Gender-Age-Physiology Research Articles

The Prognostic Role of Advanced Lung Cancer Inflammation Index in Patients with Idiopathic Pulmonary Fibrosis

Background: The advanced lung cancer inflammation index (ALI) is an innovative and thorough measure designed to assess both inflammation and nutritional status. It includes parameters such as albumin, body mass index (BMI), and the neutrophil-to-lymphocyte ratio (NLR). This research seeks to evaluate the prognosis of idiopathic pulmonary fibrosis (IPF) patients by integrating both inflammation and nutritional status, distinguishing it from conventional inflammation biomarkers. Methods: This study included 102 patients with IPF. Clinical data were extracted from the patients’ medical records. NLR and ALI scores were calculated based on data collected at the initiation of antifibrotic treatment using the following formulas: Neut/Lym for NLR and albumin × BMI/NLR for ALI. Results: ALI values were assessed across various IPF patient subgroups based on gender–age–physiology (GAP) stages (1, 2, and 3), forced vital capacity (FVC) (median split: <70% vs. ≥70%), diffusing capacity for carbon monoxide (DLCO) (<51% vs. ≥51%), 6-Minute Walk Test (6MWT) (<350 vs. ≥350), and the Charlson comorbidity index (CCI) (≤1 vs. >1). Significant differences in ALI were observed with respect to GAP stages, FVC, DLCO, and 6MWT categories (p = 0.000 for all), but not for CCI categories (p = 0.233). Receiver operating characteristic (ROC) curve analysis revealed that ALI had a sensitivity of 63.6% and a specificity of 98.9% at a threshold of 11.2 (AUC = 0.945, 95% CI 0.892–0.998, p < 0.000). Conclusions: Our findings indicate that ALI levels are significantly associated with disease severity and mortality in IPF patients.

Oxygen saturation recovery after 6-minute walk test in patients with idiopathic pulmonary fibrosis

BackgroundThe six-minute walk test (6MWT) is widely used to assess functional capacity and prognosis in patients with idiopathic pulmonary fibrosis (IPF). However, studies on oxygen saturation recovery after the 6MWT in patients with IPF are rare. In our study, we investigated the relationship between oxygen saturation recovery time and dyspnea, fatigue, quality of life, prognostic markers and pulmonary hypertension (PH).MethodsIn this cross-sectional study, IPF patients diagnosed according to current guidelines and followed up in our Interstitial Lung Disease Outpatient Clinic between 2021 and 2022 were included. Demographics, data from spirometry, diffusion capacity measurement, arterial blood gas analysis, transthoracic echocardiography and the 6MWT were recorded. The oxygen saturation recovery time, distance saturation product (DSP), gender-age-physiology (GAP) index and composite physiological index (CPI) scores were calculated. Dyspnea severity was assessed by the modified Medical Research Council (mMRC) and Dyspnoea-12 (D-12) scales, fatigue severity by the Multidimensional Fatigue Inventory (MFI-20) and quality of life by the St George’s Respiratory Questionnaire (SGRQ).ResultsFifty IPF patients (34 men, 16 women, age: 66.8 ± 7.3 years) were included in the study. The mean FVC was 77.8 ± 19.3%, the DLCO was 52.9 ± 17.1%, the 6-minute walk distance (6MWD) was 385.7 ± 90.6 m, the GAP index was 3.5 ± 1.5, and the CPI was 43.7 ± 14.1. Oxygen saturation after the 6MWT reached pretest values at an average of 135.6 ± 73.5 s. The oxygen saturation recovery time was longer in patients with higher GAP index scores (Rs = 0.870, p < 0.001), CPI scores (Rs = 0.906, p < 0.001), desaturation (Rs = 0.801, p < 0.001), FVC%/DLCO% (Rs = 0.432, p = 0.002), sPAP (Rs = 0.492, p = 0.001), TRV (Rs = 0.504, p = 0.001), mMRC (Rs = 0.913, p < 0.001), MFI-20 (Rs = 0.944, p < 0.001), D-12 scale (Rs = 0.915, p < 0.001) and SGRQ scores (Rs = 0.927, p < 0.001); lower FVC (%) (Rs=-0.627, p < 0.001), DLCO (%) (Rs=-0.892, p < 0.001), PaO2 (Rs=-0.779, p < 0.001), DSP (Rs=-0.835, p < 0.001), and 6MWD (Rs=-0.763, p < 0.001). A total of twenty patients (40%) exhibited an increased risk of PH. According to our multiple regression analysis, oxygen saturation recovery time was independently associated with the GAP index (p = 0.036), the lowest oxygen saturation occurring during the 6MWT (p = 0.011) and the SGRQ score (p < 0.001).ConclusionsOur results showed that oxygen saturation recovery time is associated with dyspnea, fatigue, quality of life, increased risk of PH and prognostic markers in IPF. Therefore, we recommend continuous measurement of oxygen saturation after 6MWT until pretest values are reached.

