits of lipid lowering.[1-8] However, many women with CVD do not receive adequate low-density lipoprotein cholesterol (LDL-C) lowering therapy. In the Heart and Estrogen/
Progestin Replacement Study (HERS), only 10% of the 2763 women with CVD enrolled in the trial had achieved an LDL-cholesterol of 100 mg/dL.[9] The reasons for failure to achieve National Cholesterol Education Program Adult Treatment Panel II (NCEP ATP II) targets are multiple and include the moderate efficacy of older cholesterol-lowering agents[10] and failure to increase medication dose or to use combination therapy. Patients with abdominal obesity and concomitant mixed dyslipidemia are at high risk for CVD,[11,12] but few studies have determined whether patients with this atherogenic phenotype respond adequately to statin monotherapy. The WATCH Study (Womens' Atorvastatin Trial on Cholesterol) was a multicenter 16-week study in women with dyslipidemia carried out in 43 Canadian centers; it represents the first prospective study of lipid lowering in a large population of women with well-defined CVD risk factors, with and without CVD. The WATCH Study was designed to determine the efficacy and frequency of achieving guideline (NCEP ATP II) target LDL-C concentrations according to the presence of coronary heart disease or risk factors and the presence of mixed dyslipidemia with obesity with atorvastatin therapy.

Methods

Study Design

This study was a 16-week, open-label, nonrandomized, treat-to-target clinical trial using atorvastatin with conditional titration from 10 to 80 mg given once a day dependent on the achievement of LDL-C targets in all eligible patients. Study patients were classified into 2 primary subgroups as having either confirmed CVD or risk factors for CVD according to the NCEP ATP II risk factor count (<2 and 2 risk factors). CVD was defined as established atherosclerosis present in one or more of the coronary, cerebral, and or peripheral vascular beds. Criteria for CVD included confirmed ischemia on rest or exercise electrocardiogram or cardiac perfusion imaging, documented myocardial infarct, angiographic evidence of coronary or peripheral atherosclerosis, carotid or ileofemoral bruit, history of transient ischemic attack or nonhemorrhagic stroke, or revascularization procedure. At screening (week -3), a complete medical history and physical examination were completed and any current lipid-lowering medications were withdrawn before a 3-week dietary stabilization period. At baseline (week 0) all patients were assigned to an initial dose of atorvastatin 10 mg with a conditional titration to 20 mg at week 4, to 40 mg at week 8, and to 80 mg at week 12 as required to achieve NCEP ATP II LDL-C target concentrations (Figure 1).

figure1


Figure 1. Atorvastatin treatment schedule: This was a 16-week study with a screening visit at week -3. All eligible patients with and without prior lipid treatment underwent a 3-week washout period on diet alone. At baseline (week 0) patients started treatment with atorvastatin 10 mg with a conditional titration to 20 mg at week 4, to 40 mg at week 8, and to 80 mg at week 12 dependent on the dose required to achieve NCEP LDL-C targets. Once the LDL-C target was reached, the patient remained at the target dose for the remainder of the study.


Study Patients

Patients were recruited at 43 secondary and tertiary referral sites in Canada. Inclusion criteria were women, aged 18 to 75 years inclusive, who met NCEP ATP II LDL-C criteria for untreated or treated patients and who were using an acceptable method of contraception or who were postmenopausal. The NCEP ATP II LDL-C criteria for eligibility were as follows: (1) women with a diagnosis of CVD: LDL-C 130 mg/dL (3.4 mmol/L) if not currently treated with hypolipidemic medication or LDL-C 100 mg/dL (2.6 mmol/L) if on hypolipidemic medication; (2) women with 2 CVD risk factors: LDL-C 160 mg/dL (4.1 mmol/L) if not currently treated with hypolipidemic medication or LDL-C 130 mg/dL (3.4 mmol/L) if on hypolipidemic medication; (3) women with <2 CVD risk factors: LDL-C 190 mg/dL (4.9 mmol/L) if not currently treated with hypolipidemic medication or LDL-C 160 mg/dL (4.1 mmol/L) if on hypolipidemic medication. Patients previously treated with a lipid-lowering medication who after a 3-week washout period off medication met the NCEP ATP II criteria for untreated patients were considered eligible for initiation of drug treatment. Risk factors were assessed according to NCEP ATP II[8] as follows:

