Methods

Top Methods Results Discussion Author & Article Info References

Study Selection

We used MEDLINE searches, bibliographies found in comprehensive reviews, and bibliographies supplied by major pharmaceutical companies to locate clinical trials that examined the effects of antihypertensive agents on blood pressure and levels of fasting total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, or very-low-density lipoprotein (VLDL) cholesterol. For the two MEDLINE searches, we used the keywords "hypertension therapy, human, and cholesterol" or "hypertension, therapy, human, and lipids." The search period extended from 1966 through 1993. We also examined the bibliographies of all review articles located through the MEDLINE searches and wrote to major pharmaceutical companies to obtain bibliographies with information on the effects of antihypertensive medications on lipids. The reports of the studies were in English, French, Spanish, Italian, or German. We did not include abstracts and proceedings from scientific meetings. We included only studies that reported the means of lipid values before and after treatment, the absolute change in lipid values before and after treatment, or the mean lipid values at baseline and the mean percentage change that would allow us to estimate the absolute change as the product of the baseline and the percentage change.

Multiple Linear Regression

We used multiple linear regression to determine the relative magnitude and independent effects of different agents, classes of agents, treatment durations, patient characteristics, and study design features on lipids in controlled and uncontrolled studies [19]. We included each group of patients treated with one or more antihypertensive agents as a separate case in the analysis. The regression was weighted by the product of the estimated inverse variance of the change in end point and a study quality index: W_i = Q_i/(V_i+ ²), where W_i is the regression weight for the i-th study group, V_i is the estimated within-study variance, and ² is an estimate of the between-study variability of the effects of different agents [20]. The value was calculated as a fraction (1/2 to 1/5) of the median estimated V_i value across all studies. Q_i is the study quality index. We estimated V_i for end points using the variance of the values before and after treatment for each experimental group: V_i(X – Y) = V_i(X) + V_i(Y) –2 _XY x radical(V_i[X]) x radical(V_i[Y]), where X and Y are the means of the treatment and baseline measurements, respectively, and _XY is the correlation coefficient between X and Y, estimated from the experimental group means across all studies.

Q_i is the sum of points for the following: inclusion (+0.5) and exclusion (+0.5) criteria, masked investigators (+1.0) and study participants (+1.0), random allocation (+3.0), a placebo control group (+2.0), randomized controlled design (+2.0), multiagent comparison (+1.0), crossover design (+1.0), simple before-and- after treatment with one experimental group ( –3.0),sequential treatment with multiple agents ( –2.0),a run-in period (+2.0) with placebo (+1.0), lipoprotein measurements using analytical (+2.0) or routine (+1.0) techniques, use of frozen samples ( –1.0),lipid values reported to only two places ( –3.0),values reported without an estimate of variability ( –2.0),lipid ( –2.0)or blood pressure ( –1.0)values estimated from a figure, age ( –1.0)or sex ( –1.0)missing, final sample size less than 50% of initial size ( –1.0),publication as a supplement or letter ( –1.0),and support from public funding (+1.0).

No uniformly applied indices for quality are available in published meta-analyses. Therefore, the index that we selected for study quality was necessarily arbitrary but included features frequently used in assessing study quality in meta-analysis [21-23]. The relative weights given to individual components of the quality index were also arbitrary and were based loosely on literature suggesting the relative importance of different study design features for validity. For example, it has been reported that nonrandom studies overestimated effect size by about one third compared with randomized studies [24, 25]. We therefore chose a weighting factor of 3.0 to reflect the relative importance of this study design feature. The quality index was normally distributed over a range that gives threefold more weight to a study of the 95th percentile than to a study of the 5th percentile.

The regression weight (W_i) was normally distributed. A sensitivity analysis was done on some of the final regression models to determine the effect at the regression weighting on the results. There were few differences in the models whether regression was weighted by W_i, Q (_i), or sample size or was unweighted (data not shown). When the regression analysis was limited to studies with regression weight values greater as opposed to less than the median, the results for agents represented by an adequate number of studies in both groups were also similar (data not shown). Thus, with respect to regression weighting, the results appeared to be robust.

