Burden of elevated lipoprotein(a) among patients with atherosclerotic cardiovascular disease: Evidence from a systematic literature review and feasibility assessment of meta-analysis.

BACKGROUND: Elevated lipoprotein(a) [Lp(a)] level is an independent genetic risk factor that increases the risk of atherosclerotic cardiovascular disease (ASCVD) by 2-4 fold. We aimed to report the burden of clinically relevant elevated Lp(a) in secondary prevention ASCVD population as the evaluation of such evidence is lacking. METHODS: A systematic literature review (SLR) was conducted using Embase®, MEDLINE®, and MEDLINE® In-Process databases to identify studies reporting burden of elevated Lp(a) levels from January 1, 2010, to March 28, 2022. Full-text, English-language studies including ≥500 participants with ≥1 Lp(a) assessment were included. RESULTS: Sixty-one studies reported clinical burden of elevated Lp(a). Of these, 25 observational studies and one clinical trial reported clinical burden of clinically relevant elevated Lp(a) levels. Major clinical outcomes included major adverse cardiovascular event (MACE; n = 20), myocardial infarction (MI; n = 11), revascularization (n = 10), stroke (n = 10), cardiovascular (CV) mortality (n = 9), and all-cause mortality (n = 10). Elevated Lp(a) levels significantly increased the risk of MACE (n = 15) and revascularization (n = 8), while they demonstrated a trend for positive association with remaining CV outcomes. Meta-analysis was not feasible for included studies due to heterogeneity in Lp(a) thresholds, outcome definitions, and patient characteristics. Three studies reported humanistic burden. Patients with elevated Lp(a) levels had higher odds of manifesting cognitive impairment (odds ratio [OR] [95% confidence interval; CI]: 1.62 [1.11-2.37]) and disability related to stroke (OR [95% CI]:1.46 [1.23-1.72)]) (n = 2). Elevated Lp(a) levels negatively correlated with health-related quality of life (R = -0.166, p = 0.014) (n = 1). A single study reported no association between elevated Lp(a) levels and economic burden. CONCLUSIONS: This SLR demonstrated a significant association of elevated Lp(a) levels with major CV outcomes and increased humanistic burden in secondary prevention ASCVD population. These results reinforce the need to quantify and manage Lp(a) for CV risk reduction and to perform further studies to characterize the economic burden.

Evaluation of COPD Treatments: A Multicriteria Decision Analysis of Aclidinium and Tiotropium in the United States.

BACKGROUND: Comparisons of the use of aclidinium bromide and tiotropium bromide for the treatment of chronic obstructive pulmonary disease often concentrate on key end points (exacerbations) at the expense of other benefits and risks. Multicriteria decision analysis (MCDA) can help overcome this by using stakeholder preferences to combine multiple end points into an overall value estimate. OBJECTIVES: To evaluate the use of aclidinium bromide twice daily via Pressair™ (AstraZeneca Pharmaceuticals LP, Wilmington, DE) and of tiotropium once daily via HandiHaler® (Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT) from the perspective of patients using MCDA. METHODS: Literature reviews and clinician engagement were used to identify value criteria. Performance of criteria was estimated from a clinical trial and clinician opinion. Scores and swing weights came from six clinicians who, during a 2-day workshop, reflected their patients' preferences. Scenario and sensitivity analyses were used to explore uncertainty in model designs and inputs. RESULTS: Fourteen criteria, covering clinical effectiveness, safety, and convenience of the treatments of chronic obstructive pulmonary disease, were identified. Exacerbations and device preloading were identified as the most important to patients; the least important was rescue medication use. Tiotropium's higher overall clinical effectiveness score was offset by aclidinium's better performance on safety and convenience outcomes. The MCDA generated a -42 (worst performance) to 100 (best performance) scale. The net impact of benefits over risks of aclidinium (38.5) exceeded that of tiotropium (13.2), and patients preferred aclidinium 79.7% of the time. CONCLUSIONS: When considering clinical benefits and risks, aclidinium and tiotropium generate similar value to patients, but when convenience criteria are considered, aclidinium may be preferred. Further work is required to replicate these results, including eliciting preferences directly from patients.

The Economic Impact of Lower Protein Infant Formula for the Children of Overweight and Obese Mothers.

