Real-world literature on the epidemiology of rare EADs, such as EGPA, is limited. Findings from this sub-study of REVEAL provide details on the prevalence of EGPA in a real-world US population as well as the HCRU and economic burden for these patients. Furthermore, observed trends in elevated blood eosinophil counts suggest that the eosinophilic inflammation underlying EGPA may be associated with multiple overlapping EADs.

As expected, patients with EGPA were most likely to have disease overlap with COPD, PA, CRSwNP, and AD; however, the frequencies of disease overlap of EGPA with asthma (38.1%) and of EGPA with CRSwNP (33.2%) in the current study were both lower than previously reported (severe asthma: > 65%; chronic sinusitis: 60–80%; nasal polyps: 40–60%) [13, 28, 30, 31]. One reason for EGPA overlapping less with asthma and CRSwNP in this REVEAL sub-study could be that patients diagnosed with EGPA may have had these EADs diagnosed prior to the study window, as these conditions are typically present earlier in the EGPA disease course than the vasculitic symptoms associated with EGPA. Additionally, the inclusion of GPA in the patient population, represented by the ICD-9 code 446.4, may have also affected the frequencies of overlap of EGPA with other respiratory diseases. However, it is also important to acknowledge that the limited study window, inconsistencies with coding, and the strict case definitions applied in this study to identify the EADs of interest may have impacted the frequencies of overlap of EGPA with other EADs.

Patients in the ICM and non-ICM groups were equally as likely to have overlapping severe COPD. This could be because EGPA is associated with asthma and high levels of eosinophilic inflammation, meaning that patients may be at an increased risk of developing a persistent airway obstruction [32]. Patients in the ICM group, compared with the non-ICM group, were more likely to have overlap with severe forms of other EADs with a more typical type 2 inflammatory mechanism of disease, such as AD, CRSwNP, and PA [33].

In our study, many patients had blood eosinophil counts ≤ 500 cells/μL, suggesting an absence of peripheral eosinophilia and a potential treatment effect [16, 17]. The percentage of patients with elevated blood eosinophil counts generally increased as the number of EAD overlaps increased, regardless of prior ICM treatment received. This reinforces the idea that eosinophilic inflammation may play an important role in the development of comorbid EADs in some patients, and it suggests a potentially high disease burden in these patients [2]. Conversely, comorbid EADs may also contribute to elevated blood eosinophil counts, leading to eosinophilic inflammation [34, 35]. Our finding that patients in the ICM group appeared to have lower blood eosinophil counts than patients in the non-ICM group can be explained, in part, by the types of treatments these patients had received. Patients in the ICM group were more intensively managed than patients in the non-ICM group, as suggested by higher EGPA-related HCRU costs, and were receiving treatments such as mepolizumab, which may have reduced blood eosinophil counts.

EGPA was associated with substantial all-cause and EGPA-related HCRU. Patients with EGPA had annual all-cause costs of approximately $100,000, which is higher than previously observed in the literature. All-cause costs per patient have been previously reported as $41,400 for patients with GPA and $49,593 for patients with EGPA [23, 36]; however, these differences are likely due to different study objectives and methods. Our study is the first to assess HCRU by prior treatments received and overlap with other EADs. All-cause costs were largely driven by frequent outpatient visits and inpatient admissions, and increased with the number of overlapping EADs but not with prior ICM treatment. Patients with EGPA and overlapping EADs had approximately double the all-cause costs of those with EGPA only, in part driven by a higher utilization of inpatient services. This trend was consistent across all patients with EGPA, highlighting that prior ICM treatment did not influence the effect of the number of overlapping EADs on all-cause costs.

EGPA-related costs accounted for 10% of overall costs and were 2.7 times higher in patients in the ICM group versus patients in the non-ICM group, with the majority of the costs associated with inpatient care and outpatient visits. Despite the higher EGPA-related costs associated with patients in the ICM group, patients in this group were slightly less likely to receive inpatient care (annual all-cause HCRU, annual EAD-related HCRU) than patients in the non-ICM group. As mentioned above, patients in the ICM group were receiving more intensive therapy, which was perhaps reflected in the reduced need for inpatient care.

As well as the strengths of REVEAL, it is also important to acknowledge the limitations. This study was based on data from one administrative health claims database in the US; as such, the generalizability of results to other populations is limited. The reliance on data from insurance claims databases to identify patients with EADs is a major limitation, as they are somewhat unreliable for identifying disease prior to study windows and could be inaccurate due to the incorrect entry of diagnosis codes. Moreover, insurance claims data do not capture disease severity, so this had to be defined for the overlapping EADs of interest using the literature and proxies such as procedures and treatments. In this REVEAL sub-study, unlike the other EADs of interest, EGPA was not assessed by guideline definitions of severity but instead by prior ICM treatment received, which may explain why there were minimal differences in EAD overlap between the two groups. It is also important to note that data on prior rituximab (recommended for patients with severe EGPA [16, 19]) use were not collected for this analysis, and this may have also contributed to some of the minor differences observed between the two groups.

Another limitation to consider is that this analysis used ICD-9 and ICD-10 diagnosis codes to establish the EGPA cohort, which may have affected frequency estimations. Despite ICD-9 representing the broader patient population of those with the distinct disease GPA as well as those with EGPA, this could potentially contribute to overestimates of EGPA frequency. Moreover, while EGPA is a multi-organ disease, this analysis did not encompass all EAD-specific procedure codes, and it only included ICD-9/-10 claims of EGPA in EGPA-related HCRU analyses, excluding instances where EGPA may have impacted other organs. As a result, EAD- and EGPA-related HCRU and costs are likely to be underestimated and therefore may not reflect the full burden of EGPA HCRU.

In addition, patients who experienced uncontrolled disease manifestations, such as asthma exacerbations, may have been coded as both EGPA and asthma rather than EGPA only, which could have affected the EAD overlap findings.

Regarding the identification period, a minimum of 2 years of follow-up from the index date was required, and so patients who were in the system for less than this were excluded. In this study, the index date referred to the first diagnosis of any EAD, rather than the first diagnosis of EGPA specifically. If a patient was diagnosed with EGPA close to the database end, there would have been a limited window to accurately capture EGPA-related costs, meaning that our findings may be an underestimate.

Finally, blood eosinophil laboratory values within 3 months of any EAD diagnosis were used and were not controlled for any variability related to sampling time or treatment effect, therefore limiting accuracy.