Nebulised interferon beta-1a (SNG001) in the treatment of viral exacerbations of COPD.

BACKGROUND: Respiratory viral infections are major drivers of chronic obstructive pulmonary disease (COPD) exacerbations. Interferon-ß is naturally produced in response to viral infection, limiting replication. This exploratory study aimed to demonstrate proof-of-mechanism, and evaluate the efficacy and safety of inhaled recombinant interferon-ß1a (SNG001) in COPD. Part 1 assessed the effects of SNG001 on induced sputum antiviral interferon-stimulated gene expression, sputum differential cell count, and respiratory function. Part 2 compared SNG001 and placebo on clinical efficacy, sputum and serum biomarkers, and viral clearance. METHODS: In Part 1, patients (N = 13) with stable COPD were randomised 4:1 to SNG001 or placebo once-daily for three days. In Part 2, patients (N = 109) with worsening symptoms and a positive respiratory viral test were randomised 1:1 to SNG001 or placebo once-daily for 14 days in two Groups: A (no moderate exacerbation); B (moderate COPD exacerbation [i.e., acute worsening of respiratory symptoms treated with antibiotics and/or oral corticosteroids]). RESULTS: In Part 1, SNG001 upregulated sputum interferon gene expression. In Part 2, there were minimal SNG001-placebo differences in the efficacy endpoints; however, whereas gene expression was initially upregulated by viral infection, then declined on placebo, levels were maintained with SNG001. Furthermore, the proportion of patients with detectable rhinovirus (the most common virus) on Day 7 was lower with SNG001. In Group B, serum C-reactive protein and the proportion of patients with purulent sputum increased with placebo (suggesting bacterial infection), but not with SNG001. The overall adverse event incidence was similar with both treatments. CONCLUSIONS: Overall, SNG001 was well-tolerated in patients with COPD, and upregulated lung antiviral defences to accelerate viral clearance. These findings warrant further investigation in a larger study. TRIAL REGISTRATION: EU clinical trials register (2017-003679-75), 6 October 2017.

Predicting the risk of chest radiograph abnormality 12-weeks post hospitalisation with SARS CoV-2 PCR confirmed COVID-19.

BACKGROUND: Routine follow-up of patients hospitalised with COVID-19 is recommended, however due to the ongoing high number of infections this is not without significant health resource and economic burden. In a previous study we investigated the prevalence of, and risk factors for, persistent chest radiograph (CXR) abnormalities post-hospitalisation with COVID-19 and identified a 5-point composite score that strongly predicted risk of persistent CXR abnormality at 12-weeks. Here we sought to validate and refine our findings in an independent cohort of patients. METHODOLOGY: A single-centre prospective study of consecutive patients attending a virtual post-hospitalisation COVID-19 clinic and CXR as part of their standard clinical care between 2nd March - 22nd June 2021. Inpatient and follow-up CXRs were scored by the assessing clinician for extent of pulmonary infiltrates (0-4 in each lung) with complete resolution defined as a follow-up score of zero. RESULTS: 182 consecutive patients were identified of which 31% had persistent CXR abnormality at 12-weeks. Patients with persistent CXR abnormality were significantly older (p < 0.001), had a longer hospital length of stay (p = 0.005), and had a higher incidence of both level 2 or 3 facility admission (level 2/3 care) (p = 0.003) and ever-smoking history (p = 0.038). Testing our composite score in the present cohort we found it predicted persistent CXR abnormality with reasonable accuracy (area under the receiver operator curve [AUROC 0.64]). Refining this score replacing obesity with Age ≥ 50 years, we identify the SHADE-750 score (1-point each for; Smoking history, Higher-level care (level 2/3 admission), Age ≥ 50 years, Duration of admission ≥ 15 days and Enzyme-lactate dehydrogenase (LDH ≥ 750U/L), that accurately predicted risk of persistent CXR abnormality, both in the present cohort (AUROC 0.73) and when retrospectively applied to our 1st cohort (AUROC 0.79). Applied to both cohorts combined (n = 213) it again performed strongly (AUROC 0.75) with all patients with a score of zero (n = 18) having complete CXR resolution at 12-weeks. CONCLUSIONS: In two independent cohorts of patients hospitalised with COVID-19, we identify a 5-point score which accurately predicts patients at risk of persistent CXR abnormality at 12-weeks. This tool could be used by clinicians to identify patients in which radiological follow-up may not be required.

