Transferability of Real World Evidence to Support HTA Recommendations in Lower Income European Countries

. 2026 Feb ; 9 (2) : e71534. [epub] 20260127

Status PubMed-not-MEDLINE Jazyk angličtina Země Spojené státy americké Médium electronic-ecollection

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid41608382

BACKGROUND AND AIMS: Lower income European countries (LIECs) have more limited financial resources to cover high-cost technologies in rare diseases than higher income European countries (HIECs). Our study explores how treatment recommendations in myelodysplastic syndrome (MDS) can be supported in LIECS by transferring real-world evidence (RWE) generated by target trial emulation (TTE) method in HIECs. METHOD: In the HTx project transferability aspects of the MDS case study were considered upfront. HTA agency consortium partners set expectations for the MDS case study team on how to integrate the new TTE methodology into the routine work of HTA bodies. In consecutive workshops consortium members and external HTA experts identified the main challenges of transferring evidence generated by TTE method to LIECs and made conclusions on how to overcome these challenges. RESULTS: The lack of local real-world data before making reimbursement decisions is an important challenge to apply the TTE method to LIECs. Differences in patient pathways and comparator technologies, limited expertise and resources for adapting international HTA methods are significant barriers of transferring RWE from other countries.Still, transferring RWE to LIECs from other countries based on the TTE methodology represents an improvement to the current standard HTA methods, especially if joint clinical assessment provides the unbiased judgement on the relative effectiveness of orphan medicines. The TTE approach also provides an opportunity to LIECs to judge the value of high-cost technologies for different patient subgroups. However, HTA professionals in LIECs need training about advanced methodologies. CONCLUSION: This is the first study to explore how RWE generated by the TTE method can be transferred to optimize treatment decisions of patients with a rare disease in countries with limited HTA capacities. Five general concluding statements were made on the novelty of the TTE method and on how to overcome main challenges of transferring TTE results to HTA systems in LIECs.

Academy for Medical and Social Applied Sciences Gdańsk Poland

Center for Health Technology Assessment Semmelweis University Budapest Hungary

Center for Pharmacology and Drug Research and Development Semmelweis University Budapest Hungary

Centre for Health Economics University of York York UK

Cogvio Prague Czechia

Department of Organisation and Management in Pharmacy Faculty of Pharmacy Comenius University Bratislava Slovakia

Department of Organization and Economics of Pharmacy Faculty of Pharmacy Medical University of Sofia Sofia Bulgaria

Department of Pharmacoeconomics University of Medicine and Pharmacy of Craiova Craiova Romania

Department of Pharmacology Faculty of Medicine Masaryk University Brno Czechia

Department of Pharmacology Titu Maiorescu University Bucharest Romania

Division of Pharmacoepidemiology and Clinical Pharmacology Utrecht Institute for Pharmaceutical Sciences Utrecht University Utrecht Netherlands

Erasmus School of Health Policy and Management Erasmus University Rotterdam Rotterdam Netherlands

Faculty of Mathematics and Physics University of Ljubljana Ljubljana Slovenia

Faculty of Medicine University of Rijeka and University Hospital Centre Rijeka Rijeka Croatia

Health Policy Institute Gdańsk Poland

HTA Department of State Expert Centre Ministry of Health Kyiv Ukraine

Institute of Mathematics Physics and Mechanics Ljubljana Slovenia

National Health Care Institute Diemen The Netherlands

National Institute for Value and Technologies in Healthcare Bratislava Slovakia

Salidat Kairbekova National Research Center for Health Development Astana Kazakhstan

School of Economics and Business University of Ljubljana Ljubljana Slovenia

Syreon Research Institute Budapest Hungary

The Dental and Pharmaceutical Benefits Agency Stockholm Sweden

Value Outcomes Prague Czechia

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European Union: Regulation (EU) 2021/2282 of the European Parliament and of the Council of 15 December 2021 on Health Technology Assessment and Amending Directive 2011/24/EU 2021, accessed on March 11, 2024, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32021R2282.