Positive risk factors

Negative risk factor

Qualifying women were also classified according to the presence or absence of mixed dyslipidemia with obesity, defined as LDL-C >130 mg/dL (3.4 mmol/L), triglycerides >200 mg/dL (2.3 mmol/L), body mass index (BMI) >26 kg/m[2], and abdominal circumference >90 cm. Patients were excluded from the study if they had known hypersensitivities to 3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitors, were pregnant or breast-feeding, had serum creatine phosphokinase (CPK) >3 times the upper normal limit, used any investigational drug within 30 days before screening, consumed >14 ounces of alcohol per week, or required treatment with erythromycin or immunosuppressive agents. Patients were also excluded if they had a history of unstable angina pectoris, myocardial infarction, coronary angioplasty, coronary artery bypass grafting, or major surgery within the prior 3 months, type I diabetes or onset of diabetes before the age of 30 years, untreated hypothyroidism, renal disease, or hepatic dysfunction. The study was approved by the Institutional Review Board of each participating center and informed written consent was obtained from all patients.

Laboratory Analyses

Primary laboratory assessments at screening, at baseline, and at end point included a full lipid profile and standard laboratory tests (biochemistry and hematology). Adverse events and laboratory parameters (alanine aminotransferase, aspartate aminotransferase, CPK, total bilirubin, and alkaline phosphatase) were performed at screening and the end of the study. Additional laboratory safety assessments were obtained if malaise or muscle symptoms were reported. A full lipid profile after a 14-hour fast was completed at each of the 6 visits. Lipoproteins were measured according to the Lipid Research Clinic's Manual of Laboratory Operations using methods that were standardized in the Centers for Disease Control and Prevention-National Heart, Lung, and Blood Institute Lipid Standardization Program.[13,14] The Friedewald equation was used to calculate LDL-C for samples with triglycerides 430 mg/dL (4.8 mmol/L).[15] LDL-C determination by ultracentrifugation was performed when triglycerides were >430 mg/dL (4.8 mmol/L) (as the difference between the d <1.006 g/mL cholesterol and HDL-C).

Statistical Analysis

The sample size was based on a 2-sided test of comparisons of proportions at the 5% level of significance. A sample size of 125 patients per strata for a total of 250 patients was calculated to provide 80% power to detect a difference of 18% between groups. The results presented are based on intent-to-treat data. Categorical outcome measures were analyzed with a Cochran-Mantel-Haenzel[16] analysis that stratified according to the presence of CVD or risk factors for CVD. The analysis of percent reduction from baseline was performed using an analysis of covariance[17] that included baseline lipid level as a covariate and center number. The c[2] test was used to test discrete variables, and the Student t test was used to test continuous variables. All statistical analyses were carried out by Innovus Research, Burlington, Ontario, Canada.

Results

Patient Characteristics

A total of 353 female patients were eligible on initial screening. Of those, 35 patients failed to qualify for active treatment on the basis of ineligible lipids after the 3-week washout period (28 patients), abnormal laboratory values (3 patients), adverse events (1 patient), and administrative reasons (3 patients). A total of 318 women initiated study treatment and consisted of 120 women with risk factors for CVD and 198 with confirmed CVD. Of the CVD group, 85% had confirmed CVD and the remainder had clinically evident peripheral vascular disease or carotid artery disease. Study subjects are described in Table I. CVD risk factors for patients with and without CVD were similar. However, CVD patients were significantly older and the majority were postmenopausal (82%). Total cholesterol concentrations at baseline were higher for non-CVD patients but other lipid variables did not differ significantly. A total of 261 patients were postmenopausal and 91 of these were on hormone replacement therapy (HRT) (>90% of these were on oral estrogen with or without progestin). For women in the postmenopausal category, 38% of those without CVD and 33% of those with CVD were on HRT. BMI (weight [kg]/height [m2]) and abdominal girth were similar for patients with and without CVD (Table I). Patients (CVD and non-CVD) with mixed dyslipidemia with obesity (23% of patients) demonstrated differences in the frequency of several CHD risk factors (Table II).

Before entry into the study, 48% of patients in the non-CVD group and 75% of patients in the CVD group had been treated with lipid-lowering medication, statins other than atorvastatin being the most commonly prescribed therapy (91% for patients of both groups). Before the study, despite statin therapy, these patients had not achieved the LDL-C target. For non-CVD patients, LDL-C concentrations after the 3-week washout period were significantly higher for those previously treated with hypolipidemic medication (263 ± 70 mg/dL [6.8 ± 1.8 mmol/L] vs 217 ± 62 mg/dL [5.6 ± 1.6 mmol/L] [P = .001]), but for CVD patients the baseline LDL-C level did not differ according to the presence or absence of previous hypolipidemic treatment.

