PharmacoEconomics最新文献

Objectives: Bevacizumab was approved for first-line treatment of metastatic colorectal cancer (mCRC) in 2004. However, adding bevacizumab to treatment consistently fails to be cost-effective owing to modest response rates. Recently, the European Commission (EC) funded ANGIOPREDICT consortium ( www.angiopredict.com ) identified a link between bevacizumab treatment response and intermediate-to-high chromosomal instability (CIN) in mCRC. Thus, the objective of the current study was to compare the cost-effectiveness of adding bevacizumab with first-line chemotherapy in the bevacizumab responsive CIN subtype across three European countries (Germany, Ireland and Spain) with varying costs of care and reimbursement policies.

Methods: We developed an open-source health economic model to estimate cost-effectiveness. The ANGIOPREDICT cohort informed progression risks and cause-specific mortality. Health utilities and adverse events probabilities were obtained from the literature. Costs were derived from surveys of collaborating consortium hospitals in Germany, Ireland, and Spain that participated in the recently completed EC funded COLOSSUS translational study (ANGIOPREDICT successor initiative) and the literature. Sensitivity analyses included individual and simultaneous variation of input parameters from a priori defined distributions.

Results: Bevacizumab was not cost effective even at willingness-to-pay (WTP) thresholds that are appreciably higher than those considered realistic. The highest incremental cost-effectiveness ratio (ICER) was in Germany at €241,188 per quality-adjusted life year (QALY), while the lowest was in Ireland at €180,477 per QALY. All deterministic and probabilistic sensitivity analyses demonstrated that these results were robust.

Conclusions: Even for patients with mCRC manifesting improved outcomes, adding bevacizumab to first-line chemotherapy is invariably not cost-effective in any of the countries examined. Variability in pricing, healthcare costs and WTP thresholds across countries did not commute this result.

Valuing pediatric health-related quality of life (HRQOL) is essential for economic evaluations in child healthcare. Instruments like EQ-5D-Y were developed for this purpose. A key methodological innovation-though controversial-has been the use of the child perspective for valuation of EQ-5D-Y health states, where adults value health states imagining a 10-year-old child. This paper critically reviews empirical findings on this approach, examines potential biases, assesses alignment with stakeholder views, and explores alternatives. We relied on a targeted review of empirical literature, including studies comparing adults valuing their own health (adult perspective) and using child perspectives, as well as stakeholder opinion studies. Findings were synthesized into ten key learnings: (1) Child-perspective valuations are typically higher than adult ones for the same health states. (2) Adults prioritize pain/discomfort and being sad/unhappy differently for children. (3) Child age has minimal impact. Mechanisms contributing to differences between adult and child perspectives include (4) discomfort with child death, (5) different valuations of life duration, (6) psychological distance, (7) emotional difficulty deciding for others, and (8) external goals influencing results. Stakeholder engagement shows that (9) the effects of using child perspectives do not align well with societal preferences, and (10) stakeholders express a preference for approaches that directly involve children and adolescents in valuation tasks. We conclude that relying on child perspectives may introduce systematic biases, potentially undermining the validity of pediatric health utilities. A re-evaluation of current valuation methods for EQ-5D-Y may be warranted, with greater consideration for direct child involvement, mapping techniques, and group-based deliberative approaches.

Background and objective: Collaborative engagement with individuals invested in or affected by health research, beyond researchers themselves, is advantageous and encouraged by major funding bodies. However, the degree of collaborative engagement in health state valuation is unclear. A scoping review was conducted to (i) identify recommendations on best practice in collaborative engagement in health economics and related literature; (ii) identify examples of collaborative engagement in valuation studies; and (iii) map (ii) onto (i) to identify current practice and future recommendations.

Methods: Eight databases were searched in March-May 2024, with grey literature searches in August-September 2024. For objective (i), reports or manuscripts in health economics or patient-reported outcome measure development/evaluation of any date providing recommendations for collaborative engagement were included. For objective (ii), articles published since 2019 featuring health state valuation and collaborative engagement were included. Best practice recommendations were extracted and thematically synthesised. Examples of collaborative engagement were extracted and mapped against recommendations.

