Summary of evidence
Our analysis is, to date, the most comprehensive analysis of the existing data on the comparative effectiveness of different antihypertensive drug-classes used in primary prevention of cardiovascular diseases.
As for most other systematic reviews in this field we find limited evidence of important differences between the various drug-classes. The differences we do find are not easy to put into practice as the ranking of a drug-class depends on which outcome one chooses to emphasize, and no drugs are consistently among the best across all important outcomes.
Our ranking of drug-classes, as presented in Table may be useful to decision makers, or it may add to the confusion. By presenting the chance that a drug is among the top three for an outcome, we had hoped that one or two drugs would emerge as first choice candidates by being among the three best drugs across several important outcomes. However, no such pattern appeared. We should also point out that the quality of the underlying evidence is not taken into consideration in the ranking, thus the results should be interpreted cautiously, and in conjunction with the drug-comparison findings (Tables and ).
Beta-blockers (atenolol) were inferior to all drug-classes for all primary outcomes, and although the difference in many cases was non-significant and the quality of the evidence was mixed, this may be seen as evidence against opting for these drugs as the first choice. Beta-blockers and alpha-blockers were the only drug-classes that were not significantly superior to any drug, for any outcome, which could suggest not recommending these as first line medication.
Successful management of hypertension is dependent on many factors, and choice of drug class is one that seems to be of limited importance. Thus, clinicians should probably focus more on issues such as limiting adverse events, improving adherence and better follow up of patients rather than on which drug to select. However, there is considerable variation in costs across different antihypertensive agents, thus cost-effectiveness assessments may be important for decisions about choice of medications.
Our findings in relation to other systematic reviews
Other research groups have conducted network meta-analyses in this field before us, but our contribution adds important dimensions. First, some reviewers have only included one clinical outcome, while we included six clinically important ones. Second, others have reported only on selected drug-drug comparisons [8
], rather than the full range of competing options. Third, a weakness across earlier reviews of the comparative effectiveness of different antihypertensive drugs is that they have not included an explicit assessment of the quality of the evidence backing the reported effect estimates. An important exception is the systematic review that informed the recently updated guidance from the National Institute of Health and Clinical Excellence (NICE), but their effect-estimates were based on the traditional, not the network meta-analytical approach [9
Although disagreements between our findings and those of other systematic reviews are few and relatively minor, the conclusions drawn by authors vary somewhat [5
In two recent network analyses on the effectiveness of antihypertensive drugs, the authors limited their analysis to one outcome: heart failure [14
] and diabetes incidence [13
]. Despite slightly different study inclusion criteria, their effect estimates are very similar to ours. The systematic review and network meta-analysis by Psaty and colleagues only included comparisons against diuretics, not between other types of antihypertensive drugs [8
]. A network analysis by Aursnes and colleagues, also from 2003, focussed on comparing ACE-inhibitors and CCB, and was limited to three outcomes [56
]. Our findings are not in full agreement with these two earlier reports, presumably due to our more strict inclusion criteria and perhaps also to the inclusion of results from more recent studies.
Law and colleagues authored a recent comprehensive review and meta-analysis on antihypertensive drug treatment [6
]. They conducted traditional meta-analyses, without the network approach. Their conclusion was that "all the classes of blood pressure lowering drugs have a similar effect in reducing CHD (coronary heart disease) effects and stroke". This is close to, but not entirely in agreement with our findings, which may be due to some of the following issues. First, they elected to compare each drug class with the pooled results from all other drug classes, for example, beta-blockers versus all non-beta-blockers. This analytical approach can be misleading because favorable effects from one non-beta-blocker may be off-set by unfavorable effects from another non-beta-blocker drug-class. Second, they included trials where high dose diuretics were used. This may be misleading as there are good reasons to believe that high dose diuretics lead to less favorable outcomes than low dose diuretics [7
]. Consequently, as high dose diuretics were used in many of the trials comparing beta-blockers and diuretics, beta-blockers came out more favorably in their analyses than they probably should. Third, in two studies included in their analysis the participants were randomised to either active drug or placebo [54
], and these should, therefore, not be classified as drug comparison studies, in our view. Fourth, they did not explicitly assess the quality of the evidence underlying their effect-estimates, which is essential for judgements about how confident we can be about the validity of the findings. Last, they included two studies we classified as non-randomised trials [60
Systematic reviews, as other types of research, are inevitably based on subjective judgements. The assessments were, however, done by at least two reviewers, making misjudgements less likely, but still possible.
