Approach to Clinical Trials for the Prevention of Pulmonary Fibrosis

Interstitial lung disease (ILD) refers to a group of disorders of the lung parenchyma that are characterized by inflammation, cellular proliferation, and/or fibrosis predominantly involving the alveolar interstitium. Many ILDs are detected after years of nonspecific and insidiously progressive symptoms, resulting in moderately advanced fibrosis at the time of diagnosis (1, 2). Current pharmacologic therapies aim to slow lung function decline. They do not improve symptoms and carry significant side effects (3–5). There is an urgent need for better disease-modifying treatments that improve clinical outcomes at all stages of disease.

There is growing interest in identifying individuals before or at the earliest stages of onset of pulmonary fibrosis (Figure 1). The optimal management of these individuals, including appropriate monitoring and treatment to prevent disease progression, is presently unknown and requires clinical trials. The goals of this review are to: 1) summarize methods to identify the target population for a preventive clinical trial, 2) propose a framework for an approach to a clinical trial that tests therapeutic interventions to attenuate the risk of progression to clinical disease, and 3) outline gaps that need to be addressed to accomplish such a trial.

Figure 1.

Clinical trajectory of adults with pulmonary fibrosis over time.

Methods to Identify Trial Participants

The target population for a potential clinical trial for the prevention of pulmonary fibrosis is individuals without clinically overt disease who are at increased risk for the development of fibrotic ILD. In this review, we use the broad term “at-risk individuals” to refer to this group, which includes adults who have preclinical imaging findings and/or a genetic predisposition to ILD but not those with undiagnosed ILD. Here we describe potential methods to identify this target population. We do not specifically address approaches to the prevention of ILD in patients with systemic autoimmune diseases like rheumatoid arthritis and systemic sclerosis even though they are also at risk for the development of fibrotic ILD. Preventive clinical trials in this population require a thorough and nuanced discussion of unique determinants of risk and the potential role of immunomodulating therapies, which is beyond the scope of this document.

Interstitial Lung Abnormalities

The most studied and clinically accessible method to identify at-risk individuals is the visual detection of interstitial lung abnormalities (ILAs) on chest computed tomography (CT) (Table 1) (6). These have been extensively described and examined in various research and clinical cohorts and are associated with all-cause mortality, respiratory-related mortality, and worse lung function (7, 8). Importantly, ILAs are associated with genetic factors known to increase susceptibility for fibrotic ILD and have histopathologic correlates that overlap with findings seen in surgical lung biopsies of patients with ILD (i.e., microscopic honeycombing, fibroblastic foci) (9–12).

Table 1.

