PharmacoEconomics最新文献

Objective: In this study we aimed to identify possible changes over time in validation efforts and the way in which they are reported for model-based health economic (HE) evaluations, given the introduction of several new validation tools and methods in the past decade.

Methods: A systematic review was conducted using PubMed and Embase on published HE models for early breast cancer (EBC) for the period 2016 to 2024. AdViSHE-consisting of four validation categories that cover the main HE model aspects-was utilized to systematically evaluate the reported evaluation efforts. The percentage of studies reporting validation per category was compared with the review by de Boer et al. that covers the years 2008 to 2015.

Results: Of the 2199 records, 78 studies fulfilled the eligibility criteria. Reported validation efforts did not significantly improve compared with the previous period, except for the validation of input data by experts. Reporting on the validation of the conceptual model remained low with around 10% of the studies providing validation. Validation of the computerized model and validation against outcomes using alternative input data were the most underreported validation categories with < 4% of the studies. The validation of model outcomes, specifically cross validity and the comparison with empirical data, remained the most reported categories in this review also, with 52% and 36%, respectively. When validation efforts were reported, this was done in a non-systematic manner, and the tests and results were rarely detailed.

Conclusion: Overall reporting of validation efforts for model-based HE evaluations in the past decade did not significantly change compared with the previous decade.

Introduction: Stakeholder preference evaluations are increasingly emphasized in healthcare policy and health technology assessment. Discrete choice experiments (DCEs) are the most common method for quantifying preferences among patients, the public, and healthcare professionals. While prior reviews (1990-2017) have examined DCE trends, no comprehensive synthesis exists for studies published since 2018. This updated review (2018-2023) provides critical insights into evolving methodologies and global trends in health-related DCEs.

Methods: A systematic search (2018-2023) of Medline, Embase, and Web of Science identified relevant studies. Studies were screened for inclusion and data were extracted, including details on DCE design and analysis. To enable trend comparisons, the search strategy and extraction items aligned with previous reviews.

Results: Of 2663 identified papers, 1279 met the inclusion criteria, reflecting a significant rise in published DCEs over time. DCEs were conducted globally, with a remarkable increase in publications from Asia and Africa compared with previous reviews. Experimental designs and econometric models have advanced, continuing prior trends. Notably, most recent DCEs were administered online.

Discussion: The rapid growth of DCE applications underscores their importance in health research. While the methodology is advancing rapidly, it is crucial that researchers provide full transparency in reporting their methods, particularly in detailing experimental designs and validity tests, which are too often overlooked. Key recommendations include improving reporting of experimental designs, applying validity tests, following good practices for presenting benefit-risk attributes, and adopting open science practices. Ensuring methodological rigor will maximize the impact and reproducibility of DCE research in health economics.

Introduction: The EQ-5D is the most commonly used preference-based measure of health-related quality of life. There is limited evidence about the use of the EQ-5D in the Middle East and North Africa (MENA) region. This study aimed to systematically identify, review, summarize, and synthesize the published literature on using the EQ-5D in this region.

Methods: A systematic literature review was conducted, according to the PRISMA 2020 guidelines, using PubMed, Cochrane, PsycINFO, and CINAHL and covering the period up to 30 August 2024. Studies using any version of the EQ-5D in adults or youth in the MENA region were included. Pilot studies, guidelines, study protocols, and reviews were excluded. Key study characteristics and outcomes assessed included study design, clinical area, population, type of EQ-5D data reported, reference value set used, and mode of administration. Title/abstract screening was conducted independently by two reviewers to assess eligibility for inclusion. Two researchers completed full-text screening and extracted data using a standardized form. Disagreements were referred to a third reviewer if not resolved by discussion. Results were summarized in systematic evidence tables.

Results: After removing duplicates, 18,034 references were considered for title/abstract screening. In total, 184 studies were included with a total sample size of 128,164 subjects. Of the included single-country studies, 42% were reported in Iran, 20% in Saudi Arabia, and 11% in Jordan. Patient populations were investigated in 86% of the studies, 23% of which targeted endocrine diseases. Study design was observational in 57% and experimental in 14% of the studies. Only 10% of the included studies applied the EQ-5D in an economic evaluation. The EQ-5D-3L version was used in 40% of the studies. However, the trend is towards a greater use of the 5L version in more recent years. Twenty percent of the studies reported EQ-5D results using the index score, frequencies of severity levels per dimension, and visual analog scale scores. EQ-5D modes of administration and funding sources were not reported in 16% and 20% of the studies, respectively.

