Regulatory and HTA Considerations for Development of Real-World Data Derived External Controls.
Journal
Clinical pharmacology and therapeutics
ISSN: 1532-6535
Titre abrégé: Clin Pharmacol Ther
Pays: United States
ID NLM: 0372741
Informations de publication
Date de publication:
08 2023
08 2023
Historique:
received:
13
02
2023
accepted:
12
04
2023
medline:
23
10
2023
pubmed:
20
4
2023
entrez:
20
04
2023
Statut:
ppublish
Résumé
Regulators and Health Technology Assessment (HTA) bodies are increasingly familiar with, and publishing guidance on, external controls derived from real-world data (RWD) to generate real-world evidence (RWE). We recently conducted a systematic literature review (SLR) evaluating publicly available information on the use of RWD-derived external controls to contextualize outcomes from uncontrolled trials submitted to the European Medicines Agency (EMA), the US Food and Drug Administration (FDA), and/or select HTA bodies. The review identified several key operational and methodological aspects for which more detailed guidance and alignment within and between regulatory agencies and HTA bodies is necessary. This paper builds on the SLR findings by delineating a set of key takeaways for the responsible generation of fit-for-purpose RWE. Practical methodological and operational guidelines for designing, conducting, and reporting RWD-derived external control studies are explored and discussed. These considerations include: (i) early engagement with regulators and HTA bodies during the study planning phase; (ii) consideration of the appropriateness and comparability of external controls across multiple dimensions, including eligibility criteria, temporality, population representation, and clinical evaluation; (iii) ensuring adequate sample sizes, including hypothesis testing considerations; (iv) implementation of a clear and transparent strategy for assessing and addressing data quality, including data missingness across trials and RWD; (v) selection of comparable and meaningful endpoints that are operationalized and analyzed using appropriate analytic methods; and (vi) conduct of sensitivity analyses to assess the robustness of findings in the context of uncertainty and sources of potential bias.
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
303-315Informations de copyright
© 2023 Regeneron Pharmaceuticals Inc and The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.
Références
European Federation of Pharmaceutical Industries and Associations. Evidence mix (measures, insights, and examples): Evaluating the EU regulatory system <https://www.efpia.eu/media/636564/evidence-mix_final-9-dec-2021.pdf> (2021). Accessed March 31 2023.
Mack, C., Christian, J., Brinkley, E., Warren, E.J., Hall, M. & Dreyer, N. When context is hard to come by: external comparators and how to use them. Ther. Innov. Regul. Sci. (2019). https://doi.org/10.1177/2168479019878672
Thorlund, K., Dron, L., Park, J.J.H. & Mills, E.J. Synthetic and external controls in clinical trials - a primer for researchers. Clin. Epidemiol. 12, 457-467 (2020).
Cave, A., Kurz, X. & Arlett, P. Real-world data for regulatory decision making: challenges and possible solutions for Europe. Clin. Pharmacol. Ther. 106, 36-39 (2019).
US FDA. Framework for FDA's real-world evidence program <https://www.fda.gov/media/120060/download> (2018). Accessed March 31 2023.
Rivera, D.R. et al. Clinical evidence generation during a pandemic: lessons learned for sustaining progress. Cancer J. 28, 151-156 (2022).
Arlett, P., Kjaer, J., Broich, K. & Cooke, E. Real-world evidence in EU medicines regulation: enabling use and establishing value. Clin. Pharmacol. Ther. 111, 21-23 (2022).
EMA. Guideline on registry-based studies <https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-registry-based-studies_en-0.pdf> (2021). Accessed March 31 2023.
HAS. Real-world studies for the assessment of medicinal products and medical devices <https://www.has-sante.fr/upload/docs/application/pdf/2021-06/real-world_studies_for_the_assessment_of_medicinal_products_and_medical_devices.pdf> (2021). Accessed March 31 2023.
