Ian D Pavord1,2. 1. Nuffield Department of Medicine and. 2. Oxford Respiratory NIHR Biomedical Research Center University of Oxford Oxford, United Kingdom.
I suspect that history will judge the introduction in the early
1990s of a noninvasive method to assess airway inflammation using induced sputum as the
most important advance in the assessment of airway disease in the last 50 years (1–3). The use of this technique in the clinic established that the pattern of
airway dysfunction, the severity of impaired function, demographic characteristics
(including diagnostic label), and severity of symptoms or lung function impairment
provide a very limited insight into the nature and severity of lower airway inflammation
(4–6). It also become clear that identification of type 2–high
eosinophilic airway inflammation is important because it is associated with an increased
risk of exacerbations of asthma (7–9) and chronic obstructive pulmonary disease
(COPD) (10) and a better response to
corticosteroids (9–11) and biologic agents targeting type 2 cytokines (12–16). Thus, an approach to risk stratification and the introduction and
titration of treatment that relies on symptoms and recognition of different patterns of
airflow limitation is flawed. There is now strong evidence that this is the case;
proof-of-concept studies have shown consistently that biomarker-directed use of
corticosteroid results in better outcomes (10,
17) and targeting biomarker-identified type
2 inflammation was key to the recognition of the efficacy of biologics targeting type 2
cytokines (12, 14, 15).Progress in rolling out this thinking into everyday clinical practice has been slow,
probably reflecting the technical challenge of performing induced-sputum
inflammatory-cell counting outside specialist centers. Horn and colleagues suggested 45
years ago that the blood eosinophil count, a more clinically accessible biomarker, was
useful for regulating corticosteroid doses and predicting asthma attacks (18). Two observations 10 years ago put the blood
eosinophil count back in the spotlight. First, Bafadhel and colleagues showed that the
blood eosinophil count was the standout biomarker of an exacerbation of COPD associated
with a raised sputum eosinophil count and a positive response to prednisolone (19, 20).
Second, the blood eosinophil count emerged as the best predictor of response to the
anti–IL-5 monoclonal antibody Mepolizumab in the DREAM (Dose Ranging Efficacy And
Safety with Mepolizumab in Severe Asthma) study (13). In both studies, a count less than
0.15 × 109/L (near the upper end of the normal range
in a nonatopic healthy population) (21)
identified patients who did not respond to treatment (22).The evaluation of the blood eosinophil count as a prognostic and predictive biomarker has
since proceeded at pace, driven by a very receptive pharmaceutical industry that saw an
opportunity to increase the therapeutic index of inhaled corticosteroid (ICS) treatment
and clarify the role of dual bronchodilator therapy. Their willingness to devote
considerable resources to this area and produce clinical practice–changing
research outputs over a short period has been impressive. In this issue of the
Journal, Singh and coauthors (pp. 660–671), all leading
players in this area, provide an excellent review of the many post hoc
and prespecified analyses of phase 3 studies of ICS/long-acting
β2-agonist combination treatment in patients with moderate and severe
COPD (23). These studies have firmly
established the blood eosinophil count as a prognostic biomarker and a predictor of
response to ICS. The Global Initiative for Chronic Obstructive Lung Disease guidelines
have changed to reflect these new findings, and now, for the first time in COPD,
treatment with ICS is targeted at a measured biological process rather than at
potentially unrelated symptoms and airway dysfunction (24). This radical change has been difficult for some to digest, and
questions on the validity, accuracy, and diagnostic value of the blood eosinophil count
continue to be asked. These issues are dealt with effectively and systematically by
Singh and colleagues (23). They remind us that
the additional information provided by a biomarker is greater if the context of the test
is known, if the result is clearly abnormal (or normal), and if the finding is
persistent. This is not rocket science, and I believe that biomarker-directed management
of airway disease is eminently suitable for nonspecialist primary care clinicians. This
group has, after all, delivered a remarkable 70% reduction in cardiovascular diseasemortality over the last 10 years in adult men in the United Kingdom, primarily by
delivering high-quality biomarker-directed primary and secondary risk-reduction
treatments.So where might we be heading with biomarker-directed management of airway disease? I see
progress in three main areas. First, there is growing evidence that blood
eosinophil–directed use of oral corticosteroids to treat acute exacerbations of
COPD is an effective and safe way to limit exposure to a potentially toxic treatment
(20, 25). This approach needs to be evaluated in larger definitive studies
involving different healthcare settings and different patient groups. Second,
biomarker-directed risk stratification and reduction should be extended beyond COPD and
severe asthma clinics. There is now evidence from large intervention studies in mild,
moderate, and severe asthma that the blood eosinophil count is independently associated
with up to a fivefold increased risk for severe exacerbations as well as a greater
response to ICS and biological agents (8, 9, 14,
26). Most studies have shown that another
easy to measure biomarker, exhaled nitric oxide, adds prognostic and predictive
information to blood eosinophil–based stratification (8, 26). It seems obvious
that this information would help clinicians and patients make good decisions about the
need for long-term preventative treatment. Why, then, do guideline groups continue to
make weak and equivocal recommendations on the question of whether type 2 biomarkers
should be used to predict outcomes and guide asthma treatment (27, 28)? It is becoming
crucial that this stance is reconsidered, particularly because any concerns about the
safety of not treating biomarker-low patients with regular ICS disappear completely if
as-needed ICS/rapid-onset β2-agonist becomes the standard of care for
milder asthma (29).A third area requiring more work is whether we should move from secondary to primary
prevention of problems associated with biomarker-identified type 2 airway inflammation.