Conclusion: There is an increased use of the EQ-5D in the MENA region, especially since 2020. In the region, the use of the EQ-5D is more prevalent in clinical studies than in economic evaluation studies. The reporting heterogeneity indicates the need for guidance in reporting EQ-5D study results in this region.

Objectives: Multiple sclerosis (MS) is a progressive, degenerative, autoimmune neuronal disease. This study compares the impact of a societal versus a healthcare perspective on the cost effectiveness of treatment of primary progressive MS (PPMS) with ocrelizumab (OCR) versus best supportive care (BSC) in New Zealand.

Methods: The analysis utilises a lifetime cohort Markov model based on ten Expanded Disability Status Scale (EDSS) states, plus death. It has two structurally identical arms, with forward transition probabilities in the treatment arm obtained by multiplying forward transition probabilities (converted to rates, and back to probabilities) in the control arm by the 12-week disability progression hazard ratio in the clinical trial ORATORIO. Direct and indirect costs of MS were estimated from a 2017 Australian survey and converted to 2024 NZ dollars using purchasing power parity and the NZ consumer price index. Future costs and benefits were discounted at 3.5% per annum. The model is calibrated to NZ mortality for PPMS, and therapy ends when wheelchair dependence (EDSS7) is reached.

Results: For a modelled cohort 40 years of age starting at the ORATORIO distribution of EDSS, at 50% of the list price (viz. 50% rebate on $NZ37,384 per patient per annum), the incremental cost-effectiveness ratio (ICER) of OCR versus BSC is $NZ114,427 per QALY ($US64,651) from a societal perspective or $NZ146,711 ($US82,892) from a healthcare perspective. From a societal perspective, at Treasury's willingness to pay (WTP) criterion of $NZ120,200, an acquisition cost up to 56% of list price ($NZ20,935; 44% rebate) is justifiable. From a healthcare payer perspective, at Treasury's implied WTP of $NZ43,313, an acquisition cost up to 10% of list price ($NZ3738; 90% rebate) is justifiable. Based on this metric, a 5.6-fold higher investment in OCR can be justified from a societal perspective compared with a healthcare perspective. Alternatively, an acquisition cost up to 37.9% of list price (viz. 62.1% rebate or $NZ14,169) could be justified if the criterion of one GDP per capita ($NZ83,011) is used as a societal funding threshold. These results are sensitive to the cost of BSC from a societal perspective but not from a healthcare perspective. From both perspectives the cost effectiveness is sensitive to the acquisition cost and efficacy of OCR, potential waning of efficacy, the age and EDSS state when therapy begins, the cost and timing of entry of a biosimilar pharmaceutical and the discount rate.

Conclusions: Treatment of PPMS with OCR is more cost effective from a societal than a healthcare perspective, therefore prioritisation of public funding of novel pharmaceuticals for MS and other resource intensive chronic health conditions will depend critically upon the study perspective.

Objectives: Impacts on informal carers are increasingly being incorporated into cost-of-illness and cost-effectiveness analyses. However, little is known about whether the method used to identify carers affects the estimated impacts. We compare a novel time diary technique to a common self-declaration question for identifying carers. We investigate whether it: (1) detects more and different carers, and (2) if carers across identification techniques have different mental health outcomes.

Methods: We use the Innovation Panel component of the UK Household Longitudinal Study, which records all activities performed in two 24-h periods and contains a rich set of individual characteristics. We use regression analysis to compare the number and characteristics of carers identified across the two methods. We then use the doubly robust approach of entropy balancing combined with regression adjustment to estimate the mental health impacts of caregiving across both methods.

Results: Among 1055 individuals, we identify 261 carers by at least one method. The self-declaration method fails to classify 16% of individuals identified as carers through time diary data. We find that carers identified by the time diary have a 1.24 (p < 0.05) higher score on the 36-point General Health Questionnaire (GHQ) scale in the subsequent survey wave compared with similar non-carers. For self-declared carers, the estimated difference in GHQ score is 0.36 (p > 0.1), a smaller and statistically non-significant association compared with that observed among time diary-identified carers CONCLUSIONS: The mental health impacts of caregiving may be underestimated when carers are identified by self-declaration. Supplementing self-declaration with time diaries may offer a means of including more carers. Future research, if only one method is applied, should more carefully consider the means of identifying informal carers and the implications that the use of one method may have on conclusions.

Background: People with stomas report a substantial negative impact of stomal effluent leaking outside the ostomy baseplate and subsequent complications in their professional and social lives, causing immense worry. However, many patients are not able to recognize leakages in a timely manner. We conducted a cost-effectiveness study to evaluate the impact of a digital leakage notification system (DLNS) to reduce leakages outside the baseplate (LOB) and worry about leakage for people with intestinal stomas from a UK National Health Service and Personal Social Services perspective.

