Expert Review of Pharmacoeconomics & Outcomes Research最新文献

Objectives: We evaluated the cost-effectiveness of implementing different pneumococcal conjugate vaccines (PCV) - 20-valent (PCV20; 3 + 1), 13-valent (PCV13; 2 + 1), and 15-valent (PCV15; 2 + 1) - into the Spanish pediatric national immunization program (NIP) for pneumococcal disease prevention.

Methods: A Markov model adopting a Spanish National Healthcare System perspective and annual cycles estimated the health and cost impact of PCV20, PCV13, and PCV15 over 10 years among children. Epidemiological, cost, and utility inputs were derived from published literature and official databases; vaccine efficacy inputs were based on PCV13 clinical effectiveness and 7-valent PCV efficacy and impact studies. Sensitivity analyses evaluated model robustness.

Results: PCV20 implementation was predicted to reduce the pneumococcal disease burden, preventing > 1,000,000 pneumococcal disease cases and > 150 deaths, versus both comparators. The adoption of PCV20 was estimated to result in cost-savings of approximately €1 billion versus PCV13 and PCV15. PCV20 demonstrated dominance over both alternatives, with 100% of 1,000 probabilistic sensitivity analysis iterations indicating PCV20 dominance.

Conclusion: Incorporating PCV20 3 + 1 into the Spanish pediatric NIP was predicted to be more effective at a lower cost than PCV13 2 + 1 and PCV15 2 + 1 due to its broader serotype coverage and enhanced protection against pneumococcal disease.

Objective: Variant transthyretin (ATTRv) amyloidosis is a rare genetic multisystem disease inducing progressive morbidity. Evidence about its economic burden is scarce. This study estimated annual use and costs of healthcare-resource-utilization (HRU) and indirect costs for ATTRv mutation carriers and patients with polyneuropathy from a societal perspective in Spain.

Methods: A cross-sectional, retrospective non-interventional multicenter study was conducted in 2018-2020 to characterize asymptomatic carriers of mutations in the TTR gen (AC) and Coutinho stage 1 transthyretin amyloidosis polyneuropathy patients (PA). HRU, associated costs, and indirect wages were assessed during 12 months prior to enrollment.

Results: One-hundred-five participants were analyzed: 86 AC and 19 PA. Average healthcare cost-per-person-per-year was significantly higher in PA: €2,323.6 vs. €953.3 (p < 0.001), due to higher utilization of medical specialty visits, hospitalizations, and nerve conduction studies. Indirect costs were statistically not different (€380.1 for AC and €781.3 for PA, p = 0.581). Days worked with fatigue/pain were significantly higher in PA: 53.9 vs 5.5 (p = 0.034). Total cost was significantly higher in PA than AC (€3,105.0 vs €1,333.4; p < 0.001).

Conclusions: Both AC and early-stage ATTRv-PN patients showed a meaningful economic burden to the National Health System and society. We observed an annual incremental economic burden of €1,771.5 in PA versus AC.

Objectives: Lacking national policy for adult pneumococcal vaccination, local Indian guidelines recommend 13-valent pneumococcal polysaccharide conjugate vaccine (PCV13) followed by 23-valent pneumococcal polysaccharide vaccine (PPV23). However, no vaccination ('NV') or PPV23 alone are most common in clinical practice. We evaluated cost-effectiveness of PCV13 versus NV and, alternatively, PPV23 in India.

Methods: Cohort model with Markov-type process projected lifetime cases, deaths, and costs associated with invasive pneumococcal disease and all-cause non-bacteremic pneumonia (discounting = 5%/year). Cost per quality-adjusted life year (QALY) gained was assessed among at-risk/high-risk adults aged 50-59 years and all aged 60-99 years (N = 209.5 M) from private/patient and government/payer perspectives, which differed on medical costs, vaccination costs, and uptake rates.

Results: From private/patient perspective, PCV13 versus NV yielded ₹480,908/QALY (ΔCosts=₹27.2B;ΔQALYs = 56,560), whereas PCV13 was dominant versus PPV23 (ΔCosts=-₹359.1 M; ΔQALYs = 53,861).From government/payer perspective, corresponding ratios were ₹610,178/QALY (ΔCosts=₹84.4B;ΔQALYs = 138,382), and ₹456,048/QALY (ΔCosts=₹60.2B; ΔQALYs = 131,933). In probabilistic sensitivity analyses, cost-effectiveness was <₹600,000/QALY in 72.9%-99.7% of replications (N = 1000/analysis), depending on comparison/perspective.

Conclusions: PCV13 versus NV among at-risk/high-risk adults aged 50-59 years and all aged ≥ 60 years would be cost-effective from both perspectives considering willingness-to-pay equaling approximately 3× gross domestic product/capita. Furthermore, PCV13 versus PPV23 would be cost-effective and cost saving from government/payer and private/patient perspectives, respectively.