Feasibility of home administration of nebulised interferon ß-1a (SNG001) for COVID-19: a remote study.

BACKGROUND: Effective therapeutics given early to high-risk ambulatory patients with coronavirus disease 2019 (COVID-19) could improve outcomes and reduce overall healthcare burden. However, conducting site visits in non-hospitalised patients, who should remain isolated, is problematic. AIM: To evaluate the feasibility of a purely remote (virtual) study in non-hospitalised patients with COVID-19; and the efficacy and safety of nebulised recombinant interferon-ß1a (SNG001) in this setting. DESIGN & SETTING: Randomised, double-blind, parallel-group study, which was conducted remotely. METHOD: Eligible patients aged ≥65 years (or ≥50 years with risk factors) with COVID-19 and not requiring hospital admission were recruited remotely. They were randomised to SNG001 or placebo once-daily via nebuliser for 14 days. The main outcomes were assessments of feasibility and safety, which were all conducted remotely. RESULTS: Of 114 patients treated, 111 (97.4%) completed 28 days of follow-up. Overall compliance to study medication was high, with ≥13 doses taken by 89.7% and 92.9% of treated patients in the placebo and SNG001 groups, respectively. Over the course of the study, only two patients were hospitalised, both in the placebo group; otherwise there were no notable differences between treatments for the efficacy parameters. No patients withdrew owing to an adverse event, and a similar proportion of patients experienced on-treatment adverse events in the two treatment groups (64.3% and 67.2% with SNG001 and placebo, respectively); most were mild or moderate and not treatment-related. CONCLUSION: This study demonstrated that it is feasible to conduct a purely virtual study in community-based patients with COVID-19, when the study included detailed daily assessments and with medication administered via nebuliser.

Prediction of Chronic Obstructive Pulmonary Disease Exacerbation Events by Using Patient Self-reported Data in a Digital Health App: Statistical Evaluation and Machine Learning Approach.

BACKGROUND: Self-reporting digital apps provide a way of remotely monitoring and managing patients with chronic conditions in the community. Leveraging the data collected by these apps in prognostic models could provide increased personalization of care and reduce the burden of care for people who live with chronic conditions. This study evaluated the predictive ability of prognostic models for the prediction of acute exacerbation events in people with chronic obstructive pulmonary disease by using data self-reported to a digital health app. OBJECTIVE: The aim of this study was to evaluate if data self-reported to a digital health app can be used to predict acute exacerbation events in the near future. METHODS: This is a retrospective study evaluating the use of symptom and chronic obstructive pulmonary disease assessment test data self-reported to a digital health app (myCOPD) in predicting acute exacerbation events. We include data from 2374 patients who made 68,139 self-reports. We evaluated the degree to which the different variables self-reported to the app are predictive of exacerbation events and developed both heuristic and machine learning models to predict whether the patient will report an exacerbation event within 3 days of self-reporting to the app. The model's predictive ability was evaluated based on self-reports from an independent set of patients. RESULTS: Users self-reported symptoms, and standard chronic obstructive pulmonary disease assessment tests displayed correlation with future exacerbation events. Both a baseline model (area under the receiver operating characteristic curve [AUROC] 0.655, 95% CI 0.689-0.676) and a machine learning model (AUROC 0.727, 95% CI 0.720-0.735) showed moderate ability in predicting exacerbation events, occurring within 3 days of a given self-report. Although the baseline model obtained a fixed sensitivity and specificity of 0.551 (95% CI 0.508-0.596) and 0.759 (95% CI 0.752-0.767) respectively, the sensitivity and specificity of the machine learning model can be tuned by dichotomizing the continuous predictions it provides with different thresholds. CONCLUSIONS: Data self-reported to health care apps designed to remotely monitor patients with chronic obstructive pulmonary disease can be used to predict acute exacerbation events with moderate performance. This could increase personalization of care by allowing preemptive action to be taken to mitigate the risk of future exacerbation events.