Background and objective: The Dutch costing manual, part of the national guideline for economic evaluations, provides reference prices and standardized cost calculation methods to ensure transparency and comparability. Since its last update in 2015, new evidence, updated cost data, and user needs prompted an updated version to reflect current best practices and expand scope. The aim of this article is to present the update of the costing manual and the introduction of the web application facilitating regular updates.
Methods: The update of the costing manual followed a three-step approach. First, improvement needs were identified by user surveys and experts. Secondly, methodological guidance was revised using recent literature, national data sources, and expert input. Thirdly, the reference prices were updated. In parallel, a technical web application was developed and tested to facilitate ongoing digital access and regular updates.
Results: The updated costing manual consists of revised and updated references prices, including expanded intersectoral reference prices (e.g., education and justice). Clearer methodological guidance and improved transparency were established. Testing showed that the web-based application was intuitive to use and accurately reproduced reference prices consistent with the updated costing manual.
Conclusions: The costing manual was updated in line with the recent guidelines for economic evaluations. The manual is a comprehensive manual for use in costing studies for economic evaluations in healthcare from a societal perspective. The web-based application translated the costing manual into a practical digital tool, automating cost calculations and demonstrated usability, accuracy, and consistency with the manual.
Objective: To develop a patient-level simulation model of type 1 diabetes (T1D) covering both childhood and adulthood. The goal is to identify and evaluate the cost-effectiveness of optimal screening for pre-symptomatic T1D.
Methods: We developed a Python-based simulation model to track 100,000 participants screened in childhood, capturing a subset of those at risk and transitioning to T1D, to estimate the incremental cost-effectiveness per life year gained of screening versus no screening. Our multi-objective optimisation approach sought to minimise three objectives: incremental cost effectiveness ratio, diabetic ketoacidosis (DKA) events at onset and the maximum number of screening tests a child can have with the healthcare system. The NSGA-II algorithm is used to explore the set of possible screening strategies from combinations of genetic risk score (GRS) and islet autoantibody (IA) measurements at different ages and frequencies during the first 15 years of life. Data for transition probabilities include large scale screening studies such as The Environmental Determinants of Diabetes in the Young, TrialNet, published risk functions, clinical trials and epidemiologic studies.
Results: We illustrate the use of multi-objective optimisation in patient-level simulations by estimating an optimal subset of T1D screening strategies in the USA. We identify four screening strategies with incremental cost-effectiveness ratios that meet commonly cited cost-effectiveness thresholds, which require, respectively, a maximum of 1, 2 3 and 4 islet autoantibody (IA) tests.
Conclusions: This article and corresponding model code can be used as a reference for implementing a multi-objective optimisation pipeline in patient-level simulation models.
Purpose: Healthcare decision-making often assumes equal value for quality-adjusted life years (QALYs) across patient groups, yet societal preferences suggest that the value of a QALY may vary with characteristics such as age. Evidence indicates some willingness to prioritise child health gains, though findings are inconsistent. This study used person trade-off (PTO) to estimate the relative social value of different types of health gains for children and adolescents (aged 0-24 years) compared with adults.
Methods: A representative Australian sample aged 16 years and above (n = 2098) completed an online survey comparing life extension and quality-of-life improvements for different ages. A 'chaining' approach tested response consistency, and logistic regression explored associations between PTO choices and respondent characteristics. Attitudinal questions and open text responses provided additional insights.
Results: PTO responses show that health gains for children and adolescents (4-24 years) are generally valued more highly than those for adults (age 40 or 55 years), with weights ranging from 1 to 1.3. For very young children, findings vary by health gain type: life extensions for infants (1 month or 2 years) are weighted lower, but pain alleviation is higher (weights ≥ 1.2). Qualitative and attitudinal data reveal diverse views, with many opposing age-weighting. Younger respondents and those with young children prioritise children more, while older and female participants preferred equal treatment.
Conclusions: The relative value of child QALY gains varies by age of the child, by health gain type, and by adult comparison age. While alleviating children's pain is strongly supported (weights ≥ 1.2), overall views are polarised, highlighting the complexity of age-based prioritisation.
Introduction: Prostate cancer (PC) is the second most common cancer in men. Although many studies have assessed its economic burden, no recent reviews have focused on studies conducted under current clinical guidelines. This study systematically reviews recent cost-of-illness studies evaluating direct and indirect costs associated with PC.
Methods: A systematic search was conducted using the PICOS framework and a combination of free-text and MeSH terms in PubMed and the Cochrane Library, and only free-text terms in EconLit. The search included articles published between January 2015 and October 2025. Data on total, direct, and indirect costs were extracted and synthesized. All costs were converted to 2025 USD, and quality of studies was assessed with a simplified version of the CHEERS checklist.
Results: Ninety-five studies met the inclusion criteria. Direct medical costs for non-metastatic prostate cancer (nmPC) varied widely by disease stage, treatment, and country, ranging from approximately US$1200 to US$280,000 per patient-year, with higher costs observed in advanced stages and in patients experiencing treatment-related adverse events (AEs). Progression to metastatic disease was associated with a marked cost escalation, with annual costs largely driven by systemic therapies and skeletal-related events. Indirect costs ranged from US$666 to US$12,900 per patient-year and accounted for up to 30% of total PC-related costs, primarily due to productivity losses from premature mortality.
Conclusions: PC imposes a substantial economic burden on healthcare systems and society, particularly in advanced stages. Policy promoting early detection, risk-adapted treatment, and equitable therapy access may help contain costs. Further research should address the economic impact of emerging diagnostics and minimally invasive interventions.
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.
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