The term ultra-rare diseases was first introduced in 2004 by the National Institute for Health and Care Excellence during the evaluation of drugs indicated for conditions with a prevalence of fewer than 1 case per 50,000 people. This review aims to systematically examine the clinical evidence synthesis practices used worldwide to support decision-making on the incorporation of new drugs for treating ultra-rare diseases and to identify the definitions of ultra-rare diseases adopted internationally. This review follows the JBI methodology for reviews of textual evidence, including narrative reports, expert opinions, and policy documents. Eligible sources will include texts and studies addressing patients with ultra-rare diseases. The phenomenon of interest is the set of methods and practices used for synthesizing clinical evidence to inform the incorporation of health technologies for ultra-rare genetic diseases. This review focuses on the context of global health technology assessment (HTA) agencies. Searches will be conducted in the PubMed, Embase, CENTRAL, and Virtual Health Library databases, as well as on the websites of major international HTA agencies. Study selection, data extraction, and risk-of-bias assessment will be performed independently and in duplicate. Proportional meta-analyses will be conducted to summarize the frequency of study designs, outcomes, and recommendations according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach applied by HTA agencies when assessing drugs for ultra-rare diseases. The findings of this review are expected to inform the development of methodological guidelines for evidence synthesis in ultra-rare diseases-from defining ultra-rare conditions to establishing best practices for evidence generation and evaluation. In the long term, the results may guide strategies to address methodological challenges in primary studies on the efficacy and safety of health technologies for ultra-rare diseases, such as strengthening national patient registries and promoting multicenter collaborative research. PROSPERO CRD420250652106.

The majority of decision analytic models submitted to health technology assessment (HTA) agencies are developed using Microsoft Excel. The approaches commonly used to construct these models have not been substantially updated in decades, and studies have found that spreadsheet models are often slower and more difficult to validate than models built using R. However, Excel and Google Sheets were recently upgraded to add support for dynamic array functions. This allows for many of the techniques used in R modeling to be applied to spreadsheet models. This paper provides a tutorial on how these new functions can be leveraged to build efficient Markov cohort models using modern spreadsheet software. A novel approach is presented for conducting Monte Carlo simulation using a single formula in one cell, without the need for Visual Basic for Applications (VBA) macros. A number of template formulas are also provided that can be used to assist in common modeling tasks, including constructing a Markov trace and calculating the table of probabilities needed to plot cost-effectiveness acceptability curves (CEACs). These template formulas may be directly copied and pasted into any spreadsheet model, with no add-ons, plug-ins, or additional packages required. These advancements have the potential to modernize how spreadsheet models are developed, simplifying their construction, improving their calculation speed, and reducing the time needed for validation. They will also aid in teaching more efficient approaches for decision analytic modeling to a new generation of students.

Cardiac implantable electronic devices (CIEDs) are crucial in managing various cardiac conditions, but their monitoring poses considerable challenges. Algorithm-enabled remote monitoring of these devices has emerged as a promising solution to enhance patient outcomes and potentially reduce health care expenditures; however, its economic impact remains underexplored. This systematic review protocol aims to review and synthesize the existing evidence on the cost-effectiveness and cost-utility of algorithm-enabled remote monitoring for CIEDs in patients with or at risk of heart failure. The search of literature will be performed in MEDLINE, Embase, Scopus, Web of Science, and the Cochrane Library, with supplementary searches in the National Health Service Economic Evaluation Database, the National Institute for Health and Care Excellence, the Canadian Agency for Drugs and Technologies in Health, the International Network of Agencies for Health Technology Assessment, and the National Institute for Health and Care Research. This protocol is reported in accordance with the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols) 2015 statement, and the completed review will be reported following the PRISMA 2020 statement. Following database searching and deduplication, 3108 records were retrieved; 731 (23.5%) duplicates were removed, leaving 2377 (76.5%) records for title and abstract screening. The review will identify and synthesize economic evaluations of algorithm-enabled remote monitoring in adults with CIEDs, summarizing reported costs, outcomes, and cost-effectiveness results. Methodological quality, risk of bias, and sources of heterogeneity across studies will be assessed. The findings of this review may help inform health care providers, policymakers, and other stakeholders by clarifying the current economic evidence on these monitoring systems, informing adoption decisions, and identifying areas requiring further research.

