Outcomes In Idiopathic Pulmonary Fibrosis Research Articles

Body mass index is associated with clinical outcomes in idiopathic pulmonary fibrosis

Association between body mass index (BMI) and prognosis in patients with idiopathic pulmonary fibrosis (IPF) remains uncertain. We investigated the association between BMI and clinical outcomes in patients with IPF using national health claims data. The study included 11,826 patients with IPF and rare incurable disease exemption codes (mean age: 68.9 years, male: 73.8%) and available BMI data who visited medical institutions between January 2002 and December 2018. Multivariable Cox proportional hazard models were used to evaluate the association of BMI with all-cause mortality and hospitalization. Based on BMI, 3.1%, 32.8%, 27.8%, and 36.4% were classified as underweight, normal, overweight, and obese, respectively. Multivariable analysis showed independent associations of overweight (hazard ratio [HR] 0.856, 95% confidence interval [CI] 0.801–0.916) and underweight (HR 1.538, 95% CI 1.347–1.757) with mortality in patients with IPF. Similarly, overweight (HR 0.887, 95% CI 0.834–0.943) and underweight (HR 1.265, 95% CI 1.104–1.449) were also associated with hospitalization in patients with IPF in the multivariable analysis. Spline HR curve analysis adjusted for all covariates revealed a non-linear relationship between BMI and mortality in patients with IPF. Our data suggest that BMI is associated with clinical outcomes in patients with IPF.

When the Third Time Is Not the Charm—Trial Outcomes in Idiopathic Pulmonary Fibrosis

When the Third Time Is Not the Charm—Trial Outcomes in Idiopathic Pulmonary Fibrosis

Smoking status and clinical outcome in idiopathic pulmonary fibrosis: a nationwide study

BackgroundSmoking status has been linked to the development of idiopathic pulmonary fibrosis (IPF). However, the effect of smoking on the prognosis of patients with IPF is unclear. We aimed to investigate the association between smoking status and all-cause mortality or hospitalisation by using national health claims data.MethodsIPF cases were defined as people who visited medical institutions between January 2002 and December 2018 with IPF and rare incurable disease exempted calculation codes from the National Health Insurance Database. Total 10,182 patients with available data on smoking status were included in this study. Ever-smoking status was assigned to individuals with a history of smoking ≥ 6 pack-years. The multivariable Cox proportional hazard model was used to evaluate the association between smoking status and prognosis.ResultsIn the entire cohort, the mean age was 69.4 years, 73.9% were males, and 45.2% were ever smokers (current smokers: 14.2%; former smokers: 31.0%). Current smokers (hazard ratio [HR]: 0.709; 95% confidence interval [CI]: 0.643–0.782) and former smokers (HR: 0.926; 95% CI: 0.862–0.996) were independently associated with all-cause mortality compared with non-smokers. Current smokers (HR: 0.884; 95% CI: 0.827–0.945) and former smokers (HR: 0.909; 95% CI: 0.862–0.959) were also associated with a reduced risk of all-cause hospitalisation compared with non-smokers. A non-linear association between smoking amount and prognosis was found in a spline HR curve and showed increasing risk below 6 pack-years.ConclusionEver-smoking status may be associated with favourable clinical outcomes in patients with IPF.

Modified blood cell GAP model as a prognostic biomarker in idiopathic pulmonary fibrosis (max 90 characters incl. spaces)