We identified the independent predictor variables, agent and patient characteristics, using a P value less than 0.05 to enter a stepwise, multiple linear regression model. We classified agents as diuretics, thiazide-like diuretics, loop diuretics, potassium-sparing diuretics, ß-blockers, cardioselective ß-blockers, ß-blockers with intrinsic sympathomimetic activity, -blockers, central sympatholytic agents, angiotensin-converting enzyme inhibitors, calcium antagonists, dihydropyridine calcium antagonists, or vasodilators. Some agents shared more than one characteristic, and some groups were treated with combinations, such as combined –and ß-blocker therapy. We also investigated the potential interactive effects of specific drug combinations and analyzed the effects of diuretic dose. We defined high dose as follows: for hydrochlorothiazide and chlorthalidone, greater than 50 mg/d; for chlorthiazide, greater than 500 mg/d; for bendroflumethiazide and indapamide, greater than 5 mg/d; and for cyclothiazide, greater than 2 mg/d [26]. Treatment with a low-sodium diet under rigidly controlled conditions in a hospital or metabolic unit was included as a covariate. The magnitude of sodium restriction varied. Treatment with a low-fat diet, when the diet was accompanied by antihypertensive therapy, was also used as a covariate if patients were obviously given diet instruction and follow-up as part of the study. Untreated or placebo groups were included as pooled controls.

We analyzed the proportion of patients in each experimental group who were male, diabetic, or black. Age, body mass index, and baseline end point values for lipids and blood pressure were each standardized to a mean of 0 and a standard deviation of 1. Because the effects of study duration and patient characteristics on lipids were unlikely to be the same for different agents, these effects were investigated as interactions with each agent class. Finally, we examined whether individual agents, if included in more than two studies, differed from others in their class. Because the number of individual agents was large relative to the number of studies that examined each agent, we used a P value of less than 0.025 as a minimum model entry criteria.

Data on age were available for 93% of the 945 groups, and patient sex was reported in 88%. We estimated missing body mass indexes using the regression relation among mean body weight, sex, and body mass index generated from cases with complete data. Data on actual body mass index, or body mass index estimated from body weight and sex, were available for 57% of the groups. The proportion of black patients was reported in only 22% of studies. Most studies that did not mention race were from areas of the world where the number of blacks would be expected to be low, and we estimated that the proportion of black persons was zero in studies that did not indicate otherwise. Missing value substitutions for age were randomly selected from cases in which age was known. For other variables, we used regression relations to estimate the missing value by randomly selecting a value from a normal distribution with a mean determined by the regression relation and the standard deviation for cases in which data were not missing. We examined errors introduced by including missing value substitutes. Specifically, the multiple imputation method of Rubin and Schenker [27] was used with five sets of complete data generated by supplying randomly selected substitutes for each missing value.

We examined normalized and studentized residuals using histogram and probability plots. In each case, the residuals appeared to be normally distributed, and normal probability plots of observed compared with expected values were nearly linear. For each model, we identified 10 outliers and examined the effect of removing these cases. Coefficients are the mean of the means of the regression coefficients from five models, in which each model was generated with a different set of randomly imputed missing values. We generated confidence intervals using a combined variance of within-model and between-model variance, with the latter reflecting variability caused by imputing missing values [27]. The analysis was done using the Statistical Package for the Social Sciences software [28].

Meta-analysis of Controlled Clinical Trials

The treatment effect of each randomized controlled clinical trial was defined by Delta = Delta_T – Delta_C, where Delta_T and Delta (_C) were the changes in end points for the treatment and control groups, respectively. For example, in the case of cholesterol, Delta = (cholesterol level after treatment -cholesterol level before treatment) –(cholesterol level after placebo – cholesterol level before placebo). Treatment effects were weighted by the inverse variance of each end point. We calculated the pooled treatment effect and 95% CIs as described by Cappuccio and colleagues [29]. The results were considered significant at = 0.05 when the 95% CI did not include 0. For this analysis, we included only experiment groups that compared the effects of a single antihypertensive agent with those of a control group.

Results

Top Methods Results Discussion Author & Article Info References

Study Characteristics

We identified 474 studies with 945 experimental or control groups and more than 65 000 patients (Table 1). Patients were randomly allocated in 66% of the 945 groups. In 39% of studies, investigators were blinded, whereas in 43%, study participants were blinded. A wash-in period was used in 78%. A controlled, parallel group design was used in 16% of studies, a crossover design in 17%, a single-agent design (without a control group) in 25%, and a sequential multiagent design in 6%. In 64% of studies, more than one antihypertensive medication was compared. Thirty percent of studies were done in North America, and 64% were done in Europe.

