Zinpentraxin Alfa for Idiopathic Pulmonary Fibrosis: The Randomized Phase III STARSCAPE Trial.

Rationale: A phase II trial reported clinical benefit over 28 weeks in patients with idiopathic pulmonary fibrosis (IPF) who received zinpentraxin alfa. Objectives: To investigate the efficacy and safety of zinpentraxin alfa in patients with IPF in a phase III trial. Methods: This 52-week phase III, double-blind, placebo-controlled, pivotal trial was conducted at 275 sites in 29 countries. Patients with IPF were randomized 1:1 to intravenous placebo or zinpentraxin alfa 10 mg/kg every 4 weeks. The primary endpoint was absolute change from baseline to Week 52 in FVC. Secondary endpoints included absolute change from baseline to Week 52 in percent predicted FVC and 6-minute walk distance. Safety was monitored via adverse events. Post hoc analysis of the phase II and phase III data explored changes in FVC and their impact on the efficacy results. Measurements and Main Results: Of 664 randomized patients, 333 were assigned to placebo and 331 to zinpentraxin alfa. Four of the 664 randomized patients were never administered study drug. The trial was terminated early after a prespecified futility analysis that demonstrated no treatment benefit of zinpentraxin alfa over placebo. In the final analysis, absolute change from baseline to Week 52 in FVC was similar between placebo and zinpentraxin alfa (-214.89 ml and -235.72 ml; P = 0.5420); there were no apparent treatment effects on secondary endpoints. Overall, 72.3% and 74.6% of patients receiving placebo and zinpentraxin alfa, respectively, experienced one or more adverse events. Post hoc analysis revealed that extreme FVC decline in two placebo-treated patients resulted in the clinical benefit of zinpentraxin alfa reported by phase II. Conclusions: Zinpentraxin alfa treatment did not benefit patients with IPF over placebo. Learnings from this program may help improve decision making around trials in IPF. Clinical trial registered with www.clinicaltrials.gov (NCT04552899).

High-resolution CT phenotypes in pulmonary sarcoidosis: a multinational Delphi consensus study.

One view of sarcoidosis is that the term covers many different diseases. However, no classification framework exists for the future exploration of pathogenetic pathways, genetic or trigger predilections, patterns of lung function impairment, or treatment separations, or for the development of diagnostic algorithms or relevant outcome measures. We aimed to establish agreement on high-resolution CT (HRCT) phenotypic separations in sarcoidosis to anchor future CT research through a multinational two-round Delphi consensus process. Delphi participants included members of the Fleischner Society and the World Association of Sarcoidosis and other Granulomatous Disorders, as well as members' nominees. 146 individuals (98 chest physicians, 48 thoracic radiologists) from 28 countries took part, 144 of whom completed both Delphi rounds. After rating of 35 Delphi statements on a five-point Likert scale, consensus was achieved for 22 (63%) statements. There was 97% agreement on the existence of distinct HRCT phenotypes, with seven HRCT phenotypes that were categorised by participants as non-fibrotic or likely to be fibrotic. The international consensus reached in this Delphi exercise justifies the formulation of a CT classification as a basis for the possible definition of separate diseases. Further refinement of phenotypes with rapidly achievable CT studies is now needed to underpin the development of a formal classification of sarcoidosis.

Combination of BAL and Computed Tomography Differentiates Progressive and Non-progressive Fibrotic Lung Diseases.