Proteomic profiling of bronchoalveolar lavage fluid uncovers protein clusters linked to survival in idiopathic forms of interstitial lung disease

BackgroundIdiopathic interstitial pneumonias (IIPs) such as idiopathic pulmonary fibrosis (IPF) and interstitial pneumonia with autoimmune features (IPAF), present diagnostic and therapeutic challenges due to their heterogeneous nature. This study aimed to identify intrinsic molecular signatures within the lung microenvironment of these IIPs through proteomic analysis of bronchoalveolar lavage fluid (BALF).MethodsPatients with IIP (n=23) underwent comprehensive clinical evaluation including pre-treatment bronchoscopy and were compared to controls without lung disease (n=5). Proteomic profiling of BALF was conducted using label-free quantitative methods. Unsupervised cluster analyses identified protein expression profiles which were then analyzed to predict survival outcomes and investigate associated pathways.ResultsProteomic profiling successfully differentiated IIP from controls.k-means clustering, based on protein expression revealed three distinct IIP clusters, which were not associated with age, smoking history, or baseline pulmonary function. These clusters had unique survival trajectories and provided more accurate survival predictions than the Gender Age Physiology (GAP) index (C-index 0.794versus0.709). The cluster with the worst prognosis featured decreased inflammatory signaling and complement activation, with pathway analysis highlighting altered immune response pathways related to immunoglobulin production and B cell-mediated immunity.ConclusionsThe unsupervised clustering of BALF proteomics provided a novel stratification of IIP patients, with potential implications for prognostic and therapeutic targeting. The identified molecular phenotypes underscore the diversity within the IIP classification and the potential importance of personalized treatments for these conditions. Future validation in larger, multi-ethnic cohorts is essential to confirm these findings and to explore their utility in clinical decision-making for patients with IIP.

Proteomic profiling of bronchoalveolar lavage fluid uncovers protein clusters linked to survival in idiopathic forms of interstitial lung disease.

Idiopathic interstitial pneumonias (IIPs) such as idiopathic pulmonary fibrosis (IPF) and interstitial pneumonia with autoimmune features (IPAF), present diagnostic and therapeutic challenges due to their heterogeneous nature. This study aimed to identify intrinsic molecular signatures within the lung microenvironment of these IIPs through proteomic analysis of bronchoalveolar lavage fluid (BALF). Patients with IIP (n=23) underwent comprehensive clinical evaluation including pre-treatment bronchoscopy and were compared to controls without lung disease (n=5). Proteomic profiling of BALF was conducted using label-free quantitative methods. Unsupervised cluster analyses identified protein expression profiles which were then analyzed to predict survival outcomes and investigate associated pathways. Proteomic profiling successfully differentiated IIP from controls. k-means clustering, based on protein expression revealed three distinct IIP clusters, which were not associated with age, smoking history, or baseline pulmonary function. These clusters had unique survival trajectories and provided more accurate survival predictions than the Gender Age Physiology (GAP) index (C-index 0.794 vs. 0.709). The cluster with the worst prognosis featured decreased inflammatory signaling and complement activation, with pathway analysis highlighting altered immune response pathways related to immunoglobulin production and B cell-mediated immunity. The unsupervised clustering of BALF proteomics provided a novel stratification of IIP patients, with potential implications for prognostic and therapeutic targeting. The identified molecular phenotypes underscore the diversity within the IIP classification and the potential importance of personalized treatments for these conditions. Future validation in larger, multi-ethnic cohorts is essential to confirm these findings and to explore their utility in clinical decision-making for patients with IIP.