BackgroundThe Gender, Age and Physiology (GAP) model is a simple mortality prediction tool in patients with idiopathic pulmonary fibrosis (IPF) using demographic and physiological variables available at initial evaluation. White blood cell (WBC) variables may have associations with IPF outcomes. We evaluated whether incorporation of blood cell counts in modified GAP (cGAP) models would improve outcome prediction in patients with IPF.Patients and methodsThis retrospective analysis included pooled data from randomised Phase III trials of pirfenidone in IPF (ASCEND, CAPACITY 004, CAPACITY 006). Study outcomes (IPF progression, all-cause mortality, all-cause hospitalisation, respiratory-related hospitalisation) were evaluated during the initial 1-year period. Shared frailty models were used to evaluate associations between continuous and categorical baseline WBC and red blood cell (RBC) parameters and study outcomes in a bivariate context; and the impact of adding continuous monocyte count (cGAP1) or WBC and RBC parameters (cGAP2) to traditional GAP variables in a multivariable context based on C-statistics changes.ResultsData were pooled from 1247 patients (pirfenidone, n=623; placebo, n=624). Significant associations (bivariate analyses) were: IPF progression with neutrophil and eosinophil counts; all-cause mortality with monocyte and neutrophil counts; all-cause hospitalisation with monocyte count, neutrophil count and haemoglobin level; and respiratory-related hospitalisation with monocyte count, neutrophil count and haemoglobin level. In multivariate analyses, C-statistics were highest for the cGAP2 model for each of the outcomes.ConclusionModified GAP models incorporating monocyte counts alone or plus other WBC and RBC variables may be useful to improve prediction of outcomes in patients with IPF.Trial registration numberClinicalTrials.gov identifiersNCT01366209;NCT00287716;NCT00287729.

Association of musculoskeletal involvement with lung function and mortality in patients with idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive disease associated with high mortality. Low muscle mass, frailty and sarcopenia lead to functional impairment that negatively impact quality of life and survival but are not used in clinical practice. We aimed to determine the association of Fat-free mass index (FFMI) and frailty with lung function, exercise tolerance and survival in patients with IPF. In this study, 70 patients with IPF underwent assessment of body composition, lung function, 6-min walk distance (6MWD) testing, hand grip strength, quality of life (QoL) assessment by St. George’s Respiratory questionnaire (SGRQ) and frailty assessment using the SHARE-FI tool. FFMI was calculated using pectoralis muscle cross-sectional area (PM-CSA) on CT chest images and the lowest quartile defined reduced muscle mass. Sarcopenia was defined as low FFMI and handgrip strength. Regression analyses were conducted to determine predictive value of frailty, low FFMI and sarcopenia on clinical outcomes. The Cox proportional hazards model was used to analyze the impact of FFMI and frailty score on survival. The mean age was 70 years with moderate impairment in lung function (mean ppFVC 68.5%, ppDLCO 45.6%). Baseline forced vital capacity (p < 0.001), diffusion capacity of lung for carbon monoxide (p = < 0.01), 6WMD (p < 0.05) were significantly lower in frail patients compared to non-frail patients. BMI was found to closely correlate with FFMI (r = 0.79, p < 0.001), but not with frailty score (r = − 0.2, p = 0.07). Frailty was a significant predictor of FVC, DLCO, 6MWD, SGRQ scores when adjusted for age and gender. Muscle mass and sarcopenia were significant predictors of FVC, DLCO, but not 6MWD or QoL scores. Multivariate cox-proportional hazards ratio model adjusting for age and gender showed that frailty was significantly associated with increased mortality (HR = 2.6, 95% CI 1.1–6.1). Low FFMI (HR = 1.3, 95% CI 0.6–2.8), and sarcopenia (HR = 2.1, 95% CI 0.8–5.3), though associated with a trend to increased mortality, were not statistically significant. Frailty is associated with lower lung function and higher mortality in patients with IPF. Longitudinal evaluations are necessary to further determine the associations between low FFMI, sarcopenia and frailty with outcomes in IPF.