The global prevalence of obesity is rising rapidly, highlighting the importance of understanding risk factors related to the condition. Childhood obesity, which has itself become increasingly prevalent, is an important predictor of adulthood obesity. Studies suggest that the protein content consumed in infanthood is an important predictor of weight gain in childhood, which may contribute to higher body mass index (BMI). For instance, there is evidence that a lower protein infant formula (lpIF) for infants of overweight or obese mothers can offer advantages over currently-used infant formulas with regard to preventing excessive weight gain. The current study used health economic modelling to predict the long-term clinical and economic outcomes in Mexico associated with lpIF compared to a currently-used formula. A discrete event simulation was constructed to extrapolate the outcomes of trials on the use of formula in infanthood to changes in lifetime BMI, the health outcomes due to the changes in BMI and the healthcare system costs, productivity and quality of life impact associated with these outcomes. The model predicts that individuals who receive lpIF in infancy go on to have lower BMI levels throughout their lives, are less likely to be obese or develop obesity-related disease, live longer, incur fewer health system costs and have improved productivity. Simulation-based economic modelling suggests that the benefits seen in the short term, with the use of lpIF over a currently-used formula, could translate into considerable health and economic benefits in the long term. Modelling over such long timeframes is inevitably subject to uncertainty. Further research should be undertaken to improve the certainty of the model.

Model-based cost-effectiveness analyses for the treatment of chronic lymphocytic leukaemia: a review of methods to model disease outcomes and estimate utility.

Assessing the economic value of treatments for chronic lymphocytic leukaemia (CLL) is necessary to support healthcare decision makers; however, it poses a number of challenges. This paper reviews economic models of CLL treatment to learn the lessons from this experience and support ongoing model efforts. A search of databases and submissions to key health technology assessment agencies identified nine models. The modelling approaches adopted across these studies were fairly similar, with most models adopting a cohort Markov structure, though one example of a discrete event simulation was identified. While the cohort Markov approach has been acceptable to the National Institute for Health and Care Excellence, the review identifies a number of key uncertainties with these models, including the extrapolation of survival outcomes beyond the period observed by the trial, the effectiveness of second-line therapies, and estimates of health state utility. Further work is required to overcome these uncertainties, including comprehensive sensitivity analysis, systematic review of the evidence on the natural progression of CLL, and the collection of longer-term trial and registry data.

Model-based cost-effectiveness analyses for the treatment of chronic myeloid leukaemia: a review and summary of challenges.

Assessing the economic value of treatments for chronic myeloid leukaemia (CML) is important but poses a number of challenges. This paper reviews economic models of CML treatment to learn lessons from this experience and support ongoing efforts to model CML. A search of databases and submissions to key health technology assessment agencies identified 12 studies that reported 22 models. Common practice included the use of cohort Markov models-most models used health states organised around the key stages in CML: chronic phase, accelerated phase and blast phase-and the use of utility estimates in the literature that correspond with the National Institute for Health and Care Excellence reference case. Two key areas of uncertainty were the extrapolation of survival outcomes beyond the period observed by the trial; and the effectiveness of second-line therapies. Further work is required to overcome these uncertainties in existing models, such as longer-term trial data collection, including trials of second-line therapies; validation of health-related quality-of-life instruments; and the testing of alternative modelling approaches. In the meantime, it is important that the impact of uncertainties is tested through the use of sensitivity and scenario analysis.

Assessing the value of healthcare interventions using multi-criteria decision analysis: a review of the literature.

The objective of this study is to support those undertaking a multi-criteria decision analysis (MCDA) by reviewing the approaches adopted in healthcare MCDAs to date, how these varied with the objective of the study, and the lessons learned from this experience. Searches of EMBASE and MEDLINE identified 40 studies that provided 41 examples of MCDA in healthcare. Data were extracted on the objective of the study, methods employed, and decision makers' and study authors' reflections on the advantages and disadvantages of the methods. The recent interest in MCDA in healthcare is mirrored in an increase in the application of MCDA to evaluate healthcare interventions. Of the studies identified, the first was published in 1990, but more than half were published since 2011. They were undertaken in 18 different countries, and were designed to support investment (coverage and reimbursement), authorization, prescription, and research funding allocation decisions. Many intervention types were assessed: pharmaceuticals, public health interventions, screening, surgical interventions, and devices. Most used the value measurement approach and scored performance using predefined scales. Beyond these similarities, a diversity of different approaches were adopted, with only limited correspondence between the approach and the type of decision or product. Decision makers consulted as part of these studies, as well as the authors of the studies are positive about the potential of MCDA to improve decision making. Further work is required, however, to develop guidance for those undertaking MCDA.