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Journal of Hypertension:
doi: 10.1097/HJH.0000000000000201
Editorial Commentaries

Assessment of drug effects on blood pressure variability: which method and which index?

Stergiou, George S.; Kollias, Anastasios; Ntineri, Angeliki

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Hypertension Center, STRIDE Hellas-7, Third University Department of Medicine, Sotiria Hospital, Athens, Greece

Correspondence to George S. Stergiou, Hypertension Center, STRIDE Hellas-7, Third University Department of Medicine, Sotiria Hospital, 152 Mesogion Avenue, Athens 11527, Greece. Tel: +302107763117; e-mail:

Blood pressure (BP) is known to be a continuous variable with dynamic characteristics of variability in response to daily physical and mental stimuli. The idea that the variation of BP puts additional burden on the heart and vasculature beyond that of average BP has been regarded for decades as a reasonable concept by researchers, practitioners and even patients. However, in contrast to the straightforward approach required for the evaluation of average BP, the quantification of the BP variability (BPV) turned out to be a tricky task. Interestingly, several different lines of evidence suggest that the BPV has independent prognostic value beyond that of average BP. However, to date the plethora of methodological approaches applied in different studies and the lack of evidence on critical relevant research issues did not allow BPV to be used in practice as a tool for improving the management of hypertensive patients.

For the quantification of BPV, several measurement methods and sampling of BP readings have been used, and several mathematical approaches have been applied (Tables 1–2) [1–10].

Table 1
Table 1
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Table 2
Table 2
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The different methods available for office and out-of-office BP measurement have been used to provide information on different aspects of BPV. Evaluation of BPV using each of these methods has been shown to independently predict cardiovascular risk [1–3,11–17]. However, each BPV component seems to reflect different mechanisms, is likely to provide different information on cardiovascular regulation and might have different clinical implications [12,18].

Very-short-term BPV can be assessed by continuous beat-to-beat intraarterial BP monitoring or noninvasive finger-cuff photoplethysmography. The use of the former is limited because of the invasive nature and the latter because of questionable measurement accuracy.

Short-term BPV is based on intermittent BP sampling at 15–30-min intervals in a routine 24-h period, obtained using noninvasive oscillometric ambulatory monitors. This appears to be an ideal method for routine BPV evaluation, by providing information on the dispersion of BP values in different conditions of posture and activity. However, the independent prognostic value of ambulatory BPV has been questioned, and its application might not be well accepted by patients for repeated use in the long-term management of hypertension. In the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT), ambulatory BPV had less effect on vascular events than that assessed by office measurements [2]. Moreover, analysis of the International Database on Ambulatory Blood Pressure in Relation to Cardiovascular Outcome (IDACO) showed that the 24-h ambulatory BPV did not contribute much to risk stratification over and beyond the average ambulatory BP [15]. It should be mentioned, however, that most of the published studies have been limited by infrequent ambulatory BP sampling, whereas it has been shown that measurements at 15-min intervals are required to provide an accurate assessment of BPV [19].

Mid-term day-by-day BPV based on self-home BP monitoring has also been shown to provide prognostic information independent of average home BP [1,12,13,17]. Home monitoring might be more appropriate for repeated BPV assessment in clinical practice, because it is widely available and well accepted by hypertensive patients for long-term use [12,13]. However, its application requires validated devices, measurement standardization and prevention of patients’ reporting bias using automated memory [12,13].

Long-term BPV can be assessed by repeated office BP measurement in succeeding visits. Recent outcome studies demonstrated the prognostic relevance of visit-to-visit BPV [2,3,16], which might be superior to short-term ambulatory BPV [2]. In these studies, however, carefully standardized office measurements were obtained, which might not be feasible to replicate in routine clinical practice.

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Multiple mathematical approaches have been applied to determine BPV evaluated by different BP measurement methods. The SD is the classic index for BPV quantification, yet its major limitations are that it is proportional to the mean BP value and might have inferior prognostic ability than newer BPV indices. Several SD-based formulas have been introduced to eliminate the impact of mean BP (e.g. coefficient of variation), or of diurnal BP variation [4]. More recent studies tested novel BPV indices, which appear to have superior prognostic ability to SD-based indices. Some indices have been developed to handle BP readings obtained using specific measurement methods (Table 2).