The effects of 85 agents were investigated (Appendix Table 1). Diuretics were examined in 236 studies (47 agents were given at high doses), thiazide-like diuretics in 214, potassium-sparing diuretics in 29, ß-blockers in 315, cardioselective ß-blockers in 140, ß-blockers with intrinsic sympathomimetic activity in 94, -blockers in 158, central sympatholytic agents in 34, converting enzyme inhibitors in 97, calcium antagonists in 100, and vasodilators in 46. In several cases, the effects of combination therapy were examined. In many cases, a thiazide or a thiazide-like diuretic was combined with one of the following: a potassium-sparing diuretic in 29 groups, an -blocker in 15 groups, or a converting enzyme inhibitor in 15 groups. Combined effects of –and ß-blockers were examined in 29 groups, and ß-blockers that combined cardioselectivity with intrinsic sympathomimetic activity were studied in 31 groups. A low-salt diet was studied in 14 groups, and a low-fat diet was used in 15 groups. Placebo or no treatment was given in 69 groups.

Serum Lipids

Diuretics increased cholesterol and triglyceride levels (Tables 2 and 3). Increases in cholesterol levels were greater with higher doses and were also greater among blacks (Figure 1). Increases in total cholesterol levels were paralleled by increases in LDL cholesterol levels, although the increases in the latter depended on baseline LDL cholesterol levels and were greater in men than in women. Diuretic-induced changes in triglyceride levels were seen only in short-term studies and were greater in men than in women (Figure 1). Diuretics reduced HDL cholesterol levels only in patients with diabetes. Of all the diuretics studied, only ticrynafen (n = 6 study groups), a uricosuric agent no longer marketed, and bendrofluthiazide (n = 10) did not increase cholesterol levels. Chlor-thalidone caused a greater increase in LDL cholesterol levels than did other diuretics (n = 19). Indapamide failed to increase triglyceride levels (n = 12).

View larger version (25K): [in this window] [in a new window]   Figure 1. Effect of patient characteristics on lipid changes caused by antihypertensive therapy. The effect of race on diuretic-associated changes in low density lipoprotein (LDL) cholesterol levels (mean ±SE) is shown in the left panel. Only groups for which race was reported in the study are included. Numbers in parentheses refer to the number of experimental groups with fewer than 50% blacks (15% ±16%) or 50% or more blacks (86% ±20%). The effect of sex on diuretic-associated changes in triglycerides is shown in the middle panel. Numbers in parentheses refer to the number of experimental groups with fewer than 50% men (27% ±18%) or 50% or more men (82% ±19%). The effect of diabetes on changes in cholesterol levels after treatment with an angiotensin-converting enzyme (ACE) inhibitor is shown in the right panel. Numbers in parentheses refer to the number of experimental groups with fewer than 50% patients with diabetes (1% ±5%) or 50% or more patients with diabetes (100%). Significance was tested using an unweighted t-test.

ß-blockers had little effect on total and LDL cholesterol levels (Table 2). However, ß-blockers that combined cardioselectivity with intrinsic sympathomimetic activity notably reduced total cholesterol and LDL cholesterol levels. In contrast, ß-blockers caused a substantial increase in triglyceride levels that was associated with a decrease in HDL cholesterol levels (Table 3). The increase in triglycerides was slightly less with cardioselective ß-blockers, particularly when they were used in patients with diabetes. The increase in triglyceride levels was also less with ß-blockers that had intrinsic sympathomimetic activity and was greater in patients with higher baseline triglyceride levels. ß-blockers with intrinsic sympathomimetic activity caused a net increase in HDL cholesterol levels, but this increase was smaller in men and greater in studies of longer duration. Compared with other ß-blockers that have intrinsic sympathomimetic activity, oxprenolol was associated with a higher total cholesterol level (n = 11), whereas pindolol was associated with higher HDL cholesterol (n = 31) and lower triglyceride levels (n = 32).

-Blockers decreased total and LDL cholesterol levels (Table 2). These beneficial effects were negated by combining –with ß-blockade. -Blockers decreased triglyceride levels and increased HDL cholesterol levels (Table 3). The increase in HDL cholesterol levels was smaller in older persons. For both cholesterol and triglycerides, the effects of -blockers were greater in persons with higher baseline lipid levels. Prazosin caused a relatively greater reduction in LDL cholesterol levels (n = 48) than did other -blockers.