PTK2-associated gene signature could predict the prognosis of IPF

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with a poor prognosis. Current/available clinical prediction tools have limited sensitivity and accuracy when evaluating clinical outcomes of IPF. Research has shown that focal adhesion kinase (FAK), produced by the protein tyrosine kinase 2 (PTK2) gene, is crucial in IPF development. FAK activation is a characteristic of lesional fibroblasts; Thus, FAK may be a valuable therapeutic target or prognostic biomarker for IPF. This study aimed to create a gene signature based on PTK2-associated genes and microarray data from blood cells to predict disease prognosis in patients with IPF. PTK2 levels were found to be higher in lung tissues of IPF patients compared to healthy controls, and PTK2 inhibitor Defactinib was found to reduce TGFβ-induced FAK activation and increase α-smooth muscle actin. Although the blood PTK2 levels were higher in IPF patients, blood PTK level alone could not predict IPF prognosis. From 196 PTK2-associated genes, 11 genes were prioritized to create a gene signature (PTK2 molecular signature) and a risk score system using univariate and multivariate Cox regression analysis. Patients were divided into high-risk and low-risk groups using PTK2 molecular signature. Patients in the high-risk group experienced decreased survival rates compared to patients in the low-risk group across all discovery and validation cohorts. Further functional enrichment and immune cell proportion analyses revealed that the PTK2 molecular signature strongly reflected the activation levels of immune pathways and immune cells. These findings suggested that PTK2 is a molecular target of IPF and the PTK2 molecular signature is an effective IPF prognostic biomarker.

Neighborhood Health and Outcomes in Idiopathic Pulmonary Fibrosis.

Rationale: Living in a disadvantaged neighborhood has been associated with worse survival in people with idiopathic pulmonary fibrosis (IPF), however, prior studies have only examined the impact of neighborhood health on outcomes in IPF as a composite measure. Objectives: To investigate the association between neighborhood health and disease severity, measured by pulmonary function at presentation, and death in follow-up, with an additional focus on the contributions of the neighborhood's underlying physical and social factors to these outcomes. Methods: In a retrospective study of participants from the University of California, San Francisco, IPF Cohort (2001-2020), geocoded home addresses were matched to the California Healthy Places Index (HPI), a census-tract measure of neighborhood health. The HPI comprises 25 indicators of neighborhood health that are organized into eight physical and social domains, each of which is weighted and summed to provide a composite HPI score. Regression models were used to examine associations between the HPI as a continuous variable, in quartiles, and across each physical and social domain of the HPI (higher values indicate greater advantage) and forced vital capacity (FVC) percent predicted (% predicted), diffusing capacity of the lung for carbon monoxide (DlCO) % predicted, and death, adjusting for demographic and clinical covariates. We also studied the interaction between disease severity at presentation and neighborhood health in our time-to-event models. Results: In 783 participants with IPF, each 10% increase in HPI was associated with a 1% increase in FVC % predicted and DlCO % predicted (95% confidence intervals [CIs] = 0.55, 1.72; and 0.49, 1.49, respectively). This association appeared primarily driven by the economic, education, access, and social HPI domains. We also observed differences in the associations of HPI with mortality depending on disease severity at presentation. In participants with normal to mildly impaired FVC % predicted (⩾70%) and DlCO % predicted (⩾60%), decreased HPI was associated with higher mortality (hazard ratio = 2.91 Quartile 1 vs. Quartile 4; 95% CI = 1.20, 7.05). No association was observed between the HPI and death for participants with moderate to severely impaired FVC % predicted and DlCO % predicted. Conclusions: Living in disadvantaged neighborhoods was associated with worse pulmonary function in participants with IPF and was independently associated with increased mortality in participants with normal to mild physiological impairment at presentation.

Deep Learning-Based Quantification of Traction Bronchiectasis Severity For Predicting Outcome in Idiopathic Pulmonary Fibrosis

Deep Learning-Based Quantification of Traction Bronchiectasis Severity For Predicting Outcome in Idiopathic Pulmonary Fibrosis

