Is Borrowing Outcomes from US or China the Future for Rare Conditions?

Limited patient populations resulting in small study sample sizes is a difficulty associated with the development of therapies for rare diseases. Other hurdles include uncertainties around disease history, target patient profiles, and the existence of appropriate comparators. Here we discuss whether outcome estimates based on small numbers of patients can be trusted and how uncertainties in evidence can be addressed. 

At a Virtual ISPOR Europe 2021 Workshop, Cytel’s Chief Data Officer, Radek Wasiak, PhD, and Paul Arora, VP, Advanced Epidemiology, explored the conditions and methods under which real-world data on rare diseases may be robustly borrowed from sources in US and China. In this workshop, they were joined by two other speakers, Sreeram Ramagopalan, PhD, F. Hoffmann-La Roche, and Mei Yang, PhD, Happy Life Technology.

Using US Data as Benchmark

For post-authorization safety studies, US data is routinely used as benchmark for safety signals in Europe. For instance, for the evidence collection on Entrectinib for treating neurotrophic tyrosine receptor kinase (NTRK) fusion-positive solid tumors, NICE is considering the use of US data sources - Flatiron data and the Foundation Medicine genomic database. During the workshop, Dr. Wasiak shared more examples of how it is being done and the conditions under which this data can serve as a benchmark for real-world outcome evaluations in Europe.

The Methodological Approaches

Using a favorable historical control group in which the outcome of comparator treatment is artificially poor is a threat to internal validity. To minimize the risk of bias, historical control groups should be identified from a systematic, transparent, and reproducible review. Additionally, more than one control cohort should be selected from different sources, wherever it is possible. It is best to establish these control group(s) before patients are enrolled in the prospective, single-arm trial of the experimental treatment, and agreement is sought with regulators and other decision-makers.

Although real world data is being increasingly used to provide insight and inform decisions across the drug development and reimbursement process, several biases may be introduced when using RWD. There are several approaches to account for measured confounders and the selection is made based on the situation. For example, when the number of events is low, a fair number of covariates need to be adjusted, and the sample size is large, a propensity score matching (PSM) method is preferred.

While this (and other) statistical approaches account for measured confounders, they do not account for:

• unmeasured confounding;
• imperfect measurement of exposure, outcome and other covariates;
• bias introduced by incorrectly specifying the mechanism of missingness; and
• differences in follow-up

Quantitative Bias Analyses (QBA) are a series of methods that quantify how drastic the range of assumptions about missing data and unmeasured/residual confounding must be for the conclusions to be nullified or reversed. Performing QBAs are becoming increasingly popular. In September 2021, the FDA released a draft guidance for assessing electronic health records (EHR) and medical claims data to support regulator decisions and recommended exploring the certainty of findings with QBA.

Chinese RWD for Rare Conditions

China has an estimated population of over 20 million people with rare diseases. Chinese treatment guidelines are quickly adapted following those in the US and Europe. However, unlike in the US, a small number of large hospitals and KoLs in China manage a large portion of patients with rare diseases. Hence, complete medical information are collected in these hospitals and data quality has largely improved in recent years. With a high-level of health information digitization and social media integration in people’s daily life, patients with rare conditions are more amenable to being approached and managed longitudinally. Rapidly growing patient advocacy groups also provide opportunities to collect data from patients with rare conditions. Case studies presented at the ISPOR Europe workshop illustrate how Chinese RWD can be leveraged to assess real-world outcomes for HTA agreements.

Click below to access the slide deck from Cytel's Workshop presentation at Virtual ISPOR Europe.

With thanks to Radek Wasiak, PhD and Paul Arora.