Clinical trials with endothelin receptor antagonists: What went wrong and where can we improve?

In the early 1990s, within three years of cloning of endothelin receptors, orally active endothelin receptor antagonists (ERAs) were tested in humans and the first clinical trial of ERA therapy in humans was published in 1995. ERAs were subsequently tested in clinical trials involving heart failure, pulmonary arterial hypertension, resistant arterial hypertension, stroke/subarachnoid hemorrhage and various forms of cancer. The results of most of these trials – except those for pulmonary arterial hypertension and scleroderma-related digital ulcers – were either negative or neutral. Problems with study design, patient selection, drug toxicity, and drug dosing have been used to explain or excuse failures. Currently, a number of pharmaceutical companies who had developed ERAs as drug candidates have discontinued clinical trials or further drug development. Given the problems with using ERAs in clinical medicine, at the Twelfth International Conference on Endothelin in Cambridge, UK, a panel discussion was held by clinicians actively involved in clinical development of ERA therapy in renal disease, systemic and pulmonary arterial hypertension, heart failure, and cancer. This article provides summaries from the panel discussion as well as personal perspectives of the panelists on how to proceed with further clinical testing of ERAs and guidance for researchers and decision makers in clinical drug development on where future research efforts might best be focused

Risk of cardiovascular disease and total mortality in adults with type 1 diabetes: Scottish registry linkage study

<p>Background: Randomized controlled trials have shown the importance of tight glucose control in type 1 diabetes (T1DM), but few recent studies have evaluated the risk of cardiovascular disease (CVD) and all-cause mortality among adults with T1DM. We evaluated these risks in adults with T1DM compared with the non-diabetic population in a nationwide study from Scotland and examined control of CVD risk factors in those with T1DM.</p> <p>Methods and Findings: The Scottish Care Information-Diabetes Collaboration database was used to identify all people registered with T1DM and aged ≥20 years in 2005–2007 and to provide risk factor data. Major CVD events and deaths were obtained from the national hospital admissions database and death register. The age-adjusted incidence rate ratio (IRR) for CVD and mortality in T1DM (n = 21,789) versus the non-diabetic population (3.96 million) was estimated using Poisson regression. The age-adjusted IRR for first CVD event associated with T1DM versus the non-diabetic population was higher in women (3.0: 95% CI 2.4–3.8, p<0.001) than men (2.3: 2.0–2.7, p<0.001) while the IRR for all-cause mortality associated with T1DM was comparable at 2.6 (2.2–3.0, p<0.001) in men and 2.7 (2.2–3.4, p<0.001) in women. Between 2005–2007, among individuals with T1DM, 34 of 123 deaths among 10,173 who were <40 years and 37 of 907 deaths among 12,739 who were ≥40 years had an underlying cause of death of coma or diabetic ketoacidosis. Among individuals 60–69 years, approximately three extra deaths per 100 per year occurred among men with T1DM (28.51/1,000 person years at risk), and two per 100 per year for women (17.99/1,000 person years at risk). 28% of those with T1DM were current smokers, 13% achieved target HbA1c of <7% and 37% had very poor (≥9%) glycaemic control. Among those aged ≥40, 37% had blood pressures above even conservative targets (≥140/90 mmHg) and 39% of those ≥40 years were not on a statin. Although many of these risk factors were comparable to those previously reported in other developed countries, CVD and mortality rates may not be generalizable to other countries. Limitations included lack of information on the specific insulin therapy used.</p> <p>Conclusions: Although the relative risks for CVD and total mortality associated with T1DM in this population have declined relative to earlier studies, T1DM continues to be associated with higher CVD and death rates than the non-diabetic population. Risk factor management should be improved to further reduce risk but better treatment approaches for achieving good glycaemic control are badly needed.</p&gt

Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease

Chronic kidney disease is common in the general population and associated with excess cardiovascular disease (CVD), but kidney function does not feature in current CVD risk-prediction models. We tested three formulae for estimated glomerular filtration rate (eGFR) to determine which was the most clinically informative for predicting CVD and mortality. Using data from 440,526 participants from UK Biobank, eGFR was calculated using serum creatinine, cystatin C (eGFRcys) and creatinine-cystatin C. Associations of each eGFR with CVD outcome and mortality were compared using Cox models and adjusting for atherosclerotic risk factors (per relevant risk scores), and the predictive utility was determined by the C-statistic and categorical net reclassification index. We show that eGFRcys is most strongly associated with CVD and mortality, and, along with albuminuria, adds predictive discrimination to current CVD risk scores, whilst traditional creatinine-based measures are weakly associated with risk. Clinicians should consider measuring eGFRcys as part of cardiovascular risk assessment

Comparison of conventional lipoprotein tests and apolipoproteins in the prediction of cardiovascular disease: data from UK Biobank

Background: Total cholesterol and high-density lipoprotein cholesterol (HDL-C) measurements are central to cardiovascular disease (CVD) risk assessment, but there is continuing debate around the utility of other lipids for risk prediction. Methods: Participants from UK Biobank without baseline CVD and not taking statins, with relevant lipid measurements (n=346 686), were included in the primary analysis. An incident fatal or nonfatal CVD event occurred in 6216 participants (1656 fatal) over a median of 8.9 years. Associations of nonfasting lipid measurements (total cholesterol, HDL-C, non–HDL-C, direct and calculated low-density lipoprotein cholesterol [LDL-C], and apolipoproteins [Apo] A1 and B) with CVD were compared using Cox models adjusting for classical risk factors, and predictive utility was determined by the C-index and net reclassification index. Prediction was also tested in 68 649 participants taking a statin with or without baseline CVD (3515 CVD events). Results: ApoB, LDL-C, and non–HDL-C were highly correlated (r>0.90), while HDL-C was strongly correlated with ApoA1 (r=0.92). After adjustment for classical risk factors, 1 SD increase in ApoB, direct LDL-C, and non–HDL-C had similar associations with composite fatal/nonfatal CVD events (hazard ratio, 1.23, 1.20, 1.21, respectively). Associations for 1 SD increase in HDL-C and ApoA1 were also similar (hazard ratios, 0.81 [both]). Adding either total cholesterol and HDL-C, or ApoB and ApoA, to a CVD risk prediction model (C-index, 0.7378) yielded similar improvement in discrimination (C-index change, 0.0084; 95% CI, 0.0065, 0.0104, and 0.0089; 95% CI, 0.0069, 0.0109, respectively). Once total and HDL-C were in the model, no further substantive improvement was achieved with the addition of ApoB (C-index change, 0.0004; 95% CI, 0.0000, 0.0008) or any measure of LDL-C. Results for predictive utility were similar for a fatal CVD outcome, and in a discordance analysis. In participants taking a statin, classical risk factors (C-index, 0.7118) were improved by non–HDL-C (C-index change, 0.0030; 95% CI, 0.0012, 0.0048) or ApoB (C-index change, 0.0030; 95% CI, 0.0011, 0.0048). However, adding ApoB or LDL-C to a model already containing non–HDL-C did not further improve discrimination. Conclusions: Measurement of total cholesterol and HDL-C in the nonfasted state is sufficient to capture the lipid-associated risk in CVD prediction, with no meaningful improvement from addition of apolipoproteins, direct or calculated LDL-C

Glycated hemoglobin, prediabetes and the links to cardiovascular disease: data from UK Biobank

OBJECTIVE: HbA1c levels are increasingly measured in screening for diabetes; we investigated whether HbA1c may simultaneously improve cardiovascular disease (CVD) risk assessment, using QRISK3, American College of Cardiology/American Heart Association (ACC/AHA), and Systematic COronary Risk Evaluation (SCORE) scoring systems. RESEARCH DESIGN AND METHODS: UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes. RESULTS: Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0–47.9 mmol/mol [6.0–6.4%]) and 0.7% (n = 2,573) had undiagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69–1.97) and 2.26 (95% CI 1.96–2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03–1.20) and 1.20 (1.04–1.38), respectively. Adding HbA1c to the QRISK3 CVD risk prediction model (C-index 0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001–0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models. CONCLUSIONS: The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed

Association with outcomes and response to treatment of trimethylamine N-oxide in heart failure (from BIOSTAT-CHF)