Potential role of SIRT-1 and SIRT-3 as biomarkers for the diagnosis and prognosis of idiopathic pulmonary fibrosis

BackgroundIdiopathic pulmonary fibrosis (IPF) is a debilitating and progressive lung disease of unknown aetiology, characterized by the relentless deposition of fibrotic tissue. Biomarkers may play a pivotal role as indicators of disease presence, progression, and treatment response. Sirtuins, a family of enzymes with ADP ribosyltransferase or deacetylase activity, have been implicated in several diseases, including pulmonary fibrosis.MethodsA cross-sectional, prospective, observational single-center study was conducted to investigate the potential role of serum SIRTs levels as biomarkers in patients with IPF. Demographic, clinical, and functional data and serological samples were collected from 34 patients with IPF followed at the Interstital Lung and Rare Diseases Outpatient Clinic of the Vanvitelli Pneumology Clinic, Monaldi Hospital, Naples, Italy and from 19 age-matched controls.ResultsSerum SIRT-1 levels were significantly reduced in IPF patients compared to controls (median IPF 667 [435–858] pg/mL versus controls 925 [794–1173] pg/mL; p < 0.001 ). In contrast, serum SIRT-3 levels were significantly increased in IPF patients compared to controls (median IPF 338 [230–500] pg/mL versus controls 154 [99.8–246] pg/mL; p < 0.001). There were no statistically significant differences in serum SIRT-6 and SIRT-7 levels between IPF and controls. In addition, we found a significant positive correlation between SIRT-1 and lung function parameters such as FEV1% (ϱ=0.417;p = 0.016), FVC% (ϱ=0.449;p = 0.009) and DLCO% (ϱ=0.393;p = 0.024), while a significant negative correlation was demonstrated between SIR-1 and GAP score, demonstrating a significant reduction in SIRT-1 in advanced Gender-Age-Physiology (GAP) stages 2–3 compared to GAP stage 1 (p = 0.008).ConclusionsThis prospective, cross-sectional study showed that SIRT-1 was associated with lung function and IPF severity and that both SIRT-1 and SIRT-3 could be considered as potential biomarkers of IPF, whereas SIRT-6 and SIRT-7 were not associated with IPF.

Assessment of the impact of social deprivation, distance to hospital and time to diagnosis on survival in idiopathic pulmonary fibrosis

BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive condition associated with a variable prognosis. The relationship between socioeconomic status or distance travelled to respiratory clinics and prognosis is unclear. Research questionTo determine whether socioeconomic status, distance to hospital and time to referral affects survival in patients with IPF. Study design and methodsIn this retrospective cohort study, we used data collected from the British Thoracic Society Interstitial Lung Diseases Registry, between 2013 and 2021 (n = 2359) and calculated the quintile of Index of Multiple Deprivation 2019 score, time from initial symptoms to hospital attendance and distance as the linear distance between hospital and home post codes. Survival was assessed using Cox proportional hazards models. ResultsThere was a significant association between increasing quintile of deprivation and duration of symptoms prior to hospital presentation, Gender Age Physiology (GAP) index and receipt of supplemental oxygen and antifibrotic therapies at presentation. The most deprived patients had worse overall survival compared to least deprived after adjusting for smoking status, GAP index, distance to hospital and time to referral (HR = 1.39 [1.11, 1.73]; p = 0.003). Patients living furthest from a respiratory clinic also had worse survival compared to those living closest (HR = 1.29 [1.01, 1.64]; p = 0.041). InterpretationThe most deprived patients with IPF have more severe disease at presentation and worse outcomes. Living far from hospital was also associated with poor outcomes. This suggests inequalities in access to healthcare and requires consideration in delivering effective and equitable care to patients with IPF.

Factors influencing long-term outcomes in fibrotic interstitial lung disease (F-ILD) diagnosed through multidisciplinary discussion (MDD): a prospective cohort study

BackgroundThe diagnostic process for fibrotic interstitial lung disease (F-ILD) is notably intricate, necessitating a multidisciplinary discussion to achieve consensus based on both clinical and radiological features. This study investigated the shared and distinctive long-term mortality predictors among the two primary phenotypes of F-ILD, namely idiopathic pulmonary fibrosis (IPF) and connective tissue disease-associated interstitial lung disease (CTD-ILD).MethodsWe included patients with F-ILD diagnosed from December 2018 to December 2019 and conducted follow-up assessments until February 2023. Age, gender, usual interstitial pneumonia (UIP) pattern, gender–age–physiology (GAP) score, modified Medical Research Council (mMRC) dyspnea score, antifibrotic agent use, pulmonary function test parameters, and six-minute walking test (6MWT) parameters were recorded at baseline and used as mortality predictors in a multivariate Cox regression model.ResultsWe enrolled 104 ILD patients. The survival rate of non-IPF patients was more than twice that of IPF patients (78.9% vs. 34%, p < 0.001), and the survival rate of patients with a GAP score of 0–2 was more than twice that of patients with a score of > 2 (93.2% vs. 36.6%, p < 0.001). Older age, male gender, definite UIP pattern, higher GAP score, higher mMRC dyspnea score, lower forced expiratory volume in one second/forced vital capacity (FEV1/FVC), shorter 6MWT distance, and lower initial and final SpO2 were also associated with higher long-term mortality (p < 0.05). In multivariable analysis, only a GAP score of > 2 (hazard ratio [HR]:16.7; 95% confidence interval [CI] 3.28–85.14; p = 0.001) and definite UIP pattern (HR: 4.08; 95% CI 1.07–15.5; p = 0.039) were significantly associated with overall mortality.ConclusionThe long-term mortality rate of IPF patients was higher than that of CTD-ILD patients. The GAP score and UIP patterns were significant mortality predictors for both IPF and CTD-ILD patients.

