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P221: Important Tool in our Rare Disease Toolbox: Hybrid Retrospective-Prospective Natural History Studies as External Comparators 





Poster Presenter

      Gerd Rippin

      • Senior Director, Biostatistics, Real-World Solutions
      • IQVIA
        Germany

Objectives

Describe design considerations for hybrid Natural History of Disease studies intended for use as single-arm trial external comparators in rare disease clinical development programs and detail applicability, strengths, scientific and operational considerations.

Method

We present two broad categories of hybrid Natural History of Disease studies: 1) “mixed patient”, and 2) “same patient”/ ambispective designs and detail applicability, strengths and operational considerations. [Co-authors: J Heidt, J Largent, E Bratton, L Hester, S Turner, C Mack]

Results

Hybrid Natural History of Disease studies are appropriate to study rare diseases which often have limited existing data, limited and heterogeneous patient populations, and require long follow-up. “Mixed patient” designs include a set of patients followed prospectively either in real-world settings or in a clinical trial, and another set of patients for which retrospective longitudinal data is available. “Same patient” designs include retrospective and prospective data collected on the same set of patients. Design choice depends on disease dynamics (e.g., fatality, evolution of variants), patient heterogeneity, and practical factors inherent to the clinical development program (e.g., anticipated truncation of patient follow-up). Mixed patient designs quicken patient accrual and increase sample size. Same-patient designs capture key aspects of disease course, lengthen available patient follow-up, and can shorten prospective follow-up. A meaningful example is fosdenopeterin, which was approved for a rare cofactor deficiency indication, based on overall survival at 3 years (32 vs 24 months) of a treatment arm of 13 patients compared to a genotype-matched untreated hybrid external control group of 18 patients. More typical retrospective or prospective-only designs may have had inadequate sample size and/or limited observation of important aspects of the disease. Hybrid external comparator studies require regulatory-grade feasibility review of each data source, specialized study design (e.g., nuances of time zero definition, availability of prognostic variables, standardized endpoint assessments across sources), and analytical considerations (e.g., missingness and unmeasured confounding differences in the retrospective and prospective periods/patients). Ultimately, early feedback from the agency on the approach is critical to success.

Conclusion

Real-world evidence (RWE) from Natural History of Disease studies can well-support regulatory approval, including as external comparator arms for single-arm trials. Natural History of Disease Studies are typically either prospective or retrospective; less common are hybrid external comparator cohorts, which combine retrospective and prospective data. In rare diseases or rare subgroups of common diseases specific situations arise in which prospective or retrospective data collection alone may not be feasible, sufficient or fit-for-purpose. The hybrid design gives investigators more options to leverage Real World Data (RWD) as part of the totality of evidence. These can be a useful option for creating fit-for-purpose RWD by taking advantage of strengths across different datasets and data collection strategies. However, differences in data availability, timing, and quality between sources present unique methodological challenges and the need to evaluate potential bias. Optimizing the benefits of the hybrid studies as external comparators for single arm trials requires that investigators first evaluate the suitability of this design, including the type of hybrid study that is applicable or feasible for the target disease, and carefully consider specific design and operational elements from study conceptualization to analysis. Hybrid Natural History of Disease studies allow for more robust contextual information on natural course of disease, improving suitability and robustness of the data for an external comparator. As adoption increases, investigators will benefit from regulatory guidance on acceptable scenarios for these designs.

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