Aim: Epcoritamab, the first subcutaneous (SC) bispecific approved for relapsed/refractory diffuse large B-cell lymphoma (R/R-DLBCL), offers potential advantages in terms of healthcare resource utilization (HCRU) associated with its SC administration. This study aimed to estimate HCRU and associated costs of R/R-DLBCL treatments, to inform health technology assessment agencies, institutional decision makers and healthcare professionals (HCP) from both a Canadian and Quebec perspective. Secondary objectives included using a societal perspective and estimating chair time and HCP time involved in administering treatments. Materials & methods: A 1-year costing analysis was developed comparing epcoritamab to other R/R-DLBCL treatments, including glofitamab, CAR-T cell therapies, chemotherapy, Pola-BR and Tafa-Len. HCRU and associated costs included pretreatment, administration, monitoring, and adverse event management. Acquisition costs of active treatments were excluded. Multiple time horizons were assessed. Model inputs were retrieved from product labels and validated by clinical experts to reflect practice. Results: From the Canadian and Quebec healthcare system perspective, total 1-year HCRU costs ranged from $11,009 to $54,946 and $10,041 to $54,362, respectively. Epcoritamab ranked as the second least costly comparator after chemotherapy, with notable HCRU savings driven by low administration costs of SC injections and adverse event management costs. Epcoritamab ranked similarly from a societal perspective and scenario analysis evaluating a 2-year time-horizon. Epcoritamab had the lowest annual chair time and HCP time, freeing up resources and HCP availability. Conclusion: Considering the highly constrained Canadian healthcare system, SC epcoritamab offers substantial HCRU-related cost saving, chair time savings and HCP time savings when compared with other available treatments, making it an effective, efficient and patient-centric treatment option for R/R-DLBCL in Canada.

Rare diseases affect more than 400 million people globally with only a small number having currently approved treatments. Drugs for rare diseases (medications developed to treat conditions affecting small patient populations), which may include innovative drugs (medications with novel mechanisms/new active ingredients) can face access challenges as they are often found not to be cost-effective under conventional health technology assessment methods. In this review we provide a comprehensive and up-to-date understanding of challenges associated with the economic evaluation of innovative drugs for severe-rare diseases, and any proposed solutions and associated barriers to solution adoption. This review included searches of electronic databases and select health technology assessment agency websites to identify relevant publications, guidelines or recommendations from 1st January 2014 to 29th July 2024. A pre-authorised protocol, including detailed eligibility criteria, was used to ensure robust methodology in the capture of materials. Relevant data extracted from included publications were synthesised thematically to support identification of the most prominent concepts within current literature. Of the 1,803 records identified, 31 publications and eight health technology assessment guidance were included. Main challenges were related to the utilitarian principle underlying cost-effectiveness analysis, the limited scope of the quality-adjusted life year and the value elements assessed. Associated solutions included the incorporation of a societal willingness-to-pay or inclusion of equity in healthcare decision making, reduced weighting of the economic evaluation in resource allocation, consideration of additional value elements, and introducing a quality-adjusted life year weighting or alternative measures of health outcomes. While some payers have implemented modifications to economic evaluation guidelines in an attempt to address the challenges, for example including the consideration of additional value elements, the solutions employed are not consistent across payers and often do not address the root issue. Economic evaluation as part of health technology assessment therefore remains challenging for manufacturers of drugs for rare diseases. Conventional methods of economic evaluation contribute to the access challenge for innovative drugs for rare diseases. Collaboration between payers, manufacturers, and healthcare decision makers to foster greater understanding of how to evolve and adopt these novel solutions will be key to ensuring timely patient access.

Ontologies support transparent and reproducible conceptual modeling in Health Technology Assessment (HTA), but their population remains resource-intensive and reliant on expert input. This study evaluates the feasibility, reliability, and methodological implications of using generative artificial intelligence (GenAI) to populate ontology individuals for HTA applications. A factorial experimental framework was developed using the Ontology for Simulation Modeling (OSDi) and three HTA-relevant use cases of varying complexity. Two GenAI systems were evaluated under multiple experimental conditions, including prompting strategy, serialization format, and provision of supporting information. Generated ontology individuals were validated by an HTA expert and assessed across four quality dimensions: consistency, relevance, completeness, and adequacy. Multivariate and regression analyses were conducted to examine the effects of experimental factors on quality outcomes and hallucination likelihood. GenAI systems successfully generated ontology individuals across use cases, although performance varied by quality dimension and experimental condition. Iterative prompting significantly improved completeness, while serialization format strongly influenced reliability, with Turtle serialization associated with substantially lower hallucination likelihood compared with XML. Other factors showed dimension-specific effects, highlighting the multidimensional nature of ontology quality. Errors occurred more frequently in structurally complex ontology components, suggesting a relationship between ontological complexity and generative performance. GenAI-assisted ontology population can enhance the efficiency and scalability of HTA conceptual modeling, enhancing the agility of HTA agencies in exploratory phases. Its effective use requires structured prompting, appropriate representation formats, and expert validation. Further research should evaluate its impact on HTA decision modeling workflows and validation frameworks.