Multidisciplinary-derived clinical score for accurate prediction of long-term mortality in fibrotic lung disease patients

BackgroundIdiopathic pulmonary fibrosis (IPF) stands out as one of the most aggressive forms of interstitial lung diseases (ILDs), currently without a definitive cure. Multidisciplinary discussion (MDD) is now considered a cornerstone in diagnosing and differentiating ILD subtypes. The Gender-Age-Physiology (GAP) score, developed to assess IPF prognosis based on sex, age, forced vital capacity, and diffusion capacity for carbon monoxide (DLCO), is limited in not considering dyspnea and functional impairment during the walking test. We proposed a MDD-based clinical score for mortality prediction among those patients.MethodsFrom December 2018 to December 2019, we enrolled ILD patients with IPF and non-IPF and followed-up them till December 2020. Based on DLCO, modified Medical Research Council (mMRC) Dyspnea Scale, and six-minute walking test (6MWT) distance, a functional score was developed for mortality prediction.ResultsWe enrolled 104 ILD patients, 12 (11.5%) died by the one-year follow-up. In receiver operating characteristic (ROC) curve analysis, DLCO (% predicted) was the most accurate variable predicting one-year mortality with an area under curve (AUC) of 0.88 (95% confidence interval [CI] = 0.80–0.94), followed by mMRC Dyspnea Score (AUC = 0.82 [95% CI = 0.73–0.89]), 6MWT distance (AUC = 0.80 [95% CI = 0.71–0.88]), and GAP score (AUC = 0.77 [95% CI = 0.67–0.84]). Only the GAP score (hazard ratio [HR] = 1.55, 95% CI = 1.03–2.34, p = 0.0.37) and functional score (HR = 3.45, 95% CI = 1.11–10.73, p = 0.032) were significantly associated with one-year mortality in multivariable analysis.ConclusionThe clinical score composite of DLCO, mMRC Dyspnea Scale, and 6MWT distance could provide an accurate prediction for long-term mortality in ILD patients, laying out a helpful tool for managing and following these patients.

Prognostic factors of progressive fibrotic hypersensitivity pneumonitis: a large, retrospective, multicentre, observational cohort study.

Fibrotic hypersensitivity pneumonitis (fHP) is an immune-mediated interstitial lung disease caused by sensitisation to chronic allergen inhalation. This study aimed to determine prognostic indicators of progression and mortality in fHP. This was a retrospective, multicentre, observational, cross-sectional cohort study of consecutive patients diagnosed with fHP from 1 January 2012 to 31 December 2021. Multivariate Cox regression analyses were used to calculate hazard ratios (HRs) with 95% confidence intervals for predictors of progression and survival. A total of 403 patients were diagnosed with fHP: median (interquartile range) age 66.5 (14.0) years, 51.9% females and 55.1% never-smokers. The cause of fHP was mainly fungal (39.7%) or avian (41.4%). Lung biopsy was performed in 269 cases (66.7%). In the whole cohort the variables that were related to mortality or lung transplant were older age (HR 1.08; p<0.001), percentage predicted forced vital capacity (HR 0.96; p=0.001), lymphocytosis in bronchoalveolar lavage (BAL) (HR 0.93; p=0.001), presence of acute exacerbation during follow-up (HR 3.04; p=0.001) and GAP (gender, age and lung physiology) index (HR 1.96; p<0.01). In the group of biopsied patients, the presence of fibroblastic foci at biopsy (HR 8.39; p<0.001) stands out in multivariate Cox regression analyses as a highly significant predictor for increased mortality or lung transplant. GAP index (HR 1.26; p=0.009), lymphocytosis in BAL (HR 0.97; p=0.018) and age (HR 1.03; p=0.018) are also predictors of progression. The study identified several prognostic factors for progression and/or survival in fHP. The presence of fibroblastic foci at biopsy was a consistent predictor for increased mortality and the presence of lymphocytosis in BAL was inversely related to mortality.