Kaló Z., van den Akker L. H. M., Vokó Z., Csanádi M., and Pitter J. G., “Is There a Fair Allocation of Healthcare Research Funds by the European Union?,” PlosOne 14 (2019): e0207046. PubMed PMC

Löblová O., “Three Worlds of Health Technology Assessment: Explaining Patterns of Diffusion of HTA Agencies in Europe,” Health Economics, Policy and Law 11 (2016): 253–273. PubMed

Kaló Z., Gheorghe A., Huic M., Csanádi M., and Kristensen F. B., “HTA Implementation Roadmap in Central and Eastern European Countries,” Health Economics 25, no. S1 (2016): 179–192. PubMed PMC

Sekeres M. A. and Taylor J., “Diagnosis and Treatment of Myelodysplastic Syndromes: A Review,” Journal of the American Medical Association 328 (2022): 872–880. PubMed

Hoeks M., Yu G., Langemeijer S., et al., EUMDS Registry Participants ., “Impact of Treatment With Iron Chelation Therapy in Patients With Lower‐Risk Myelodysplastic Syndromes Participating in the European MDS Registry,” Haematologica 105 (2020): 640–651. PubMed PMC

L. de Swart, , Smith A., Fenaux P., et al., “Early Mortality in 1000 Newly Diagnosed MDS Patients With Low‐And intermediate‐1 Risk MDS in the European Leukemianet MDS (EUMDS) Registry,” Blood 120 (2012): 3830.

Hernán M. A., Wang W., and Leaf D. E., “Target Trial Emulation: A Framework for Causal Inference From Observational Data,” Journal of the American Medical Association 328 (2022): 2446–2447. PubMed

Wang S. V., Schneeweiss S., Franklin J. M., et al., “RCT‐DUPLICATE Initiative Emulation of Randomized Clinical Trials With Nonrandomized Database Analyses: Results of 32 Clinical Trials,” Journal of the American Medical Association 329 (2023): 1376–1385. PubMed PMC

Hernán M. A., Brumback B., and Robins J. M., “Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments,” Journal of the American Statistical Association 96, no. 454 (2001. 1): 440–448.

M. J. van der Laan, and Rubin D., “Targeted Maximum Likelihood Learning,” International Journal of Biostatistics 2 (2006): 1. PubMed PMC

M. J. van der Laan, and Gruber S., “Targeted Minimum Loss Based Estimation of Causal Effects of Multiple Time Point Interventions,” International Journal of Biostatistics 8 (2012): 1. PubMed

Schomaker M., Luque‐Fernandez M. A., Leroy V., and Davies M. A., “Using Longitudinal Targeted Maximum Likelihood Estimation in Complex Settings With Dynamic Interventions,” Statistics in Medicine 38 (2019): 4888–4911. PubMed PMC

Lendle S. D., Schwab J., Petersen M. L., and van der Laan M. J., “ltmle: An R Package Implementing Targeted Minimum Loss‐Based Estimation for Longitudinal Data,” Journal of Statistical Software 81 (2017): 1–21.

Chakraborty B. and Murphy S. A., “Dynamic Treatment Regimes,” Annual Review of Statistics and its Application 1 (2014): 447–464. PubMed PMC

Kamusheva M., Németh B., Zemplényi A., et al., “Using Real‐World Evidence in Healthcare From Western to Central and Eastern Europe: A Review of Existing Barriers,” Journal of Comparative Effectiveness Research 11 (2022): 905–913. PubMed

Németh B., Kamusheva M., Mitkova Z., et al., “Guidance on Using Real‐World Evidence From Western Europe in Central and Eastern European Health Policy Decision Making,” Journal of Comparative Effectiveness Research 12 (2023): e220157. PubMed PMC

Ádám I., Callenbach M., Németh B., et al., “Outcome‐Based Reimbursement in Central‐Eastern Europe and Middle‐East,” Frontiers in Medicine 9 (2022): 940886. PubMed PMC

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