Proteomic Biomarkers of Survival in Idiopathic Pulmonary Fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) causes progressive lung scarring and high mortality. Reliable and accurate prognostic biomarkers are urgently needed. Objectives: To identify and validate circulating protein biomarkers of IPF survival. Methods: High-throughput proteomic data were generated using prospectively collected plasma samples from patients with IPF from the Pulmonary Fibrosis Foundation Patient Registry (discovery cohort) and the Universities of California, Davis; Chicago; and Virginia (validation cohort). Proteins associated with three-year transplant-free survival (TFS) were identified using multivariable Cox proportional hazards regression. Those associated with TFS after adjustment for false discovery in the discovery cohort were advanced for testing in the validation cohort, with proteins maintaining TFS association with consistent effect direction considered validated. After combining cohorts, functional analyses were performed, and machine learning was used to derive a proteomic signature of TFS. Measurements and Main Results: Of 2,921 proteins tested in the discovery cohort (n = 871), 231 were associated with differential TFS. Of these, 140 maintained TFS association with consistent effect direction in the validation cohort (n = 355). After cohorts were combined, the validated proteins with the strongest TFS association were latent-transforming growth factor β-binding protein 2 (hazard ratio [HR], 2.43; 95% confidence interval [CI] = 2.09-2.82), collagen α-1(XXIV) chain (HR, 2.21; 95% CI = 1.86-2.39), and keratin 19 (HR, 1.60; 95% CI = 1.47-1.74). In decision curve analysis, a proteomic signature of TFS outperformed a similarly derived clinical prediction model. Conclusions: In the largest proteomic investigation of IPF outcomes performed to date, we identified and validated 140 protein biomarkers of TFS. These results shed important light on potential drivers of IPF progression.

Histologic Analysis of Idiopathic Pulmonary Fibrosis by Morphometric and Fractal Analysis.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive fibrotic lung disorder, ultimately leading to respiratory failure and death. Despite great research advances in understanding the mechanisms underlying the disease, its diagnosis, and its treatment, IPF still remains idiopathic without known biological or histological markers able to predict disease progression or response to treatment. The histologic hallmark of IPF is usual interstitial pneumonia (UIP), with its intricate architectural distortion and temporal inhomogeneity. We hypothesize that normal lung alveolar architecture can be compared to fractals, such as the Pythagoras tree with its fractal dimension (Df), and every pathological insult, distorting the normal lung structure, could result in Df variations. In this study, we aimed to assess the UIP histologic fractal dimension in relationship to other morphometric parameters in newly diagnosed IPF patients and its possible role in the prognostic stratification of the disease. Clinical data and lung tissue specimens were obtained from twelve patients with IPF, twelve patients with non-specific interstitial pneumonia (NSIP), and age-matched "healthy" control lung tissue from patients undergoing lung surgery for other causes. Histology and histomorphometry were performed to evaluate Df and lacunarity measures, using the box counting method on the FracLac ImageJ plugin. The results showed that Df was significantly higher in IPF patients compared to controls and fibrotic NSIP patients, indicating greater architectural distortion in IPF. Additionally, high Df values were associated with higher fibroblastic foci density and worse prognostic outcomes in IPF, suggesting that Df may serve as a potential novel prognostic marker for IPF. The scalability of Df measurements was demonstrated through repeated measurements on smaller portions from the same surgical biopsies, which were selected to mimic a cryobiopsy. Our study provides further evidence to support the use of fractal morphometry as a tool for quantifying and determining lung tissue remodeling in IPF, and we demonstrated a significant correlation between histological and radiological Df in UIP pattern, as well as a significant association between Df and FF density. Furthermore, our study demonstrates the scalability and self-similarity of Df measurements across different biopsy types, including surgical and smaller specimens.

Predictive investigation of idiopathic pulmonary fibrosis subtypes based on cellular senescence-related genes for disease treatment and management.