Deep learning-based prognostication in idiopathic pulmonary fibrosis using chest radiographs.

To develop and validate a deep learning-based prognostic model in patients with idiopathic pulmonary fibrosis (IPF) using chest radiographs. To develop a deep learning-based prognostic model using chest radiographs (DLPM), the patients diagnosed with IPF during 2011-2021 were retrospectively collected and were divided into training (n = 1007), validation (n = 117), and internal test (n = 187) datasets. Up to 10 consecutive radiographs were included for each patient. For external testing, three cohorts from independent institutions were collected (n = 152, 141, and 207). The discrimination performance of DLPM was evaluated using areas under the time-dependent receiver operating characteristic curves (TD-AUCs) for 3-year survival and compared with that of forced vital capacity (FVC). Multivariable Cox regression was performed to investigate whether the DLPM was an independent prognostic factor from FVC. We devised a modified gender-age-physiology (GAP) index (GAP-CR), by replacing DLCO with DLPM. DLPM showed similar-to-higher performance at predicting 3-year survival than FVC in three external test cohorts (TD-AUC: 0.83 [95% CI: 0.76-0.90] vs. 0.68 [0.59-0.77], p < 0.001; 0.76 [0.68-0.85] vs. 0.70 [0.60-0.80], p = 0.21; 0.79 [0.72-0.86] vs. 0.76 [0.69-0.83], p = 0.41). DLPM worked as an independent prognostic factor from FVC in all three cohorts (ps < 0.001). The GAP-CR index showed a higher 3-year TD-AUC than the original GAP index in two of the three external test cohorts (TD-AUC: 0.85 [0.80-0.91] vs. 0.79 [0.72-0.86], p = 0.02; 0.72 [0.64-0.80] vs. 0.69 [0.61-0.78], p = 0.56; 0.76 [0.69-0.83] vs. 0.68 [0.60-0.76], p = 0.01). A deep learning model successfully predicted survival in patients with IPF from chest radiographs, comparable to and independent of FVC. Deep learning-based prognostication from chest radiographs offers comparable-to-higher prognostic performance than forced vital capacity. •A deep learning-based prognostic model for idiopathic pulmonary fibrosis was developed using 6063 radiographs. •The prognostic performance of the model was comparable-to-higher than forced vital capacity, and was independent from FVC in all three external test cohorts. •A modified gender-age-physiology index replacing diffusing capacity for carbon monoxide with the deep learning model showed higher performance than the original index in two external test cohorts.

Neutrophil–lymphocyte ratio in patients with idiopathic pleuroparenchymal fibroelastosis

BackgroundIdiopathic pleuroparenchymal fibroelastosis (iPPFE), a progressive fibrotic disease, is characterised by upper lobe–dominant lung fibrosis involving the pleura and subpleural lung parenchyma. However, no prognostic markers have been established for...

Computed Tomography-Based Deep Learning Model for Assessing the Severity of Patients With Connective Tissue Disease-Associated Interstitial Lung Disease.

This study aimed to develop a computed tomography (CT)-based deep learning model for assessing the severity of patients with connective tissue disease (CTD)-associated interstitial lung disease (ILD). The retrospective study included 298 CTD-ILD patients between January 2018 and May 2022. A deep learning-based RDNet model was established (1610 fully annotated CT images for training and 402 images for validation). The model was used to automatically classify and quantify 3 radiologic features (ground glass opacities [GGOs], reticulation, and honeycombing), along with a volumetric sum of 3 areas (ILD%). As a control, we used 4 previously defined CT threshold methods to calculate the ILD assessment index. The Spearman rank correlation coefficient ( r ) evaluated the correlation between various indicators and the lung function index in the remaining 184 CTD-ILD patients who were staged according to the gender-age-physiology (GAP) system. The RDNet model accurately identified GGOs, reticulation, and honeycombing, with corresponding Dice indexes of 0.784, 0.782, and 0.747, respectively. A total of 137 patients were at GAP1 (73.9%), 36 patients at GAP2 (19.6%), and 11 patients at GAP3 (6.0%). The percentages of reticulation and honeycombing at GAP2 and GAP3 were markedly elevated compared with those at GAP1 ( P < 0.001). The percentage of GGOs was not significantly different among the GAP stages ( P = 0.62). As the GAP stage increased, all lung function indicators tended to decrease, and the composite physiologic index (CPI) indicated an upward tendency. The percentage of honeycombs moderately correlated with the percentage of diffusing capacity of the lung for carbon monoxide (DLco%) ( r = -0.58, P < 0.001) and CPI ( r = 0.63, P < 0.001). The ILD assessment index calculated by the CT threshold method (-260 to -600 Hounsfield units) had a low correlation with DLco% and CPI (DLco%: r = -0.42, P < 0.001; CPI: r = 0.45, P < 0.001). The RDNet model can quantify GGOs, reticulation, and honeycombing of chest CT images in CTD-ILD patients, among which honeycombing had the most significant effect on lung function indicators. In addition, this model provided good clinical utility for evaluating the severity of CTD-ILD.