Rationale: Identifying patients with pulmonary fibrosis (PF) at risk of progression can guide management. Objectives: To explore the utility of combining baseline BAL and computed tomography (CT) in differentiating progressive and nonprogressive PF. Methods: The derivation cohort consisted of incident cases of PF for which BAL was performed as part of a diagnostic workup. A validation cohort was prospectively recruited with identical inclusion criteria. Baseline thoracic CT scans were scored for the extent of fibrosis and usual interstitial pneumonia (UIP) pattern. The BAL lymphocyte proportion was recorded. Annualized FVC decrease of >10% or death within 1 year was used to define disease progression. Multivariable logistic regression identified the determinants of the outcome. The optimum binary thresholds (maximal Wilcoxon rank statistic) at which the extent of fibrosis on CT and the BAL lymphocyte proportion could distinguish disease progression were identified. Measurements and Main Results: BAL lymphocyte proportion, UIP pattern, and fibrosis extent were significantly and independently associated with disease progression in the derivation cohort (n = 240). Binary thresholds for increased BAL lymphocyte proportion and extensive fibrosis were identified as 25% and 20%, respectively. An increased BAL lymphocyte proportion was rare in patients with a UIP pattern (8 of 135; 5.9%) or with extensive fibrosis (7 of 144; 4.9%). In the validation cohort (n = 290), an increased BAL lymphocyte proportion was associated with a significantly lower probability of disease progression in patients with nonextensive fibrosis or a non-UIP pattern. Conclusions: BAL lymphocytosis is rare in patients with extensive fibrosis or a UIP pattern on CT. In patients without a UIP pattern or with limited fibrosis, a BAL lymphocyte proportion of ⩾25% was associated with a lower likelihood of progression.

Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation.

Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung diseases, while its manual delineation is unduly burdensome. To alleviate this time-consuming and potentially subjective manual procedure, researchers have proposed methods to automatically segment airways from computerized tomography (CT) images. However, some small-sized airway branches (e.g., bronchus and terminal bronchioles) significantly aggravate the difficulty of automatic segmentation by machine learning models. In particular, the variance of voxel values and the severe data imbalance in airway branches make the computational module prone to discontinuous and false-negative predictions, especially for cohorts with different lung diseases. The attention mechanism has shown the capacity to segment complex structures, while fuzzy logic can reduce the uncertainty in feature representations. Therefore, the integration of deep attention networks and fuzzy theory, given by the fuzzy attention layer, should be an escalated solution for better generalization and robustness. This article presents an efficient method for airway segmentation, comprising a novel fuzzy attention neural network (FANN) and a comprehensive loss function to enhance the spatial continuity of airway segmentation. The deep fuzzy set is formulated by a set of voxels in the feature map and a learnable Gaussian membership function. Different from the existing attention mechanism, the proposed channel-specific fuzzy attention addresses the issue of heterogeneous features in different channels. Furthermore, a novel evaluation metric is proposed to assess both the continuity and completeness of airway structures. The efficiency, generalization, and robustness of the proposed method have been proved by training on normal lung disease while testing on datasets of lung cancer, COVID-19, and pulmonary fibrosis.

External validation of the PROGRESS-CTO complication risk scores: Individual patient data pooled analysis of 3 registries.

BACKGROUND: Chronic total occlusion (CTO) percutaneous coronary intervention (PCI) is associated with a considerable risk of complications, and risk stratification is of utmost importance. AIMS: To assess the clinical usefulness of the recently developed PROGRESS-CTO (NCT02061436) complication risk scores in an independent cohort. METHODS: Individual patient data pooled analysis of 3 registries was performed. RESULTS: Of the 4569 patients who underwent CTO PCI, 102 (2.2%) had major adverse cardiovascular events (MACE). Patients with MACE were older (69 ± 11 vs. 65 ± 10, p < 0.001), more likely to have a history of prior coronary artery bypass graft surgery, and unfavorable angiographic characteristics J-CTO score (2.4 ± 1.2 vs. 2.1 ± 1.3, p = 0.007), including blunt stump (59% vs. 49%, p = 0.047). Technical success was lower in patients with MACE (59% vs. 86%, p < 0.001). The area under the receiver operating characteristic curve of the PROGRESS-CTO complication risk models were as follows: MACE 0.72 (95% confidence interval [CI], 0.67-0.76), mortality 0.73 (95% CI, 0.61-0.85), and pericardiocentesis 0.69 (95% CI, 0.62-0.77) in the validation dataset. The observed complication rates increased with higher PROGRESS-CTO complication scores. The PROGRESS-CTO MACE score showed good calibration in this external cohort, with MACE rates similar to the original study: 0.7% (score 0-1), 1.5% (score 2), 2.2% (score 3), 3.8% (score 4), 4.9% (score 5), 5.8% (score 6-7). CONCLUSION: Given the good discriminative performance, calibration, and ease of calculation, the PROGRESS-CTO complication scores could help assess the risk of complications in patients undergoing CTO PCI.

