Efficacy and effectiveness of valsartan/amlodipine and valsartan/amlodipine/hydrochlorothiazide in hypertension: randomized controlled versus observational studies

Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials: a meta-epidemiological study

BACKGROUND

Researchers and decision-makers often use evidence from randomised controlled trials (RCTs) to determine the efficacy or effectiveness of a treatment or intervention. Studies with observational designs are often used to measure the effectiveness of an intervention in 'real world' scenarios. Numerous study designs and their modifications (including both randomised and observational designs) are used for comparative effectiveness research in an attempt to give an unbiased estimate of whether one treatment is more effective or safer than another for a particular population. An up-to-date systematic analysis is needed to identify differences in effect estimates from RCTs and observational studies. This updated review summarises the results of methodological reviews that compared the effect estimates of observational studies with RCTs from evidence syntheses that addressed the same health research question.

OBJECTIVES

To assess and compare synthesised effect estimates by study type, contrasting RCTs with observational studies. To explore factors that might explain differences in synthesised effect estimates from RCTs versus observational studies (e.g. heterogeneity, type of observational study design, type of intervention, and use of propensity score adjustment). To identify gaps in the existing research comparing effect estimates across different study types.

SEARCH METHODS

We searched MEDLINE, the Cochrane Database of Systematic Reviews, Web of Science databases, and Epistemonikos to May 2022. We checked references, conducted citation searches, and contacted review authors to identify additional reviews.

SELECTION CRITERIA

We included systematic methodological reviews that compared quantitative effect estimates measuring the efficacy or effectiveness of interventions tested in RCTs versus in observational studies. The included reviews compared RCTs to observational studies (including retrospective and prospective cohort, case-control and cross-sectional designs). Reviews were not eligible if they compared RCTs with studies that had used some form of concurrent allocation.

DATA COLLECTION AND ANALYSIS

Using results from observational studies as the reference group, we examined the relative summary effect estimates (risk ratios (RRs), odds ratios (ORs), hazard ratios (HRs), mean differences (MDs), and standardised mean differences (SMDs)) to evaluate whether there was a relatively larger or smaller effect in the ratio of odds ratios (ROR) or ratio of risk ratios (RRR), ratio of hazard ratios (RHR), and difference in (standardised) mean differences (D(S)MD). If an included review did not provide an estimate comparing results from RCTs with observational studies, we generated one by pooling the estimates for observational studies and RCTs, respectively. Across all reviews, we synthesised these ratios to produce a pooled ratio of ratios comparing effect estimates from RCTs with those from observational studies. In overviews of reviews, we estimated the ROR or RRR for each overview using observational studies as the reference category. We appraised the risk of bias in the included reviews (using nine criteria in total). To receive an overall low risk of bias rating, an included review needed: explicit criteria for study selection, a complete sample of studies, and to have controlled for study methodological differences and study heterogeneity. We assessed reviews/overviews not meeting these four criteria as having an overall high risk of bias. We assessed the certainty of the evidence, consisting of multiple evidence syntheses, with the GRADE approach.

MAIN RESULTS

We included 39 systematic reviews and eight overviews of reviews, for a total of 47. Thirty-four of these contributed data to our primary analysis. Based on the available data, we found that the reviews/overviews included 2869 RCTs involving 3,882,115 participants, and 3924 observational studies with 19,499,970 participants. We rated 11 reviews/overviews as having an overall low risk of bias, and 36 as having an unclear or high risk of bias. Our main concerns with the included reviews/overviews were that some did not assess the quality of their included studies, and some failed to account appropriately for differences between study designs - for example, they conducted aggregate analyses of all observational studies rather than separate analyses of cohort and case-control studies. When pooling RORs and RRRs, the ratio of ratios indicated no difference or a very small difference between the effect estimates from RCTs versus from observational studies (ratio of ratios 1.08, 95% confidence interval (CI) 1.01 to 1.15). We rated the certainty of the evidence as low. Twenty-three of 34 reviews reported effect estimates of RCTs and observational studies that were on average in agreement. In a number of subgroup analyses, small differences in the effect estimates were detected: - pharmaceutical interventions only (ratio of ratios 1.12, 95% CI 1.04 to 1.21); - RCTs and observational studies with substantial or high heterogeneity; that is, I2 ≥ 50% (ratio of ratios 1.11, 95% CI 1.04 to 1.18); - no use (ratio of ratios 1.07, 95% CI 1.03 to 1.11) or unclear use (ratio of ratios 1.13, 95% CI 1.03 to 1.25) of propensity score adjustment in observational studies; and - observational studies without further specification of the study design (ratio of ratios 1.06, 95% CI 0.96 to 1.18). We detected no clear difference in other subgroup analyses.