Efficacy Achievement of NCEP ATP II Target LDL-C

With rapid titration at 4-week intervals and, despite the presence of severe dyslipidemia, the majority of WATCH participants without CVD (63%) reached LDL-C targets with 10 mg of atorvastatin, 79% with up to 20 mg, and, with maximal titration up to 80 mg atorvastatin, 87% of women achieved LDL-C targets. Of women with established CVD and very elevated LDL-C concentrations, 34% reached the LDL-C target of 100 mg/dL (2.6 mmol/L) with 10 mg and 60% with up to 20 mg of atorvastatin, and with maximal titration up to 80 mg, 80% of women with CVD achieved the LDL-C target (Figure 2). The major determinants of the dose of atorvastatin required to achieve the NCEP ATP II target were the initial LDL-C concentration and the presence or absence of CVD, which dictated the LDL-C treatment target (Figures 3 and 4). At 10 mg, the frequency of reaching the LDL-C target was significantly different between patients with and without established CVD, although with maximal titration to, and including, 80 mg the frequency of reaching LDL-C targets was similar for both groups. For patients without CVD, the mean baseline LDL-C level for patients who did not reach target on 80 mg of atorvastatin was 337 mg/dL (8.7 mmol/L). For patients with CVD, the mean baseline LDL-C for patients who did not achieve target on 80 mg of atorvastatin was 298 mg/dL (7.7 mmol/L). Patients who met the criteria for mixed dyslipidemia with obesity achieved the NCEP LDL-C goals with a frequency not significantly different compared with those patients who did not have this metabolic profile (87% vs 81%). The percentage of patients achieving NCEP ATP II LDL-C goals was 78% (67/86) for patients previously treated with hypolipidemic medication (but not having achieved LDL-C target at entry into the study) and 85% (174/205) for patients not previously treated with hypolipidemic medication. This difference did not reach statistical significance.

figure2


Figure 2. Cumulative frequency of achieving NCEP ATP II LDL-C target by atorvastatin dose and cardiac risk group. The majority of WATCH participants without CVD (63%) reached LDL-C targets with 10 mg of atorvastatin, 79% with up to 20 mg, and with maximal titration up to 80 mg atorvastatin 87% of women achieved LDL-C targets. For women with established CVD, 34% reached the LDL-C target of 100 mg/dL (2.6 mmol/L) with 10 mg and 60% with up to 20 mg of atorvastatin and with maximal titration up to 80 mg 80% of women with CVD achieved LDL-C target.


figure3


Figure 3. Mean LDL-C concentrations at baseline and termination by dose at first achievement of target for non-CVD patients. This figure shows both the mean baseline LDL-C concentrations as well as the mean LDL-C level of patients who achieved LDL-C targets at each titrated dose. Three parallel lines indicate LDL-C targets dependent on NCEP ATP II risk category. This figure shows a continuous increase in the mean baseline LDL-C at each titrated dose of atorvastatin with a parallel increase in the mean percent reduction of LDL-C. The mean percent reduction at 80 mg includes only 3 patients and therefore is not a reliable mean percent reduction at the 80 mg dose. Patients who did not achieve targets had a mean baseline LDL-C of 337 mg/dL (8.7 mmol/L).


figure4


Figure 4. Mean LDL-C concentrations at baseline and termination by dose at first achievement of target for CVD patients. This figure shows both the mean baseline LDL-C concentrations as well as the mean LDL-C level of patients who had achieved LDL-C targets at each titrated dose. Three parallel lines indicate LDL-C targets dependent on NCEP ATP II risk category. The LDL-C target for the CVD group was 100 mg/dL (2.6 mmol/L). This figure shows a continuous increase in the mean baseline LDL-C at each titrated dose of atorvastatin with a parallel increase in the mean percent reduction of LDL-C at each dosage increase. Patients who did not achieve target had a mean baseline LDL-C of 298 mg/dL (7.7 mmol/L).


Efficacy Lipid Lowering

Patients with and without CVD enrolled in this study had relatively high baseline total cholesterol and LDL-C concentrations. Atorvastatin treatment resulted in highly significant changes in mean plasma concentrations of all lipoprotein fractions (Table III, Figures 3 and 4). The patients with mixed dyslipidemia and obesity entered the study with higher concentrations of triglycerides and lower concentrations of HDL-C. The mean decreases in LDL-C, triglycerides, and apolipoprotein B were not significantly different but the increase in HDL-C was greater for patients with mixed dyslipidemia and obesity compared with patients without this phenotype (Table IV).