Background: Idiopathic pulmonary fibrosis (IPF), a chronic, progressive lung disease characterized by interstitial remodeling and tissue destruction, affects people worldwide and places a great burden on society. Cellular senescence is thought to be involved in the mechanisms and development of IPF. The aim of this study was to predictively investigate subtypes of IPF according to cellular senescence-related genes and their correlation with the outcome of patients with IPF, providing possible treatment and management options for disease control. Methods: Gene expression profiles and follow-up data were obtained from the GEO database. Senescence-related genes were obtained from the CSGene database and analyzed their correlation with the outcome of IPF. A consensus cluster was constructed to classify the samples based on correlated genes. The GSVA and WGCNA packages in R were used to calculate the immune-related enriched fractions and construct gene expression modules, respectively. Metascape and the clusterProfiler package in R were used to enrich gene functions. The ConnectivityMap was used to probe suitable drugs for potential treatment. Results: A total of 99 cellular senescence-related genes were associated with IPF prognosis. Patients with IPF were divided into two subtypes with significant prognostic differences. Subtype S2 was characterized by enhanced fibrotic progression and infection, leading to acute exacerbation of IPF and poor prognosis. Finally, five cellular senescence-related genes, TYMS, HJURP, UBE2C, BIRC5, and KIF2C, were identified as potential biomarkers in poor prognostic patients with IPF. Conclusion: The study findings indicate that cellular senescence-related genes can be used to distinguish the prognosis of patients with IPF. Among them, five genes can be used as candidate biomarkers to predict patients with a poor prognostic subtype for which anti-fibrosis and anti-infection treatments could be suitable.

Change in gait speed and adverse outcomes in patients with idiopathic pulmonary fibrosis: A prospective cohort study.

Gait speed is associated with survival in individuals with idiopathic pulmonary fibrosis (IPF). The extent to which four-metre gait speed (4MGS) decline predicts adverse outcome in IPF remains unclear. We aimed to examine longitudinal 4MGS change and identify a cut-point associated with adverse outcome. In a prospective cohort study, we recruited 132 individuals newly diagnosed with IPF and measured 4MGS change over 6 months. Death/first hospitalization at 6 months were composite outcome events. Complete data (paired 4MGS plus index event) were available in 85 participants; missing 4MGS data were addressed using multiple imputation. Receiver-Operating Curve plots identified a 4MGS change cut-point. Cox proportional-hazard regression assessed the relationship between 4MGS change and time to event. 4MGS declined over 6 months (mean [95% CI] change: -0.05 [-0.09 to -0.01] m/s; p= 0.02). A decline of 0.07 m/s or more in 4MGS over 6 months had better discrimination for the index event than change in 6-minute walk distance, forced vital capacity, Composite Physiologic Index or Gender Age Physiology index. Kaplan-Meier curves demonstrated a significant difference in time to event between 4MGS groups (substantial decline: >-0.07 m/s versus minor decline/improvers: ≤-0.07 m/s; p= 0.007). Those with substantial decline had an increased risk of hospitalization/death (adjusted hazard ratio [95% CI] 4.61 [1.23-15.83]). Similar results were observed in multiple imputation analysis. In newly diagnosed IPF, a substantial 4MGS decline over 6 months is associated with shorter time to hospitalization/death at 6 months. 4MGS change has potential as a surrogate endpoint for interventions aimed at modifying hospitalization/death.

CC Chemokines in Idiopathic Pulmonary Fibrosis: Pathogenic Role and Therapeutic Potential.

Idiopathic pulmonary fibrosis (IPF), characterized by progressive worsening of dyspnea and irreversible decline in lung function, is a chronic and progressive respiratory disease with a poor prognosis. Chronic or repeated lung injury results in inflammation and an excessive injury-repairing response that drives the development of IPF. A number of studies have shown that the development and progression of IPF are associated with dysregulated expression of several chemokines and chemokine receptors, several of which have been used as predictors of IPF outcome. Chemokines of the CC family play significant roles in exacerbating IPF progression by immune cell attraction or fibroblast activation. Modulating levels of detrimental CC chemokines and interrupting the corresponding transduction axis by neutralizing antibodies or antagonists are potential treatment options for IPF. Here, we review the roles of different CC chemokines in the pathogenesis of IPF, and their potential use as biomarkers or therapeutic targets.