Health Canada. Health Canada's evolving approach to leveraging real world evidence (RWE) for drug regulatory decisions <https://www.canada.ca/en/health-canada/services/drugs-health-products/drug-products/announcements/optimizing-real-world-evidence-regulatory-decisions.html> (2019). Accessed March 31 2023.
IQWiG. Concepts for the generation of routine practice data and their analysis for the benefit assessment of drugs according to §35a social code book V (SGB V) <https://www.iqwig.de/download/a19-43_routine-practice-data-for-the-benefit-assessment-of-drugs_rapid-report_v1-0.pdf> (2020). Accessed April 1 2023.
NICE. NICE real-world evidence framework <https://www.nice.org.uk/corporate/ecd9/resources/nice-realworld-evidence-framework-pdf-1124020816837> (2022). Accessed March 31 2023.
US FDA. Considerations for the use of real-world data and real-world evidence to support regulatory decision-making for drug and biological products <https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-use-real-world-data-and-real-world-evidence-support-regulatory-decision-making-drug> (2021). Accessed March 31 2023.
US FDA. Real-world data: Assessing registries to support regulatory decision-making for drug and biological products guidance for industry <https://www.fda.gov/media/154449/download> (2021). Accessed March 31 2023.
US FDA. Real-world data: Assessing electronic health records and medical claims data to support regulatory decision-making for drug and biological products <https://www.fda.gov/media/152503/download> (2021). Accessed March 31 2023.
US FDA. Data standards for drugs and biological product submissions containing real-world data guidance for industry <https://www.fda.gov/media/153341/download> (2021). Accessed April 1 2023.
US FDA. Real-world evidence <https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence> (2023). Accessed March 31 2023.
Gatto, N.M. et al. The structured process to identify fit-for-purpose data: a data feasibility assessment framework. Clin. Pharmacol. Ther. 111, 122-134 (2022).
Gatto, N.M., Reynolds, R.F. & Campbell, U.B. A structured preapproval and postapproval comparative study design framework to generate valid and transparent real-world evidence for regulatory decisions. Clin. Pharmacol. Ther. 106, 103-115 (2019).
Wang, S.V. et al. Harmonized protocol template to enhance reproducibility of hypothesis evaluating real-world evidence studies on treatment effects: a good practices report of a joint ISPE/ISPOR task force. Value Health 25, 1663-1672 (2022).
Beyrer, J., Abedtash, H., Hornbuckle, K. & Murray, J.F. A review of stakeholder recommendations for defining fit-for-purpose real-world evidence algorithms. J. Comp. Eff. Res. 11, 499-511 (2022).
Burns, L. et al. Real-world evidence for regulatory decision-making: guidance from around the world. Clin. Ther. 44, 420-437 (2022).
Jahanshahi, M. et al. The use of external controls in FDA regulatory decision making. Ther. Innov. Regul. Sci. 55, 1019-1035 (2021).
Levenson, M.S. Regulatory-grade clinical trial design using real-world data. Clin. Trials 17, 377-382 (2020).
Sola-Morales, O. et al. Effectively leveraging RWD for external controls: a systematic literature review of regulatory & HTA decisions. Clin Pharmacol Ther. (Accepted Author Manuscript). https://doi.org/10.1002/cpt.2914
Mahendraratnam, N., Mercon, K., Gill, M., Benzing, L. & McClellan, M.B. Understanding use of real-world data and real-world evidence to support regulatory decisions on medical product effectiveness. Clin. Pharmacol. Ther. 111, 150-154 (2022).
Flynn, R. et al. Marketing authorization applications made to the European Medicines Agency in 2018-2019: what was the contribution of real-world evidence? Clin. Pharmacol. Ther. 111, 90-97 (2022).
Carrigan, C. et al. External comparator groups derived from real-world data used in support of regulatory decision making: use cases and challenges. Curr. Epidemiol. Rep. 9, 326-337 (2022).