Adverse Events

The most frequently reported adverse events considered possibly related to atorvastatin treatment were mild to moderate headache (5% of patients) and constipation (6% of patients). Four patients had mild myalgia that resulted in discontinuation of atorvastatin treatment. One patient had an increase in creatine kinase, resulting in study discontinuation. Two CVD patients died of cardiac causes during the study.

Discussion

In a population of women with CVD or risk factors for CVD and dyslipidemia, we have demonstrated that atorvastatin is highly effective in achieving NCEP ATP II target levels for LDL-C. The current study demonstrates that achievement of an LDL-C target of 100 mg/dL (2.6 mmol/L) is feasible for the majority of women with clinically evident CVD and dyslipidemia. Mean baseline LDL-C concentrations for participating women with established CVD were in the upper 10% of the distribution for age-matched North American women and for those without CVD were in the top 5% of the LDL-C distribution for age-matched women in this population (based on data from the Lipid Research Clinic's Prevalence Study[18]). Despite these high baseline LDL-C concentrations, the majority of patients achieved NCEP ATP II LDL-C targets during atorvastatin treatment.

No previous study has determined the ability to achieve NCEP targets for LDL-C in women with clearly defined risk factors. In a recent 1-year treat-to-target comparative study in male and female patients with established CVD, treatment with 10 mg of atorvastatin resulted in achievement of NCEP-recommended target LDL concentrations in 32% of patients; 53% of patients achieved target concentrations with 10 to 20 mg of atorvastatin and 79% reached targets with up to 80 mg of atorvastatin.[19] In another trial in patients without documented CVD, 71% of patients attained NCEP target LDL-C goals with 10 mg of atorvastatin, 81% with 10 to 20 mg of atorvastatin, and 92% with up to 80 mg of atorvastatin.[20]

In the current study the percentage decrease in LDL-C and the absolute decrease in LDL-C increased with increasing doses of atorvastatin and were greatest for those patients with higher baseline LDL-C concentrations. Overall, 87% of patients without CVD and 80% of patients with CVD achieved the LDL-C target. Mean baseline LDL-C concentrations in those patients not achieving target were very high (337 mg/dL [8.7 mmol/L] for the non-CVD group and 298 mg/dL [7.87 mmol/L] for the CVD group), and such patients frequently require combination therapy to achieve optimal lipid concentrations.

In the current study particular care was taken to categorize study subjects in terms of major risk factors and the presence or absence of established CVD. In addition, we determined CVD risk factor status and response to atorvastatin for women with and without mixed dyslipidemia and obesity. CVD is the most common cause of death in women and the CVD risk factor distribution was similar for study women with and without clinically evident CVD, with the major difference between the 2 groups being age. Patients with a diagnosis of CVD were, on average, 5 years older than those without established CVD. An HDL-C level below 35 mg/dL (0.9 mmol/L) is a major risk factor for CVD[1,2] and was present in 13% of women without and 12% of women with CVD in the current study. Of note, 15% of women with clinically evident CVD had HDL-C concentrations 60 mg/dL (1.6 mmol/L). The relatively high frequency of HDL-C 60 mg/dL among women with CVD participating in the current study was partly, but not fully, explained by concomitant use of HRT. Although Framingham data demonstrate that the total cholesterol to HDL-C ratio is generally a reliable index of cardiovascular risk,[21] few Framingham women had LDL-C concentrations above 200 mg/dL (5.2 mmol/L) and the relationship between the total cholesterol to HDL-C ratio and CVD risk may not be similarly applicable in patient populations with significant hypercholesterolemia. This analysis suggests that physicians should not underestimate CVD risk in women with high plasma concentrations of HDL-C when LDL-C is also elevated.

There are accumulating data indicating that abdominal obesity is a risk factor for CVD and that much of this risk is explained by the presence of associated risk factors.[11,12] Patients in the current study, with mixed dyslipidemia and obesity, demonstrated a significantly greater frequency of 3 important CVD risk factors, including diabetes mellitus, HDL-C below 35 mg/dL (<0.9 mmol/L), and cigarette smoking and a significantly lower frequency of a negative CVD risk factor, HDL-C 60 mg/dL (1.6 mmol/L). The presence of abdominal obesity did not, however, affect the LDL-C response to atorvastatin therapy. Atorvastatin has been shown to reduce hepatic secretion of very-low-density lipoproteins (VLDL), resulting in a reduction in plasma triglycerides as well as LDL-C.[22] Mixed dyslipidemia and abdominal obesity are often associated with increased hepatic VLDL secretion, and women in this category demonstrated a greater reduction in triglycerides and increase in HDL-C in response to atorvastatin therapy compared with women without this phenotype.