Methods to identify at-risk individuals for pulmonary fibrosis

Method	Example	Description
Radiology	•Interstitial lung abnormalities (ILA) •Data-driven textural analysis (DTA) •High attenuation areas (HAA) •Normal-high attenuation (NormHA) •Quantitative interstitial lung abnormality (QIA)	•Visually detected non-dependent abnormalities involving >5% of a lung zone (6–9) •Automated approach that employs convolutional neural network architectures to classify image regions from HRCT as either normal or fibrotic, computing the percentage of total lung volume classified as fibrotic (87, 88) •Proportion of lung voxels with attenuation between −600 and −250 Hounsfield units (15, 19) •Densitometry with supervised machine learning to detect abnormal lung densities but visually normal-appearing lung tissue on CT (89) •Automated, machine learning–based approach to identifying parenchymal changes on CT (90, 91)
Genetics	•Family history of pulmonary fibrosis •Common variants (MUC5B, DSP) •Rare variants (PARN, RTEL1, TERC) •Polygenic risk scores	•ILA and preclinical pulmonary fibrosis is found in 19-31% of first degree relatives of patients with both familial and sporadic PF (10, 24, 27, 28) •MUC5B is strongly associated with higher risk of IPF and other ILD types and ILA (9, 34) •Significantly associated with higher risk and worse survival in fibrotic ILD (29) •Suggest unidentified genetic variants account for substantial risk for IPF and are associated with both risk of IPF and ILA (37, 38)
Blood biomarkers	•Telomere length •Absolute monocyte count •Matrix metalloproteinase-7 •Adhesion molecules •Growth differentiation factor 15 •Galectin-3	•Associated with more rapid disease progression (30) •Associated with disease severity and worse survival in IPF, and with ILA and its progression (92, 93). •Protease involved in degradation and remodeling of extracellular matrix and expressed in alveolar macrophages and epithelial cells (49, 94). •Mediates adhesion of cells to the endothelium; associated with worse survival in ILD, and with ILA/HAA (51, 94). Cell surface glycoprotein expressed in leukocytes, endothelial cells, alveolar macrophages and type II alveolar epithelial cells; elevated in the plasma of adults with IPF and associated with ILA and ILD-related hospitalization (51, 94) •Protein member of the transforming growth factor beta family that regulates processes related to apoptosis, cellular growth and repair, and is correlated with chronological age. Growth differentiation factor 15 is elevated in the blood and lungs of adults with IPF and strongly associated with ILA (53) •Beta-galactoside-binding lectin implicated in fibrogenesis and elevated in serum and bronchoalveolar lavage fluid in IPF (95, 96). Higher concentrations associated with ILA among community-dwelling adults (97).

Definition of abbreviations: HRCT=high-resolution CT scan; ILD=interstitial lung disease; ILA=interstitial lung abnormalities; IPF=idiopathic pulmonary fibrosis.

However, several key issues must be addressed when considering clinical trials for patients with ILA. First, the detection of ILAs is limited by heterogenous criteria for the definition and reporting of CT findings and the variability in CT protocols employed in prior studies and in clinical care, including low-dose and cardiac CT. The reproducibility of ILAs identified using these methods needs to be examined. Second, some ILAs may represent undiagnosed ILD (13). Individuals with ILAs should be evaluated for clinically established ILD per the 2020 Fleischner Society position paper, and those diagnosed with ILD should be excluded from trials focused on primary prevention (6, 14). Third, refinement and validation of risk-stratification methods to identify individuals with ILAs most likely to progress in the relative short term are needed. The prevalence of ILA in research cohorts of mostly older adults is 5–10%, but the estimated frequency of clinically established pulmonary fibrosis defined through administrative claims data is many times lower, suggesting that only a subset of ILAs progress to clinically significant disease (8, 15, 16). ILAs that are subpleural with evidence of fibrotic features (i.e., honeycombing, traction bronchiectasis) have a higher likelihood of progression and represent a potential high-risk subgroup that could be targeted in clinical trials (17). Tools that incorporate clinical information, genetics, blood biomarkers, and high-resolution and/or quantitative imaging modalities may enhance risk prediction and cohort selection in this patient population but require prospective validation (18).

Quantitative CT and Other Imaging Methods

The 2020 Fleischner Society position paper highlighted the need to further develop and validate quantitative CT methods (6). Here we focus on methods that have been used in populations without clinically overt ILD (Table 1). The simplest tools employ CT densitometry to identify early lung injury, remodeling, and fibrosis. However, densitometry relies solely on individual pixel intensities, resulting in poor specificity and potential variability due to factors like atelectasis and adiposity (15, 19). Methods that incorporate image texture, a quality formed by patterns in the spatial arrangement and intensity of voxels, can more specifically distinguish abnormal lung parenchyma (20). Deep learning provides an advance over engineered features in that model training simultaneously optimizes feature extraction and pattern classification so the most informative features for a given task are distilled from images without requiring assumptions by the algorithm designer (21). Data-driven textural analysis (DTA) is an example of a deep learning approach that can detect and quantify features suggestive of fibrosis (22). In first-degree relatives of patients with pulmonary fibrosis, higher DTA scores were associated with a higher breathlessness score, reclassified 17% of subjects as having fibrosis, and were associated with progression of ILA (23, 24). However, a lack of standardization of CT protocols and analysis methods limit the widespread adoption of quantitative CT at this point, and independent validation through collaborative efforts among cohorts with substantial CT imaging data is needed (25).

