Abstract
PDE4 inhibition reduces sputum eosinophils in those COPD patients with higher eosinophil counts. This evidence supports an effect of PDE4 inhibitors on eosinophilic inflammation. https://bit.ly/3airXw7
To the Editor:
Patients with COPD who have higher eosinophil numbers in the airways and peripheral blood demonstrate a greater clinical response to inhaled corticosteroids (ICS) [1–3]. Furthermore, the effect of the oral phosphodiesterase-4 (PDE4) inhibitor roflumilast on exacerbations in severe COPD patients with chronic bronchitis, who are treated with ICS and long-acting bronchodilators, also appears to be greater at higher blood eosinophil counts [4]. The mechanisms responsible for these differential drug effects remain to be defined, but may relate to increased type-2 inflammation and/or decreased presence of colonising airway bacteria in COPD patients with more eosinophils [5, 6], leading to different responses to anti-inflammatory drugs. An association between blood and sputum eosinophils has been observed in some, but not all studies [7–12]. Accurate sputum eosinophil count measurement requires good quality samples to make cytospins where eosinophils can be clearly counted; variable quality of sputum samples, particularly in multicentre studies, will affect the ability to show a relationship with blood eosinophil counts.
CHF6001 is an inhaled PDE4 inhibitor which showed anti-inflammatory effects in the airways after 32 days of treatment in COPD patients with chronic bronchitis on top of triple therapy [13]. In sputum, CHF6001 reduced the levels of certain cytokines and down-regulated inflammatory genes associated with eosinophil activation [14]. Previous studies with roflumilast showed inhibition of the total number of inflammatory cells in sputum, and inhibition of sputum eosinophil counts accompanied by a reduction in bronchial mucosal eosinophil numbers [8, 15]. We performed a post hoc analysis of the CHF6001 biomarker study [13] with two aims: 1) to investigate whether CHF6001 suppressed sputum eosinophil counts in those COPD patients with greater eosinophilic inflammation; and 2) to investigate the relationship between blood and sputum eosinophils, as divergent results have been published on this topic.
Samples were collected from a multicentre, three-way, placebo-controlled, double-blind crossover study which has been previously reported [13]. Patients received 32 days of treatment with CHF6001, 800 or 1600 μg twice daily, or matching placebo via a dry powder inhaler (NEXThaler). Eligibility criteria were post-bronchodilator ratio of forced expiratory volume in 1 s (FEV1) to forced vital capacity ratio <0.70 and FEV1 30–70% predicted, a history of chronic bronchitis and treatment with inhaled ICS/long-acting β-agonist/long acting muscarinic antagonist therapy for at least 2 months prior to enrolment. The study was approved by independent ethics committees for each institution. All patients provided written informed consent prior to study start. Induced sputum samples had to have a viability factor of at least 70% and epithelial cells lower than 30%. In this post hoc analysis, patients were stratified into two subgroups using a baseline (screening visit) sputum eosinophil threshold of 3%, i.e. “eosinophilhigh” (≥3%) and “eosinophillow” (<3%). The differential treatment response in these subgroups, measured as change from baseline of % sputum eosinophils to the end of the treatment period (with the latter expressed as an average of days 20, 26 and 32 assessed at 2 h after the morning dose) was evaluated using an ANCOVA model with subgroup, subject within subgroup, period, treatment, treatment-by-subgroup interaction and baseline value as independent variables. The same model was used to evaluate a potential effect of other relevant subgroups (gender or smoking status) on sputum eosinophils per cent change from baseline. In the receiver operating characteristic (ROC) curves analysis, the sensitivity was plotted as a function of 100-specificity to test the performances of per cent and absolute blood eosinophils to predict the two groups of patients. The maximum value of the Youden-index (J = sensitivity + specificity-1) was used to identify the optimum cut-off point for the diagnostic tests.
All randomised patients (n=61; mean age 66 years; 43 males; 34 current smokers) were included in the analysis. Mean±sd post-bronchodilator predicted FEV1 was 50.2±11.8% and COPD Assessment Test score was 20.7±5.8. The mean±sd baseline blood eosinophil count was 252±144 cells·µL−1 or 3.3±2.0%. Mean±sd and median (interquartile range) sputum count was 3.6±4.3% and 2% (2.9%) for eosinophils and 82.7±9.5% and 82.8% (16.9%) for neutrophils, respectively. 20 patients (33%) were eosinophilhigh; sputum mean±sd eosinophils was 0.292±0.336×106 g−1 or 8.4±4.5%. 41 patients (67%) were eosinophillow; sputum mean±sd eosinophils was 0.069±0.093×106 g−1 or 1.3±0.8%. Eosinophilhigh in comparison to eosinophillow patients were characterised by a higher proportion of males (80% versus 66%) and ex-smokers (70% versus 32%).