Cardiovascular disease is the most common cause of death in postmenopausal women and primary and secondary prevention strategies, particularly LDL-C lowering, deserve greater emphasis. Recent studies have emphasized that a large gap exists between actual and recommended cholesterol treatment for women with CVD.[9] This study, using atorvastatin monotherapy, demonstrates that achievement of NCEP-recommended LDL-C targets is feasible for the majority of women with dyslipidemia, including those with relatively severe dyslipidemia, with or without established CVD.

Statistical analyses were carried out by D. Pericak, Innovus Research Inc, Burlington, Ontario, Canada.

From the aUniversity of Ottawa Heart Institute, Ottawa, Ontario, Canada, bParke-Davis Canada, Toronto, Ontario, Canada, and the cClinical Research Institute of Montreal, Montreal, Quebec, Canada.

Table I. Demographics at baseline for intent-to-treat population by cardiac risk group

  Non-CVD
(n = 120)		 CVD
(n = 198)
Demographics
   Age (y) 54.7 ± 12.1 60.3 ± 8.7*
   BMI (kg/m2) 28.9 ± 5.3 28.1 ± 6.1
   Abdominal circumference (cm) 90.9 ± 14.7 89.2 ± 13.5
   Waist-to-hip ratio 0.85 ± 0.09 0.85 ± 0.07
   SBP (mm Hg) 127 ± 18 131 ± 16
   DBP (mm Hg) 79 ± 10 77 ± 8
   White race (%) 95 95
   Postmenopausal (%) 70 89*
   On HRT (%) 27 30
Risk factor prevalence (No. [%])
   55 y old/menopausal/no HRT 72 (60%) 149 (75%)*
   Family history or premature CVD 65 (54%) 111 (56%)
   Cigarette smoker 23 (19%) 58 (29%)
   Hypertension 51 (43%) 114 (58%)
   Diabetes mellitus 11 (9%) 21 (11%)
   HDL-C 35 mg/dL (0.9 mmol/L) 16 (13%) 24 (12%)
   HDL-C 60 mg/dL (1.6 mmol/L) 7 (6%) 30 (15%)
   <2 risk factors and no CVD 41 (34%)  
   2 risk factors and no CVD 79 (66%)  


Data are expressed as mean ± SD.
*P < .01 between groups.




Table II. Risk factor history by presence or absence of mixed dyslipidemia with obesity

Risk factor Mixed dyslipidemia
with obesity
Present
(n = 72)		 Absent
(n = 240)
55 y old/menopausal/no HRT 56 (78%) 160 (67%)
Family history of premature CVD 37 (51%) 135 (56%)
Cigarette smoker 27 (38%) 53 (22%)*
Hypertension 44 (61%) 119 (50%)
Diabetes mellitus 14 (19%) 17 (7%)*
HDL-C 35 mg/dL (0.9 mmol/L) 19 (26%) 21 (9%)*
HDL-C 60 mg/dL (1.6 mmol/L) 2 (3%) 34 (14%)*


*P < .01 between groups.




Table III. Lipids at baseline and termination: non-CVD and CVD patients

  Non-CVD (n = 120) CVD (n = 198)
Baseline Final Baseline Final
Cholesterol
   mg/dL 314.9 ± 67.1 210.3 ± 31.0* 299.3 ± 63.0 199.1 ± 34.6*
   mmol/L 8.1 ± 1.7 5.4 ± 0.8* 7.7 ± 1.6 5.0 ± 0.9*
Triglycerides
   mg/dL 212.1 ± 87.6 169.8 ± 76.5* 226.0 ± 82.3 164.5 ± 63.7*
   mmol/L 2.4 ± 1.0 1.9 ± 0.9* 2.5 ± 0.9 1.9 ± 0.7*
LDL-C
   mg/dL 226.2 ± 65.6 128.3 ± 31.2* 206.3 ± 60.9 111.1 ± 32.1*
   mmol/L 5.8 ± 1.7 3.3 ± 0.8* 5.3 ± 1.6 2.9 ± 0.8*
HDL-C
   mg/dL 46.7 ± 9.9 48.8 ± 11.8 48.1 ± 11.8 48.4 ± 11.0
   mmol/L 1.21 ± 0.26 1.26 ± 0.30 1.24 ± 0.30 1.25 ± 0.28
Apolipoprotein B (g/L) 2.10 ± 0.46 1.35 ± 0.24* 1.99 ± 0.43 1.24 ± 0.28*


Data are presented as mean ± SD.
*P < .0001 versus baseline.