While SD merely reflects the BP excursions around the mean, the time rate of BP variation measures the speed of ambulatory BP fluctuations between successive readings and integrates the direction of these changes [5,20]. There is evidence that the time rate of BP variation is independently associated with target organ damage [5,20].

The average real variability (ARV) also overcame deficiencies of SD and added unique additional prognostic value to short-term ambulatory BPV, being more sensitive to the individual BP measurement order and less so to the low sampling frequency of ambulatory monitoring [6,15,21].

The variability independent of mean (VIM), introduced in the analysis of prognostic ability of visit-to-visit BPV in the ASCOT and the Medical Research Council (MRC) Trial, transformed SD into a new statistical tool uncorrelated with mean BP and with independent prognostic value [2]. Asayama et al. [1] explored the prognostic ability of ARV, VIM and the maximum–minimum BP difference of home measurements, and concluded that none of them incrementally predicts cardiovascular outcome over and beyond mean SBP. Finally, the residual BPV (RSD) reflects the erratic component of short-term BPV, and has been shown to be positively associated with left ventricular mass index [7] and cardiovascular risk [14].

Interindividual versus intraindividual BPV has been an issue of debate in the analysis of outcome trials. In the ASCOT, interindividual BPV was lower with amlodipine than with atenolol, mainly because of lower intraindividual BPV, and in the MRC study, both interindividual and intraindividual BPV increased with atenolol compared with placebo or diuretic [2]. Although there was a relatively good correlation between intravariability and intervariability, they cannot be regarded as interchangeable indices but probably reflect different physiological or therapeutic phenomena [22,23]. Interindividual BPV during treatment may primarily depend on the individual's BP response to treatment rather than the variance of BP response over time [22,23]. This view is supported by the European Lacidipine Study on Atherosclerosis (ELSA) that showed higher interindividual than intraindividual visit-to-visit office and ambulatory BPV, suggesting that only the latter is able to reflect precisely the treatment-induced changes [22].

Specific indices have been developed to quantify the effect of antihypertensive drugs on ambulatory BP. The trough-to-peak ratio (TPR), introduced to evaluate the duration of antihypertensive drug action, reflects the ambulatory BP decline in two narrow time intervals, is poorly reproducible and has wide interpatient variability [24]. In contrast, the smoothness index is based on the entire 24-h recording period and takes into account both the degree of BP reduction and its 24-h distribution [8,24]. Thus, it reflects the homogeneity of 24-h drug effect, and is more reproducible and more closely related to treatment-induced regression of organ damage than the TPR [8,25].

In this issue of the journal, Parati et al. [9] introduced the treatment-on-variability index (TOVI), calculated by dividing the treatment-induced hourly BP reduction to the degree of absolute BPV under the same treatment. Thus, the TOVI allows the assessment of the impact of antihypertensive drug treatment on both mean BP and BPV over 24 h. TOVI was compared with smoothness index in a retrospective analysis of 10 drug trials receiving placebo, monotherapy or two-drug combination, with ambulatory BP available before and during treatment [9]. Although both smoothness index and TOVI reflect the effectiveness of drug-induced hourly BP decline, the former assesses the 24-h variation of this decline, whereas the latter quantifies the short-term BPV ridded of the impact of the nocturnal BP change [9]. The two indices showed similar behavior among treatments by discriminating their differential impact on BP and BPV. Although both indices were improved with all treatments compared with placebo, combination therapy resulted in higher values than monotherapies [9]. Higher smoothness index or TOVI was attributed to stronger BP-lowering effect and longer duration of drug action [9]. Thus, TOVI appears to be at least as useful as smoothness index, yet the clinical relevance of treatment-induced effects on these indices in terms of clinical outcomes remains to be proved.