Results: Twenty-two records featuring recommendations and 15 valuation studies were included. A 15-item framework of emerging best practice recommendations for collaborative engagement was synthesised. Most examples of collaborative engagement involved patients and/or experts helping inform health states for valuation. There was no evidence for 9 out of 15 synthesised recommendations having been applied in any of the valuation studies and only minimal evidence was extracted for the remaining six.

Conclusions: Collaborative engagement in health state valuation is underdeveloped and unaligned with literature recommendations. A 15-point framework has been developed as a strategic starting point for developing guidance to improve practice in the field.

Background: An economic evaluation is widely used to facilitate decision making regarding drug reimbursement in many healthcare systems. However, the absence of preference-based measurement in clinical trials has hindered the health economic evaluation of drugs for rare diseases.

Objective: This study aims to develop mapping algorithms that convert disease-specific scales-Spinal Muscular Atrophy Independence Scale (SMAIS) for spinal muscular atrophy and Functional Assessment of Cancer Therapy-Anemia (FACT-An) for paroxysmal nocturnal hemoglobinuria-into five-level EQ-5D (EQ-5D-5L) and SF-6D version 2 (SF-6Dv2) utility values, thereby enabling the economic evaluation of related drugs.

Methods: Data were collected from two online surveys conducted in China. Both direct and indirect mapping methods were explored, including ordinary least squares regression, Tobit regression model, censored least absolute deviation, generalized linear model, beta mixture regression, adjusted limited dependent variable mixture model, ordinal logistic regression (OLOGIT), and multinomial logistic regression (MLOGIT). Model performance was assessed by mean absolute error (MAE), root mean squared error (RMSE), and adjusted R-square (adjusted R²). The optimal model was selected based on the lowest average ranking value, derived from the MAE and RMSE through five-fold cross-validation.

Results: A total of 192 patients with spinal muscular atrophy and 306 patients with paroxysmal nocturnal hemoglobinuria were included in the analysis. For spinal muscular atrophy, the MLOGIT, which included SMAIS total score and sex as predictors, demonstrated the best performance, with the lowest MAE and RMSE (EQ-5D-5L: MAE: 0.1471; RMSE: 0.1839; adjusted R²: 0.5932; SF-6Dv2: MAE: 0.1208; RMSE: 0.1563; adjusted R²: 0.4323) after five-fold cross-validation. For paroxysmal nocturnal hemoglobinuria, the OLOGIT model using the FACT-An dimension score performed best (EQ-5D-5L: MAE: 0.1068; RMSE: 0.1431; adjusted R²: 0.5394; SF-6Dv2: MAE: 0.0877; RMSE: 0.1162; adjusted R²: 0.6754).

Conclusions: These newly developed mapping algorithms enable the estimation of EQ-5D-5L and SF-6Dv2 utilities in the absence of a preference-based measurement, thus supporting health economic evaluations of therapies for spinal muscular atrophy and paroxysmal nocturnal hemoglobinuria.

National Institute for Health and Care Excellence (NICE) technology appraisal processes assume that the standard of care (SoC) is itself cost effective. However, many treatments in use in the UK National Health Service (NHS), particularly in rare diseases, were historically commissioned without formal value assessment and are priced without reference to cost-effectiveness thresholds. Cost-ineffective comparators distort how value is ascribed to new technologies, undermining the coherence of NICE's decision-making framework, and imposing substantial opportunity costs on the NHS. Using late-onset Pompe disease (LOPD) as an exemplar, we demonstrate the implications of a cost-ineffective comparator in assessments of innovative therapies. A clinically superior enzyme replacement therapy (ERT) may command a lower value-based price than current ERTs, whilst a hypothetical curative gene therapy is valued at over £4 million against current ERT, but just £629,392 when re-anchored against best supportive care. Here, value is driven by displacement of costs rather than health gain, raising affordability concerns that may limit access to genuine innovation. The 2025 NHS 10-Year Plan grants new NICE statutory powers to withdraw access to cost-ineffective therapies, presenting an opportunity to reform technology appraisal. We propose several policy responses, including comprehensive reassessment of active guidance with decisions made with respect to a standard cost-effectiveness frontier, reviews triggered by new comparators, and use of flexible decision rules within existing frameworks. These changes could allow the evolving value of medicines to be reflected in NHS practice, redefining NICE as a body that takes a dynamic, whole-lifecycle view of value. Deliberative public and stakeholder engagement is essential for success, given the potential consequences for manufacturers and patients.

