Discussion
This is the first real-world study to compare the parallel biologic
naïve characteristics of OMA and MEPO treated subjects against a common
comparator that remained biologic naïve (SNB) within the same cohort. A
key finding was that despite potentially overlapping clinical
indications for these drugs, OMA and MEPO treated patients showed
distinctive asthma phenotypes. Regardless of that, both biologic
response rates were comparable to RCTs and other reports (19–26). In
addition, for OMA, even though 43.3% (45/104) patients were potentially
dual-eligible for MEPO, the OMA response rate was 88.5%, reiterating
that OMA was efficacious in the phenotype that received it. Indeed, both
OMA and MEPO conferred substantial multidimensional clinical benefit to
the real-world populations which received them. This testifies to the
success of both biologics in targeting treatable traits in difficult
asthma patients. Nevertheless, non-responders emerged to both drugs,
typically characterised by worse baseline disease and psychological
comorbidity.
Of those with highest disease burden in our cohort (OMA, MEPO, SNB),
51.6% did not receive biologics. Both biologic receiving groups had
hallmarks of greater disease severity with significantly worse lung
function (Clinic FEV1%), worse airway inflammation
(FENO) and greater mOCS dependence compared to SNB. The SNB group are
noteworthy as their characterisation derives from the timepoint of WATCH
enrolment, when 42.3% of them were new clinic referrals, and thus at an
early phase of conventional treatment optimisation. Their lack of
subsequent biologic need infers a responsiveness to that conventional
optimisation. Conversely, biologics treated subjects had already
undergone substantial treatment optimisation, without sufficient
response, prior to their characterisation in this study.
Although our three high burden groups were similar with regards to ACQ6,
exacerbations and AHE, they were phenotypically distinct. OMA patients
had a younger, early-onset, atopic phenotype, with high proportions of
co-morbid ABPA and rhinitis. Conversely, MEPO patients had an older,
male, late-onset, eosinophilic but less atopic phenotype, associated
with higher prevalence of nasal polyposis but less dysfunctional
breathing. This adds further insight to preliminary suggestions of
typical patient features for these biologics outlined by GINA (27).
Additionally, stratification of biologic use by our recently described
age-of-onset/sex phenotypes (15) further corroborate these findings, as
we found significantly different biologic use across the four
phenotypes. Notably, the female/early-onset phenotype showed highest
prevalence of OMA and lowest prevalence of MEPO use, while the
male/adult-onset phenotype showed highest prevalence of MEPO use. This
may part explain a disparity in biologic effect, whereby OMA but not
MEPO, significantly improved Clinic FEV1%, mirroring
findings of another real-world UK study (26). This observed difference
could be partly explained by the higher representation of MEPO patients
among the male/adult-onset phenotype which had poorest baseline lung
function (15) in our cohort. Other reports have also confirmed that such
patients have more severe, persistent airflow limitation (28),
potentially explaining their limited lung function improvement. Another
disparity was in steroid-sparing effect, whereby MEPO but not OMA,
significantly reduced mOCS dependency. This may reflect different trial
durations. Indeed, other studies which evaluated OMA beyond 16-weeks,
found that it reduced the proportion of patients on mOCS
(16,21,22,29,30). This may also reflect clinical practice during the
single biologic phase, whereby a more conservative mOCS weaning approach
may have been adopted, given the lack of alternatives.
Overall, there is limited knowledge on clinical predictors of OMA and
MEPO response. A pooled analysis of seven clinical trials found that
baseline characteristics were unable to reliably predict OMA benefit
(23). For MEPO, post-hoc analyses of RCT data suggested that baseline
PBE could be a useful predictor of response (31), but this was not
consistently observed in real-world studies (24,26), including ours.
Instead, our data suggests that patients with the most severe and poorly
controlled baseline disease were poorest responders. Thus, for MEPO,
better baseline asthma control was independently associated with
response and super-response. This mirrored the findings of Kavanagh et
al. (26), where in their cohort, poor disease control at baseline was
independently associated with MEPO non-response. Similarly, in OMA, more
‘severe’ exacerbations, AHE, at baseline were associated with
non-response, while being on mOCS, was associated with
non-super-response. However, while AHE may represent more ‘severe’
asthma exacerbations, they may also reflect impact of multiple
influences beyond just airways disease. Indeed, Burke et al. identified
that those with repeated AHE were a subgroup of difficult asthma
patients with multiple aggravating comorbidities including obesity,
Gastrointestinal reflux disease, dysfunctional breathing and
psychological morbidity(32). Such complex multifactorial health events
may be less responsive to a simple biologic approach. It is notable that
by adopting a holistic, asthma MDT approach, they reduced AHE
significantly(32). Collectively these findings emphasise the importance
of comprehensive, up-front characterisation of difficult asthma
patients, focused on addressing all treatable traits to maximise
biologic outcome.