Central sympatholytic agents reduced total cholesterol levels Table 2 but also slightly decreased HDL cholesterol levels (Table 3). Interestingly, two agents, guanfacine (n = 8) and guanabenz (n = 5), explained most of the effects of the central sympatholytic agents on cholesterol. Other central sympatholytic agents could not be shown to affect lipids once the effects of these two agents were considered. Converting enzyme inhibitors decreased cholesterol levels in patients with diabetes Table 2 and Figure 1. A decrease in triglyceride levels was also seen, especially in patients with a high baseline triglyceride level (Table 3). This decrease in triglyceride levels was smaller in older persons. With the exception of lisinopril, which failed to decrease triglyceride levels (n = 6), the effects of different converting enzyme inhibitors were similar. Calcium antagonists had no effect on lipids (Tables 2 and 3). Vasodilators reduced total and LDL cholesterol levels Table 2 and increased HDL cholesterol levels (Table 3). Vasodilators also negated some of the increase in triglyceride levels associated with ß-blockers and appeared to selectively reduce triglyceride levels in blacks.

Correlations among Changes in Blood Pressure and Lipid and Glucose Levels

Overall, blood pressure was reduced (regression constant) because of changes in control groups and changes in treatment groups that were independent of therapeutic agents, that is, a placebo effect (Table 4). This reduction was greater when the baseline blood pressure was higher. Duration of follow-up was also associated with a greater reduction in blood pressure, whereas reductions were smaller in older persons and tended to be smaller among blacks. For most agents, reductions in blood pressure were similar. However, diuretics were more effective in older persons and less effective in patients with diabetes. Cardioselective ß-blockers were relatively less effective in older persons. -Blockers were more effective in patients with diabetes but less effective in blacks. The effects of combining - and ß-blockers were greater than those of either agent alone but were somewhat less than expected if the effects were simply additive. Dihydropyridine calcium antagonists caused relatively greater reductions in blood pressure than did other calcium antagonists, whereas calcium antagonists in general appeared to be less effective in men than in women.

Because changes in cardiovascular risk may be the cumulative effects of changes in inter-related risk factors, we also examined the correlations between different study end points. Across all experimental and control groups, changes in LDL and total cholesterol levels were strongly correlated (r = 0.82; n = 681; P < 0.001). Changes in VLDL cholesterol levels were nearly identical to those of triglyceride levels (r = 0.95; n = 827; P < 0.001), and results for triglycerides did not substantively differ from those for VLDL cholesterol. There was an inverse relation between changes in triglyceride and HDL cholesterol levels (r = –0.40;n =663; P < 0.001). Changes in blood pressure correlated weakly with changes in total cholesterol (r = 0.19; n = 659; P < 0.001) and LDL cholesterol levels (r = 0.14; n = 487; P = 0.002) but not with changes in triglyceride (r = –0.05)or HDL cholesterol levels (r = 0.02). Multiple linear regression analysis showed that the association between cholesterol and blood pressure changes were independent of specific agents and patient characteristics (data not shown). There were also correlations between changes in levels of fasting blood sugar and total cholesterol (r = 0.30; n = 320; P < 0.001), triglycerides (r = 0.26; n = 295; P < 0.001), LDL cholesterol (r = 0.27; n =212; P < 0.001), and HDL cholesterol (r = –0.18;n = 215; P = 0.008) and in blood pressure (r = 0.12; n =269; P = 0.022). These correlations were seen with several classes of agents, including diuretics, ß-blockers, -blockers, and converting enzyme inhibitors. Likewise, changes in glycosylated hemoglobin levels correlated with changes in levels of cholesterol (r = 0.34; n = 77; P = 0.001), triglycerides (r = 0.46; n =73; P < 0.001), and LDL cholesterol (r = 0.34; n = 63; P = 0.006) and in blood pressure (r = 0.30; n = 73; P = 0.011).

Randomized Controlled Trials

Fifty-six controlled clinical trials compared the effects of monotherapy with those of placebo (Table 5). Most of these trials examined the effects of diuretics, ß-blockers, or -blockers. Diuretics adversely affected total, LDL, and HDL cholesterol and triglyceride levels. Nonselective ß-blockers decreased HDL cholesterol levels and increased triglyceride levels. -Blockers decreased total and LDL cholesterol levels. Fewer controlled trials compared other agents, and none of their effects on lipids was significant. Interestingly, the magnitudes of the treatment effects among the randomized controlled trials were, in most cases, similar to corresponding regression coefficients in the multiple linear regression. For example, the treatment effect for -blockers on total cholesterol levels was –0.15 mmol/L among randomized controlled trials Table 5, and the regression coefficient was –0.23 mmol/L (Table 2).

