Patient-Reported Outcomes in Orphan Drug Labels Approved by the US Food and Drug Administration

Abstract

In recent years, there has been increasing recognition of the need to assess treatment benefit from the patient's perspective. The extent of patient-reported outcome (PRO) data included in labeling for rare disease treatment is largely unknown. The objective of this study was to review trends over time for PRO-based labeling granted by the US Food and Drug Administration (FDA) for orphan drugs.Study Design: Review of FDA package inserts.Methods: Products included in this analysis were all new molecular entities (NMEs) and biologic license applications (BLAs) with orphan designations approved by the FDA from 2002 through 2017. For identified products, package inserts were reviewed to determine the number and type of PRO claim(s) granted, endpoint status, and PRO measure named. Two trends were analyzed: (1) over all years 2002 to 2017 and (2) 2002 to 2017 stratified into 3 periods (before draft FDA PRO guidance [2006], between draft and final guidance release, and after final guidance [2009] release.Results: A total of 156 NMEs and BLAs with orphan designations were approved between 2002 and 2017. Of these, 13 products (8.3%) had PRO-based labeling, and 7 of 13 were symptom-related. The percent of orphan drugs approved with PRO-based

The Use of Patient-Reported Outcome Measures in Rare Diseases and Implications for Health Technology Assessment

“…conceptelicitation interviews can evaluate differences in patient experience across disease subtype [5,11] To help ensure accuracy of core outcome measures, the perspective of all stakeholders should be considered insofar as possible, especially patients and carers, e.g. concept-elicitation interviews can evaluate differences in patient experience across disease subtype [5,11] Need for recognition and buy-in of core outcome measures developed for specific disease areas, and time commitment to gather and include stakeholder perspectives Small, heterogeneous populations With small population sizes, it can be difficult to recruit enough patients for trials or PROM development/validation [13,21,22] Consider collaborating with patient advocacy groups and/or clinical care networks to maximize recruitment [22] Feasible: Requires collaboration stakeholder willingness for planning and time commitment but has the potential to save a substantial amount of time later in the process Consider using specialized statistical software that can work with small sample sizes while maintaining adequate psychometric properties [23] Feasible: Using statistical software depends on resources and knowledge, but using available tools to overcome as many data collection challenges as possible does not require substantial time or structural changes Multi-site/international data collection to pool samples and gain larger sizes [12,13,[24][25][26][27][28]45] Feasible with additional challenges: Multi-site/ international data collection is a good way to overcome the small sample size issue but poses challenges with regard to obtaining cross-cultural validity, and may thus require more consolidated and adhered to guidance to produce data of sufficient quality [13,33] Use of children-specific PROMs [33] Feasible: Proxy measures can and have been used, but care must be taken to ensure they are capturing the perspective of the patient as best as possible Use of observer-reported outcomes [32] Help of an interviewer when inability to selfreport is due to physical impairments [22,24,30,32] Need for recognition of challenges in collecting PROM data from certain patient populations and ensuring alternatives are accepted…”

“…Instruments are often not fit for purpose, and HTA evaluators are often not convinced a PROM is measuring what it is claimed to be measuring [29,31] Prior discussion with the relevant evaluating agencies can help to ensure a PROM is compatible with their standards [5,22,32] Probably feasible: This requires stakeholder willingness for planning and time commitment but has the potential to save a substantial amount of time later in the process Need for early and, if possible, iterative engagement between RDT developers and HTA evaluators Conventional methods are not always suitable for psychometric analysis in RDs because they require large samples and high-quality data [13,33,35] RD populations can be combined with populations with similar disease presentations to increase sample size [14] Feasible: Combining populations with similar disease characteristics would require guidelines and best practices, but, if done properly, provides a promising solution to overcoming the limited RD sample size Use of expert panel review to determine face validity/generalizability; hybrid conceptelicitation or cognitive interviews or linking items to international classification systems to determine content validity [11,36] Probably feasible: Qualitative data can be a good approach to ensuring validity without relying on large sample sizes but would require time and resource investment Need for recognition of the importance of, and willingness to consider, other forms of evidence in informing HRQoL impact…”

Measuring health-related quality of life in patients with rare disease

“…How a concept is addressed in regulatory guidance documents, as well as how often results for a specific concept are included in label claims, can provide an insight into the level of attention devoted to the concept from the regulatory perspective. Two recent reviews examined the use of PRO measures in approved rare disease labels [24,25] demonstrating low rates of PROs in label claims.…”

“…How a concept is addressed in regulatory guidance documents, as well as how often results for a specific concept are included in label claims, can provide an insight into the level of attention devoted to the concept from the regulatory perspective. Two recent reviews examined the use of PRO measures in approved rare disease labels [ 24 , 25 ] demonstrating low rates of PROs in label claims. The first examined labels of FDA-approved orphan drugs between 2002 and 2017 and revealed that, while the number of orphan drug approvals has continued to rise, only 8.3% of approved labels included results based on PRO measures.…”

“…The first examined labels of FDA-approved orphan drugs between 2002 and 2017 and revealed that, while the number of orphan drug approvals has continued to rise, only 8.3% of approved labels included results based on PRO measures. Most of these claims were based on symptom measures and only one product with HRQoL labeling was identified [ 24 ]. A later review for the same period, including European Medicines Agency and FDA approvals, reviewed 258 designations in rare non-oncology disease.…”