External validation and longitudinal application of the DO-GAP index to individualise survival prediction in idiopathic pulmonary fibrosis.

The Distance-Oxygen-Gender-Age-Physiology (DO-GAP) index has been shown to improve prognostication in idiopathic pulmonary fibrosis (IPF) compared to the Gender-Age-Physiology (GAP) score. We sought to externally validate the DO-GAP index compared to the GAP index for baseline risk assessment in patients with IPF. Additionally, we evaluated the utility of serial change in the DO-GAP index in predicting survival. We performed an analysis of patients with IPF from the Pulmonary Fibrosis Foundation-Patient Registry (PFF-PR). Discrimination and calibration of the two models were assessed to predict transplant-free survival and IPF-related mortality. Joint longitudinal time-to-event modelling was utilised to individualise survival prediction based on DO-GAP index trajectory. There were 516 patients with IPF from the PFF-PR with available demographics, pulmonary function tests, 6-min walk test data and outcomes included in this analysis. The DO-GAP index (C-statistic: 0.73) demonstrated improved discrimination in discerning transplant-free survival compared to the GAP index (C-statistic: 0.67). DO-GAP index calibration was adequate, and the model retained predictive accuracy to identify IPF-related mortality (C-statistic: 0.74). The DO-GAP index was similarly accurate in the subset of patients taking antifibrotic medications. Serial change in the DO-GAP index improved model discrimination (cross-validated area under the curve: 0.83) enabling the personalised prediction of disease trajectory in individual patients. The DO-GAP index is a simple, validated, multidimensional score that accurately predicts transplant-free survival in patients with IPF and can be adapted longitudinally in individual patients. The DO-GAP may also find use in studies of IPF to risk stratify patients and possibly as a clinical trial end-point.

Comparison of clinical scoring to predict mortality risk in mild-to-moderate idiopathic pulmonary fibrosis.

During the last decade, a number of clinical scores, such as Gender-Age-Physiology (GAP) Index, TORVAN Score and Charlson Comorbidity Index (CCI), have been separately used to measure comorbidity burden in idiopathic pulmonary fibrosis (IPF). However, no previous study compared the prognostic value of these scores to assess mortality risk stratification in IPF patients with mild-to-moderate disease. All consecutive patients with mild-to-moderate IPF who underwent high-resolution computed tomography, spirometry, transthoracic echocardiography and carotid ultrasonography at our Institution, between January 2016 and December 2018, were retrospectively analyzed. GAP Index, TORVAN Score and CCI were calculated in all patients. Primary endpoint was all-cause mortality, whereas secondary endpoint was the composite of all-cause mortality and rehospitalizations for all-causes, over medium-term follow-up. Seventy IPF patients (70.2±7.4 yrs, 74.3% males) were examined. At baseline, GAP Index, TORVAN Score and CCI were 3.4±1.1, 14.7±4.1 and 5.3±2.4, respectively. A strong correlation between coronary artery calcification (CAC) and common carotid artery (CCA) intima-media thickness (IMT) (r=0.88), CCI and CAC (r=0.80), CCI and CCA-IMT (r=0.81), was demonstrated in the study group. Follow-up period was 3.5±1.2 years. During follow-up, 19 patients died and 32 rehospitalizations were detected. CCI (HR 2.39, 95% CI: 1.31-4.35) and heart rate (HR 1.10, 95% CI: 1.04-1.17) were independently associated with primary endpoint. CCI (HR 1.54, 95% CI: 1.15-2.06) predicted secondary endpoint, also. A CCI ≥6 was the optimal cut-off for predicting both outcomes. Due to the increased atherosclerotic and comorbidity burden, IPF patients with CCI ≥6 at an early-stage disease have poor outcome over medium-term follow-up.