Percutaneous coronary intervention of native coronary artery versus saphenous vein graft in patients with prior coronary artery bypass graft surgery: Rationale and design of the multicenter, randomized PROCTOR trial.

BACKGROUND: Patients with prior coronary artery bypass grafting (CABG) frequently require repeat percutaneous revascularization due to advanced age, progressive coronary artery disease and bypass graft failure. Percutaneous coronary intervention (PCI) of either the bypass graft or the native coronary artery may be performed. Randomized trials comparing native vessel PCI with bypass graft PCI are lacking and long-term outcomes have not been reported. METHODS: PROCTOR (NCT03805048) is a prospective, multicenter, randomized controlled trial, that will include 584 patients presenting with saphenous vein graft (SVG) failure and a clinical indication for revascularization, as determined by the local Heart Team. The trial is designed to compare the clinical and angiographic outcomes in patients randomly allocated in a 1:1 fashion to either a strategy of native vessel PCI or SVG PCI. The primary study endpoint is a 3-year composite of major adverse cardiac events (MACE: all-cause mortality, non-fatal target coronary territory myocardial infarction [MI], or clinically driven target coronary territory revascularization). At 3-years, after evaluation of the primary endpoint, follow-up invasive coronary angiography will be performed. Secondary endpoints comprise individual components of MACE at 1, 3 and 5 years follow-up, PCI-related MI, MI >48 hours after index PCI, target vessel failure, target lesion revascularization, renal failure requiring renal-replacement therapy, angiographic outcomes at 3-years and quality of life (delta Seattle Angina Questionnaire, Canadian Cardiovascular Society Grading Scale and Rose Dyspnea Scale). CONCLUSION: PROCTOR is the first randomized trial comparing an invasive strategy of native coronary artery PCI with SVG PCI in post-CABG patients presenting with SVG failure.

International randomized trial on the effect of revascularization or optimal medical therapy of chronic total coronary occlusions with myocardial ischemia - ISCHEMIA-CTO trial - rationale and design.

BACKGROUND: Chronic total occlusions (CTO) are frequent among patients with coronary artery disease. Revascularization with percutaneous coronary intervention (PCI) is safe and feasible in experienced hands. However, randomized data are needed to demonstrate symptomatic as well as prognostic effect of CTO-PCI compared to optimal medical therapy alone. METHODS: This trial aims to evaluate the effect of CTO PCI in patients with a CTO lesion and target vessel diameter ≥ 2.5 mm, and myocardial ischemia in the relevant territory. First, all patients are subjected to optimal medical therapy (OMT) for at least for 3 months and non-CTO lesions are managed according to guidelines. Subsequently, prior to randomization myocardial ischemia and quality of life (Seattle Questionnaire (SAQ)) is assessed. Patients are divided into two cohorts based on their SAQ score and randomized to either OMT alone or OMT and CTO-PCI. Cohort A is defined as Low- or asymptomatic patients with a quality-of-life score > 60 and/or CCS class < 2, and more than 10 % ischemia in the left ventricle (LV). Cohort B is symptomatic patients with a quality-of-life score < 60 or CCS class angina > 1 and at least ischemia in 5% of the LV. The primary end-point in cohort A is a composite of major adverse cardiac and cerebral events, hospitalization for heart failure and malignant ventricular arrhythmias. The primary endpoint in cohort B is difference in quality of life 6 months after randomization. IMPLICATIONS: This trial is designed to investigate if CTO-PCI improves QoL and MACCE. Both positive and negative outcome of the trial will affect future guidelines and recommendations on how to treat patients with CTO.

Quantitative computed tomography and machine learning: recent data in fibrotic interstitial lung disease and potential role in pulmonary sarcoidosis.