Background: Living with type 2 diabetes can be demanding from multiple perspectives. Many individuals with type 2 diabetes experience limited self-care ability and poor adherence to self-care recommendations. Objective: To describe factors that influence self-care adherence among adults with type 2 diabetes. Methods: A systematic review based on 19 studies using quantitative, qualitative, and mixed-method designs. The study design is a systematic literature review in accordance with the guidelines of the Swedish Agency for Health Technology Assessment and Assessment of Social Services (SBU) and PRISMA guidelines. The articles were retrieved from the research databases CINAHL, PubMed, and PsycInfo. Quality appraisal was conducted using the MMAT, and the studies were analyzed through meta-aggregation and subsequently compiled into a unified set of findings. Results: The findings showed that numerous factors influence adherence to self-care. These were presented in categories: sociodemographic factors; disease- and treatment-related factors; healthcare-related factors; and psychological factors. Psychological factors played a decisive role in adherence, particularly regarding motivation. Conclusions: Living with Type 2 diabetes demands considerable engagement and supporting them as a district nurse is a multidimensional task consisting of several components. Self-care adherence in type 2 diabetes cannot be understood as the result of isolated factors but rather as a complex interplay of psychological, social, economic circumstances. Understanding effective patient education enhances knowledge and understanding of the importance of adhering to treatment is the key to improving compliance in patients with type 2 diabetes.

Health technology assessment (HTA) is increasingly recognized as a critical tool for evidence-informed decision-making in Eastern Europe and Central Asia (EECA), a region characterized by substantial diversity in health system maturity, financial resources, and institutional capacities. Building on the previous Eurasian HTA Initiative conducted a decade earlier, this study aimed to update the regional assessment of HTA implementation, expand country representation, and identify evolving strengths, weaknesses, opportunities, and threats affecting the advancement of HTA across the region. An online multilingual survey, informed by the original SWOT framework, was disseminated between August and October 2025 to experts from national authorities, HTA agencies, academia, and health sector stakeholders across eleven EECA countries. Twenty-two responses were analyzed descriptively. Key strengths included strong regional collaboration interest, growing availability of online HTA resources, and sustained global support. Major weaknesses centered on the limited trained HTA/EBM personnel and the absence of standardized national training programs. Opportunities reflected expanding interest in EBM, pressure from rising healthcare costs, and prospects for regional advocacy, educational exchanges, and international collaboration. Principal threats involved insufficient funding for capacity building, low policy-maker and clinician awareness, commercial influence from industry, and limited incentives for EBM uptake. Overall, respondents emphasized gradual progress in selected areas but persistent structural barriers requiring coordinated national and regional action.

Health Technology Assessment (HTA) is a cost-effective solution that decreases inefficiencies and improper investments in health systems. Tanzania has made remarkable efforts in the field of HTA with the establishment of the national HTA committee in 2017; yet, literature on its institutionalization is limited. Using a systems thinking and analytical approach, this study examined Tanzania’s HTA system, focusing on conceptualization, management, implementation, capacity, and use in policy and decision-making. The study was conducted between 2021 and 2023, purposely targeting experts and organizations involved in HTA. Six national HTA experts participated in virtual In-Depth Interviews (IDIs) of HTA from a policy perspective, and eight members of HTA-associated organizations from governmental and non-governmental sectors. Each organization completed one electronic institutional survey to understand HTA from a technical perspective. Findings from both data sources were consistent; half (n = 4) of the participating organisations surveyed affirmed an understanding of the HTA, but the majority showed limited knowledge of a central HTA agency or formal process. The Ministry of Health (MOH) is the main recipient of the HTA reports. Sustainable funding allocated for HTA is limited, and it is irregularly funded by private companies. Key values included safety, cost, economic evaluation, feasibility considerations, and community acceptability. HTA reports were used to inform clinical guidance, healthcare coverage, and pricing decisions. Experts identified the need to strengthen HTA awareness, advocacy, implementation, and institutionalization, supported by political commitment and inclusive governance. Strengthening the Tanzanian national HTA system through a more inclusive national body is essential to address these challenges.