Methods: A Markov model for ostomy care was used to compare health-related quality of life and costs for adults with ileostomies or colostomies using UK standard of care ostomy products with the DLNS (intervention) or without the DLNS (comparator). The base case model used a 3-year time horizon with 1-week cycles and an annual 3.5% discounting of utilities and costs. Patients in all health states experience LOB events and/or worry about leakage as events associated with one-time utility decrements and costs of additional healthcare provider visits and ostomy product use. Probabilities of LOB (DLNS, 46.5%; comparator, 78.6%) and worry about leakage (DLNS, 39.1%; comparator, 78.6%) were based on clinical trial results. Peristomal skin complications were included in the model with the same probabilities of occurrence in the intervention and comparator arms. Sensitivity and scenario analyses were performed to test the robustness of the base case model assumptions.

Results: In the base case analysis, the DLNS arm had 49.81 fewer LOB events per person than the comparator arm, resulting in 0.309 incremental quality-adjusted life-years (QALYs) and cost savings of British Pound Sterling (GBP) £1703 per person over 3 years (2023/2024 costing year). The DLNS arm had 56.98 fewer worry about leakage events per person, resulting in cost savings of £403 per person. Total costs and QALYs were £18,600 and 1.818 for the intervention arm, respectively, and £18,566 and 1.509 for the comparator arm. Overall, the DLNS provided 0.309 incremental QALYs at an incremental cost of £34 versus the comparator arm for an incremental cost-effectiveness ratio of £110/QALY gained, well below a willingness-to-pay threshold of £20,000/QALY. Sensitivity analyses showed the DLNS was cost-effective in 97.6% of simulations.

Conclusions: This analysis suggests that the DLNS added to standard of care ostomy products is a cost-effective intervention to help prevent LOB events and reduce worry about leakage for people with stomas in the UK. Results of the present study suggest that timely awareness of leakage has a positive impact on the health-related quality of life of people with stomas and on the direct costs of stoma management in the UK.

Microsimulation models have become increasingly common in the field of decision modeling for health. Because microsimulation models are computationally more demanding than traditional Markov cohort models, the use of computer programming languages in their development has become more common. C++ is a programming language that has gained widespread recognition in computationally intensive fields, including systems modeling and performance-critical applications. It offers powerful tools for building high-performance microsimulation models, outpacing many traditional modeling software solutions, such as native R, in terms of speed and control over memory management. However, there is limited accessible guidance for implementing microsimulation models in C++. This tutorial offers a step-by-step approach to constructing microsimulation models in C++ and demonstrates its application through simplified but adaptable example decision models. We walk the reader through essential steps and provide generic C++ code that is flexible and suitable for adapting to a range of models. Finally, we present the standalone C++ models and their Rcpp counterparts run within R, and compare their performance to equivalent R implementations in terms of speed and memory efficiency.

Background: Numerous health technology assessment guidance documents emphasize the importance of biological/clinical plausibility of modeled lifetime incremental survival without clearly defining it.

Objectives: This paper defines biologically and clinically plausible lifetime survival extrapolations and proposes a framework to systematically assess this by comparing survival expectations estimated premodeling, with the final modeled survival extrapolations. This framework is embedded in a survival extrapolation protocol template, which ensures that both the expectations and extrapolations are based on unified, comprehensive evidence.

Methods: A targeted review was conducted of 29 guidance documents from National Institute for Health and Care Excellence, Pharmaceutical Benefits Advisory Committee, Haute Autorité de Santé, Canada's Drug Agency, and European joint clinical assessment, focusing on survival analysis, evidence synthesis, cost-effectiveness modeling methods, and use of observational data.

Results: Survival extrapolations are biologically/clinically plausible when "predicted survival estimates that fall within the range considered plausible a-priori, obtained using a-priori justified methodology." These a priori expectations should utilize the totality of evidence available and take into account local target setting (i.e., survival-influencing aspects such as patient population, treatment pathway, and country). Pre-protocolized biologically/clinically plausible survival extrapolation was operationalized in a five-step DICSA approach: (1) Describe the target setting as defined by all relevant treatment and disease aspects that influence survival; (2) collect Information from relevant sources; (3) Compare survival-influencing aspects across information sources; (4) Set pre-protocolized survival expectations and plausible ranges; and (5) Assess how trial-based extrapolations align with the set expectations by comparing modeled survival extrapolations to the range of values a priori considered to be plausible.

Conclusion: The definition of plausibility of survival extrapolations, the operationalization of its assessment, and the corresponding extrapolation protocol template can contribute to the transparent development of biologically/clinically plausible survival extrapolations.