Closing the Evidence Gap in Interstitial Lung Disease. The Promise of Real-World Data

Walking the path of treatable traits in interstitial lung diseases

Interstitial lung diseases (ILDs) are complex and heterogeneous diseases. The use of traditional diagnostic classification in ILD can lead to suboptimal management, which is worsened by not considering the molecular pathways, biological complexity, and disease phenotypes. The identification of specific "treatable traits" in ILDs, which are clinically relevant and modifiable disease characteristics, may improve patient's outcomes. Treatable traits in ILDs may be classified into four different domains (pulmonary, aetiological, comorbidities, and lifestyle), which will facilitate identification of related assessment tools, treatment options, and expected benefits. A multidisciplinary care team model is a potential way to implement a "treatable traits" strategy into clinical practice with the aim of improving patients' outcomes. Multidisciplinary models of care, international registries, and the use of artificial intelligence may facilitate the implementation of the "treatable traits" approach into clinical practice. Prospective studies are needed to test potential therapies for a variety of treatable traits to further advance care of patients with ILD.

Digital outcome measures in pulmonary clinical trials

PURPOSE OF REVIEW

We highlight recent advances in the development and use of digital outcome measures in clinical trials, focusing on how to select the appropriate technology, use digital data to define trial endpoints, and glean important lessons from current experiences with digital outcome measures in pulmonary medicine.

RECENT FINDINGS

A review of emerging literature demonstrates that the use of digital health technologies, particularly pulse oximeters, remote spirometers, accelerometers, and Electronic Patient-Reported Outcomes, has surged in both pulmonary practice and clinical trials. Lessons learned from their use can help researchers to design the next generation of clinical trials leveraging digital outcomes to improve health.

SUMMARY

In pulmonary diseases, digital health technologies provide validated, reliable, and usable data on patients in real-world environments. More broadly, digital endpoints have accelerated innovation in clinical trial design, improved clinical trial efficiency, and centered patients. As investigators adopt digital health technologies, it is important to follow a framework informed by both the opportunities and challenges of digitization. Successful use of digital health technologies will transform clinical trials by improving accessibility, efficiency, patient-centricity, and expanding opportunities for personalized medicine.

Looking Ahead: Interstitial Lung Disease Diagnosis and Management in 2030

Important advancements have been made in interstitial lung disease (ILD) in recent years, with improved understanding of risk factors, disease pathogenesis, and clinical care. This article summarizes the current and future state of ILD management, with proposed short-term initiatives for immediate action, and longer-term objectives for innovation and discovery.

Australasian interstitial lung disease registry (AILDR): objectives, design and rationale of a bi-national prospective database

Background

Interstitial Lung Disease (ILD) is a group of respiratory conditions affecting the lung interstitium often associated with progressive respiratory failure. There is increasing recognition of the need for improved epidemiological data to help determine best practice and improve standardisation of care. The Australasian ILD Registry (AILDR) is a bi-national registry of patients with all ILD subtypes designed to establish a clinically meaningful database reflecting real world practice in Australasia with an objective to improve diagnostic and treatment pathways through research and collaboration.

Methods

AILDR is a prospective observational registry recruiting patients attending ILD clinics at centres around Australia and New Zealand. Core and non-core data are stored on a secure server. The pilot phase was launched in 2016 consisting of four sites in Australia. Currently in its second phase a further 16 sites have been recruited, including three in New Zealand.

Results

A total of 1061 participants were consented during the pilot phase. Baseline data demonstrated a mean age 68.3 ± 12.5 (SD) years, mean FVC (%predicted) 79.1 ± 20.4 (SD), mean DLCO (%predicted) 58.5 ± 17.9 (SD) and nadir exertional SpO2 (%) 91 ± 6.9 (SD). Idiopathic pulmonary fibrosis (31%) and connective-tissue disease related ILD (21.7%) were the two most common subtypes. Baseline demographics and physiology were not significantly different across the four centres.

Conclusion

AILDR is an important clinical and research tool providing a platform for epidemiological data that will prove essential in promoting understanding of a rare cohort of lung disease and provide foundations for our aspiration to standardise investigation and treatment pathways of ILD across Australasia.

[Respiratory Disease in the Era of Big Data]

One of the key elements of medicine in the second decade of the 21st century is the exponential growth of patient-produced information, due not only to the transition to the digitization of medical records, but also to the emergence of new sources of information and the capacity for analysis and interpretation of existing ones. The amount of medical information is expected to double every 2 years, which means that there will be 50 times more information available in 2020 than in 2011. In this setting, these large amounts of data or «big data» must be properly managed to implement new initiatives that improve the diagnosis, treatment, and prognosis of patients on the path to personalized medicine.The concept of personalization or precision medicine is of special interest in chronic respiratory disease. In recent years, research in entities such as asthma, COPD, cancer, or SAHS has focused on the identification of genomic, molecular, metabolic, and protein changes (biomarkers). Big data analysis tools can be used to move on from models based on the mean response to treatment, which are suboptimal for most patients, to focus on the individualized response. Part of this journey involves systems medicine, which also integrates clinical and population data to provide a multidimensional view of the disease and help identify causal associations that are usually only evident on big data analysis.

Corticosteroid use is not associated with improved outcomes in acute exacerbation of IPF

BACKGROUND AND OBJECTIVE

AE-IPF has profound prognostic implications, preceding approximately half of all IPF-related deaths. Despite this clinical significance, there are limited data to guide management decisions. Corticosteroids remain the mainstay of treatment despite a lack of strong supporting evidence and mounting concern that they may be harmful. We assessed the impact of corticosteroid therapy on in-hospital mortality in AE-IPF patients.

METHODS

AE-IPF subjects were retrospectively identified in the UCSF medical centre's electronic health records from 1 January 2010 to 1 August 2018 using a code-based algorithm followed by case validation. The relationship between corticosteroid treatment and in-hospital mortality was assessed using a Cox model and a propensity score to control for confounding by indication. Secondary outcomes included hospital readmissions and overall survival.

RESULTS

In total, 82 AE-IPF subjects were identified, of whom 37 patients (45%) received corticosteroids. AE-IPF subjects treated with corticosteroids were more likely to require ICU level care and mechanical ventilation. There was no statistically significant association between corticosteroid treatment and in-hospital mortality (propensity score weighted, adjusted HR: 1.31; 95% CI: 0.26-6.55; P = 0.74). Overall survival was reduced in AE-IPF subjects receiving corticosteroids (HR: 6.17; 95% CI: 1.35-28.14; P = 0.019).

CONCLUSION

Our study found no evidence that corticosteroid use improves outcomes in IPF patients admitted to the hospital with acute exacerbation. Furthermore, corticosteroid use may contribute to reduced overall survival following an exacerbation. Observational cohort studies using larger real-world cohorts can more definitively assess the relationship between corticosteroid treatment and short-term outcomes in AE-IPF.