Genes related to N6-methyladenosine in the diagnosis and prognosis of idiopathic pulmonary fibrosis.

Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive pulmonary fibrotic disease with unknown etiology and poor outcomes. It severely affects the quality of life. In this study, we comprehensively analyzed the expression of N6-methyladenosine (m6A) RNA methylation regulators using gene expression data from various tissue sources in IPF patients and healthy volunteers. Methods: The gene expression matrix and clinical characteristics of IPF patients were retrieved from the Gene Expression Omnibus database. A random forest model was used to construct diagnosis signature m6A regulators. Regression analysis and correlation analysis were used to identify prognosis m6A regulators. Consensus cluster analysis was used to construct different m6A prognosis risk groups, then functional enrichment, immune infiltration and drug sensitivity analysis were performed. Result: Five candidate m6A genes from lung tissue were used to predict the incidence, and the incidence was validated using datasets from bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells. Subsequently, the BALF dataset containing outcomes data was used for the prognosis analysis of m6A regulators. METTL14, G3BP2, and ZC3H13 were independent protective factors. Using correlation analysis with lung function in the lung tissue-derived dataset, METTL14 was a protective factor in IPF. Based on METTL14 and G3BP2, a consensus cluster analysis was applied to distinguish the prognostic m6A regulation patterns. The low-risk group's prognosis was significantly better than the high-risk group. Biological processes regulated by various risk groups included fibrogenesis and cell adhesion. Analysis of immune cell infiltration showed upregulation of neutrophils in the m6A high-risk group. Subsequently, five m6A high-risk group sensitive drugs and one m6A low-risk group sensitive drug were identified. Discussion: These findings suggest that m6A regulators are involved in the diagnosis and prognosis of IPF, and m6A patterns are a method to identify IPF outcomes.

Multi-center evaluation of baseline neutrophil-to-lymphocyte (NLR) ratio as an independent predictor of mortality and clinical risk stratifier in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal disorder with a variable disease trajectory. The aim of this study was to assess the potential of neutrophil-to-lymphocyte ratio (NLR) to predict outcomes in IPF. We adopted a two-stage discovery (n=71) and validation (n=134) design using patients from the UCL partners (UCLp) cohort. We then combined discovery and validation cohorts and included an additional 794 people with IPF, using real-life data from 5 other UK centers, to give a combined cohort of 999 patients. Data were collected from patients presenting over a 13-year period (2006-2019) with mean follow up of 3.7 years (censoring: 2018-2020). In the discovery analysis, we showed that high values of NLR (>/=2.9 vs<2.9) were associated with increased risk of mortality in IPF (HR 2.04, 95% CI 1.09-3.81, n=71, p=0.025). This was confirmed in the validation (HR 1.91, 95% CI 1.15-3.18, n=134, p=0.0114) and combined cohorts (HR 1.65, n=999, 95% CI 1.39-1.95; p<0·0001). NLR correlated with GAP stage and GAP index (p<0.0001). Stratifying patients by NLR category (low/high) showed significant differences in survival for GAP stage 2 (p<0.0001), however not for GAP stage 1 or 3. In a multivariate analysis, a high NLR was an independent predictor of mortality/progression after adjustment for individual GAP components and steroid/anti-fibrotic use (p<0·03). Furthermore, incorporation of baseline NLR in a modified GAP-stage/index, GAP-index/stage-plus, refined prognostic ability as measured by concordance (C)-index. We have identified NLR as a widely available test that significantly correlates with lung function, can predict outcomes in IPF and refines cohort staging with GAP. NLR may allow timely prioritisation of at-risk patients, even in the absence of lung function. Breathing Matters, GSK, CF Trust, BLF-Asthma, MRC, NIHR Alpha-1 Foundation.

Quantitative computed tomography predicts outcomes in idiopathic pulmonary fibrosis.

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. 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. 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). 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.