Izem, R., Buenconsejo, J., Davi, R., Luan, J.J., Tracy, L. & Gamalo, M. Real-world data as external controls: practical experience from notable marketing applications of new therapies. Ther. Innov. Regul. Sci. 56, 704-716 (2022).
Jaksa, A. et al. A comparison of seven oncology external control arm case studies: critiques from regulatory and health technology assessment agencies. Value Health 25, 1967-1976 (2022).
US FDA. Considerations for the design and conduct of externally controlled trials for drug and biological products guidance for industry <https://www.fda.gov/media/164960/download> (2023). Accessed April 1 2023.
EMA. Eurpoean Medicines Agency guidance for applicants seeking scientific advice and protocol assistance <https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/european-medicines-agency-guidance-applicants-seeking-scientific-advice-protocol-assistance_en.pdf> (2022). Accessed April 1 2023.
ICMRA. ICMRA statement on international collaboration to enable real-world evidence (RWE) for regulatory decision-making <https://icmra.info/drupal/sites/default/files/2022-07/icmra_statement_on_rwe.pdf> (2022). Accessed April 1 2023.
Concato, J. & Corrigan-Curay, J. Real-world evidence - where are we now? N. Engl. J. Med. 386, 1680-1682 (2022).
US FDA. NDA 211723 NME - multi-disciplinary review and evaluation tazverik (tazemetostat) <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2020/211723Orig1s000MultidisciplineR.pdf> (2018). Accessed April 1 2023.
US FDA. NDA/BLA multi-disciplinary review and evaluation - NDA 212306: Xpovio (selinexor) <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212306Orig1s000MultidisciplineR.pdf> (2020). Accessed April 1 2023.
EMA. Scientific advice and protocol assistance <https://www.ema.europa.eu/en/human-regulatory/research-development/scientific-advice-protocol-assistance#:~:text=EMA%20gives%20scientific%20advice%20by,development%20of%20a%20particular%20medicine.&text=Scientific%20advice%20from%20EMA%20is,applications%20for%20the%20medicine%20concerned> (2023). Accessed April 1 2023.
European Parliament and the Council of the 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 <https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32021R2282> (2021). Accessed April 1 2023.
EUnethta. Joint scientific consultation (JSC) <https://eur-lex.europa.eu/eli/reg/2021/2282/oj> (2021). Accessed April 1 2023.
US FDA. Guidance for industry formal meetings between the FDA and sponsors or applicants <https://www.fda.gov/media/72253/download> (2009). Accessed April 1 2023.
Burcu, M. et al. Real-world evidence to support regulatory decision-making for medicines: considerations for external control arms. Pharmacoepidemiol. Drug Saf. 29, 1228-1235 (2020).
NICE. Zydelig: Technology appraisal guidance <https://www.nice.org.uk/guidance/ta604/resources/idelalisib-for-treating-refractory-follicular-lymphoma-pdf-82608896324293> (2019). Accessed April 1 2023.
Yap, T.A., Jacobs, I., Baumfeld Andre, E., Lee, L.J., Beaupre, D. & Azoulay, L. Application of real-world data to external control groups in oncology clinical trial drug development. Front. Oncol. 11, 695936 (2021).
Arondekar, B. et al. Real-world evidence in support of oncology product registration: a systematic review of new drug application and biologics license application approvals from 2015-2020. Clin. Cancer Res. 28, 27-35 (2022).
Duke-Margolis Center for Health Policy. Characterizing RWD quality and relevancy for regulatory purposes <https://healthpolicy.duke.edu/sites/default/files/2020-03/characterizing_rwd.pdf> (2018). Accessed April 1 2023.
Dagenais, S., Russo, L., Madsen, A., Webster, J. & Becnel, L. Use of real-world evidence to drive drug development strategy and inform clinical trial design. Clin. Pharmacol. Ther. 111, 77-89 (2022).
Oksen, D. et al. Treatment effectiveness in a rare oncology indication: lessons from an external control cohort study. Clin. Transl. Sci. 15, 1990-1998 (2022).