Use of illness severity scores to predict mortality in interstitial lung disease patients hospitalised with acute respiratory deterioration

IntroductionHospitalisations relating to acute respiratory deteriorations (ARD) in Interstitial Lung Disease (ILD) have poor outcomes. Factors predicting adverse outcomes are not fully understood and data addressing the use of illness severity scores in prognostication are limited. ObjectiveTo investigate the use of CURB-65 and NEWS-2 severity scores in the prediction of mortality following ARD-ILD hospitalisation, using prospective methodology and to validate previously determined cut-offs, derived from a retrospective study cohort. MethodsA dual-centre prospective observational cohort study of all adults (≥18y) hospitalised with ARD-ILD in Bristol, UK (n = 179). Gender-Age-Physiology (GAP), CURB-65 and NEWS-2 scores were calculated for each eligible admission.Receiver operating characteristics (ROC) curve analysis was used to quantify the strength of discrimination for NEWS-2 and CURB-65 scores. Univariable and multivariable logistic regression analyses were performed to explore the relationship between baseline severity scores and mortality. ResultsGAP showed some merit at predicting 30-day mortality (AUC = 0.64, P = 0.015); whereas CURB-65 showed modest predictive value for in-hospital (AUC = 0.72, P < 0.001) and 90-day mortality (AUC = 0.67, P < 0.001). NEWS-2 showed higher predictive value for in-hospital (AUC = 0.80, P < 0.001) and 90-day mortality (AUC = 0.75, P < 0.001), with an optimal derived cut-off ≥6.5 found to be sensitive and specific for predicting in-hospital (83% and 63%) and 90-day (73% and 72%) mortality. In exploratory analyses, GAP score addition improved the predictive ability of NEWS-2 against 30-day mortality and CURB-65 across all time-periods. ConclusionNEWS-2 has good discriminatory value for predicting in-hospital mortality and moderate discriminatory value for predicting 90-day mortality. The optimal NEWS-2 cut-off value determined was the same as in a previous retrospective cohort, confirming the NEWS-2 score shows promise in predicting mortality following ARD-ILD hospitalisation.

Prognostic role of CHA2DS2-VASc score for mortality risk assessment in non-advanced idiopathic pulmonary fibrosis: a preliminary observation.

During the last decade, the CHA2DS2-VASc score has been used for stratifying the mortality risk in both atrial fibrillation (AF) and non-AF patients. However, no previous study considered this score as a prognostic indicator in non-AF patients with mild-to-moderate idiopathic pulmonary fibrosis (IPF). All consecutive non-AF patients with mild-to-moderate IPF, diagnosed between January 2016 and December 2018 at our Institution, entered this study. All patients underwent physical examination, blood tests, spirometry, high-resolution computed tomography and transthoracic echocardiography. CHA2DS2-VASc score, Gender-Age-Physiology (GAP) index and Charlson Comorbidity Index (CCI) were determined in all patients. Primary endpoint was all-cause mortality, while the secondary endpoint was the composite of all-cause mortality and rehospitalizations for all causes over mid-term follow-up. 103 consecutive IPF patients (70.7 ± 7.3 yrs, 79.6% males) were retrospectively analyzed. At the basal evaluation, CHA2DS2-VASc score, GAP index and CCI were 3.7 ± 1.6, 3.6 ± 1.2 and 5.5 ± 2.3, respectively. Mean follow-up was 3.5 ± 1.3 yrs. During the follow-up period, 29 patients died and 43 were re-hospitalized (44.2% due to cardiopulmonary causes). On multivariate Cox regression analysis, CHA2DS2-VASc score (HR 2.15, 95% CI 1.59-2.91) and left ventricular ejection fraction (LVEF) (HR 0.91, 95% CI 0.86-0.97) were independently associated with all-cause mortality in IPF patients. CHA2DS2-VASc score (HR 1.66, 95% CI 1.39-1.99) and LVEF (HR 0.94, 95% CI 0.90-0.98) also predicted the secondary endpoint in the same study group. CHA2DS2-VASc score > 4 was the optimal cut-off for predicting both outcomes. At mid-term follow-up, a CHA2DS2-VASc score > 4 predicts an increased risk of all-cause mortality and rehospitalizations for all causes in non-AF patients with mild-to-moderate IPF.

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.