A significant effect of the eosinophilhigh/low groups (p<0.01) but not of gender or smoking status was observed on sputum eosinophils per cent change from baseline. In the eosinophilhigh group, both CHF6001 doses significantly reduced the percentage of sputum eosinophils over placebo: 95% CI −3.09 to −0.58 for CHF6001 800 µg twice daily, and −2.71 to −0.25 for CHF6001 1600 µg twice daily (change from baseline estimates for placebo, CHF6001 800 µg twice daily and 1600 µg twice daily were 1.69, −0.15 and 0.21, respectively). In the eosinophillow group, the effect of CHF6001 on the percentage of eosinophils was less pronounced, and hence not statistically significant: 95% CI −1.41 to 0.47 for CHF6001 800 µg twice daily, and −1.27 to 0.60 for CHF6001 1600 µg twice daily) (figure 1a).
a) Effect of CHF6001 (800 ug and 1600 ug twice daily) over placebo on sputum eosinophil per cent levels in eosinophilhigh and eosinophillow patients. b) Correlation between blood absolute and percentage sputum eosinophil values with regression line and 95% confidence intervals. Receiver operating characteristic (ROC) area under the curve (AUC) analysis of sensitivity and specificity of c) per cent and d) absolute blood eosinophil count to predict eosinophilhigh and eosinophillow patients, with the corresponding 95% confidence intervals.
Eosinophilhigh patients had higher mean±sd absolute and per cent count in blood compared to eosinophillow; 350±172 cells·µL−1 or 4.7±2.0% versus 204±101 cells·µL−1 or 2.6±1.6% (t-test p≤0.0001). Furthermore, there was a moderate correlation between per cent sputum and per cent blood eosinophils (Pearson r=0.46, p=0.0002) and between per cent sputum and absolute blood eosinophils (Pearson r=0.54, p<0.0001) (figure 1b). ROC curves analysis (figure 1c and d) showed that both per cent and absolute blood eosinophils are good predictors of per cent eosinophils levels in sputum. Specifically, per cent and absolute blood eosinophils were able to predict eosinophilhigh and eosinophillow patients with ROC areas under the curve (AUCs) of 0.82 and 0.79, respectively (p<0.001). For per cent blood eosinophils, a threshold of 2.8% showed a sensitivity of 90% and a specificity of 66%. For absolute blood eosinophils, the optimal threshold was identified at 257 cells·µL−1, showing a sensitivity of 75% and a specificity of 78%.
This clinical trial employed highly standardised conditions of sputum collection, processing and centralised reading, leading to a median viability of 92% and very low contamination by epithelial squamous cells (median 1.3%). Additionally, all the patients had chronic bronchitis, making the acquisition of sputum samples easier. In these circumstances, we were able to demonstrate an association between blood and sputum eosinophil counts, and good predictive performance for blood eosinophil counts to predict sputum eosinophilia. Larger multicentre studies can suffer with practical difficulties in obtaining sufficient evaluable samples [9], likely due to a combination of patient factors and variations in laboratory expertise. Nevertheless, it has been reported that blood absolute and per cent eosinophil counts can identify sputum counts ≥3% with ROC-AUCs ranging from 0.75 to 0.8 [7, 12]. In our study, thresholds in blood of 257 cells·µL−1 and 2.8% predicted sputum eosinophils ≥3% in approximately 75% and 90% of patients, respectively, with diagnostic performances (ROC-AUC) of 0.79–0.82.
The ability of CHF6001 to reduce sputum eosinophil counts appears most relevant to individuals with higher eosinophils. Although this effect could be driven by the higher eosinophil levels at baseline, our data are compatible with the reduction of sputum and bronchial mucosal eosinophils by roflumilast [8]. A post hoc analysis showed that higher blood eosinophil counts predict a greater effect of roflumilast on exacerbations [4]. These previous results, coupled with our current data, indicate an effect of PDE4 inhibitors on eosinophilic inflammation in COPD patients. The good predictivity of blood eosinophils to identify sputum eosinophilia suggests promise for this blood biomarker as a predictive marker of response to PDE4 inhibitors in COPD patients with chronic bronchitis already being treated with triple therapy.