Background: In most developed countries, overall survival rates for low-risk cancers (e.g. localized prostate and thyroid cancer) are comparable to those of the general population. The general population's survival rate may serve as an upper bound for survival in people with these cancers.

Methods: By applying this concept, we demonstrated limitations of using Markov models for low-risk cancers and proposed an alternative modeling approach.

Results: Markov disease progression models typically depict a gradual progression from early to advanced cancer stages and an increasing risk of cancer-specific mortality over time. However, data showed that the risk of death from cancer was often the greatest within the first few years following diagnosis. We therefore proposed an alternative modeling approach. This method involves calculating the average quality-adjusted life-years (QALYs) from the integrals of the survival curve, multiplied by the corresponding health utility curve. Alternatively, QALYs may be estimated by averaging survival and utility within each time interval and summing these estimates across intervals. We also applied these concepts to the critical appraisal of published economic evaluations.

Conclusions: Understanding the upper bound of survival for low-risk cancers enables health economists to more accurately conduct cost-effectiveness analyses and assess the credibility of published economic evaluations. [Figure: see text].

Introduction: Fatigue is a multifactorial phenomenon that affects individuals across several conditions. Fatigue Severity Scale (FSS) is a widely used questionnaire to measure perceived fatigue. This systematic review aims to identify the psychometric properties of FSS across different populations where it has been validated.

Methods: The study selection process was conducted from April 2024 to January 2025. The databases used to identify included studies were MEDLINE (via PubMed), SCOPUS, Web of Science, and CINAHL (via EBSCO). The risk of bias was evaluated using the COSMIN checklist. For the meta-analysis, studies reporting the internal consistency of the scale were analyzed.

Results: At the end of the selection process, 59 articles were included in the review; the sample sizes ranged from 20 to 2017 participants, and the mean age spanned from 21,86 to 68,1 years.

Conclusion: The FSS is a valid and reliable instrument for fatigue assessment. It would be desirable to investigate heterogeneity; it would be beneficial to investigate responsiveness and to explore the settings in which it is used. Another advise would be to calculate cutoff in healthy subjects to better understand fatigue symptoms and the differences in perception between populations.

Registration: PROSPERO (CRD42025635211).

Introduction: Recently, new technologies have emerged for the prevention of respiratory syncytial virus (RSV) infections. Reliable epidemiological data are essential for accurately assessing the disease burden and informing health economic evaluations (HEE). This review evaluates how HEE of RSV maternal vaccination (MV) estimated the RSV disease burden.

Methods: A systematic search was conducted in MEDLINE, SCOPUS, EMBASE, NHS EED, HTA, Tufts CEA Registry, LILACS, and Web of Science for full HEE of RSV MV. Reporting quality was assessed with the CHEERS 2022 checklist, costs were converted to 2024 U.S. dollars, and a descriptive, interpretive synthesis of the data was performed.

Results: All 21 included studies were cost-utility analyses, 10 conducted in high-income countries. The HEE utilized a wide range of data sources to build epidemiological estimates, frequently relying on non-local data, particularly for outpatient rates. National data on RSV hospitalization rates were the most commonly available. No study included equity assessments. The maternal vaccine dose price was identified as a critical factor in the strategy's cost-effectiveness.

Conclusion: Enhancing local data availability for RSV, by strengthening the respiratory virus surveillance, is crucial to improve the reliability of HEE of RSV prevention strategies and enable more informed and effective policy decisions.

Registration: PROSPERO: CRD42024549989.

Introduction: Integrated Evidence Planning (IEP) is a strategic approach that optimizes drug development and market access by ensuring evidence generation aligns with regulatory, clinical, and market needs. The increasing integration of advanced technologies, including artificial intelligence/machine learning (AI/ML), natural language processing (NLP), and generative AI is set to revolutionize IEP by enhancing decision-making and improving patient access.

Areas covered: This article examines the role of IEP in drug development, focusing on its application across the product lifecycle, pre-clinical to post-launch. It highlights the integration of various analytical techniques, including descriptive analysis, ML, and causal inference to generate evidence. Challenges in implementing IEP, such as organizational barriers, data accessibility, and needs for specialized software tools are discussed. The evolving role of real-world evidence is emphasized, advocating for IEP as a dynamic, iterative process that adapts to market changes. Additionally, the potential of generative AI and real-time analytics to improve evidence generation and stakeholder collaboration is explored.

Expert opinion: The transformative potential of generative AI in IEP facilitates on-demand insights and conversational data access. However, challenges such as organizational inertia and the need for cross-functional alignment remain. Successful IEP implementation requires strong leadership, stakeholder buy-in, and optimized resource allocation to fully capitalize on its benefits.