Objective: This exploratory study presents an international, multi-stakeholder snapshot of perceptions regarding real-world data and real-world evidence in health technology assessment. The aim is to identify perceived opportunities, barriers, and enabling conditions rather than to generate generalizable conclusions. Methods: A 21-item, expert-validated questionnaire was distributed via LimeSurvey to diverse health technology assessment stakeholders, including academia, industry, health technology assessment agencies, healthcare providers, policymakers, patients, and payers. The survey explored perceptions of value, methodological and regulatory challenges, and future outlooks for RWD/RWE use in HTA. Ethical approval was obtained by the University of West Attica Ethics Committee, and pilot testing was conducted prior to dissemination. Data were analyzed using descriptive statistics, consistent with the study's exploratory intent and acknowledging that results are preliminary and not statistically generalizable. Results: Thirty-two completed responses demonstrated preliminary stakeholder support for integrating real-world data and real-world evidence into health technology assessment. Respondents represented academia, industry, HTA agencies, healthcare providers, policymakers, and patient/advocacy groups; however, no payer responses were obtained. Respondents emphasized the value of real-world data in complementing clinical trials by capturing real-world effectiveness, patient diversity, and long-term outcomes, especially in rare diseases and cancer. Key challenges included poor data quality, confounding biases, and regulatory barriers. Stakeholders highlighted the importance of standardization, transparency, and international collaboration. Opportunities included better decision-making, personalized healthcare, and improved post-market monitoring, with strong calls for robust infrastructure, clear methodologies, patient involvement, and supportive health policy frameworks. Conclusions: Real-world data and evidence enhance health technology assessment by supporting better decisions and personalized care. However, issues like data quality, methods, and trust must be addressed through standardization, strong infrastructure, and collaboration to ensure effective and impactful implementation in healthcare, while acknowledging these insights are based on a small exploratory sample.

Transportability assesses if study results (from Randomized Controlled Trials (RCTs) or Real-World Data (RWD)) can be applied to different target populations, including other real-world settings, geographic regions, or specific subgroups. Although Health Technology Assessment agencies advocate for transportability to optimize resources and improve decision-making, there is little guidance on specific methods to achieve it. This review aims to identify statistical methods to achieve transportability applied from RCTs or RWD to real-world populations. A literature review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We identified articles by searching MEDLINE and Embase until 18th October 2023. The review focused on studies describing and applying statistical methods for transporting evidence from RCTs to real-world populations and from RWD to other RWD contexts. To be included, a manuscript should use statistical methods to address transportability and present practical, health-related examples of transportability. If the publications focused on methodological aspects without practical examples or aimed to test model validity, they were excluded. The search identified 441 records and 13 were included for analysis. Of these, ten used Inverse Odds of Sampling Weights (IOSW), one used Inverse Probability Weighting (IPW), one used G-computation and another used standardization. Most studies applied transportability methods to transport RCT findings to real-world populations, two to transport between RWD sources for applications across disease areas or geographic locations. Common limitations reported included unmeasured confounding, differences in patient management and motivation, and challenges related to sample size. IOSW was the primary method used for transportability, predominantly within the same country when individual-level data from both the study population and target population could be combined. Our findings reveal that practical applications of transportability remain largely limited to national contexts, with few cross-country implementations observed.

Integrating economic evidence into clinical practice guideline (CPG) development is key to optimally allocating finite healthcare resources. Economic analysis contributes to decisions that enhance population health by investing in effective and affordable care. However, the absence of an accepted approach for using economic evidence to guide decisions in CPGs is challenging. This study, part of the Global Evidence, Local Adaptation (GELA) project in Malawi, Nigeria, and South Africa, examines and summarises available methodological guidance in the literature for including economic evidence in CPG development. We searched MEDLINE (via PubMed), World Health Organization (WHO), and Guideline International Network (GIN) libraries from 2013 to 2023 for English-language guidance documents that provided methodological recommendations on integrating economic evidence in CPG development. We also searched ten websites of key guideline development institutions, professional societies, and health technology assessment agencies. Drawing on the various recommendations in eligible guidance documents, we present a summary of suggested approaches. We identified 168 guidance documents; after excluding 151 and assessing 17 full-text documents, eight were eligible. Available guidance was categorised into four key processes: assessing the need for economic evidence, defining priorities, outlining the scope of the analysis, and assessing the evidence. Key methodological challenges identified included managing the nuances of building whole disease models and using results from economic evaluations with differing underlying assumptions to inform recommendations. We also identified critical actions for incorporating economic evidence in final guideline recommendations in three areas: methods, presentation of results, and the judgment of cost-effectiveness. A transparent and structured process for integrating economic evidence into guideline recommendations is essential for ensuring the relevance of decisions to the implementation context and enhancing confidence in the process. Our findings may support healthcare professionals, guideline developers, health economists, and policymakers involved in CPG development. Not applicable.