Reinforcing this, our data uniquely showed that psychological
co-morbidities may be associated with biologic non-response, an
unexplored aspect by other real-world biologic studies. Anxiety was
independently associated with OMA non-response while depression was
independently associated with OMA non-super-response and was associated
with MEPO non-response. Psychopathologies have been associated with
biologic non-response in other diseases. Analysis of the British Society
for Rheumatology Biologics registry showed that depression reduced the
odds of biologic response (33). The impact of psychopathology on
biologic outcome could be secondary to the well documented interplay
between psychological disease and SA (34). Psychopathologies have been
associated with worse asthma control, more exacerbations and more AHE
(35–37). Furthermore, studies have shown that proinflammatory cytokines
associated with asthma are raised in depression and anxiety (38,39),
which may dampen biologic effect. Brown et al showed in a RCT that
12-week continuous escitalopram therapy for SA patients with co-morbid
major depression significantly reduced OCS use and asthma control (40).
As such, our findings encourage proactive management of psychological
comorbidity alongside consideration of asthma biologics.
Analysis of our pooled biologic data allowed us to describe an overall
biologic unresponsive group. They had early-onset asthma, were
predominantly female yet had comparable exacerbations, mOCS dependence,
FENO, lung function and asthma ICU admissions to responders. However,
they were characterised by more AHE, a larger proportion of multiple
AHE, significantly worse baseline asthma control, alongside greater
proportions of anxiety and depression. We postulate their biologic
unresponsiveness may have been augmented by their high burden of
psychopathologies as although their objective disease markers and
clinical co-morbidities were equivalent, their subjective markers of
disease were not. Our recent work has shown that this group of
early-onset, female patients have the highest prevalence of
psychological co-morbidities, yet also have the highest frequency of
biologic use (15). This reiterates the importance of holistically
addressing treatable traits, through addressing psychopathologies before
biologic therapy.
Head-to-head comparisons between OMA and MEPO response rates were not
appropriate in our data, given their different phenotypic traits, and
the different response tools employed. However, notably,10/15 MEPO
‘non-responders’ displayed responses in domains outside NICE criteria.
Particularly noteworthy were those who sustained an improvement in AHE
status, including one who had both ACQ and AHE status response. However,
despite improvements in disease control and healthcare utilisation,
important markers of economic and patient-centred efficacy, these MEPO
patients were not classified as responders according to NICE
criteria(14). A post-hoc analysis of two MEPO RCTs found that ACQ was
unreliable in predicting MEPO response (41). Though important, their
findings were based on RCT data which may have limited transferability
to real-world patients (7–9). Additionally, ACQ is used to gauge MEPO
response in the Australian Mepolizumab Registry, and shown to correlate
with improvements in objective measures(25). Conversely, few MEPO
responders did not sustain an ACQ or AQLQ response. This could be
because improvement in NICE defined domains may not equate to the
patient’s perception of better asthma control, or quality-of-life. Thus,
in those who are borderline responders, consideration might be made to
measure MEPO response more holistically, perhaps by taking into account
a wider range of measures. However, the economic implications of any
such move need careful deliberation.
Our study had limitations. Inherent to real-world observational studies,
we had some missing data. However, real-world data capture is
representative of clinical populations receiving these treatments. Our
report is also limited by the small numbers in the MEPO group, which
prevented us from uncovering whether the different age-of-onset/sex
phenotypes had differing response predictors. Therefore, future studies
are needed to clarify these findings and further explore
age-of-onset/sex related signals. Our study had several strengths. We
are the first to report detailed real-world clinical outcomes on both
OMA and MEPO in parallel, against a non-biologic comparator in a
difficult asthma cohort. Additionally, our cohort represents an
extensively characterised difficult asthma population from a wide
geographical catchment, enhancing generalisability of findings. This
allowed mapping of previously described clinical clusters onto our data,
consolidating our observations. We also undertook pooled analysis of the
non-responder group and explored other definitions of response in MEPO,
compared to OMA.