Genetics

A family history of ILD is a strong risk factor for pulmonary fibrosis, and studies of first-degree relatives of patients with ILD show a high prevalence of radiologic abnormalities, making this a key target population for preventive studies (10, 26–28). Rare genetic variants that confer a high risk of pulmonary fibrosis among carriers have been identified in familial cohorts, many of them implicated in telomere maintenance (e.g., PARN, RTEL1, and TERC) (29). Telomere shortening in itself is associated with higher risks of ILA, idiopathic pulmonary fibrosis (IPF), and other ILDs, as well as more rapid disease progression, supporting its utility as a potential blood biomarker for at-risk individuals (24, 30–33). The MUC5B gene promoter polymorphism (rs35705950, G→T) is a common variant that has a carrier frequency of approximately 18–20% among non-Hispanic White individuals of European ancestry in the general population and is strongly associated with an increased risk of IPF and other ILD types, as well as ILA, particularly subpleural and fibrotic subtypes (34–36). Genome-wide association studies have identified multiple common variants associated with ILA, many overlapping with those identified in adults with IPF (e.g., MUC5B, DSP) (12). Polygenic risk scores that account for common and rare variant effects may have utility in risk stratification (37, 38).

Challenges to using genetic and genomic markers for cohort selection include ethical, legal, and social implications of genetic screening and limited access due to cost and lack of insurance reimbursement. However, genetic testing of patients and relatives has been more widely accepted in other conditions that have moved toward personalized precision-based care, such as cancer (39). The feasibility of using genetic testing for cohort selection in IPF has been demonstrated in the ongoing PRECISIONS (Prospective Treatment Efficacy in IPF Using Genotype for NAC Selection) clinical trial (40). Second, racial and ethnic diversity has been lacking in ILD studies and has been particularly absent in genetic studies, resulting in an incomplete understanding of susceptibility (41, 42). The overwhelming majority of studies have been restricted to non-Hispanic White individuals of European ancestry despite health disparities disproportionately impacting clinical outcomes of individuals from other racial and/or ethnic groups (43). This has potential implications in that underrepresented groups may end up excluded from clinical trials designed for cohort enrichment based on genetic variants. However, recent studies show that including genomic biomarkers from diverse populations is feasible and could enhance our understanding of their prognostic value across different ancestries (44). For instance, transethnic and multiethnic approaches to genetic and multi-omics studies of hypertension and hematological traits have identified novel variants related to risk and prognosis (45, 46). Recent multiethnic genetic studies have discovered unreported loci associated with pulmonary function and chronic obstructive pulmonary disease in population-based and disease-enriched cohorts (47, 48). Such studies have benefited from collaborative efforts across countries with large and diverse cohorts and harmonized phenotyping. As our understanding of ILD advances, significant efforts are needed to pool diseased and population-based cohorts and accurately adjudicate the incidence and prevalence of ILD. To promote equity and improved accuracy, it is essential that future genetic studies deliberately focus on greater diversity. The inclusion of racial and ethnic minorities in trials that use a precision-medicine approach would help to mitigate current health disparities.