PURPOSE OF REVIEW: The aim of this study was to summarize quantitative computed tomography (CT) and machine learning data in fibrotic lung disease and to explore the potential application of these technologies in pulmonary sarcoidosis. RECENT FINDINGS: Recent data in the use of quantitative CT in fibrotic interstitial lung disease (ILD) are covered. Machine learning includes deep learning, a branch of machine learning particularly suited to medical imaging analysis. Deep learning imaging biomarker research in ILD is currently undergoing accelerated development, driven by technological advances in image processing and analysis. Fundamental concepts and goals related to deep learning imaging research in ILD are discussed. Recent work highlighted in this review has been performed in patients with idiopathic pulmonary fibrosis (IPF). Quantitative CT and deep learning have not been applied to pulmonary sarcoidosis, although there are recent deep learning data in cardiac sarcoidosis. SUMMARY: Pulmonary sarcoidosis presents unsolved problems for which quantitative CT and deep learning may provide unique solutions: in particular, the exploration of the long-standing question of whether sarcoidosis should be viewed as a single disease or as an umbrella term for disorders that might usefully be considered as separate diseases.

Quantitative computed tomography predicts outcomes in idiopathic pulmonary fibrosis.

BACKGROUND AND OBJECTIVE: Prediction of disease course in patients with progressive pulmonary fibrosis remains challenging. The purpose of this study was to assess the prognostic value of lung fibrosis extent quantified at computed tomography (CT) using data-driven texture analysis (DTA) in a large cohort of well-characterized patients with idiopathic pulmonary fibrosis (IPF) enrolled in a national registry. METHODS: This retrospective analysis included participants in the Australian IPF Registry with available CT between 2007 and 2016. CT scans were analysed using the DTA method to quantify the extent of lung fibrosis. Demographics, longitudinal pulmonary function and quantitative CT metrics were compared using descriptive statistics. Linear mixed models, and Cox analyses adjusted for age, gender, BMI, smoking history and treatment with anti-fibrotics were performed to assess the relationships between baseline DTA, pulmonary function metrics and outcomes. RESULTS: CT scans of 393 participants were analysed, 221 of which had available pulmonary function testing obtained within 90 days of CT. Linear mixed-effect modelling showed that baseline DTA score was significantly associated with annual rate of decline in forced vital capacity and diffusing capacity of carbon monoxide. In multivariable Cox proportional hazard models, greater extent of lung fibrosis was associated with poorer transplant-free survival (hazard ratio [HR] 1.20, p < 0.0001) and progression-free survival (HR 1.14, p < 0.0001). CONCLUSION: In a multi-centre observational registry of patients with IPF, the extent of fibrotic abnormality on baseline CT quantified using DTA is associated with outcomes independent of pulmonary function.

Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography.

Rationale: Reliable outcome prediction in patients with fibrotic lung disease using baseline high-resolution computed tomography (HRCT) data remains challenging. Objectives: To evaluate the prognostic accuracy of a deep learning algorithm (SOFIA [Systematic Objective Fibrotic Imaging Analysis Algorithm]), trained and validated in the identification of usual interstitial pneumonia (UIP)-like features on HRCT (UIP probability), in a large cohort of well-characterized patients with progressive fibrotic lung disease drawn from a national registry. Methods: SOFIA and radiologist UIP probabilities were converted to Prospective Investigation of Pulmonary Embolism Diagnosis (PIOPED)-based UIP probability categories (UIP not included in the differential, 0-4%; low probability of UIP, 5-29%; intermediate probability of UIP, 30-69%; high probability of UIP, 70-94%; and pathognomonic for UIP, 95-100%), and their prognostic utility was assessed using Cox proportional hazards modeling. Measurements and Main Results: In multivariable analysis adjusting for age, sex, guideline-based radiologic diagnosis, anddisease severity (using total interstitial lung disease [ILD] extent on HRCT, percent predicted FVC, DlCO, or the composite physiologic index), only SOFIA UIP probability PIOPED categories predicted survival. SOFIA-PIOPED UIP probability categories remained prognostically significant in patients considered indeterminate (n = 83) by expert radiologist consensus (hazard ratio, 1.73; P < 0.0001; 95% confidence interval, 1.40-2.14). In patients undergoing surgical lung biopsy (n = 86), after adjusting for guideline-based histologic pattern and total ILD extent on HRCT, only SOFIA-PIOPED probabilities were predictive of mortality (hazard ratio, 1.75; P < 0.0001; 95% confidence interval, 1.37-2.25). Conclusions: Deep learning-based UIP probability on HRCT provides enhanced outcome prediction in patients with progressive fibrotic lung disease when compared with expert radiologist evaluation or guideline-based histologic pattern. In principle, this tool may be useful in multidisciplinary characterization of fibrotic lung disease. The utility of this technology as a decision support system when ILD expertise is unavailable requires further investigation.

