Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAVs) are rare autoimmune diseases characterized by heterogeneous clinical presentation and substantial morbidity. Evidence suggests high healthcare utilization and economic burden of ANCA-associated vasculitis (AAV), particularly owing to hospitalization as well as geographic variation in the organization of specialized care. However, national-level analyses examining outcomes, resource use, and geographic differences in care pathways remain limited. The study aimed to identify hospitalized patients with granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA) using administrative data, characterize their hospital burden and geographic care pathways in Italy, and investigate determinants of hospital costs and in-hospital mortality. Nationwide Italian hospital discharge records (2010–2019) were used to identify patients with GPA and MPA using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)-based algorithms. Hospital resource use, costs, in-hospital mortality, inter-regional mobility, and continuity of specialized care were estimated. Determinants of hospital costs were analyzed using generalized linear models (gamma distribution and log link), and in-hospital mortality was analyzed using the Cox proportional hazards model. We identified 3763 patients with GPA and 1206 patients with MPA, with a mean of 6.9 and 8.6 admissions per patient, respectively, over 10 years. In-hospital mortality was 20.3
Developing local value sets for child and adolescent health is critical for economic evaluation in Nigeria. Discrete choice experiments (DCEs) can elicit these preferences, yet data on choice behaviour from Nigerian populations are lacking. The aim of this study was to analyse DCE-based preferences for EQ-5D-Y-3L health states among Nigerian adult proxies, examining dimension-level drivers of choice, prevalence and correlates of preference reversals, and overall data quality. A DCE was administered to 2699 adults across six Nigerian states, generating 40,485 choice task observations. Paired health states were constructed using an efficient design. The EuroQol Portable Valuation Technology (EQ-PVT) recorded choices and identified logical reversals. Analyses included descriptive statistics, mixed-effects logistic regression, and comparative tests examining differences between reversed and normal tasks. Reversals, which reflect respondent-level software orientation rather than task-level choice behaviour, occurred in 50.32
Health economic models (HEMs) are crucial for assessing the cost-effectiveness of healthcare interventions, informing policy decisions and guiding reimbursement strategies. This study examines the feasibility of employing generative artificial intelligence (Gen-AI) for the conceptualisation of HEMs. Two proof-of-concept studies were conducted, implementing a first-of-its-kind agentic Gen-AI-augmented approach for model conceptualisation. An agentic Gen-AI framework was developed, incorporating the chain-of-thought (CoT) reasoning algorithm through advanced prompt engineering, compounded with self-consistency, executed in an external Python programming environment. Within this framework, an agentic execution layer (the ‘agent’) autonomously orchestrated a multi-step retrieval–reasoning–generation task. Additionally, a graph-based retrieval-augmented generation (RAG) technique was implemented by linking the large language model (LLM) to an external database curated with user-selected data specific to HEM. Two case studies were explored: breast cancer, representing a data-rich disease area, and transthyretin amyloid polyneuropathy (ATTR-PN), exemplifying a data-sparse rare disease. The agentic Gen-AI framework successfully generated two key outputs that were subsequently validated against published literature and expert review from health economic (HE) modelers and clinicians: (1) a disease concept diagram illustrating the progression of the disease and its associated health states, and (2) a model structure diagram depicting patient transitions between various health states. The findings suggest that Gen-AI-augmented methodologies can enhance multiple aspects of HEM conceptualisation, including problem definition, disease and treatment effect pathway development, model structure recommendations, and drafting of model specification plans. To the best of the authors’ knowledge, this is the first study to integrate cutting-edge Gen-AI techniques such as human-in-the-loop (HITL), chain of thought–self-consistency (CoT–SC), and graph-based RAG for HEM conceptualisation or broader health economics and outcomes research (HEOR) applications.
Phenylketonuria (PKU) is a rare autosomal recessive metabolic disorder resulting from a deficiency in phenylalanine hydroxylase (PAH) enzyme activity. This systematic literature review (SLR) aims to synthesize the available evidence on the economic and humanistic burden of PKU on patients and their caregivers. A comprehensive SLR was conducted using PubMed, Embase, Cochrane Library, International Prospective Register of Systematic Reviews (PROSPERO), EconLit, and the Cost-Effectiveness Analysis (CEA) Registry, from database inception to June 2026. Eligible studies were published in English, included individuals diagnosed with PAH deficiency (including PKU) and/or their caregivers, and reported original data on either the economic or humanistic burden of the condition. Of 2131 records identified, 1330 were screened after deduplication, and 313 underwent full-text review. A total of 130 studies were included, with 44 reporting on economic burden and 87 covering humanistic burden-related outcomes. The economic burden of dietary management was substantial, with mean per patient per year (PPPY) costs ranging from US1634 to US35,946, and an estimated 233–359 h PPPY dedicated to diet-related activities. Humanistic burden was also significant; the long-term metabolic control significantly influenced multiple domains of health-related quality of life (HRQoL). In a study involving adults with PKU (n = 88), dietary protein restriction was found to be negatively associated with HRQoL (Rp = 0.265, p < 0.05), and similarly, anxiety was also negatively correlated with blood phenylalanine (Phe) levels (Rs = 0.186–0.209, p < 0.05). Findings underscore the substantial financial, time, and psychological burden of PKU, particularly in relation to dietary management.
Multiple myeloma is a life-threatening hematologic malignancy with a rising incidence and significant economic burden, driven largely by costly novel therapies. This study estimated the value-based price of belantamab, a novel agent for relapsed or refractory multiple myeloma, from the perspective of the Chinese healthcare system. A three-state partitioned survival model was constructed to compare belantamab plus bortezomib and dexamethasone (BVd) versus daratumumab plus bortezomib and dexamethasone (DVd) for the treatment of relapsed or refractory multiple myeloma over a lifetime horizon. Efficacy data were based on the DREAMM-7 trial (ClinicalTrials.gov identifier: NCT04246047). Cost inputs included the drug acquisition and administration, subsequent treatment, monitoring for post progression, disease evaluation and laboratory testing, and serious adverse events management. Health utilities were derived from published studies. Both costs and quality-adjusted life years (QALYs) were discounted at an annual rate of 4.5