Aim: Real-world evidence (RWE) - defined here as clinical evidence derived from the analysis of real-world data (RWD) on patient health status and healthcare delivery - has become a cornerstone of regulatory and health technology assessment (HTA) decision making. However, despite broad consensus on its value, policy frameworks governing RWE generation and evaluation remain heterogeneous across jurisdictions. Importantly, this heterogeneity partly reflects the distinct purposes for which RWE is used, including regulatory safety assessment, effectiveness evaluation, health-economic modeling and natural-history research. These functional differences are not inherently problematic; however, fragmented operational requirements can create duplication, inefficiency and delays in patient access. Materials & methods: This study employed a narrative comparative policy review of RWE guidance issued by twelve major regulatory and HTA agencies, including the Medicines and Healthcare products Regulatory Agency (MHRA), the EMA, the US FDA and the Canadian Agency for Drugs and Technologies in Health (CADTH). Frameworks were compared across four domains: data quality, statistical methods, registry governance and transparency. Harmonization is defined as alignment across these domains sufficient to enable consistent planning, analysis and interpretation of RWE across jurisdictions, rather than uniformity of decision making. Results: The analysis identified convergence in high-level principles but persistent divergence in operational expectations. The MHRA emphasizes flexibility and scientific dialogue; the EMA prioritizes consistency and structured governance; and the FDA provides comprehensive but resource-intensive guidance, reflecting detailed documentation requirements, prespecified analytic expectations and extensive methodological review. HTA bodies apply additional evidentiary criteria related to comparative effectiveness and value, sustaining functional fragmentation even within the same healthcare systems. Conclusion: RWE fragmentation reflects both legitimate functional differences and avoidable operational misalignment. Progress toward harmonization therefore requires shared minimum standards and transparency mechanisms rather than additional guidance documents. The UK's post-Brexit autonomy positions it as a test environment for collaborative pilots with the European Medicines Agency, the International Council for Harmonization (ICH) and the International Coalition of Medicines Regulatory Authorities (ICMRA). Six strategic actions are proposed to support pragmatic alignment while preserving contextual flexibility.

The overall aim is to understand the practices, views, and needs of health technology assessment (HTA) practitioners worldwide regarding the use of health-related quality of life (HRQoL) data for generating cost-effectiveness evidence. We invited HTA practitioners in sixty countries to complete an online survey on their perspectives on the measurement and valuation of health. We performed descriptive analyses of the overall sample, examined response differences across six regions, and pooled responses to open-ended questions for content analysis. A total of 238 individuals from 45 countries completed the survey, with a mean response number per country of 5.28 (SD: 4.45). Most responses came from public sector employees (seventy-two percent), and ninety percent were involved in cost-effectiveness-related work. The top three most frequently used utility instruments were EQ-5D, SF-6D, and EQ-5D-Y, and the elicitation methods were time trade-off, visual analogue scale, and standard gamble. Health-state preferences of the general public from another country were more frequently used than the preferences of the local public. Common data quality issues were poor sample representativeness and a small sample size of utility data. In Asia and Western Europe, the top-voted research priority was developing utility instruments that capture both healthcare and social care impact. In four regions, developing utility instruments for children was the second-highest research priority. The survey addressed important knowledge gaps regarding current practices in measuring and valuing HRQoL in HTA and provided insights into HTA practitioners' views on instruments, methods, and data-related challenges and needs for generating HRQoL evidence.