Peripheral Blood Biomarkers

Peripheral blood biomarkers that can reliably screen, diagnose, and prognosticate have been widely used to identify and risk-stratify individuals at risk for cardiovascular disease and other medical conditions. Aside from serological screening for autoimmune disease during the diagnostic evaluation, no biomarker has been widely adopted for clinical purposes in pulmonary fibrosis. With presumed overlap in pathological processes in early and established disease, some biomarkers that have been investigated in clinically overt disease may be useful to identify individuals at high risk for a fibrotic ILD (Table 1). The most well-studied of these is MMP-7 (matrix metalloproteinase-7), which is associated with worse outcomes in IPF, a greater burden of lung parenchymal changes on CT among persons at risk for familial pulmonary fibrosis (FPF), and lower forced vital capacity (FVC) and a higher risk of death in community-dwelling adults (10, 49, 50). Other candidate biomarkers include those related to aging (e.g., growth differentiation factor-15), host defense (peripheral blood monocyte count, galectin-3), and inflammation (vascular cell adhesion molecule-1) (51–53). None of these are specific enough to be used alone, but a recent proteomic analysis identified four to eight protein models that, in combination with demographic factors, were strongly predictive of ILA and ILA progression (18). The significant overlap of biomarkers among different ILD types suggests that they can be used to identify shared pathways underlying the pathogenesis of different fibrotic ILD subtypes (52).

Clinical and Other Risk Factors and Prediction Models

Older age and cigarette smoking are two of the strongest risk factors most consistently associated with a higher burden of early interstitial abnormalities on imaging and the progression of these abnormalities across multiple independent cohorts (7, 53). Other potential factors include air pollution, occupational exposure, and metabolic factors (24, 54–56). The relative contributions of each of these risk factors to the overall risk of ILD development is unknown. Higher chronological age and radiologic, genomic, and blood-based biomarkers, as well as comorbidities and harmful exposures, collectively point to an aging biology of the lungs underlying the development of ILD. A cumulative impairment of function at the organism to cellular levels may put an individual on a “runaway train” to pulmonary fibrosis (57, 58). The development and validation of markers that can capture early senescent changes in the lung are critical to facilitate clinical trial enrichment of at-risk individuals who may benefit the most from an intervention.

A risk prediction model that combines multiple factors to derive an index score that risk-stratifies individuals would facilitate screening recommendations and cohort selection for interventional trials, similar to a Framingham Risk Score for coronary heart disease (59). A major limitation has been the low disease incidence and lack of clinical outcome data in large research cohorts not specifically designed to study ILD. The most relevant outcome for prediction model development is one that captures characteristics related to fibrotic ILD, including the combination of physiologic decline (i.e., FVC and/or diffusing capacity for carbon monoxide), fibrotic imaging features, and signs and/or symptoms like cough, bibasilar crackles, and exercise capacity decline. Recent developments in technologies and software that can curate electronic health records, including the review of radiological reports, laboratory tests, and notes, make them appealing tools to aid with screening and cohort enrichment. Recent studies demonstrate the feasibility of using electronic health records to predict the future risk of IPF and identify patients with ILD for possible clinical trial enrollment (60, 61). An ongoing major barrier to using these tools is the absence of documentation of abnormalities, particularly with imaging reports. Future collaborative efforts that leverage population-based and other cohorts with detailed phenotypic data and a composite outcome of adjudicated pulmonary fibrosis diagnoses, lung function decline, and fibrotic imaging patterns are critical to allow for the derivation and validation of a risk prediction model.

Clinical Trial Efficacy Outcomes

Outcomes in clinical trials for patients with clinically diagnosed ILD traditionally consist of physiologic decline and/or clinical events (e.g., hospitalization and death) (3–5). The translatability of these same outcomes to trials for prevention depends on the clinical, genomic, and other risk profiles of the enrolled participants and the heterogeneity of the target population. Here we discuss potential outcomes that could be considered in clinical trials for the prevention of pulmonary fibrosis.

Incidence of Pulmonary Fibrosis

The most clinically relevant primary endpoint is the incidence of pulmonary fibrosis. Although this outcome is not feasible for trials that enroll a population with a low or heterogenous risk profile, it may be reasonable for a trial that recruits individuals selected for high risk. For example, among first-degree relatives of patients with FPF (whereby two or more family members are diagnosed with fibrotic ILD), 19% had incident ILD events over a period of 5 years, defined as extensive abnormalities on high-resolution CT (HRCT), a clinical diagnosis of ILD, or an increase in the semiquantitative extent of abnormalities on CT (24). The incidence of pulmonary fibrosis may be a reasonable outcome in such a cohort, especially with inclusion criteria that combine older age (>50 or >60 yr), high-risk radiologic features, and/or genetic risk. The challenge here lies in the lack of a clear definition for what constitutes disease, with radiologic progression by extent or development of fibrotic features used variably in different cohorts as proxies for incident ILD (13, 24, 28). Accordingly, in a different cohort of relatives of patients with IPF, the incidence of fibrotic ILD-like changes on CT (labeled preclinical pulmonary fibrosis) was 6% over an average of 4 years (or 1.6% per year) (28).