Table IV. Lipids at baseline and termination by presence or absence of mixed dyslipidemia and abdominal obesity

  Mixed dyslipidemia and abdominal obesity
Present (n = 72) Absent (n = 240)
Baseline Final Baseline Final
Cholesterol
   mg/dL 306.4 ± 55.6 200.6 ± 3.5* 305.3 ± 67.7 198.7 ± 34.9*
   mmol/L 7.9 ± 1.4 5.2 ± 0.9* 7.9 ± 1.8 5.1 ± 0.9*
Triglycerides
   mg/dL 293.8 ± 55.5 216.9 ± 1.7* 199.3 ± 79.4 151.3 ± 59.6*
   mmol/L 3.3 ± 0.6 2.4 ± 0.8* 2.2 ± 0.9 1.7 ± 0.7*
LDL-C
   mg/dL 206.9 ± 55.0 114.2 ± 1.6* 216.3 ± 65.6 119.1 ± 33.1*
   mmol/L 5.4 ± 1.4 3.0 ± 0.8* 5.6 ± 1.7 3.1 ± 0.9*
HDL-C
   mg/dL 41.5 ± 8.5 44.1 ± 0.5* 49.3 ± 11.2 49.7 ± 11.1
   mmol/L 1.07 ± 0.22 1.14 ± 0.27* 1.27 ± 0.29 1.28 ± 0.29
Apolipoprotein B (g/L) 2.10 ± 0.36 1.35 ±.23* 2.02 ± 0.47 1.27 ± 0.28*


Data are presented as mean ± SD.
*P < .0001 versus baseline.




References

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Book Review

How to Read a Paper: The Basics of Evidence Based Medicine, 2nd Edition


By Trisha Greenhalgh
BMJ Books
Copyright 2001
222 pages
ISBN: 0-7279-1578-9
$29.95 paperback

Reviewed by: Lorri Zipperer, MA

The term "evidence based" has evolved into a trendy way of describing many efforts to improve process, service, and decision making. When the first edition of How to Read a Paper: The Basics of Evidence Based Medicine came out, a smattering of academics were just beginning to explore the concept of applying results from systematic research to clinical practice. Now, as author Trisha Greenhalgh states, evidence-based medicine (EBM) has become a growth industry. Per Greenhalgh's calculations, there are currently 200 other books, 200 Web sites, and over 1500 articles available on the topic. For the initiate, these other offerings probably don't include many better resources about the application of scientific review methods than How to Read a Paper. In fact, the book is listed by the highly regarded Brandon/Hill list as 1 of 5 suggested EBM titles to include in a core hospital library collection.[1] Indeed, author Greenhalgh, a physician who teaches at Royal Free and University College Medical School in London, is qualified, funny, instructional, and succinct in her explanations. She does a good job of justifying why one should learn about EBM.

How to Read a Paper consists of 12 chapters that outline key issues one must grasp in order to understand the EBM process, and presents subsets of literature ripe for EBM review. The book opens by discussing why EBM is important, briefly touching on the controversy about its practicality and the difficulty of getting clinicians who are used to practicing medicine in a distinct manner to adopt EBM methods. Greenhalgh next covers why the literature should be read and how it can be found most effectively through online searching.

The meatiest section of the book dives into the nitty-gritty of teaching readers to critically appraise medical literature. First, Greenhalgh outlines the 3 major elements of a paper the reader should look at to determine the validity of published research: the type of study it reports, the methodologic quality of the reported activity, and the statistics supporting the conclusions. Once the chapter on statistics has been ingested (the author fully recognizes the universal aversion to statistics and makes plowing through this chapter as painless as possible), distinct types of literature and studies are singled out, common faults highlighted, and questions posed to help the reader ascertain their quality. Pharmacologic studies, diagnostic test explorations, systematic reviews, meta-analyses, clinical guidelines, cost analyses, and qualitative research reports are all discussed with an evidence-based eye.

The final pages of the book are practical in nature. Greenhalgh suggests how to implement evidence-based findings. She then presents a set of appendices and checklists that give the reader a snapshot of what they need to take away from the book in each distinct area. There is, of course, an index to the volume.