Integration and Application of Clinical Practice Guidelines for the Diagnosis of Idiopathic Pulmonary Fibrosis and Fibrotic Hypersensitivity Pneumonitis.

Recent clinical practice guidelines have addressed the diagnosis of idiopathic pulmonary fibrosis (IPF) and fibrotic hypersensitivity pneumonitis (fHP). These disease-specific guidelines were developed independently, without clear direction on how to apply their respective recommendations concurrently within a single patient, where discrimination between these two fibrotic interstitial lung diseases represents a frequent diagnostic challenge. The objective of this review, created by an international group of experts, was to suggest a pragmatic approach on how to apply existing guidelines to distinguish IPF and fHP. Key clinical, radiologic, and pathologic features described in previous guidelines are integrated in a set of diagnostic algorithms, which then are placed in the broader context of multidisciplinary discussion to guide the generation of a consensus diagnosis. Although these algorithms necessarily reflect some uncertainty wherever strong evidence is lacking, they provide insight into the current approach favored by experts in the field based on currently available knowledge. The authors further identify priorities for future research to clarify ongoing uncertainties in the diagnosis of fibrotic interstitial lung diseases.

ERS International Congress 2021: highlights from the Clinical Techniques, Imaging and Endoscopy Assembly.

This article summarises the highlights from the European Respiratory Society's "Clinical techniques, imaging and endoscopy" Assembly 14 presented at the virtual 2021 European Respiratory Society International Congress. Cutting-edge innovative developments in both diagnostic approaches and therapeutic strategies in patients with lung cancer, interstitial lung disease, obstructive airway disorders and infectious diseases were presented on this year's interactive congress platform. In this article, the Assembly 14 subgroups summarise the key take home messages given new research outcomes and place them in the context of the current knowledge.

Integrating Clinical Probability into the Diagnostic Approach to Idiopathic Pulmonary Fibrosis: An International Working Group Perspective.

Background: When considering the diagnosis of idiopathic pulmonary fibrosis (IPF), experienced clinicians integrate clinical features that help to differentiate IPF from other fibrosing interstitial lung diseases, thus generating a "pre-test" probability of IPF. The aim of this international working group perspective was to summarize these features using a tabulated approach similar to chest HRCT and histopathologic patterns reported in the international guidelines for the diagnosis of IPF, and to help formally incorporate these clinical likelihoods into diagnostic reasoning to facilitate the diagnosis of IPF. Methods: The committee group identified factors that influence the clinical likelihood of a diagnosis of IPF, which was categorized as a pre-test clinical probability of IPF into "high" (70-100%), "intermediate" (30-70%), or "low" (0-30%). After integration of radiological and histopathological features, the post-test probability of diagnosis was categorized into "definite" (90-100%), "high confidence" (70-89%), "low confidence" (51-69%), or "low" (0-50%) probability of IPF. Findings: A conceptual Bayesian framework was created, integrating the clinical likelihood of IPF ("pre-test probability of IPF") with the HRCT pattern, the histopathology pattern when available, and/or the pattern of observed disease behavior, into a "post-test probability of IPF." The diagnostic probability of IPF was expressed using an adapted diagnostic ontology for fibrotic interstitial lung diseases. Interpretation: The present approach will help incorporate the clinical judgment into the diagnosis of IPF, thus facilitating the application of IPF diagnostic guidelines and, ultimately improving diagnostic confidence and reducing the need for invasive diagnostic techniques.

Outcomes following PCI in CABG candidates during the COVID-19 pandemic: The prospective multicentre UK-ReVasc registry.