Physiologic and Functional Decline

At-risk individuals who already have radiologic abnormalities may be a potential group to enroll in a trial that uses spirometry-based endpoints. For instance, in a population-based cohort, individuals with progressive ILA had a mean FVC decrease of 64 ml/yr (62). The issue here is clearly defining what constitutes individuals at risk versus those with suspected early ILD, as it is the latter group that has been shown to have poor outcomes in population-based cohorts (13). Additionally, FVC decrease may follow distinct trajectories in different age groups and may be further impacted by concomitant radiological abnormalities like emphysema (63, 64). Changes in symptoms and quality of life are important patient-centered outcomes to include in clinical trials but have been challenging to accurately measure in studies of patients with clinically established disease (65). Typical symptoms tied to fibrotic ILD (e.g., dyspnea, cough) may be very minimal in at-risk individuals. Nineteen percent of FPF relatives had worsening dyspnea scores over a mean of 4 years of follow-up, although the incidence was much higher (38%) among those who also had radiologic abnormalities (28). Rigorous research and development of responsive instruments in this population are needed.

Potential Novel Tools to Assess Treatment Response

There has been ongoing interest in developing novel markers that are more directly related to early disease activity and progression. Potential imaging-based candidates are summarized in Table 2. CT-based measures that employ machine learning and textural analysis, such as DTA, the adaptive multiple features method, and Computer-Aided Lung Informatics for Pathology Evaluation and Ratings, are promising tools for detecting treatment response but lack standardization and prospective validation, which limits their utility. Building on technical advances that have improved lung parenchymal resolution and extraction of lung functional information, magnetic resonance imaging, positron emission tomography, and endobronchial optical coherence tomography have emerged as promising tools. These techniques, which include dynamic contrast-enhanced and hyperpolarized xenon 129 magnetic resonance imaging, can quantify ventilatory and perfusion-related changes that associate with disease severity or progression in pulmonary fibrosis (66–68). Positron emission tomography may be a noninvasive way to ascertain in vivo molecular changes with the use of probes that bind targets relevant to disease activity (e.g., αvβ6, chemokine receptor 2, and collagen) (69–71). Endobronchial optical coherence tomography can identify early microscopic features of ILDs without tissue biopsy by generating real-time three-dimensional imaging using endogenous tissue contrast, and may provide unique abilities to assess microscopic disease changes in response to therapy, including collagen remodeling changes (72–75).

Table 2.