Health interventions, particularly those targeted at health promotion and disease prevention, often have a range of impacts that span beyond the healthcare sector. Making the case for investment in these interventions may require an inventory of costs and outcomes across multiple sectors beyond the health sector. To perform a scoping review of economic evaluations that used existing approaches for cross-sectoral evaluation of healthcare interventions and provide an understanding of how these approaches have been applied in empirical studies. Scoping reviews, a type of evidence synthesis, follow a systematic approach to map evidence on a topic and identify main concepts, theories, sources, and knowledge gaps. We used the PRISMA extension for scoping reviews and a pearl-growing search approach. A forward citation searching in Google Scholar and Web of Science of an initial set of selected papers that recommend cross-sectoral evaluations of health interventions was performed, complemented by free-word search in Google and Google Scholar. Cross-sectoral evaluations of health interventions that consider costs and outcomes beyond healthcare were included. From the 204 identified cross-sectoral evaluation studies of health interventions, the vast majority (85%) were cost-effectiveness and cost-utility analyses taking the societal costing perspective. Other approaches included social return on investment (6%), cost-benefit analysis (4%), cost study (3%), and combined approaches (2%). Two-thirds of the studies evaluated a treatment-based intervention while the remainder evaluated preventive interventions. In addition to healthcare, studies evaluated mostly costs related to productivity and non-direct medical costs, e.g., transport costs. Outcomes were focused on clinical results and patient-reported health and well-being. There is a limited number of published cross-sectoral evaluations of health interventions despite the need of public and private investors for global value assessment. Issuing guidance on performing cross-sectoral evaluations and highlighting their need by health technology assessment agencies may improve existing evidence and therefore novel forms of investment in population health interventions.

Health Technology Assessment (HTA) is a cornerstone of evidence for informing health policy and resource allocation globally. Rapid advancements and the proliferation of digital health technologies and artificial intelligence (AI) have prompted the re-examination of HTA processes and methods. While traditional approaches are manual and labor-intensive, HTA processes are now exploring the use of AI and other digital technologies for automation, decision support, and evidence synthesis. To date, however, there have been very limited studies that map the innovative technological solutions of HTA, the models of integration, and the associated barriers, facilitators, and governance considerations. As such, this scoping review aims to address this critical gap by mapping the landscape of the global knowledge and practices related to AI and DTs used in and for HTA and identifying the key barriers and enablers influencing their adoption, integration, and effective application within HTA processes. A scoping review will be conducted between August and November 2025, following the Arksey and O'Malley framework, enhanced by Joanna Briggs Institute (JBI) recommendations, and reported according to Preferred Reporting Items for Systematic Reviews and Meta‑Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Literature searches will be performed in electronic databases such as Medline (Ovid), Embase (Ovid), Global Health (Ovid), CINAHL (Ebsco), Scopus, Web of Science, and all regional indexes in the World Health Organization's Global Index Medicus, and other region-specific sources for studies published between 2020 and 2025. Eligible studies will include peer-reviewed articles and grey literature describing the integration of digitization, automation, and AI in global HTA processes. Dual independent screening, data extraction, and quality appraisal will be employed. Findings from this review will provide a map of how digitization, automation, and AI are integrated into HTA practice, highlighting key enablers, barriers, and knowledge gaps. The insights will be used to better guide researchers, policymakers, HTA agencies, and AI developers, further supporting future research and implementation strategies for better informed decision-making.

Systematic literature reviews (SLRs) are essential for evidence synthesis in healthcare decision making, including health technology assessment (HTA), but their time and resource demands are substantial. Artificial intelligence (AI) may enhance efficiency of conducting SLRs, but its acceptance by HTA bodies remains underexplored. This SLR quantifies published health-related SLRs reporting AI use, identifies AI tools used at each SLR stage, and evaluates HTA guidance on AI in evidence synthesis. We searched Embase, Medline, and the Cochrane Library (up to 9 September 2025), supplemented by hand searches and reviews of HTA agency websites. Titles and abstracts were screened in Rayyan by a single reviewer, with full-text review confirming eligibility. Data were extracted and synthesized narratively along key themes. In total, 112 studies covering 111 unique SLRs were identified, reporting 134 implementations of 45 unique AI tools (29 publicly available; 16 custom-built). AI use has risen since 2013 and was most frequently applied during title and abstract screening (88 of the 134 implementations). Human oversight remained essential, with no fully autonomous AI reported. Three HTA agencies (CDA-AMC, IQWiG, NICE), EUnetHTA, JBI and Cochrane have provided guidance, indicating the formal integration of AI into HTA processes. This SLR provides a quantitative overview of AI use in health-related SLRs and current HTA guidance. These findings may inform development of clearer methodological recommendations and support integration of AI-assisted evidence synthesis in HTA submissions. Further research and policy development are needed to optimize its role in evidence synthesis and healthcare decision making.