Greenhalgh's chapters are replete with definitions, real-life examples, tables, and charts that illustrate the concepts outlined. By adding new references [albeit somewhat British in their scope] to the second edition that support her ideas and instructions, her book becomes a tool to be used both to make headway in understanding the process and as a link to more in-depth treatments on the issue; it is an easier, more practical companion to some lengthier treatments of the subject, such as Sackett's 1991 text Clinical Epidemiology - A Basic Science for Clinical Medicine, which Greenhalgh refers to often,[2] and the recently compiled series of JAMA articles, Users' Guides to the Medical Literature.

A few quibbles. It is curious that in the clearly written "How to Search" chapter, Greenhalgh chooses to demonstrate search functionality by using a Medline vendor that is apt to not be used by a wider audience. PubMed, although perhaps not the most sophisticated search tool, is available free via the US National Library of Medicine's Web page. Illustrating these techniques by using PubMed may have served a broader, international audience who may not have access to more costly versions of Medline.

It is somewhat curious that more of a reflection of the work of K. Ann McKibbon and others from McMaster University in Hamilton, Canada, and the Centres for Health Evidence aren't mentioned; but then again, this author is somewhat Anglo-centric in the examples she chooses and doesn't promise comprehensiveness on the subject.

This book is also text heavy. How to Read a Paper, while building some useful tables and charts, would benefit from a designer's eye. The checklists are a prime example. Another possibility would be to include screen presentations in the next edition to help bring the searching chapters to life.

The biggest omission, however, is the lack of a glossary. It would make the book more useful to have the fine definitions scattered throughout its pages all in one place for ease of access. Granted, the index does help one locate terms and meanings, but a glossary would make that easier.

Due to the proliferation of electronic peer-reviewed journals and the Internet, more people now have access to medical literature than in 1997 when the first edition of How to Read a Paper was released. Greenhalgh provides this ever-widening audience with the guidance they might need, not only to work their way through the morass of new publications, but also to make medical knowledge and experience more useful to improve patient care. This title gives the reader -- medical student, primary researcher, librarian, practitioner, or invested patient -- a pragmatic, systematic tool from which to approach the assessment of the validity of research in medicine.


References
1. Hill DR, Stickell HN. The Brandon/Hill select list of print books and journals for the small medical library. Bull Med Libr Assoc. 2001;89:131-153.
2. Sackett DL, Haynes RB, Guyatt GH, Tugwell P. Clinical Epidemiology -- a Basic Science for Clinical Medicine. London: Little Brown; 1991.


Melatonin Helps Sleep Quality in Diabetics, Facilitates Withdrawal From Benzodiazepines


VANCOUVER, British Columbia (Reuters Health) Jul 06 - As a person ages, the incidence of sleep disorders increases and the quality of sleep decreases. But melatonin usage may help older persons with insomnia, according to two related studies presented here on Wednesday at the 17th Congress of the International Association of Gerontology.

Israeli researchers reported that controlled-release melatonin (CRM) improved sleep quality in type 2 diabetics with insomnia and also facilitated discontinuation of benzodiazepines in an elderly population.

"Melatonin is secreted in response to darkness," said Dr. Doron Garfinkel, who is from the department of Aging Research and Internal Medicine at E. Wolfson Medical Center, in Holon. "It induces sleep through its synchronizing effect on the internal biologic clock."

In a randomized double-blind crossover trial, 38 type 2 diabetics used CRM or a placebo for 3 weeks. The objective of the study was to assess the efficacy of CRM in improving sleep quality in diabetic patients, and also to evaluate its influence on antioxidants, biochemicals and metabolic parameters.

At follow-up, there was a 3.6% increase in sleep efficiency, and a 38.6% decrease in nocturnal awakenings.

"The patients had been spending more than an hour awake, Dr. Garfinkel told conference attendees. "The time awake went down from an average of 63 minutes to 31 minutes, so it's quite an impressive improvement."

CRM had no significant effect on serum glucose, fructosamine, insulin, C-peptide or antioxidant levels. It did appear, however, to influence hemoglobin A1C (HbA1C) concentration, and after 6 months of using CRM at a dosage of 2 mg, HbA1C concentrations decreased. This effect was most pronounced in diabetics who high HbA1C levels.

Dr. Garfinkel concluded that overall, CRM replacement therapy improved sleep quality in type 2 diabetics suffering from insomnia, and also had a beneficial effect on HbA1C levels.

The second study, the investigators found that CRM effectively facilitated withdrawal from benzodiazepines, which were prescribed for sleep disorders.

"Benzodiazepines are widely used in the elderly population for the initiation of sleep," Dr. Garfinkel said. "And we also know that very frequently complaints about poor sleep maintenance persist, despite benzodiazepine treatment."