Potential clinical trial endpoints

Endpoint	Advantages	Disadvantages
Clinical
Incidence of PF	•Most clinically relevant	•Long follow up time to reach endpoint may be needed •No consensus definition
Spirometry (FVC and DlCO)	•Validated surrogate marker of progression in IPF and other ILD •Accepted by the FDA as a primary endpoint in clinical trial enrolling patients with clinically overt disease	•Relevance as a markers of disease progression among at-risk individuals unknown •Rate of decline may be impacted by age and comorbid conditions (e.g., emphysema)
Imaging
Visual progression of ILA or fibrotic features on CT	•Clinically relevant and accessible •Fibrotic ILA is associated with poor outcomes and has strong validity as a marker of early ILD	•Lack of standard definition •Unclear if increased extent of abnormalities versus development of new fibrotic features (i.e., traction bronchiectasis, honeycombing) carry same prognostic implications •Poor interreader agreement
Quantitative CT	•Many platforms/algorithms (e.g., DTA, AMFM, HAA, QIA, CALIPER, QLF, others) •Automated, objective •Correlates with changes in markers of disease progression among individuals with clinically overt disease (e.g., FVC, DlCO, 6MWT, symptoms)	•Limited data on responsiveness to therapy and clinically relevant thresholds for change •Limited data for at-risk individuals, most studies performed in adults with clinically established IPF and other ILDs •Limited longitudinal data
MRI	•Several approaches (DCE, hyperpolarized 129Xe) may be useful in detecting microvascular alterations •Hyperpolarized 129Xe MRI provides information on ventilation, tissue microstructure, and gas exchange with high sensitivity and spatial resolution	•Has not been studied among at-risk individuals for PF •Access to equipment is limited to select specialized centers •Technically challenging to implement
PET	•Provides in vivo molecular information •Multiple probes can be developed depending on target of interest •Can detect increased collagen deposition in the lungs of adults with IPF in both regions of fibrotic and normal-appearing lung on CT •Proof-of-concept studies show changes in response to antifibrotic therapy	•Limited access •Technically challenging to implement
EB-OCT	•Minimally invasive bronchoscopic imaging modality that detects microscopic features of fibrotic interstitial lung disease and its changes over time	•Invasive •Access to equipment limited at few specialized centers •Requires skilled pathologist to interpret
Blood biomarkers
Protein	•Easy to collect •Individual biomarkers (MMP-7, SP-D, neoepitopes) can be cheap and easy to measure and have prognostic implications •Combinations of biomarkers and large proteomic platforms are becoming cheaper and easier to measure, yielding extensive data on biologic mechanisms	•Limited data on whether longitudinal changes in biomarkers correlate with disease progression among those with PF •None so far have demonstrated responsiveness to treatment •No prospective validation in individuals at risk
Gene expression	•Baseline gene expression profiles have been shown to be strongly predictive of disease progression and survival among adults with PF •Longitudinal changes in gene expression may correlate with disease progression •Provides insights into biologic activity	•Longitudinal gene-expression signature that captures early progression to PF has not been established •Difficult to implement and scale up to clinical practice

Definition of abbreviations: 6MWT = six-minute-walk test; ¹²⁹Xe = xenon 129; AMFM = adaptive multiple features method; CALIPER = Computer Aided Lung Informatics for Pathology Evaluation and Rating; CT = computed tomography; DCE = dynamic contrast enhanced; Dl_CO = diffusing capacity of the lung for carbon monoxide; DTA = deep textural analysis; EB-OCT = endobronchial optical coherence tomography; FDA = Food and Drug Administration; FVC = forced vital capacity; HAA = high attenuation area; ILA = interstitial lung abnormality; ILD = interstitial lung disease; IPF = idiopathic pulmonary fibrosis; MMP-7 = matrix metalloproteinase-7; MRI = magnetic resonance imaging; PET = positron emission tomography; PF = pulmonary fibrosis; QIA = quantitative interstitial lung abnormality; QLF = quantitative lung fibrosis; SP-D = surfactant protein-D.

Although there is limited evidence of candidate blood-based biomarkers that can capture biological progression over time to pulmonary fibrosis, there are studies in adults with clinically established disease that suggest this is plausible. Longitudinal changes in extracellular matrix neoepitopes and oncogenic-related proteins are associated with disease progression in IPF, with the former used as a primary endpoint in a nintedanib clinical trial (although the biomarkers evaluated were not responsive to treatment) (76). Longitudinal changes in peripheral gene expression may capture disease progression in adults with IPF and represent another potential method among adults at risk for fibrosis (77). The “ideal” clinical trial endpoint biomarker may differ based on the specific mechanism of action of the therapeutic intervention. For these novel candidate endpoints, it will be critical to determine the clinical relevance of incremental changes in these measures.