Aims: Association of elevated circulating levels of trimethylamine N-oxide (TMAO) with adverse outcomes in patients with heart failure (HF) has been described. However, response of TMAO levels to treatment and medications has not been investigated. Therefore, we investigated whether TMAO levels are responsive to guideline-recommended treatment and medications, and further reflect changes in outcomes. Methods and Results: TMAO levels were investigated in the systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF), which addressed response to guideline-recommended pharmacological treatment. TMAO levels in 2,234 patients with new-onset or progressively worsening HF showed strong associations with adverse events (mortality and /or rehospitalisation) at 1,2 and 3 years (HR 1.37–1.51, p≤0.019). Analysis of 972 patients with plasma available at both enrolment and follow-up visit showed reductions of B-type natriuretic peptide levels with guideline-based treatment (p<0.001), but not for TMAO levels. Moreover, patients with higher TMAO levels than median before and after treatment showed increased association with adverse outcomes (HR 2.21, 95% CI: 1.43-3.43, p<0.001) compared to patients with lower than median levels either before or after treatment (HR 1.13, 95% CI: 0.63-2.04, p=0.684 and HR 1.14, 95% CI: 0.64-2.03, p=0.662, respectively). Conclusion: TMAO levels were associated with adverse outcomes (mortality and/or rehospitalisation) in BIOSTAT-CHF, and did not respond to guideline-based pharmaceutical treatment in contrast to BNP levels which did as expected. Lower TMAO levels regardless of treatment were associated with favorable outcome

Contemporary Risk of Hip Fracture in Type 1 and Type 2 Diabetes:A National Registry Study From Scotland

The purpose of this study was to compare contemporary risk of hip fracture in type 1 and type 2 diabetes with the nondiabetic population. Using a national diabetes database, we identified those with type 1 and type 2 diabetes who were aged 20 to 84 years and alive anytime from January 1, 2005 to December 31, 2007. All hospitalized events for hip fracture in 2005 to 2007 for diabetes patients were linked and compared with general population counts. Age- and calendar-year-adjusted incidence rate ratios were calculated by diabetes type and sex. One hundred five hip fractures occurred in 21,033 people (59,585 person-years) with type 1 diabetes; 1421 in 180,841 people (462,120 person-years) with type 2 diabetes; and 11,733 hip fractures over 10,980,599 person-years in the nondiabetic population (3.66 million people). Those with type 1 diabetes had substantially elevated risks of hip fracture compared with the general population incidence risk ratio (IRR) of 3.28 (95% confidence interval [CI] 2.52–4.26) in men and 3.54 (CI 2.75–4.57) in women. The IRR was greater at younger ages, but absolute risk difference was greatest at older ages. In type 2 diabetes, there was no elevation in risk among men (IRR 0.97 [CI 0.92–1.02]) and the increase in risk in women was small (IRR 1.05 [CI 1.01–1.10]). There remains a substantial elevation relative risk of hip fracture in people with type 1 diabetes, but the relative risk is much lower than in earlier studies. In contrast, there is currently little elevation in overall hip fracture risk with type 2 diabetes, but this may mask elevations in risk in particular subgroups of type 2 diabetes patients with different body mass indexes, diabetes duration, or drug exposure

Heart failure with improved versus persistently reduced left ventricular ejection fraction:A comparison of the BIOSTAT-CHF (European) study with the ASIAN-HF registry

AimsWe investigated the prevalence, clinical characteristics, and prognosis of patients with heart failure (HF) with improved ejection fraction (HFimpEF).Methods and resultsWe used data from BIOSTAT-CHF including patients with a left ventricular ejection fraction (LVEF) ≤40% at baseline who had LVEF re-assessed at 9 months. HFimpEF was defined as a LVEF >40% and a LVEF ≥10% increase from baseline at 9 months. We validated findings in the ASIAN-HF registry. The primary outcome was a composite of time to HF rehospitalization or all-cause mortality. In BIOSTAT-CHF, about 20% of patients developed HFimpEF, that was associated with a lower primary event rate of all-cause mortality (hazard ratio [HR] 0.52, 95% confidence interval [CI] 0.28–0.97, p = 0.040) and the composite endpoint (HR 0.46, 95% CI 0.30–0.70, p < 0.001) compared with patients who remained in persistent HF with reduced ejection fraction (HFrEF). The findings were similar in the ASIAN-HF (HR 0.40, 95% CI 0.18–0.89, p = 0.024, and HR 0.29, 95% CI 0.17–0.48, p < 0.001). Five independently common predictors for HFimpEF in both BIOSTAT-CHF and ASIAN-HF were female sex, absence of ischaemic heart disease, higher LVEF, smaller left ventricular end-diastolic and end-systolic diameter at baseline. A predictive model combining only five predictors (absence of ischaemic heart disease and left bundle branch block, smaller left ventricular end-systolic and left atrial diameter, and higher platelet count) for HFimpEF in the BIOSTAT-CHF achieved an area under the curve of 0.772 and 0.688 in the ASIAN-HF (due to missing left atrial diameter and platelet count).ConclusionsApproximately 20–30% of patients with HFrEF improved to HFimpEF within 1 year with better clinical outcomes. In addition, the predictive model with clinical predictors could more accurately predict HFimpEF in patients with HFrEF