Might early use of ICS or a biologic in patients with raised biomarkers of type 2 airway
inflammation but mild or no symptoms improve longer-term outcomes? This is a
possibility, as a raised blood eosinophil count has been associated with increased rate
of decline in FEV1 in a community population independent of the presence of
symptoms or an asthma label (30). In addition,
there is existing evidence from post hoc analysis of intervention
studies that ICS prevents decline in FEV1 in patients with COPD and a blood
eosinophil count greater than 0.15 × 109/L (31) and that the anti–IL-4
receptor-α biologic dupilumab prevents decline in FEV1 over 12 months
(14). Prospective studies are needed to
answer this important question definitively.
Authors: Mario Castro; Jonathan Corren; Ian D Pavord; Jorge Maspero; Sally Wenzel; Klaus F Rabe; William W Busse; Linda Ford; Lawrence Sher; J Mark FitzGerald; Constance Katelaris; Yuji Tohda; Bingzhi Zhang; Heribert Staudinger; Gianluca Pirozzi; Nikhil Amin; Marcella Ruddy; Bolanle Akinlade; Asif Khan; Jingdong Chao; Renata Martincova; Neil M H Graham; Jennifer D Hamilton; Brian N Swanson; Neil Stahl; George D Yancopoulos; Ariel Teper Journal: N Engl J Med Date: 2018-05-21 Impact factor: 91.245
Authors: Parameswaran Nair; Marcia M M Pizzichini; Melanie Kjarsgaard; Mark D Inman; Ann Efthimiadis; Emilio Pizzichini; Frederick E Hargreave; Paul M O'Byrne Journal: N Engl J Med Date: 2009-03-05 Impact factor: 91.245
Authors: Pranab Haldar; Ian D Pavord; Ruth H Green; Dominic E Shaw; Michael A Berry; Michael Thomas; Christopher E Brightling; Andrew J Wardlaw Journal: Am J Respir Crit Care Med Date: 2008-05-14 Impact factor: 21.405
Authors: Mona Bafadhel; Susan McKenna; Sarah Terry; Vijay Mistry; Mitesh Pancholi; Per Venge; David A Lomas; Michael R Barer; Sebastian L Johnston; Ian D Pavord; Christopher E Brightling Journal: Am J Respir Crit Care Med Date: 2012-03-23 Impact factor: 21.405
Authors: Mona Bafadhel; Susan McKenna; Sarah Terry; Vijay Mistry; Carlene Reid; Pranabashis Haldar; Margaret McCormick; Koirobi Haldar; Tatiana Kebadze; Annelyse Duvoix; Kerstin Lindblad; Hemu Patel; Paul Rugman; Paul Dodson; Martin Jenkins; Michael Saunders; Paul Newbold; Ruth H Green; Per Venge; David A Lomas; Michael R Barer; Sebastian L Johnston; Ian D Pavord; Christopher E Brightling Journal: Am J Respir Crit Care Med Date: 2011-09-15 Impact factor: 21.405
Authors: Ian D Pavord; Stephanie Korn; Peter Howarth; Eugene R Bleecker; Roland Buhl; Oliver N Keene; Hector Ortega; Pascal Chanez Journal: Lancet Date: 2012-08-18 Impact factor: 79.321
Authors: Dave Singh; Mona Bafadhel; Christopher E Brightling; Frank C Sciurba; Jeffrey L Curtis; Fernando J Martinez; Cara B Pasquale; Debora D Merrill; Norbert Metzdorf; Stefano Petruzzelli; Ruth Tal-Singer; Christopher Compton; Stephen Rennard; Ubaldo J Martin Journal: Am J Respir Crit Care Med Date: 2020-03-18 Impact factor: 21.405
Authors: Aleksandra Rybka-Fraczek; Marta Dabrowska; Elzbieta M Grabczak; Katarzyna Bialek-Gosk; Karolina Klimowicz; Olga Truba; Patrycja Nejman-Gryz; Magdalena Paplinska-Goryca; Rafal Krenke Journal: J Inflamm Res Date: 2022-01-26