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Acknowledgements
The authors would like to thank the investigators and patients at the investigative sites for their support of this study.
Footnotes
This study is registered with ClinicalTrials.gov identifier: NCT03004417; and EudraCT number: 2015-005550-35. Chiesi commits to data sharing with qualified scientific and medical researchers conducting legitimate research, patient-level data, study-level data, the clinical protocol and the full clinical study report of Chiesi Farmaceutici S.p.A.-sponsored interventional clinical trials in patients for medicines and indications approved by the European Medicines Agency and/or the US Food and Drug Administration after 1 January 2015, following the approval of any received research proposal and the signature of a data sharing agreement. Chiesi provides access to clinical trial information consistently with the principle of safeguarding commercially confidential information and patient privacy. To date, the current study is out of scope of the Chiesi policy on clinical data sharing. Other information on Chiesi's data sharing commitment, access and research request approval process are available in the Clinical Trial Transparency section of www.chiesi.com/en/research-and-development/
Author contributions: The study was conceived by D. Singh and M. Govoni. D. Singh, H. Watz, K.M. Beeh, O. Kornmann, B. Leaker and B. Colgan contributed to data acquisition. Data were analysed by M. Govoni, D. Balzano and D. Santoro. All authors interpreted the data and revised the manuscript for intellectual content and approved the submitted version.
Conflict of interest: D. Singh reports received personal fees from Chiesi during the conduct of this study; outside the submitted work, he reports grants and personal fees from AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline, Glenmark, Menarini, Mundipharma, Novartis, Pfizer, Pulmatrix, Therevance, and Verona, and personal fees from Cipla, Genentech and Peptinnovate.
Conflict of interest: H. Watz reports personal fees from Chiesi during the conduct of the study; outside the submitted work, he reports personal fees from Bayer, GSK, Boehringer Ingelheim, Novartis, AstraZeneca, BerlinChemie and Roche.
Conflict of interest: K.M. Beeh declares that no personal payments were received from any pharmaceutical entity in the past 5 years; and is a full time employee of insaf Respiratory Research Institute, which has received compensation for services on advisory boards or consulting for Ablynx, Almirall, AstraZeneca, Berlin Chemie, Boehringer, Chiesi, Cytos, Mundipharma, Novartis, Pohl Boskamp and Zentiva; the institution has received compensation for speaker activities in scientific meetings supported by Almirall, AstraZeneca, Berlin Chemie, Boehringer, Cytos, ERT, GSK, Novartis, Pfizer, Pohl Boskamp and Takeda; the institution has further received compensation for design and performance of clinical trials from Almirall, Altana/Nycomed, AstraZeneca, Boehringer, Cytos, GSK, Infinity, Medapharma, MSD, Mundipharma, Novartis, Parexel, Pearl Therapeutics, Pfizer, Revotar, Teva, Sterna and Zentiva.
Conflict of interest: O. Kornmann received fees paid to his institution from Chiesi for conducting this study; and reports personal fees as speaker or advisory board member from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Sanofi and Novartis.
Conflict of interest: B. Leaker has nothing to disclose.
Conflict of interest: B. Colgan has nothing to disclose.
Conflict of interest: G. Lucci is an employee of Chiesi, the sponsor of the trial.
Conflict of interest: A. Emirova is an employee of Chiesi, the sponsor of the trial.
Conflict of interest: M.A. Nandeuil is an employee of Chiesi, the sponsor of the trial.
Conflict of interest: D. Santoro is an employee of Chiesi, the sponsor of the trial.
Conflict of interest: D. Balzano is an employee of Chiesi, the sponsor of the trial.
Conflict of interest: M. Govoni is an employee of Chiesi, the sponsor of the trial.
Support statement: This study was funded by Chiesi Farmaceutici S.p.A. Chiesi Farmaceutici S.p.A. was responsible for the design and analysis of the study, oversaw its conduct and was responsible for study report preparation. Dave Singh is supported by the National Institute for Health Research (NIHR) Manchester Biomedical Research Centre (BRC). Funding information for this article has been deposited with the Crossref Funder Registry.
- Received February 4, 2020.
- Accepted March 19, 2020.
- Copyright ©ERS 2020
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