AUTHORS' CONCLUSIONS

We found no difference or a very small difference between effect estimates from RCTs and observational studies. These findings are largely consistent with findings from recently published research. Factors other than study design need to be considered when exploring reasons for a lack of agreement between results of RCTs and observational studies, such as differences in the population, intervention, comparator, and outcomes investigated in the respective studies. Our results underscore that it is important for review authors to consider not only study design, but the level of heterogeneity in meta-analyses of RCTs or observational studies. A better understanding is needed of how these factors might yield estimates reflective of true effectiveness.

Multi-task learning for predicting synergistic drug combinations based on auto-encoding multi-relational graphs

Combinatorial drug therapy is a promising approach for treating complex diseases by combining drugs with synergistic effects. However, predicting effective drug combinations is challenging due to the complexity of biological systems and the limited understanding of pathophysiological mechanisms and drug targets. In this paper, we proposed a computational framework called VGAETF (Variational Graph Autoencoder Tensor Decomposition), which leveraged multi-relational graph to model complex relationships between entities in biological systems and predicted disease-related synergistic drug combinations in an end-to-end manner. In the computational experiments, VGAETF achieved high performances (AUROC [the area under receiver operating characteristic] = 0.9767, AUPR [the area under precision-recall] = 0.9660), outperforming other compared methods. Moreover, case studies further demonstrated the effectiveness of VGAETF in identifying potential disease-related synergistic drug combinations.

"The impact of statins addind to the fixed combination antihypertensive therapy on the arterial stiffness in patients with moderate and severe hypertension"

Aim

The objective of this study was the evaluation of the arterial stiffness, which changed after adding statins to the guidelines recommended dual or triple fixed combination antihypertensive therapy in patients with moderate to severe arterial hypertension.

Materials and methods

It was included 99 patients in total being diagnosed with moderate and severe arterial hypertension (2nd and 3rd stages of arterial hypertension) without diabetes. Those patients were divided into 2 groups. The first group (n = 59) was assigned to the dual or triple fixed combination antihypertensive therapy plus including statins.Patients in the second group (n = 40) received only the dual or triple fixed combination antihypertensive treatment following the recommended guidelines without any statins. The CAVI index was performed in order to measure in all participants before and at the end of the follow-up period. Furthermore, the Office (Clinic BP) Blood Pressure (BP) was monitored in assigned participants as well as the Ambulatory Blood Pressure Monitoring (ABPM). The laboratory investigations also took place such as the standard blood test, the urine and biochemistry analysis and the estimated Carotid Intima-Media Thicknesses with Ultrasound. The study-duration was 6 months.

Results

Office BP and ABPM had decreased significantly and equally in both treatment groups. The total cholesterol (TC) and LDL cholesterol had decreased significantly in the statin group on 1,76 mmol/l (30%, p < 0,05) and 1,51 mmol/l (41%, p < 0,05) respectively. In the group without statin therapy, there was no changes in the level of TC and LDL cholesterol. In the group without statins, it was noted a significant decrease in the level of BP, however, the CAVI index level was shown the growth to +0,9 units on the right side and +1,0 units on the left.In the group without statin's treatment, the CAVI index was changed from 7.73 ± 0.17/7.62 ± 0.19 units to 8.63 ± 0.22/8.62 ± 0.12 units on the right/left site after treatment (p < 0,05). It means there was an increase in the stiffness of the arterial wall in terms of cardio-vascular index CAVI in the group without added statin after 6 months of the therapy. In the group with added statin after 6 months of the therapy, the CAVI had not have any changes. It can be seen from the observed figures: the CAVI on the right/left site was 8.32 ± 0.16/8.33 ± 0.19 initially and 8.44 ± 0.16/8.24 ± 0.15 units treatment (p > 0,05) afterwards.We did not note any impact of statin therapy on the BP level. However, a significant correlations was found between the CAVI index with age and the serum level of blood Triglycerides before treatment, including LDL Cholesterol and HDL Cholesterol, duration of hypertension, the blood glucose level, the Potassium level and the Maximum Thickness of Intima-Media of Carotid Arteries in the statins group.