According to literature, benzodiazepines are only supposed to be used for 6 weeks, but they are often used for months or even years, he added. Benzodiazepines can also inhibit and suppress nighttime production of melatonin.

In a double-blind controlled trial, 34 benzodiazepine users were given 2 mg of CRM or placebo nightly

The subjects were encouraged to decrease their benzodiazepine usage by 50% during week 2, by 75% between weeks 3 and 4, and to stop completely between weeks 5 and 6. CRM was later administered to all of the study subjects for another 6 weeks.

At week 6, almost 80% of the subjects were able to discontinue their benzodiazepines. After 2 years, 60% of the subjects had not gone back to using them. Of this group, 52% continued to take CRM.

Eighteen percent of the group was able to reduce usage of benzodiazepines by about 30%. All of the study participants reported good quality of sleep, despite the fact that they had either discontinued or stopped their benzodiazepines.

Dr. Garfinkel concluded that "controlled release melatonin can facilitate benzodiazepine discontinuation, or significantly reduce its dosage, while maintaining the same or better sleep."


US Drugstores Look Beyond Borders for Pharmacists


NEW YORK (Reuters Health) Jul 06 - Faced with rapid growth in the use of prescription drugs, the United States may soon have to try to attract pharmacists from abroad, in the same way software companies did for programmers did in the 1990s to sustain the boom in the high-tech economy.

Obtaining working visas for pharmacists from countries such as South Africa and India would help retail drugstores fill thousands of vacancies and keep pace with the rising demands of an aging population and a surge in the number of new drugs hitting the US market, analysts and industry experts say.

The National Association of Chain Drug Stores says that four out of five patients who visit a doctor in the United States leave with a prescription. US prescription drug sales rose to about $132 billion last year, from $121 billion in 1999, and are expected to rise another 75% in the next 5 years.

"The pharmacist shortage is the biggest pain for the US pharmacy industry right now," said Steve Croke, president of the Colorado-based PharmacyChoice.com, one of the nation's leading pharmacist recruiting agencies. "The only choice available to the industry is to get people from abroad. Closing down pharmacies could be too costly for the industry."

NACDS says that unfilled full-time and part-time pharmacists positions in the United States more than doubled to 6,920 in February 2000 from 2 years earlier. The shortage, which has now surpassed 7,000 according to some industry experts, is equal to almost 7% of the 106,000 pharmacists employed at US drugstores.

Last week, CVS Corp., the No. 2 US drugstore chain behind Walgreen Co., said that some of its pharmacies have had to start shutting down earlier. Sales, it said, have been hurt by the pharmacist shortage and the resulting decline in service to customers.

Croke said that while the drug retailing industry already uses some foreign-trained pharmacists, employers are still not looking beyond US borders as aggressively as software firms once did.

Part of their problem, he said, is the often cumbersome process of hiring a foreign-trained pharmacist. It can take up to 18 months and about three tests before employers can obtain an H-1B work permit visa, which allows skilled foreign workers to be employed in the United States for up to 6 years. The United States currently allows 195,000 skilled workers to enter the country for work every year through H-1B visas.

Eyleen Schmidt, a spokeswoman for the US Immigration and Naturalization Service (INS), said medical and pharmacist-related jobs take up about 2% of all the H-1B visas issued every year. She declined to say whether there had been a recent surge in applications on behalf of foreign pharmacists.

In a bid to encourage recruitment of foreign pharmacists and make the process less daunting, Croke said he is setting up an online recruiting tool to help link employers with prospective candidates from Australia, New Zealand, South Africa, India, Nigeria, and the Philippines, as well as parts of Western Europe and the former Soviet Union. The site will go live in less than 2 weeks.

Croke said CVS is set to evaluate the new recruiting tool. "The other big benefit of this tool we've developed is that it will give employers access to our international database of resumes and other resources to help ease the process of hiring someone from abroad," he said.

"Getting people from abroad is not a bad option," said Stephen Chick, an analyst at J.P. Morgan. Still, he said the costs in relocation, travel and housing might more than offset the revenue gained by being fully staffed.

The pharmacist shortage is partly the result of increased training mandated by schools and accreditation authorities. Pharmacists in the United States have historically been required to study for 5 years, including one year of on-the-job training. But in an apparent effort to prepare the US drug retailing industry for new drug therapies, the period of study has been extended to a minimum of 6 years.

The loss of trained pharmacists to higher-paying opportunities outside the drugstore sector, such as at biotechnology and pharmaceutical companies, has also contributed to the shortage.


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