While rapid health technology assessments (HTA) are important for decision makers, there is no universally accepted definition or standardized methods. The objective of this study was to analyze the content and conduct of published rapid and mini-HTA reports. We conducted a cross-sectional analysis of rapid and mini-HTA reports identified from the International HTA Database (2014-April 2024) and supplementary searches of HTA agency websites. We extracted descriptive data on rapid HTA products; specifically, which traditional HTA domains were included or omitted, evidence synthesis methods, and approaches to interest-holder (formerly known as stakeholder) engagement. Data analysis was conducted in Stata. We included 203 rapid HTA reports. Most frequently included HTA domains were clinical effectiveness (99 percent) and safety (82.3 percent). Legal aspects (12.3 percent) and budget impact analyses (10.8 percent) were less frequently reported. Across reports reviewing clinical effectiveness (n=201), generic literature searches were the most predominantly self-reported evidence synthesis method (37.8 percent), with updates (1.5 percent) and overviews (2 percent) of systematic reviews less common. Cost-utility analyses were the most commonly self-reported form of economic evaluation (36.2 percent). Additionally, public consultations (68 percent) were the most commonly reported ways to engage with interest holders. Our analysis highlights variations across rapid HTA reports and will contribute to wider research aiming to establish a clearer definition and framework of rapid HTAs and inform when and how rapid HTAs are performed. Clearer reporting and justification of simplifications in rapid HTA reports are needed.

Surrogate endpoints are frequently used as primary outcomes in clinical trials. This is appropriate when they are validated for their ability to predict clinical benefit measured on patient-relevant target outcome(s). Such validation is often lacking, thus increasing uncertainty in the decision-making process of regulatory bodies, health technology assessment agencies and payers. This ISPOR Task Force Report provides recommendations on best practices for surrogate endpoint evaluation for health technology assessment decision making. It covers methods that address the 3 levels of evidence for surrogate endpoint validation described in several methodological guidelines: (1) association between treatment effects on the surrogate and the target outcome, (2) association between the surrogate and the target outcome, and (3) biological plausibility. Statistical methods for surrogate endpoint evaluation include meta-analytic approaches using individual participant data or aggregate data. Multivariate meta-analytic models are recommended because they account for the within-study correlation and estimation errors. Issues with limited data and generalizability might be addressed through Bayesian approaches for information sharing from different treatments, treatment classes or indications. Real-world data can complement randomized controlled trial data, especially in rare diseases, but require careful consideration of underlying bias. For plausibility of health economic modeling, the surrogacy analysis and the health economic model should be aligned. The modeled time course of surrogate and target outcomes per treatment arm, as well as the modeled relative effects, should be reported to assess plausibility. Parameter and structural uncertainty in surrogate relationships can be explored through scenario analyses, probabilistic sensitivity analyses, value of information analyses, and threshold analysis techniques.

Obesity and overweight are a global health problem affecting over 2.6 billion people worldwide. Diet and physical activity, including structured exercise, are critical components in the management of obesity. This review of reviews explores the values and preferences of children, adolescents, and their parents/caregivers that influence engagement and adherence to dietary and physical activity interventions for obesity management. Eleven electronic databases were searched (from January 2010 to June 2024) to identify reviews incorporating qualitative research on values and preferences, attitudes or experiences of children or adolescents with obesity, or their caregivers, in relation to diet or physical activity interventions. Supplementary grey literature searching, citation searching and reference lists screening of included reviews were also undertaken. The methodological quality of included reviews was appraised using the Swedish Agency for Health Technology Assessment (SBU) tool. Data synthesis was performed using a mega-ethnography approach. Fourteen reviews were included with majority of studies conducted in high-income countries. Six key factors were identified that affect children and adolescents or their caregivers when initiating and continuing with physical activity and/or dietary management interventions. These included perceptions concerning the value of interventions; competing priorities; the role of social support; the physical environment; the nature and content of the intervention; and costs. Multiple factors influence engagement with diet and physical activity programmes among children and adolescents with obesity and their caregivers, highlighting the need for emotional and psychological support, whole-family involvement, and personalised, trust-based guidance from health professionals. However, these findings are context-dependent with evidence primarily from high-income countries, which may limit their wider generalisability.