Emerging biomarkers and innovative tools for early and accurate diagnosis of PPF: Challenges and controversies

04 Oct 2023

In the ERS Congress 2023, Dr. Anna Podolanczuk from Weill Cornel Medical College of Cornell University, the United States (US), discussed the importance of early and accurate diagnosis of progressive pulmonary fibrosis (PPF), how to minimize time to diagnosis, as well as the existing and evolving diagnostic tools.1

Patients with progressive fibrotic interstitial lung diseases (ILD), specifically PPF, often grapple with uncertainty and anxiety about their future, hence, it is important for early and accurate diagnosis of PPF.1 Currently, treatments such as antifibrotic therapy reduce forced volume capacity (FVC) decline in patients with progressive fibrotic ILD, but do not reverse it.1 A trial showed that patients in the placebo arm lost almost 200mL in lung function for 52 weeks, showing that delaying antifibrotic therapy until the end of the 52 weeks can result in lower lung function with potentially more symptoms and a worse prognosis for patients.1

The International Clinical Practice guideline first defined PPF as the presence of at least two of the following criteria that occurred over the past year in patients with ILD, lung scarring other than IPF and no other explanation.1 These criteria include worsening respiratory symptoms, disease progression defined as the decline in FVC of ≥5% or a decline in diffusing capacity of the lungs for carbon monoxide (DLCO) of ≥10% and worsening fibrotic features on computed tomography (CT) scan.1 However, the issue with this definition is that for patients with IPF based on the CT scan, antifibrotic therapy will be started.1 While for patients with an identical CT scan and have rheumatoid arthritis (RA) with ILD, it is recommended to wait for potentially ≥1 year to start antifibrotic therapy due to the inability to predict the rate of progression and if that patient is going to develop PPF.1

The time to diagnosis of PPF can be improved by detecting an unusual interstitial pneumonia (UIP) pattern on biopsy or imaging, which predicts poor outcomes regardless of the ILD type.1 Hence, the identification of a UIP pattern earlier allows patients to benefit from earlier treatment.1 In cases where patients are unfit for these procedures or when there is uncertainty in the CT scan, a molecular classifier, such as the Envisia classifier, can detect a UIP pattern by identifying gene expression patterns on transbronchial lung biopsy sample.1

For blood biomarkers, multiple studies have shown a correlation between high peripheral blood monocyte count (>950/µL and in some cases >600/µL) and an increased risk of death and FVC decline in fibrotic ILD.1 Another relevant biomarker is the telomere length, with a short telomere length (<10th percentile) associated with a faster FVC decline and poor transplant-free survival.1 Evolving biomarkers include robust proteomic patterns, such as nonspecific interstitial pneumonia (NSIP), UIP, and other CT patterns that can identify patients who may benefit from earlier treatment.1 A total of 12 viable biomarker signatures were identified and are predictive of outcomes, regardless of the underlying pattern.1 Non-blood biomarkers include home spirometry, which may be a useful digital biomarker allowing patients to monitor their FVC more frequently.1 It is currently being tested using a clinical trial to validate it as a predictor of outcomes.1

In addition, the utilization of artificial intelligence (AI) and quantitative CT  has been steadily growing.1 These advanced techniques are utilized to identify patterns that can quantify fibrosis which correlates strongly with FVC decline and is being used to measure disease extent and predict patterns associated with disease progression.1 Similarly, deep learning-based outcome prediction may improve diagnostic accuracy.1 Some novel imaging tools are in the early phases of development and appear to be promising in detecting disease progression and treatment response.1

In summary, the early identification of patients at risk of developing symptoms and experiencing mortality is crucial.1 It is imperative to promptly and accurately diagnose and treat PPF.1 Molecular characterization of progressive fibrotic ILDs, elevated peripheral monocytes, and telomere length may provide risk stratification and detection of poor outcomes.1 Additionally, novel imaging techniques and proteomic signature are promising tools to identify patients with PPF at the time of diagnosis of their underlying ILD.1

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