Background: Post-traumatic stress disorder (PTSD) is a debilitating condition that arises after exposure to a traumatic event and leads to significant impairment in daily functioning if left untreated. Economic evaluations are essential for understanding the comparative value of PTSD treatments and ultimately supporting their implementation. Several model-based economic evaluations exist in this area; however, these can differ in their methodological approaches and parameter inputs, which can influence conclusions drawn.

Objective: This systematic review aimed to explore model structures and parameter inputs employed in model-based economic evaluations of PTSD treatment.

Methods: A literature search was carried out in the following databases: MEDLINE, PsycINFO, SCOPUS, Econlit, CINAHL, Web of Science Core Collection, and Cochrane Collaboration Library between 1 January 2000 and 1 May 2025. Studies were eligible if they presented a full economic evaluation of a treatment for PTSD using a decision-analytic model. Data relating to the model structure and parameter inputs were extracted and quality assessment was conducted.

Results: This review identified 14 model-based studies, of which two used decision trees, six used a Markov model, four used a combined decision tree and Markov model, and two used an agent-based model. There was significant variation across model parameters, including in disease conceptualisation and progression, data sources utilised, assumptions reported, and costs included. The quality assessment revealed the following key areas of concern: insufficient consideration of methodological uncertainty and heterogeneity, internal consistency, and incorporation of relevant disease and intervention characteristics.

Conclusions: This paper highlights important variations in current model-based economic evaluations of PTSD treatment. Future work should seek to generate evidence to support consistency in future economic evaluations of PTSD treatment options.

Background and objective: The reliability of a decision model to guide decision making depends on its ability to accurately predict patient outcomes. We present results of an external validation of the MicroSimulation Core Obesity Model (MS-COM) that was developed to compare the cost effectiveness of obesity management interventions in adults.

Methods: We updated a 2018 systematic literature review of economic models in overweight and obesity and conducted additional targeted searches to identify suitable sources and outcomes to validate against MS-COM in people with overweight or obesity with or without type 2 diabetes. We extracted baseline characteristics and cardiovascular and mortality outcomes, where these were closely matched with MS-COM, and incidence of type 2 diabetes. We performed external-dependent (sources used in MS-COM) and external-independent (sources not used in MS-COM) validation. The extent of concordance between predicted and observed outcomes was assessed using the coefficient of determination (R²), ordinary least-squares linear regression line (OLS LRL), mean absolute percentage error, root mean square percentage error and mean squared log of accuracy ratio.

Results: Ninety-nine potential independent validation sources were identified from 6381 screened records, of which nine studies reported cardiovascular and mortality outcomes that were closely matched with MS-COM, along with two studies that reported type 2 diabetes incidence (number of endpoints = 106). The dependent validation of cardiovascular and mortality outcomes (N = 18), based on the QRisk3 risk equation (normoglycaemia/prediabetes population) and UKPDS 82 (type 2 diabetes population), showed a good linear correlation with observed outcomes (R² = 0.99 and 0.98, respectively). There was some slight overprediction of QRisk3 (OLS LRL slope = 1.11) and underprediction of UKPDS 82 (OLS LRL slope = 0.97). The independent validation of cardiovascular and mortality outcomes also showed a good linear correlation with observed outcomes, particularly in adults with normoglycaemia/prediabetes (R² = 0.90; OLS LRL slope = 0.86); however, an independent validation of type 2 diabetes incidence showed a poorer fit with some degree of underprediction (R² = 0.74; OLS LRL slope = 0.66). Mean error estimates were lower in the dependent validation, showing good concordance between predicted and observed values.