OBJECTIVES: To describe outcomes following percutaneous coronary intervention (PCI) in patients who would usually have undergone coronary artery bypass grafting (CABG). BACKGROUND: In the United Kingdom, cardiac surgery for coronary artery disease (CAD) was dramatically reduced during the first wave of the COVID-19 pandemic. Many patients with "surgical disease" instead underwent PCI. METHODS: Between 1 March 2020 and 31 July 2020, 215 patients with recognized "surgical" CAD who underwent PCI were enrolled in the prospective UK-ReVasc Registry (ReVR). 30-day major cardiovascular event outcomes were collected. Findings in ReVR patients were directly compared to reference PCI and isolated CABG pre-COVID-19 data from British Cardiovascular Intervention Society (BCIS) and National Cardiac Audit Programme (NCAP) databases. RESULTS: ReVR patients had higher incidence of diabetes (34.4% vs 26.4%, P = .008), multi-vessel disease with left main stem disease (51.4% vs 3.0%, P < .001) and left anterior descending artery involvement (94.8% vs 67.2%, P < .001) compared to BCIS data. SYNTAX Score in ReVR was high (mean 28.0). Increased use of transradial access (93.3% vs 88.6%, P = .03), intracoronary imaging (43.6% vs 14.4%, P < .001) and calcium modification (23.6% vs 3.5%, P < .001) was observed. No difference in in-hospital mortality was demonstrated compared to PCI and CABG data (ReVR 1.4% vs BCIS 0.7%, P = .19; vs NCAP 1.0%, P = .48). Inpatient stay was half compared to CABG (3.0 vs 6.0 days). Low-event rates in ReVR were maintained to 30-day follow-up. CONCLUSIONS: PCI undertaken using contemporary techniques produces excellent short-term results in patients who would be otherwise CABG candidates. Longer-term follow-up is essential to determine whether these outcomes are maintained over time.

The evolution of computer-based analysis of high-resolution CT of the chest in patients with IPF.

In patients with idiopathic pulmonary fibrosis (IPF), there is an urgent need of biomarkers which can predict disease behaviour or response to treatment. Most published studies report results based on continuous data which can be difficult to apply to individual patients in clinical practice. Having antifibrotic therapies makes it even more important that we can accurately diagnose and prognosticate in IPF patients. Advances in computer technology over the past decade have provided computer-based methods for objectively quantifying fibrotic lung disease on high-resolution CT of the chest with greater strength than visual CT analysis scores. These computer-based methods and, more recently, the arrival of deep learning-based image analysis might provide a response to these unsolved problems. The purpose of this commentary is to provide insights into the problems associated with visual interpretation of HRCT, describe of the current technologies used to provide quantification of disease on HRCT and prognostication in IPF patients, discuss challenges to the implementation of this technology and future directions.

Five-year outcomes after state-of-the-art percutaneous coronary revascularization in patients with de novo three-vessel disease: final results of the SYNTAX II study.

AIMS: The SYNTAX II study evaluated the impact of advances in percutaneous coronary intervention (PCI), integrated into a single revascularization strategy, on outcomes of patients with de novo three-vessel disease. The study employed decision-making utilizing the SYNTAX score II, use of coronary physiology, thin-strut biodegradable polymer drug-eluting stents, intravascular ultrasound, enhanced treatments of chronic total occlusions, and optimized medical therapy. Patients treated with this approach were compared with predefined patients from the SYNTAX I trial. METHODS AND RESULTS: SYNTAX II was a multicentre, single-arm, open-label study of patients requiring revascularization who demonstrated clinical equipoise for treatment with either coronary artery bypass grafting (CABG) or PCI, predicted by the SYNTAX score II. The primary endpoint was major adverse cardiac and cerebrovascular events (MACCE), which included any revascularization. The comparators were a matched PCI cohort trial and a matched CABG cohort, both from the SYNTAX I trial. At 5 years, MACCE rate in SYNTAX II was significantly lower than in the SYNTAX I PCI cohort (21.5% vs. 36.4%, P < 0.001). This reflected lower rates of revascularization (13.8% vs. 23.8%, P < 0.001), and myocardial infarction (MI) (2.7% vs. 10.4%, P < 0.001), consisting of both procedural MI (0.2% vs. 3.8%, P < 0.001) and spontaneous MI (2.3% vs. 6.9%, P = 0.004). All-cause mortality was lower in SYNTAX II (8.1% vs. 13.8%, P = 0.013) reflecting a lower rate of cardiac death (2.8% vs. 8.4%, P < 0.001). Major adverse cardiac and cerebrovascular events' outcomes at 5 years among patients in SYNTAX II and predefined patients in the SYNTAX I CABG cohort were similar (21.5% vs. 24.6%, P = 0.35). CONCLUSIONS: Use of the SYNTAX II PCI strategy in patients with de novo three-vessel disease led to improved and durable clinical results when compared to predefined patients treated with PCI in the original SYNTAX I trial. A predefined exploratory analysis found no significant difference in MACCE between SYNTAX II PCI and matched SYNTAX I CABG patients at 5-year follow-up.