Composite Endpoint

Similar to recent ILD trials that have used composite endpoints combining physiologic and clinical events, integration of multiple endpoints may be a more powerful and efficient tool in trials that target at-risk individuals (78). For example, an endpoint that includes physiologic decline, development of signs and/or symptoms (i.e., crackles on examination, new-onset dyspnea or cough), and development of fibrotic features on HRCT suggests a trajectory toward clinically overt disease. We caution that this is speculative and would benefit from further validation studies to determine which of these components are most predictive of incident disease. Preventive trials should also collect data on medical resource use along with data on clinical outcomes to perform cost-effectiveness analyses, which would inform future guidelines for prevention and treatment.

Candidate Therapeutic Interventions

The ideal treatment in clinical trials that aim to prevent or modify the natural history of early pulmonary fibrosis would have the following features: 1) tolerable side-effect profile with very low rates of discontinuation, 2) ease of administration, 3) affordability and accessibility, and 4) minimal interactions with other medications.

Antifibrotic Therapies

Nintedanib and pirfenidone are approved in many countries for the treatment of IPF and other fibrotic ILDs (3–5). These medications have garnered significant interest as potential agents for the prevention of pulmonary fibrosis (79). However, careful consideration is needed in regard to the potential risks and benefits of testing antifibrotic agents in a clinical trial of at-risk individuals who may otherwise be asymptomatic. Pirfenidone and nintedanib each have side effects, which can lead to significant weight and nutritional losses, impaired quality of life, lowering of dosages, and/or discontinuation in clinical practice (78). In patients with clinically diagnosed ILD, antifibrotic agents are typically prescribed indefinitely. Treatment duration in at-risk individuals is expected to be longer. At least one study suggests that the effectiveness of antifibrotic agents in patients with IPF may wane after several years, and the long-term side effects of prolonged use are unknown (80). Further studies are needed to determine whether these agents are beneficial in at-risk individuals who may not meet the current diagnostic criteria for IPF or progressive pulmonary fibrosis (14).

The development of inhaled formulations of existing antifibrotic therapies and new interventions with fewer side effects and adverse events would facilitate their utility in the treatment and prevention of early disease. Other drugs currently being investigated for the treatment of fibrotic ILD (e.g., N-acetylcysteine, phosphodiesterase 4B inhibitors, epigallocatechin gallate) and repurposed generic drugs with low side-effect profiles that have biological plausibility in attenuating lung injury (e.g., metformin) are other potential candidate interventions (40, 81–83). Importantly, the mechanisms underlying early fibrosis may be distinct from those of the advanced stages of disease, and therapies that are ineffective in the later stages of disease should not be discarded as preventive strategies. For instance, pathways involved in host defense and inflammation have been implicated in studies of early disease, and immune-targeted treatments with favorable side-effect profiles should be explored for at-risk individuals. It is also critical to consider the cost and accessibility of potential treatments and the impact of wider screening and treatment on health systems when designing clinical trials for prevention, especially in the absence of curative interventions for chronic diseases (80).

Mitigation of Risk Factors

As discussed above, multiple factors contribute to the risk of clinically diagnosed pulmonary fibrosis as well as subclinical markers of lung inflammation and scarring (i.e., ILA and others) (7, 24, 56). Given the strong association of smoking with clinically diagnosed disease and ILAs, smoking cessation remains an important treatment strategy to attenuate the risk of progression and development of associated conditions (e.g., lung cancer). These recommendations extend to the mitigation and avoidance of other inhaled particles, including vaping, e-cigarettes, and metals and other occupational exposures, some of which have been linked to the presence of ILAs (24). Identification and mitigation of environmental inciting antigens (i.e., birds, mold) has been shown to improve outcomes in patients with clinically diagnosed hypersensitivity pneumonitis and may similarly benefit at-risk individuals, although prospective studies are lacking (84). Whether management and treatment of other factors (e.g., gastroesophageal reflux disease, cardiovascular comorbidities) is effective in reducing the risk of developing fibrosis is more uncertain and represents a potential focus for future clinical trials.