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In recent years, there has been increasing interest in the effect of antihypertensive drugs on BPV and its independent impact on cardiovascular event prevention. Several outcome trials suggested that calcium channel blockers (CCBs) are superior to other drug classes in reducing BPV, which might independently contribute to more effective cardiovascular protection.

In the ASCOT, clinic and ambulatory BPV were higher in the CCB compared with the β-blocker-treated group, independently of their effects on mean BP [2]. Interestingly, the cardiovascular event rates were lower in the CCB group, which could be partially attributed to the drug effects on BPV. In the MRC trial, visit-to-visit BPV was increased in the β-blocker compared with the diuretic and the placebo group, with these BPV trends in the β-blocker group being associated with stroke risk [2].

The above outcome data are in line with a meta-analysis of 389 trials that showed BPV to be reduced by CCBs and diuretics, and increased by β-blockers, angiotensin converting enzyme inhibitors and angiotensin receptor blockers [26]. In 21 trials with outcome data, the above effects contributed to differences in stroke risk, independently of effects on mean BP [26]. Interestingly, the aforementioned opposing effects of antihypertensive drug classes on BPV were dose–dependent and persisted when used in combinations [27]. The authors suggested that high-dose CCB monotherapy or combination with other drugs might be particularly effective for stroke prevention [27]. A recent systematic review of home BPV trials also suggested favorable effects of CCBs and not of β-blockers or angiotensin receptor blockers on BPV [13].

The abovementioned trials had different design and different methodology for BPV evaluation, yet the message is consistent in favor of CCBs. Thus, an important new chapter has opened, and there is an urgent need to establish the optimal methodology and indices for quantifying the drug treatment effects on BPV.

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A mathematical approach to select the optimal BPV index that accurately reflects the dispersion of BP values around the average unaffected by the latter is reasonable and was the rationale for introducing novel indices, such as the ARV and VIM. On the other hand, indices specifically developed to assess drug-induced BPV changes (e.g. smoothness index and TOVI) are clearly attractive. However, the ultimate test for a BPV index is to show whether its change with treatment can independently influence the risk of cardiovascular events.

The outcome trials, that showed CCBs to have favorable effects on BPV compared with other drugs with subsequent enhanced cardiovascular protective abilities, have used various methods for BPV quantification. In the ASCOT and the MRC trial, Rothwell et al. [2] tested the SD, coefficient of variation, VIM, ARV and RSD of clinic BP measurements in terms of intraindividual visit-to-visit BPV, and also SD, coefficient of variation and ARV of ambulatory BP, and concluded that mainly the effects on systolic visit-to-visit BPV and partly on systolic ambulatory BPV could account for reduced event rates in the CCB group. A meta-analysis of 21 outcome trials applied the variance ratio as an expression of interindividual visit-to-visit variability to differentiate the BPV changes with different drugs [26].

Cross-sectional and short-term studies also demonstrated the ability of several BPV indices to differentiate the effect of different drugs. Some studies obtained home BP readings and used the SD or coefficient of variation of morning BP [28], or SD of daily mean or daily morning or evening BP [13,29]. Other studies performed ambulatory BP monitoring and used the SD of systolic daytime, night-time and 24-h BP [30]. Ambulatory BP-specific indices, such as TPR, smoothness index and TOVI, have been explored in a meta-analysis of 11 trials [31], in the analysis of 10 trials in the current issue of the journal [9] and in other trials [32] with successful results. The prognostic relevance of the latter indices requires verification in outcome trials.

The optimal method and index for assessing BPV should combine technical and clinical features. Evidence should be provided that the BPV index: is easily measurable to be applicable in clinical practice; is reproducible; has defined normalcy and intervention thresholds; independently contributes to cardiovascular risk; is modifiable by treatment; and patients’ prognosis is improved when additional treatment targets are set for BPV beyond those for average BP. At present, evidence for most of these questions is missing, and therefore BPV remains a challenging research issue deserving thorough investigation. Future prospective trials should perform head-to-head comparisons of different BPV indices and test BPV as an additional target of treatment, aiming to more efficient prevention of organ damage and cardiovascular disease.

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Conflicts of interest

There are no conflicts of interest.

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