Conclusion

The adding of the statin to the current fixed dual or triple combination of the antihypertensive therapy could prevent the progression of arterial stiffness in patients with 2nd and 3rd stages of arterial hypertension.

An LC-MS/MS Method for Determination of Triple Drugs Combination of Valsartan, Amlodipine and Hydrochlorothiazide in Human Plasma for Bioequivalence Study

Background:

Current guidelines for the treatment of hypertension recommend combination therapy, which intends to control blood pressure and enhance cardiovascular protection.

Materials and Methods:

A sensitive, reliable and selective tandem mass spectrometry (LC-MS/MS) method has been developed for simultaneous quantification of amlodipine (AML), valsartan (VAL) and hydrochlorothiazide (HCTZ) in human plasma. The chromatographic system was equipped with ACE 5 C8 (50 X 2.1 mm) column and utilized a mobile phase composition of 0.5 mM Ammonium Chloride & 0.04% FA-Methanol (45:55% v/v). The method used three internal standards; AML-D4, HCTZ-D2 C13 and VAL-D3 with 10% intra- and inter-day precision, and 6% bias for all the analytes.

Results:

The assay was found to be linear with R-2 > 0.998, and the limits of quantification for AML, VAL and HCTZ were 0.2, 50.0 and 2.0 ng/mL, respectively. The analytes were found to be stable in plasma samples over short and long term storage.

:

The developed method is rapid with a run time of 3.5 min and cost-effective since the simple sample preparation method is adopted. This method was successfully applied for the bioequivalence study of AML, VAL, and HCTZ in human plasma after administration of the fixed-dose combination tablet of (10/160/25 mg). Pharmacokinetic parameters (Cmax and AUC0-72) for AML and (Cmax, AUC0-t, AUC0-∞) for VAL and HCTZ were used for bioequivalence assessment. These were determined by noncompartmental analysis of concentration data.

Conclusion:

The result showed 90% confidence intervals (obtained by ANOVA) which were within the predefined ranges. As a consequence, this method can be successfully applied for measuring and quantifying a large number of samples.

Big data and real-world data-based medicine in the management of hypertension

Big data has been a hot topic in medical and healthcare research. Big data in healthcare is considered to comprise massive amounts of information from various sources, including electronic health records (EHRs), administrative or claims data, and data from self-monitoring devices. Biomedical research has also generated a significant portion of big data relevant to healthcare. Other large datasets arise from cohorts that are recruited and followed on the basis of specific questions, although such research questions may later be expanded to enable other investigations. While the availability of big data offers many possibilities for an improved understanding of disease and treatment, the need for careful and productive use of statistical concepts should be kept in mind. Patient data routinely collected via electronic means are called real-world data (RWD) and are becoming common in healthcare research. RWD and big data are not synonymous with each other, but the two terms seem to be used without distinction with respect to observational studies. In this article, we review hypertension-related papers that use big data or RWD. There are many other sources of big data or RWD that are not covered here, each of which may pose special challenges and opportunities. While randomized clinical trials (RCTs) are considered to be the criterion standard for generating clinical evidence, the use of real-world evidence (RWE) to evaluate the efficacy and safety of medical interventions is gaining interest. On-going efforts to make use of RWD to generate RWE for regulatory decisions, as well as the challenges confronted, including reliability (quality) and relevance (fitness for purpose) of data, will also be addressed.

Nebivolol/valsartan combination for the treatment of hypertension: a review

Nebivolol (N) is a β₁-adrenoreceptor antagonist that is approved for treatment of hypertension in the USA. Effective treatment of hypertension is becoming an increasingly difficult process that often requires multiple drug combinations to meet target guidelines. This has resulted in the increasing introduction of multidrug single-pill combinations (SPCs) to facilitate cost and compliance issues. Some of the SPCs have added valsartan (V), an angiotensin receptor blocker, which is an increasingly advocated antihypertensive class. Pharmacological profiles of N and V, alone and combined, are well characterized. In 2007, the SPC of N and V, 5 and 80 mg, respectively, was approved by the US FDA for treatment of hypertension. This paper will summarize and update key issues in pharmacology, clinical use and benefit.