Although the process of grading the quality of the evidence was done using a structured approach (GRADE), the assessments are strongly influenced by our judgements. The merit of the GRADE-system is that these judgements are made explicit and accounted for.
As with other research activities, systematic reviews do not provide answers to questions not asked by the authors. We have selected the interventions and outcomes we considered most important, but there are undoubtedly other aspects that are important for decision-making in this field. We have, for example, not reviewed the side-effect profiles of the different drug-classes (except for incidence of diabetes). Our selection of outcomes is also debatable. We chose to emphasize what we considered the most important clinical outcomes and disregarded others that may be of key interest, such as intermittent claudication, vascular dementia, renal disease and retinal disease.
A fundamental challenge with the use of meta-analysis is to judge whether two or more studies are sufficiently similar to have their results pooled in one analysis. Our judgements regarding this could be criticized. It is, for instance, not obvious that drugs from the same drug-class are equivalent, as we have implicitly assumed [11
]. We had specifically planned to conduct a separate analysis where we excluded trials of beta-blockers that had used the agent atenolol, since the appropriateness of using atenolol as a comparator-drug has been questioned [11
]. However, atenolol was used in all the beta-blocker trials we included in our review, so an analysis of non-atenolol beta-blockers could not be done. Similarly, our handling of calcium channel blockers as an entity can be questioned. The pharmacological properties vary across these drugs, and it could be argued that they should be grouped according to property and not as an entity [63
In a network analysis like ours, it is assumed that all the included trials are sufficiently homogeneous to allow for the combining of all the study findings into one analysis. This assumption is difficult to validate. Differences in study populations can, in particular, distort estimates for the effects on total mortality, since these are related to the proportion of deaths that are due to cardiovascular diseases, for each study. We did not formally assess how comparable the various populations were. However, our use of relatively strict inclusion criteria, for example, including only studies where the majority of participants had no prior cardiovascular event and excluding studies of specific high-risk groups, substantiates that the populations were somewhat similar. Also, the finding that the effect-estimates from the network analysis were similar to the estimates from the direct comparisons provides some evidence that the trials were reasonably homogeneous.
The definitions of outcomes vary from study to study, for instance, regarding heart failure. Study reports are not always clear with respect to whether the number of patients with events or the total number of events were counted. We believe such differences across studies has had limited influence on our overall findings.
Our objective was to estimate the relative risk reduction for different antihypertensive drugs in individuals without cardiovascular disease (primary prevention). However, we chose to include studies where up to half the participants had experienced a cardiovascular event (secondary prevention). Our reasoning was that such studies contain information of relevance to our research question. This is in accordance with the approach used by the World Health Organization when they prepared their most recent guidelines on primary prevention of cardiovascular diseases [64
]. In several earlier reviews on antihypertensive treatment the authors have included studies where all participants were patients with cardiovascular disease. This is clearly valid if the relative effect of using antihypertensive medication is the same for healthy and for sick people, and Law and colleagues do provide some data to support such a view [6
]. Our choice to exclude such trials may thus be criticized. On the other hand, it is not firmly established that the relative treatment effect of antihypertensive medication is constant across different patient groups. And even if this proves to be the case it is still conceivable that different types of medication may work differently for people with and without cardiovascular disease, something for which Law and colleagues also found evidence [6
Our meta-analyses are based on a count of events at one moment in time, that is, at the end of each trial. This analytic approach is not entirely valid unless the relative effect size is constant over time. A more complex analysis, including time to events, would require access to more data from each study than what was available to us.
The majority of the included trials in this review were sponsored by companies with a vested interest in the study results. Such sponsorship has been associated with bias in favour of the product made by the funding company [65
]. Possible explanations include publication bias and use of inappropriate comparators. Limiting our review to large-scale studies should reduce risk of publication bias or other forms of selective reporting [20
]. Whether the most appropriate comparator drug has been selected is more difficult to assess. Biased analyses were minimized in our review because we based our effect-estimates on actual figures presented in the various articles, rather than relying on the analyses conducted by the study-authors and/or sponsors.
Future research agenda
Despite the fact that many methodologically sound large-scale trials of anti-hypertensive drugs have been conducted, our confidence in the overall findings ranged from very low to high after assessing the quality of the evidence using the GRADE-instrument. This means that the results from future trials may alter our conclusions. Future research to improve the quality of hypertension management should also focus on other issues, such as interventions to improve treatment adherence and on how to organise follow-up of patients more effectively.