Cardiovascular outcomes in patients at high cardiovascular risk with previous myocardial infarction or stroke

Cost-effectiveness of group medical visits and microfinance interventions versus usual care to manage hypertension in Kenya: a secondary modelling analysis of data from the Bridging Income Generation with Group Integrated Care (BIGPIC) trial

BACKGROUND

The Bridging Income Generation with Group Integrated Care (BIGPIC) trial in rural Kenya showed that integrating usual care with group medical visits or microfinance interventions reduced systolic blood pressure and cardiovascular risk in participants. We aimed to estimate the incremental cost-effectiveness of three BIGPIC interventions for a modelled cohort and by sex, as well as the cost of implementing these interventions.

METHODS

For this analysis, we used data collected during the BIGPIC trial, a four-group, cluster-randomised trial conducted in the western Kenyan catchment area of the Academic Model Providing Access to Healthcare. BIGPIC enrolled participants from 24 rural health facilities in rural western Kenya aged 35 years or older with either increased blood pressure or diabetes. Participants were assigned to receive either usual care, group medical visits, microfinance, or a combination of group medical visits and microfinance (GMV-MF). Our model estimated the incremental cost-effectiveness of the three BIGPIC interventions via seven health states (ie, a hypertensive state, five chronic cardiovascular-disease states, and a death state) by simulating transitions between health states for a hypothetical cohort of individuals with hypertension on the basis of QRISK3 scores. In every cycle, participants accrued costs and disability-adjusted life-years (DALYs) associated with their health state. Incremental cost-effectiveness ratios (ICERs) were calculated for the entire modelled cohort and by sex by dividing the incremental cost by the incremental effectiveness of the next most expensive intervention. The main outcome of this analysis was ICERs for each intervention evaluated. This analysis is registered at ClinicalTrials.gov (NCT02501746).

FINDINGS

Between Feb 6, 2017, and Dec 29, 2019, 2890 people were recruited to the BIGPIC trial. 2020 (69·9%) of 2890 participants were female and 870 (30·1%) were male. At baseline, mean QRISK3 score was 11·5 (95% CI 11·1-11·9) for the trial population, 11·9 (11·5-12·2) for male participants, and 11·3 (11·0-11·6) for female participants. For the population of Kenya, group medical visits were estimated to cost US$7 more per individual than usual care and result in 0·005 more DALYs averted (ICER $1455 per DALY averted). Microfinance was estimated to cost $19 more than group medical visits but was only estimated to avert 0·001 more DALYs. Relative to group medical visits, GMV-MF was estimated to cost $29 more and avert 0·009 more DALYs ($3235 per DALY averted). Relative to usual care, GMV-MF was estimated to cost $37 more and avert 0·014 more DALYs ($2601 per DALY averted). In the first year of the intervention, usual care was estimated to be the least expensive intervention to implement ($87 per participant; $10 238 per health-facility catchment area [HFCA]), then group medical visits ($99 per participant; $12 268 per HFCA), then microfinance ($120 per participant; $14 172 per HFCA), with GMV-MF estimated to be the most expensive intervention to implement ($139 per participant; $16 913 per HFCA).

INTERPRETATION

Group medical visits and GMV-MF were estimated to be cost-effective strategies to improve blood-pressure control in rural Kenya. However, which intervention to pursue depends on resource availability. Policy makers should consider these factors, in addition to sex differences in programme effectiveness, when selecting optimal implementation strategies.

FUNDING

US National Institutes of Health.

Cost-Effectiveness of a Multicomponent Primary Care Intervention for Hypertension

BACKGROUND

The SingHypertension primary care clinic intervention, which consisted of clinician training in hypertension management, subsidized single-pill combination medications, nurse-delivered motivational conversations and telephone follow-ups, improved blood pressure control and cardiovascular disease (CVD) risk scores relative to usual care among patients with uncontrolled hypertension in Singapore. This study quantified the incremental cost-effectiveness, in terms of incremental cost per unit reduction disability-adjusted life years, of SingHypertension relative to usual care for patients with hypertension from the health system perspective.

METHODS AND RESULTS

We developed a Markov model to simulate CVD events and associated outcomes for a hypothetical cohort of patients over a 10-year period. Costs were measured in US dollars, and effectiveness was measured in disability-adjusted life years averted. We present base-case results and conducted deterministic and probabilistic sensitivity analyses. Based on a willingness-to-pay threshold of US $55 500 per DALY averted, SingHypertension was cost-effective for patients with hypertension (incremental cost-effectiveness ratio: US $24 765 per disability-adjusted life year averted) relative to usual care. This result held even if risk reduction was assumed to decline linearly to 0 over 10 years but not sooner than 7 years. Incremental cost-effectiveness ratios were most sensitive to the magnitude of the reduction in CVD risk; at least a 0.13% to 0.16% point reduction in 10-year CVD risk is required for cost-effectiveness. Probabilistic sensitivity analysis indicates that SingHypertension has a 78% chance of being cost-effective at the willingness-to-pay threshold.

CONCLUSIONS

SingHypertension represents good value for the money for reducing CVD incidence, morbidity, and mortality and should be considered for wide-scale implementation in Singapore and possibly other countries.

REGISTRATION INFORMATION

REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02972619.