Discussion

Top Methods Results Discussion Author & Article Info References

Because adverse metabolic effects probably reduce the benefit of blood pressure reduction therapy [30-33], many studies have examined the effects of different antihypertensive agents on lipid levels. Several recent reviews of these trials have been published [1-18]. Although there is general consensus that thiazide diuretics and nonselective ß-blockers adversely affect lipid levels, many areas of disagreement still exist about the effects of other antihypertensive agents on lipids. This disagreement is no doubt partially caused by the impossibility of judging the results of multitudinous clinical trials that differ in design and study populations. Indeed, few studies have examined whether the effects on lipids of antihypertensive agents may differ in different patient populations. None of the reviews used meta-analysis.

Most authors reviewing the literature concluded that diuretics increase total cholesterol levels, and many [1-3, 5-10, 12-18], but not all [4, 11], concluded that they modestly increase LDL cholesterol levels. In our meta-analysis, diuretics were associated with increased total and LDL cholesterol levels, especially among blacks Table 2 and Figure 1. High doses of diuretics were associated with even greater increases in LDL cholesterol levels. The effects of different diuretic classes were similar. Most authors also agree that diuretics can increase triglyceride and VLDL cholesterol levels [1-18]. Our results suggest that the effects of diuretics on triglycerides were independent of the type of diuretic and were more marked in men than in women Table 3 and Figure 1. There has been considerable uncertainty about possible decreases in HDL cholesterol levels [1-4, 10-18]. We found that diuretics decreased HDL cholesterol levels only in patients with diabetes. Whether the effects of diuretics depend on duration of therapy has also been controversial [1-3, 5, 6, 13, 16, 18]. In our analysis, cholesterol levels tended to decrease with time in treated and untreated groups, and the relative effects of diuretics on cholesterol levels were independent of study duration. However, the effects of diuretics on triglycerides decreased over time. Relatively few studies had long-term follow-up; additional investigations of longer duration are needed.

Although most agree that ß-blockers increase triglyceride levels and decrease HDL cholesterol levels [1-11, 13-18], the extent to which cardioselectivity or intrinsic sympathomimetic activity modulates the effects of ß-blockers on lipids has been controversial. We found that increases in triglyceride levels and decreases in HDL cholesterol levels were substantially smaller for ß-blockers that have intrinsic sympathomimetic activity. Cardioselectivity moderated the increase in triglyceride levels, and cardioselectivity appeared to be more beneficial among patients with diabetes. The effects of ß-blockers on HDL cholesterol levels appeared to diminish with duration of treatment. ß-blockers had little effect on total and LDL cholesterol levels, but cardioselective ß-blockers with intrinsic sympathomimetic activity did reduce them.

Most authors agree that -blockers reduce triglyceride levels [1-18]. However, our results indicate that -blockers favorably affected not only triglyceride levels but also total, LDL, and HDL cholesterol levels. The effects of -blockade on HDL cholesterol levels were smaller in older persons, and the effects on total and LDL cholesterol levels were substantially smaller when an -blocker was used with a ß-blocker.

Most authors have concluded that converting enzyme inhibitors do not affect lipids [1-6, 8-12, 17]. However, with the possible exception of lisinopril, we found that converting enzyme inhibitors reduced triglyceride levels, especially in younger persons (Table 3). Cholesterol levels were also reduced, but this occurred only in patients with diabetes Table 3 and Figure 1. Perhaps these results should not be surprising because other investigators have shown that converting enzyme inhibitors have beneficial effects on insulin and glucose levels that could be expected to favorably influence lipids [34, 35].

Although some authors believed that centrally acting sympatholytic agents favorably affect lipids [2, 6], most concluded that the effects were neutral [4, 5, 11, 12, 16]. The results of our analysis indicate that sympatholytic agents reduced total cholesterol levels but also decreased HDL cholesterol levels. These effects appeared to be caused by two agents in this class, guanfacine and guanabenz. The observation that the reduction in total cholesterol levels appeared to be smaller in black persons deserves additional study.