Conclusions: External validation of MS-COM showed good concordance with dependent and independent sources, suggesting the model accurately predicts obesity-related complications in an overweight/obese population with normoglycaemia/prediabetes and type 2 diabetes.

Objectives: Obstructive hypertrophic cardiomyopathy (oHCM) is a myocardial disease, characterised by left ventricular hypertrophy, hampering the ventricular blood outflow. Standard of care (SoC) includes medications such as beta-blockers (BB) and calcium channel blockers (CCB) and septal reduction therapies. Recently, mavacamten, a first-in-class myosin inhibitor, became available to oHCM patients. The objective was to develop a decision analytic model to evaluate the cost effectiveness of mavacamten compared with SoC in oHCM patients from a Dutch societal perspective.

Methods: A Markov model was developed in R based on the Decision Analysis in R for Technologies in Health framework with data from the EXPLORER-HCM trial. This trial compared mavacamten in combination with background therapy (BB and CCB) versus placebo, including oHCM patients (n = 251; mean age 59 years) in New York Heart Association (NYHA) functional classes II (72.9%) and III (27.1%). For the model, four health states were defined based on the NYHA classes, including NYHA I-NYHA III/IV and death. The model evaluated mavacamten with SoC versus SoC alone over a lifetime horizon with a cycle length of 4 weeks, following the most recent Dutch guidelines. Health state utilities and societal costs were derived from the AFFECT-HCM study, with utilities measured using the EQ-5D-5L. Outcomes included (incremental) societal costs, life years (LYs), quality-adjusted life years (QALYs) and the incremental cost-effectiveness ratio (ICER). The Dutch willingness-to-pay thresholds of €50,000 and €80,000 per QALY were applied. Uncertainty of parameters was assessed in deterministic and probabilistic sensitivity and scenario analyses.

Results: Results indicate mavacamten being more effective (Δ4.75 LYs; Δ3.36 QALYs) and more costly (Δ€235,951) compared with SoC with an ICER of €70,223 per QALY gained. Varying parameters by 20% showed that the utility value of patients in NYHA class I (ICER: €57,199; €111,506 per QALY) and drug costs (ICER: €53,985; €86,555 per QALY) were most sensitive. Mavacamten accumulated most LYs, QALYs and costs by patients improving to NYHA class I, compared with SoC, and patients remained longer in that state throughout the model. For men, incremental QALYs (Δ 3.36) and costs (Δ €239,743) were slightly higher compared with women. The probability of the intervention being cost effective at the willingness-to-pay thresholds €50,000 and €80,000 per QALY was 1.3% and 87.4%, respectively. Conclusion The results show that mavacamten increased LYs and QALYs compared with SoC, however, at substantial additional costs. The probability of mavacamten being cost effective depends on the selected willingness-to-pay threshold.

Patient and public involvement (PPI) in health economics modelling is increasingly recommended, yet formal guidance for how to structure or evaluate it remains limited. The Values in Modelling (VIM) framework was developed to address this gap by helping teams identify and deliberate on value-laden decisions in modelling. Drawing on philosophical theory, the framework defines five steps to guide collaboration between modellers and transdisciplinary participators and to document their influence on decision making: (1) identify ethical issues and perspectives; (2) characterize modelling decisions; (3) select decision-making strategies; (4) deliberate 'open' decisions; and (5) report and evaluate. We applied the VIM framework in the Lifetime Exposures and Asthma Outcomes Projection (LEAP) model project, which models the cost effectiveness of high-efficiency particulate air (HEPA) filters for asthma prevention and management. In this application, the framework helped prioritize modelling decisions for PPI, supported transparent deliberation about uncertainty, and led to concrete methodological changes-including new sensitivity analyses and revised outcome measures. These results demonstrate how a theory-informed process can enhance PPI in modelling, improving transparency, justification, and adequacy-for-purpose in health economics research.