Mortality risk reduction with budesonide/glycopyrrolate/formoterol fumarate versus fluticasone furoate/umeclidinium/vilanterol in COPD: a matching-adjusted indirect comparison based on ETHOS and IMPACT

OBJECTIVE

Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide. While two approved fixed-dose inhaled corticosteroid/long-acting muscarinic antagonist (LAMA)/long-acting β2-agonist (LABA) triple therapies reduce all-cause mortality (ACM) versus dual LAMA/LABA therapy in patients with COPD, head-to-head studies have not compared the effects of these therapies on ACM. We compared ACM in adults with moderate-to-very severe COPD receiving budesonide/glycopyrrolate/formoterol fumarate (BGF) in ETHOS versus fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) in IMPACT using a matching-adjusted indirect comparison (MAIC).

METHODS

A systematic literature review identified two studies (ETHOS [NCT02465567]; IMPACT [NCT02164513]) of ≥52 weeks reporting ACM as an efficacy endpoint in patients receiving triple therapy. As ETHOS and IMPACT lack a common comparator, an unanchored MAIC compared ACM between licensed doses of BGF (320/18/9.6 μg) from ETHOS and FF/UMEC/VI (100/62.5/25 μg) from IMPACT in patients with moderate-to-very severe COPD. Using on- and off-treatment data from the final retrieved datasets of the intention-to-treat populations, BGF data were adjusted according to aggregate FF/UMEC/VI data using 11 baseline covariates; a supplementary unadjusted indirect treatment comparison was also conducted. P-values for these post-hoc analyses are not adjusted for Type I error.

RESULTS

ACM over 52 weeks was statistically significantly reduced by 39% for BGF versus FF/UMEC/VI in the MAIC (hazard ratio [HR] [95% CI]: 0.61 [0.38, 0.95], p = 0.030) and unadjusted analysis (HR [95% CI]: 0.61 [0.41, 0.92], p = 0.019).

CONCLUSION

In this MAIC, which adjusted for population heterogeneity between ETHOS and IMPACT, ACM was significantly reduced with BGF versus FF/UMEC/VI in patients with moderate-to-very severe COPD.

The challenges and pitfalls of incorporating evidence from cardiovascular outcomes trials in health economic modelling of type 2 diabetes

The clinical evidence base for evaluating modern type 2 diabetes interventions has expanded greatly in recent years, with numerous efficacious treatment options available (including dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors). The cardiovascular safety of these interventions has been assessed individually versus placebo in numerous cardiovascular outcomes trials (CVOTs), statistically powered to detect differences in a composite endpoint of major adverse cardiovascular events. There have been growing calls to incorporate these data in the long-term modelling of type 2 diabetes interventions because current diabetes models were developed prior to the conduct of the CVOTs and therefore rely on risk equations developed in the absence of these data. However, there are numerous challenges and pitfalls to avoid when using data from CVOTs. The primary concerns are around the heterogeneity of the trials, which have different study durations, inclusion criteria, rescue medication protocols and endpoint definitions; this results in significant uncertainty when comparing two or more interventions evaluated in separate CVOTs, as robust adjustment for these differences is difficult. Analyses using CVOT data inappropriately can dilute clear evidence from head-to-head clinical trials, and blur healthcare decision making. Calibration of existing models may represent an approach to incorporating CVOT data into diabetes modelling, but this can only offer a valid comparison of one intervention versus placebo based on a single CVOT. Ideally, model development should utilize patient-level data from CVOTs to prepare novel risk equations that can better model modern therapies for type 2 diabetes.

Predicting functional outcome in acute ischemic stroke patients after endovascular treatment by machine learning

BACKGROUND

Endovascular therapy (EVT) was the standard treatment for acute ischemic stroke with large vessel occlusion. Prognosis after EVT is always a major concern. Here, we aimed to explore a predictive model for patients after EVT.

METHOD

A total of 156 patients were retrospectively enrolled. The primary outcome was functional dependence (defined as a 90-day modified Rankin Scale score ≤ 2). Least absolute shrinkage and selection operator and univariate logistic regression were used to select predictive factors. Various machine learning algorithms, including multivariate logistic regression, linear discriminant analysis, support vector machine, k-nearest neighbors, and decision tree algorithms, were applied to construct prognostic models.

RESULT

Six predictive factors were selected, namely, age, baseline National Institute of Health Stroke Scale (NIHSS) score, Alberta Stroke Program Early CT (ASPECT) score, modified thrombolysis in cerebral infarction score, symptomatic intracerebral hemorrhage (sICH), and complications (pulmonary infection, gastrointestinal bleeding, and cardiovascular events). Based on these variables, various models were constructed and showed good discrimination. Finally, a nomogram was constructed by multivariate logistic regression and showed a good performance.

CONCLUSION

Our nomogram, which was composed of age, baseline NIHSS score, ASPECT score, recanalization status, sICH, and complications, showed a very good performance in predicting outcome after EVT.

Hypertension management in patients with cardiovascular comorbidities

Arterial hypertension is a leading cause of death globally. Due to ageing, the rising incidence of obesity, and socioeconomic and environmental changes, its incidence increases worldwide. Hypertension commonly coexists with Type 2 diabetes, obesity, dyslipidaemia, sedentary lifestyle, and smoking leading to risk amplification. Blood pressure lowering by lifestyle modifications and antihypertensive drugs reduce cardiovascular (CV) morbidity and mortality. Guidelines recommend dual- and triple-combination therapies using renin–angiotensin system blockers, calcium channel blockers, and/or a diuretic. Comorbidities often complicate management. New drugs such as angiotensin receptor-neprilysin inhibitors, sodium–glucose cotransporter 2 inhibitors, glucagon-like peptide-1 receptor agonists, and non-steroidal mineralocorticoid receptor antagonists improve CV and renal outcomes. Catheter-based renal denervation could offer an alternative treatment option in comorbid hypertension associated with increased sympathetic nerve activity. This review summarises the latest clinical evidence for managing hypertension with CV comorbidities.