EMA. Assessment report. Abecma. International non-proprietary name: Idecabtagene vicleucel <https://www.ema.europa.eu/en/documents/assessment-report/abecma-epar-public-assessment-report_en.pdf> (2021). Accessed April 1 2023.
Suissa, S. Immortal time bias in pharmaco-epidemiology. Am. J. Epidemiol. 167, 492-499 (2008).
US FDA. Diversity plans to improve enrollment of participants from underrepresented racial and ethnic populations in clinical trials; draft guidance for industry; availability <https://www.fda.gov/regulatory-information/search-fda-guidance-documents/diversity-plans-improve-enrollment-participants-underrepresented-racial-and-ethnic-populations> (2022). Accessed April 1 2023.
Singh, H. & Pazdur, R. Importing oncology trials from China: a bridge over troubled waters? Lancet Oncol. 23, 323-325 (2022).
Cheah, C.Y. et al. Patients with classical Hodgkin lymphoma experiencing disease progression after treatment with brentuximab vedotin have poor outcomes. Ann. Oncol. 27, 1317-1323 (2016).
McCulloch, R. et al. Efficacy of R-BAC in relapsed, refractory mantle cell lymphoma post BTK inhibitor therapy. Br. J. Haematol. 189, 684-688 (2020).
Beaulieu-Jones, B.K. et al. Examining the use of real-world evidence in the regulatory process. Clin. Pharmacol. Ther. 107, 843-852 (2020).
Korn, E.L. & Freidlin, B. Adaptive clinical trials: advantages and disadvantages of various adaptive design elements. J. Natl. Cancer Inst. 109, djx013 (2017). https://doi.org/10.1093/jnci/djx013
EMA. Chmp assessment report. Libmeldy. Usual common name: Autologous CD34+ cell encoding ARSA gene <https://www.ema.europa.eu/en/documents/assessment-report/libmeldy-epar-public-assessment-report_en.pdf> (2020). Accessed April 1 2023.
Ventz, S., Lai, A., Cloughesy, T.F., Wen, P.Y., Trippa, L. & Alexander, B.M. Design and evaluation of an external control arm using prior clinical trials and real-world data. Clin. Cancer Res. 25, 4993-5001 (2019).
Moons, K.G. et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (tripod): explanation and elaboration. Ann. Intern. Med. 162, W1-W73 (2015).
Rippin, G., Ballarini, N., Sanz, H., Largent, J., Quinten, C. & Pignatti, F. A review of causal inference for external comparator arm studies. Drug Saf. 45, 815-837 (2022).
DerSimonian, R. & Laird, N. Meta-analysis in clinical trials. Control. Clin. Trials 7, 177-188 (1986).
EMA. Assessment report. Yescarta. International non-proprietary name: Axicabtagene ciloleucel <https://www.ema.europa.eu/en/documents/variation-report/yescarta-h-c-004480-ii-0042-epar-assessment-report-variation_en.pdf> (2018). Accessed April 1 2023s.
Dong, Y. & Peng, C.Y. Principled missing data methods for researchers. Springerplus 2, 222 (2013).
US FDA. NDA/BLA multi-disciplinary review and evaluation (NDA [NME] 212018) balversatm (erdafitinib) <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212018Orig1s000MultidisciplineR.pdf> (2019). Accessed April 1 2023.
Duke-Margolis Center for Health Policy. Comment letter in response to FDA's "Real-world data: assessing electronic health records and medical claims data to support regulatory decision- making for drug and biological products; draft guidance for industry." <https://www.regulations.gov/comment/FDA-2020-D-2307-0061> (2022). Accessed April 1 2023.
EMA. Assessment report. Koselugo. International non-proprietary name: Selumetinib <https://www.ema.europa.eu/en/documents/assessment-report/koselugo-epar-public-assessment-report_en.pdf> (2021). Accessed April 1 2023.