Disparities in Rural Populations With Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease (ILD) characterized by a progressive decline in lung function.1 Early diagnosis and treatment are essential to slow lung function decline.2,3 Rural populations experience socioeconomic disadvantage and fractured access to care, both of which contribute to worse health outcomes.4 The relationship between rurality, socioeconomic factors that may impair care access, and outcomes in IPF has not been previously explored. We investigated the association between rurality and IPF disease severity, measured by pulmonary function at presentation to ILD specialty care, and mortality rates.

Impact of progressive fibrosing interstitial lung disease (ILD) in ILD patients complicated with secondary spontaneous pneumothorax.

Background:Secondary spontaneous pneumothorax (SSP) in interstitial lung disease (ILD) may influence prognosis of any ILD, and SSP onset predicts poor outcome in idiopathic pulmonary fibrosis (IPF). Recently, progressive fibrosing ILD (PF-ILD) has rapidly acquired importance.Objective:We hypothesized that PF-ILD would strongly influence the prognosis of patients with any ILD complicated with SSP.Methods:We retrospectively surveyed and collected data from patients hospitalized for SSP from January 2016 to June 2020. PF-ILD was defined as the following occurring within 24 months before SSP develops: relative decline in %forced vital capacity (FVC) ≥10% or two of the following: relative decline in %FVC between 5% and 10%, worsening respiratory symptoms, or increased extent of fibrosis on high-resolution computed tomography.Results:We analyzed 32 patients hospitalized for SSP in ILD. This study comprised 18 patients with PF-ILD and 14 patients with non-PF-ILD. PF-ILD patients had lower body mass index (BMI) and %FVC. No significant differences in survival regarding follow-up period from the time of ILD diagnosis and hospitalization for SSP were observed between the PF-ILD and non-PF-ILD patients. Older age and lower BMI were significant predictors of mortality by multivariate Cox regression analysis. ROC analysis showed BMI ≤17.8 kg/m2 to reliably predict poor prognosis.Conclusions:Regardless of whether patients have PF-ILD, older age and lower BMI in patients with ILD places them at higher risk of developing SSP, and prognosis is poor if SSP develops. Therefore, clinical management of physique is important to improve the prognosis of ILD patients.

Outcome of idiopathic pulmonary fibrosis with pregnancy: collaborative management matters

Outcome of idiopathic pulmonary fibrosis with pregnancy: collaborative management matters

Mortality and Respiratory-Related Hospitalizations in Idiopathic Pulmonary Fibrosis Not Treated With Antifibrotics.

Background: Real-world data regarding outcomes of idiopathic pulmonary fibrosis (IPF) are scarce, outside of registries. The claims data from the French National Health System (SNDS) were used to describe outcomes in patients diagnosed with IPF in 2015–2016 but who did not receive antifibrotic therapies.Method: Patients aged <50 years were excluded, as were patients with pulmonary fibrosis other than IPF, patients who had previously received a lung transplant, and those who had received antifibrotic therapies at any time between 2010 and 2016. Patients were followed-up until their last health record, lung transplantation, initiation of antifibrotic therapies, death, or the end of the study period (31 December 2017), whichever occurred first.Results: A total of 5,360 patients (43.2%) not treated with antifibrotic therapies were included. The mean age was 75.5 years, and 57.9% were males. In the year before inclusion, 47.3% of patients had a Charlson score ≥5. During follow-up, 41.2% of patients died. The unadjusted incidence rate was 29.9 per 100 person-years (95%CI = [28.7–31.2]), and the cumulative incidence of death at 3 years was 50.2% (95% CI = [48.3–52.1%]). In the study population, 35.3% of patients experienced an acute respiratory-related hospitalization. The unadjusted incidence rate was 32.1 per 100 person-years (95%CI = [30.6–33.5]) and the cumulative incidence of the event at 3 years was 41.5% (95% CI = [39.7–43.2%]).Interpretation: This observational study showed that, if untreated with antifibrotics, IPF is associated with a 50% all-cause mortality at 3 years. These figures can serve as a historical control of the natural course of the disease.