Serial decline in lung volume parameters on computed tomography (CT) predicts outcome in idiopathic pulmonary fibrosis (IPF).

OBJECTIVES: In patients with IPF, this study aimed (i) to examine the relationship between serial change in CT parameters of lung volume and lung function, (ii) to identify the prognostic value of serial change in CT parameters of lung volume, and (iii) to define a threshold for serial change in CT markers of lung volume that optimally captures disease progression. METHODS: Serial CTs were analysed for progressive volume loss or fibrosis progression in 81 IPF patients (66 males, median age = 67 years) with concurrent forced vital capacity (FVC) (median follow-up 12 months, range 6-23 months). Serial CT measurements of volume loss comprised oblique fissure posterior retraction distance (OFPRD), aortosternal distance (ASD), lung height corrected for body habitus (LH), and automated CT-derived total lung volumes (ALV) (measured using commercially available software). Fibrosis progression was scored visually. Serial changes in CT markers and FVC were compared using regression analysis, and evaluated against mortality using Cox proportional hazards. RESULTS: There were 58 deaths (72%, median survival = 17 months). Annual % change in ALV was most significantly related to annual % change in FVC (R2 = 0.26, p < 0.0001). On multivariate analysis, annual % change in ASD predicted mortality (HR = 0.97, p < 0.001), whereas change in FVC did not. A 25% decline in annual % change in ASD best predicted mortality, superior to 10% decline in FVC and fibrosis progression. CONCLUSION: In IPF, serial decline in CT markers of lung volume and, specifically, annualised 25% reduction in aortosternal distance provides evidence of disease progression, not always identified by FVC trends or changes in fibrosis extent. KEY POINTS: • Serial decline in automated and surrogate markers of lung volume on CT corresponds to changes in FVC. • Annualised reductions in the distance between ascending aorta and posterior border of the sternum on CT predict mortality beyond annualised percentage change in FVC.

Nintedanib in progressive interstitial lung diseases: data from the whole INBUILD trial.

BACKGROUND: The primary analysis of the INBUILD trial showed that in subjects with progressive fibrosing interstitial lung diseases (ILDs), nintedanib slowed the decline in forced vital capacity (FVC) over 52 weeks. We report the effects of nintedanib on ILD progression over the whole trial. METHODS: Subjects with fibrosing ILDs other than idiopathic pulmonary fibrosis, who had ILD progression within the 24 months before screening despite management deemed appropriate in clinical practice, were randomised to receive nintedanib or placebo. Subjects continued on blinded randomised treatment until all subjects had completed the trial. Over the whole trial, mean±sd exposure to trial medication was 15.6±7.2 and 16.8±5.8 months in the nintedanib and placebo groups, respectively. RESULTS: In the nintedanib (n=332) and placebo (n=331) groups, respectively, the proportions of subjects who had ILD progression (absolute decline in FVC ≥10% predicted) or died were 40.4% and 54.7% in the overall population (hazard ratio (HR) 0.66, 95% CI 0.53-0.83; p=0.0003) and 43.7% and 55.8% among subjects with a usual interstitial pneumonia (UIP)-like fibrotic pattern on high-resolution computed tomography (HRCT) (HR 0.69, 95% CI 0.53-0.91; p=0.009). In the nintedanib and placebo groups, respectively, the proportions who had an acute exacerbation of ILD or died were 13.9% and 19.6% in the overall population (HR 0.67, 95% CI 0.46-0.98; p=0.04) and 15.0% and 22.8% among subjects with a UIP-like fibrotic pattern on HRCT (HR 0.62, 95% CI 0.39-0.97; p=0.03). CONCLUSION: Based on data from the whole INBUILD trial, nintedanib reduced the risk of events indicating ILD progression.