In agreement with others [1-6, 8-12, 14, 15, 17, 18], we found that calcium antagonists had few or no effects on lipids. However, there has been little consensus about whether vasodilators have beneficial [2, 3, 9] or neutral [4, 6, 11] effects. In our analysis, vasodilators were clearly associated with decreases in total and LDL cholesterol and triglyceride levels, whereas HDL cholesterol levels increased. In general, the effects of vasodilators on lipids were not influenced by study duration or patient population characteristics. However, vasodilators may have caused a greater decrease in triglyceride levels among blacks.

Recently, several investigations have linked essential hypertension to abnormalities in insulin, glucose, and triglyceride metabolism [36, 37]. It is interesting, therefore, that changes in lipids generally paralleled changes in fasting glucose levels. This effect was relatively ubiquitous and was seen with different classes of agents. Several of these agents may affect insulin counter-regulatory hormones and sympathetic nervous system activity; these effects may lead to insulin-induced alterations in hepatic cholesterol production and lipoprotein lipase activity [2, 10]. Whether the association between glucose and lipid changes was caused by one or more common metabolic effects or resulted from unrelated mechanisms for each of the different agents is unclear. Interestingly, obesity, which is often noted to be associated with changes in blood pressure, glucose, and lipids [36, 37], did not modify the effects of any agents on blood pressure or serum lipids.

The results of our analysis show that the effects of antihypertensive agents not only on blood pressure but also on lipids differ among patient populations. In patients with diabetes, for example, diuretics were less effective in lowering blood pressure than were other agents and caused relatively greater increases in LDL cholesterol and triglyceride levels. For older persons, diuretics appeared to be more effective in lowering blood pressure, whereas ß-blockers with intrinsic sympathomimetic activity were less effective, and decreases in triglyceride levels caused by converting enzyme inhibitors were relatively smaller. Calcium antagonists appeared to be less effective in reducing blood pressure in men than in women, whereas diuretics caused greater increases in LDL cholesterol and triglyceride levels. Although fewer studies included blacks, blood pressure reductions in general tended to be smaller among blacks. -Blockers appeared to be less effective in reducing blood pressure, whereas diuretics caused a greater increase in total and LDL cholesterol levels among blacks. There was also a suggestion that vasodilators selectively reduced triglyceride levels in black persons.

Our results should be interpreted with caution. It is possible that some reported effects were the result of chance. Indeed, we examined relatively many covariates and interactions in the regression analysis, thus increasing the likelihood that some significant findings were caused by chance. The inclusion of nonrandom studies of poor quality may also increase the likelihood that some of the findings were invalid, despite the use of a study quality index in the regression weight. It is encouraging that the results of the pooled, randomized controlled trials were similar to those of the regression analysis for agents that were well represented in both analyses. However, it is possible that the results for some other agents studied only in uncontrolled trials and included in the regression analysis would be different if studied in randomized controlled trials. Finally, as with any meta-analysis, publication bias may have also influenced the results [38]. In most of these studies, however, lipids were measured as secondary end points in trials designed to examine the safety and blood pressure-lowering efficacy of agents, thus making systematic publication bias about changes in lipids seem less likely.

In theory, data from the Framingham study could be used to calculate an estimated change in cardiovascular risk with antihypertensive therapy, using expected changes in blood pressure and lipids and assuming that other risk factors such as smoking and obesity remain constant [38]. However, too few studies calculated cardiovascular risk in this manner to permit a meaningful meta-analysis of change in cardiovascular risk with different antihypertensive agents. Moreover, it is difficult to extrapolate from the results of the meta-analysis the potential effect on cardiovascular risk of different blood pressure-lowering agents in individual patients. The relative change in blood pressure and lipid levels may have different effects on cardiovascular risk, depending on baseline levels. Thus, a reduction in blood pressure in persons with severe hypertension may decrease risk substantially, even if lipids are adversely affected. Conversely, treating mild hypertension with agents that increase cholesterol levels may be counterproductive.

Nevertheless, the Framingham data suggest that for the same amount of blood pressure reduction, agents that adversely affect lipids may cause less reduction in cardiovascular disease. Indeed, this may partially explain why intervention trials with diuretics and ß-blockers failed to reduce cardiovascular disease as much as would have been expected from the degree of blood pressure reduction [30-33]. Whether newer agents that reduce blood pressure without adversely affecting lipids will more favorably affect cardiovascular disease remains to be proven in controlled clinical trials. Meanwhile, the results of this meta-analysis provide additional information suggesting that the effects of antihypertensive agents on serum lipids may be more pervasive than previously thought and that future trials should be more attentive to differences among patient populations.