Association of fitness and grip-strength with heart failure: findings from the UK Biobank population-based study

Objective: To investigate the associations of objectively measured cardiorespiratory fitness (CRF) and grip strength (GS) with incident heart failure (HF), a clinical syndrome that results in substantial social and economic burden, using UK Biobank data. Patients and Methods: Of the 502,628 participants recruited into the UK Biobank between April 1, 2007, and December 31, 2010, a total of 374,493 were included in our GS analysis and 57,053 were included in CRF analysis. Associations between CRF and GS and incident HF were investigated using Cox proportional hazard models, with adjustment for known measured confounders. Results: During a mean of 4.1 (range, 2.4-7.1) years, 631 HF events occurred in those with GS data, and 66 HF events occurred in those with CRF data. Higher CRF was associated with 18% lower risk for HF (hazard ratio [HR], 0.82; 95% CI, 0.76-0.88) per 1–metabolic equivalent increment increase and GS was associated with 19% lower incidence of HF risk (HR, 0.81; 95% CI, 0.77-0.86) per 5-kg increment increase. When CRF and GS were standardized, the HR for CRF was 0.50 per 1-SD increment (95% CI, 0.38-0.65), and for GS was 0.65 per 1-SD increment (95% CI, 0.58-0.72). Conclusion: Our data indicate that objective measurements of physical function (GS and CRF) are strongly and independently associated with lower HF incidence. Future studies targeting improving CRF and muscle strength should include HF as an outcome to assess whether these results are causal

Using matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) profiling in order to predict clinical outcomes of patients with heart failure

Background Current risk prediction models in heart failure (HF) including clinical characteristics and biomarkers only have moderate predictive value. The aim of this study was to use matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) profiling to determine if a combination of peptides identified with MALDI-MS will better predict clinical outcomes of patients with HF. Methods A cohort of 100 patients with HF were recruited in the biomarker discovery phase (50 patients who died or had a HF hospital admission vs. 50 patients who did not have an event). The peptide extraction from plasma samples was performed using reversed phase C18. Then samples were analysed using MALDI-MS. A multiple peptide biomarker model was discovered that was able to predict clinical outcomes for patients with HF. Finally, this model was validated in an independent cohort with 100 patients with HF. Results After normalisation and alignment of all the processed spectra, a total of 11,389 peptides (m/z) were detected using MALDI-MS. A multiple biomarker model was developed from 14 plasma peptides that was able to predict clinical outcomes in HF patients with an area under the receiver operating characteristic curve (AUC) of 1.000 (p = 0.0005). This model was validated in an independent cohort with 100 HF patients that yielded an AUC of 0.817 (p = 0.0005) in the biomarker validation phase. Addition of this model to the BIOSTAT risk prediction model increased the predictive probability for clinical outcomes of HF from an AUC value of 0.643 to an AUC of 0.823 (p = 0.0021). Moreover, using the prediction model of fourteen peptides and the composite model of the multiple biomarker of fourteen peptides with the BIOSTAT risk prediction model achieved a better predictive probability of time-to-event in prediction of clinical events in patients with HF (p = 0.0005). Conclusions The results obtained in this study suggest that a cluster of plasma peptides using MALDI-MS can reliably predict clinical outcomes in HF that may help enable precision medicine in HF