US FDA. NDA/BLA multi-disciplinary review and evaluation BLA 761115 trodelvy, sacituzumab govitecan-hziy <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2020/761115Orig1s000MultidisciplineR.pdf> (2018). Accessed April 1 2023.
EMA. Assessment report. Enhertu. International non-proprietary name: Trastuzumab deruxtecan <https://www.ema.europa.eu/en/documents/variation-report/enhertu-h-c-005124-ii-0014-epar-assessment-report-variation_en.pdf> (2022). Accessed April 1 2023.
US FDA. NDA/BLA multi-disciplinary review and evaluation BLA 761104, lumoxiti, moxetumomab pasudotox. <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2018/761104Orig1s000MultidisciplineR.pdf> (2018). Accessed April 1 2023.
Walker, B. et al. Comparisons of real-world time-to-event endpoints in oncology research. JCO Clin. Cancer Inform. 5, 45-46 (2021).
Li, Q. et al. Validation of real-world data-based endpoint measures of cancer treatment outcomes. AMIA Annu. Symp. Proc. 2021, 716-725 (2021).
US FDA. BLA multi-disciplinary review and evaluation BLA 761163 monjuvi (tafasitamab-cxix) <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2020/761163Orig1s000MultidisciplineR.pdf> (2020). Accessed April 1 2023.
Rubin, D.B. Using propensity scores to help design observational studies: application to the tobacco litigation. Health Serv. Outcomes Res. Methodol. 2, 169-188 (2001).
Lim, J. et al. Minimizing patient burden through the use of historical subject-level data in innovative confirmatory clinical trials: review of methods and opportunities. Ther. Innov. Regul. Sci. 52, 546-559 (2018).
Spin, P., Siddiqui, M., Hutton, B. & Cameron, C. PNS9 propensity score matching and reweighting to assess comparative efficacy of single-arm trials: a general framework and simulation study. Value Health 22, S289 (2019).
Zhang, X., Stamey, J.D. & Mathur, M.B. Assessing the impact of unmeasured confounders for credible and reliable real-world evidence. Pharmacoepidemiol. Drug Saf. 29, 1219-1227 (2020).
Berger, M.L. et al. Good practices for real-world data studies of treatment and/or comparative effectiveness: recommendations from the joint ISPOR/ISPE special task force on real-world evidence in health care decision making. Pharmacoepidemiol. Drug Saf. 26, 1033-1039 (2017).
Jaksa, A., Wu, J., Jonsson, P., Eichler, H.G., Vititoe, S. & Gatto, N.M. Organized structure of real-world evidence best practices: moving from fragmented recommendations to comprehensive guidance. J. Comp. Eff. Res. 10, 711-731 (2021).
Faria, R., Alava, M.H., Manca, A. & Wailoo, A.J. NICE DSU technical support document 17: The use of observational data to inform estimates of treatment effectiveness in technology appraisal: Methods for comparative individual patient data <https://www.sheffield.ac.uk/nice-dsu/tsds/observational-data> (2015). Accessed April 1 2023.
US FDA & EMA. General principles, EMA-FDA parallel scientific advice (human medicinal products) <https://www.fda.gov/media/105211/download?utm_medium=email&utm_source=govdelivery> (2021). Accessed April 1 2023.
EMA. Parallel joint scientific consultation with regulators and health technology assessment bodies <https://www.ema.europa.eu/en/human-regulatory/research-development/scientific-advice-protocol-assistance/parallel-joint-scientific-consultation-regulators-health-technology-assessment-bodies> (2022). Accessed April 1 2023.
AISBL, E.C.o.P.E. Pharmaboardroom opinion: New EU HTA procedure - will it reduce the complexity and burdens for manufacturers? <https://www.eucope.org/pharmaboardroom-opinion-new-eu-hta-procedure-will-it-reduce-the-complexity-and-burdens-for-manufacturers/> (2022). Accessed April 1 2023.