Computed Tomography Radiomics-based Prediction Model for Gender–Age–Physiology Staging of Connective Tissue Disease-associated Interstitial Lung Disease

To analyze the feasibility of predicting gender-age-physiology (GAP) staging in patients with connective tissue disease-associated interstitial lung disease (CTD-ILD) by radiomics based on computed tomography (CT) of the chest. Chest CT images of 184 patients with CTD-ILD were retrospectively analyzed. GAP staging was performed on the basis of gender, age, and pulmonary function test results. GAP I, II, and III have 137, 36, and 11 cases, respectively. The cases in GAP Ⅱ and Ⅲ were then combined into one group, and the two groups of patients were randomly divided into the training and testing groups with a 7:3 ratio. The radiomics features were extracted using AK software. Multivariate logistic regression analysis was then conducted to establish a radiomics model. A nomogram model was established on the basis of Rad-score and clinical factors (age and gender). For the radiomics model, four significant radiomics features were selected to construct the model and showed excellent ability to differentiate GAP I from GAP Ⅱ and Ⅲ in both the training group (the area under the curve [AUC]=0.803, 95% confidence interval [CI]: 0.724-0.874) and testing group (AUC=0.801, 95% CI:0.663-0.912). The nomogram model that combined clinical factors and radiomics features improved higher accuracy of both training (88.4% vs. 82.1%) and testing (83.3% vs. 79.2%). The disease severity assessment of patients with CTD-ILD can be evaluated by applying the radiomics method based on CT images. The nomogram model demonstrates better performance for predicting the GAP staging.

Machine Learning and BMI Improve the Prognostic Value of GAP Index in Treated IPF Patients

Patients affected by idiopathic pulmonary fibrosis (IPF) have a high mortality rate in the first 2-5 years from diagnosis. It is therefore necessary to identify a prognostic indicator that can guide the care process. The Gender-Age-Physiology (GAP) index and staging system is an easy-to-calculate prediction tool, widely validated, and largely used in clinical practice to estimate the risk of mortality of IPF patients at 1-3 years. In our study, we analyzed the GAP index through machine learning to assess any improvement in its predictive power in a large cohort of IPF patients treated either with pirfenidone or nintedanib. In addition, we evaluated this event through the integration of additional parameters. As previously reported by Y. Suzuki et al., our data show that inclusion of body mass index (BMI) is the best strategy to reinforce the GAP performance in IPF patients under treatment with currently available anti-fibrotic drugs.

Medium-long term prognosis prediction for idiopathic pulmonary fibrosis patients based on quantitative analysis of fibrotic lung volume

PurposeTo investigate the prognostic value of quantitative analysis of CT among patients with idiopathic pulmonary fibrosis (IPF) by quantifying the fibrosis extent and to attempt to provide precise medium-long term prognostic predictions for individual patients.MethodsThis was a retrospective cohort study that included 95 IPF patients in Zhongshan Hospital, Fudan University. 64 patients firstly diagnosed with IPF from 2009 to 2015 was included as the derivation cohort. Information regarding sex, age, the Gender-Age-Physiology (GAP) index, high-resolution computed tomography (HRCT) images, survival status, and pulmonary function parameters including forced vital capacity (FVC), FVC percent predicted (FVC%pred), diffusing capacity of carbon monoxide (DLCO), DLCO percent predicted (DLCO%pred), carbon monoxide transfer coefficient (KCO), KCO percent predicted (KCO%pred) were collected. 31 patients were included in the validation cohort. The Synapse 3D software was used to quantify the fibrotic lung volume (FLV) and total lung volume (TLV). The ratio of FLV to TLV was calculated and labeled CTFLV/TLV%, reflecting the extent of fibrosis. All the physiological variants and CTFLV/TLV% were analyzed for the dimension of survival through both univariate analysis and multivariate analysis. Formulas for predicting the probability of death based on the baseline CTFLV/TLV% were calculated by logistic regression, and validated by the validation cohort.ResultsThe univariate analysis indicated that CTFLV/TLV% along with DLCO%pred, KCO%pred and GAP index were significantly correlated with survival. However, only CTFLV/TLV% was meaningful in the multivariate analysis for prognostic prediction (HR 1.114, 95% CI 1.047–1.184, P = 0.0006), and the best cutoff was 11%, based on receiver operating characteristic (ROC) curve analysis. The survival times for the CTFLV/TLV% ≤ 11% and CTFLV/TLV% > 11% groups were significantly different. Given the CTFLV/TLV% data, the death probability of a patient at 1 year, 3 years and 5 years could be calculated by using a particular formula. The formulas were tested by the validation cohort, showed high sensitivity (88.2%), specificity (92.8%) and accuracy (90.3%).ConclusionQuantitative volume analysis of CT might be useful for evaluating the extent of fibrosis in the lung. The CTFLV/TLV% could be a valuable biomarker for precisely predicting the medium-long term prognosis of individual patients with IPF.