Next Steps

A growing body of evidence suggests that first-degree relatives of patients with pulmonary fibrosis represent a prime target group for a preventive clinical trial. In Figure 2, we integrate a potential approach to such a clinical trial. Based on existing data from familial cohorts, a total of 400 individuals would need to be enrolled (200 in the comparator arm and 200 in the intervention arm) to detect an absolute difference of 10% in ILD events (defined as extensive abnormalities on HRCT, clinical diagnosis of ILD, or an increase in the extent of abnormalities on CT) at an 80% power and a two-sided α of 0.05, assuming a 20% event rate over 5 years in the placebo arm. This power calculation is based on a relatively high rate of events reported in first-degree relatives of patients with FPF and a broad outcome definition (24). Studies targeting groups at lower risk of short-term progression and the use of stricter definitions of incident ILD would require much larger sample sizes.

Figure 2.

Potential proposed approach to a clinical trial for prevention of pulmonary fibrosis. CT = computed tomography; HRCT = high-resolution computed tomography; ILA = interstitial lung abnormality; ILD = interstitial lung disease; IPF = idiopathic pulmonary fibrosis.

Gaps that need to be addressed to successfully design a preventive clinical trial in pulmonary fibrosis are summarized in Table 3. A major barrier to identifying at-risk individuals and incorporating shared decision-making regarding evaluation and treatment is the ongoing underreporting and lack of standard terminology for ILA detected on CT scans performed for other indications, in addition to the lack of a consensus statement on screening and clinical management (85). Despite the considerable progress made in identifying groups of individuals who are at high risk of developing fibrotic ILD, awareness of the genetic risk in this disease remains limited. Consequently, few individuals have access to centers that offer counseling for patients and family members regarding their risk of developing disease and provide appropriate screening and diagnostic interventions (e.g., genetic testing, pulmonary function testing, imaging). Formal guidelines are needed to facilitate this process. The other major barrier to moving forward with a preventive clinical trial is the lack of an existing intervention that meets all the criteria outlined above. Fibrotic ILD is a heterogenous condition with multiple pathways underlying lung fibrosis. As new therapies enter clinical development, it is hoped that we can leverage radiological, genetic, and clinical traits to identify more targeted treatments and the individuals most likely to benefit from them, and one day conduct precision-based trials to maximize benefit and minimize risk. Large-platform clinical trials that use simpler or pragmatic approaches with Bayesian adaptive designs have recently accelerated the identification of useful treatments in other diseases and may represent an efficient way to identify effective therapies for individuals at risk for pulmonary fibrosis (86).

Table 3.

Gaps to conducting preventative clinical trials in fibrotic ILD

Gap	Potential Approaches
Who do we enroll in the trial?	•Imaging to detect lung abnormalities that represent the earlier stages of disease •Genomic screening to identify those prepositioned to develop fibrotic ILD •Proteomic biomarkers •Novel imaging modalities for further refinement of at-risk individuals
What endpoints should be used to design these trials?	•Incidence of fibrotic ILD in an enriched cohort (first-degree adult relatives) •Physiologic decline •Novel biomarkers (e.g., functional imaging, proteomic biomarker)
What interventions should be tested to prevent fibrotic ILD?	•Antifibrotics •Repurposing of generic drugs with biological plausibility (e.g., metformin) •Drugs currently being tested in clinical disease (e.g., phosphodiesterase-4B inhibitor) •Environmental exposure risk mitigation

Definition of abbreviation: ILD = interstitial lung disease.

Summary

The current approach of diagnosing and treating individuals who present with a significant burden of disease is not sufficient to achieve the goal of curing pulmonary fibrosis. We urge collaborative, international efforts to study diverse populations, leverage existing data, develop and validate methodologies to further refine identification of at-risk individuals, formalize criteria and protocols, and identify appropriate clinical trial endpoints and potential treatments to move us closer to the goal of prevention of pulmonary fibrosis.