Association between CFTR modulators and changes in iron deficiency markers in cystic fibrosis.

BACKGROUND: Iron deficiency (ID) is a common extrapulmonary manifestation in cystic fibrosis (CF). CF transmembrane conductance regulator (CFTR) modulator therapies, particularly highly-effective modulator therapy (HEMT), have drastically improved health status in a majority of people with CF. We hypothesize that CFTR modulator use is associated with improved markers of ID. METHODS: In a multicenter retrospective cohort study across 4 United States CF centers 2012-2022, the association between modulator therapies and ID laboratory outcomes was estimated using multivariable linear mixed effects models overall and by key subgroups. Summary statistics describe the prevalence and trends of ID, defined a priori as transferrin saturation (TSAT) <20 % or serum iron <60 µg/dL (<10.7 µmol/L). RESULTS: A total of 568 patients with 2571 person-years of follow-up were included in analyses. Compared to off modulator therapy, HEMT was associated with +8.4 % TSAT (95 % confidence interval [CI], +6.3-10.6 %; p < 0.0001) and +34.4 µg/dL serum iron (95 % CI, +26.7-42.1 µg/dL; p < 0.0001) overall; +5.4 % TSAT (95 % CI, +2.8-8.0 %; p = 0.0001) and +22.1 µg/dL serum iron (95 % CI, +13.5-30.8 µg/dL; p < 0.0001) in females; and +11.4 % TSAT (95 % CI, +7.9-14.8 %; p < 0.0001) and +46.0 µg/dL serum iron (95 % CI, +33.3-58.8 µg/dL; p < 0.0001) in males. Ferritin was not different in those taking modulator therapy relative to off modulator therapy. Hemoglobin was overall higher with use of modulator therapy. The prevalence of ID was high throughout the study period (32.8 % in those treated with HEMT). CONCLUSIONS: ID remains a prevalent comorbidity in CF, despite availability of HEMT. Modulator use, particularly of HEMT, is associated with improved markers for ID (TSAT, serum iron) and anemia (hemoglobin).

Familial Variability of Disease Severity in Adult Patients With ADPKD.

Introduction: Autosomal dominant polycystic kidney disease (ADPKD) is the most common monogenic nephropathy and has striking familial variability of disease severity. Methods: To better comprehend familial phenotypic variability, we analyzed clinical and pedigree data on 92 unrelated ADPKD kindreds with ≥2 affected individuals (N = 292) from an Irish population. All probands underwent genetic sequencing. Age at onset of kidney failure (KF), decline in estimated glomerular filtration rate (eGFR), predicting renal outcome in polycystic kidney disease (PROPKD) score, and imaging criteria were used to assess and grade disease severity as mild, intermediate, or severe. One mild and 1 severe case per family defined marked intrafamilial variability of disease severity. Results: Marked intrafamilial variability was observed in at least 13% of the 92 families, with a higher proportion of families carrying PKD1-nontruncating (PKD1-NT) variants. In families with ≥2 members affected by KF, the average intrafamilial age difference was 7 years, and there was no observed difference in intrafamilial variability of age at KF between allelic groups. The prespecified criteria showed marked familial variability in 7.7%, 8.4%, and 24% for age at KF, the PROPKD score, and imaging criteria, respectively. In our multivariate mixed-effects model, the intrafamilial variability in kidney survival was independent of the measured genotypic factors associated with prognosis and survival (P = <0.001). Conclusion: Using objective measures, we quantified marked intrafamilial variability in ADPKD disease phenotype in at least 13% of families. Our findings indicate that intrafamilial phenotypic variability remains incompletely understood and necessitates a more thorough identification of relevant clinical and genotypic factors.

Local heterogeneity of normal lung parenchyma and small airways disease are associated with COPD severity and progression.

BACKGROUND: Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline. METHODS: PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n = 8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model. RESULTS: Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (ß of 0.106, p < 0.001) and VfSAD (ß of 0.065, p = 0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69. CONCLUSIONS: We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Chronic inflammation is associated with worsening working memory performance: Preliminary evidence from a diverse, longitudinal cohort of adolescents and young adults.

Many depressed individuals experience cognitive difficulties that persist when depression is in remission. Inflammation is hypothesized to play a role in cognitive dysfunction in depression; however, many aspects of this relationship are not well characterized. The current study examined whether inflammation is associated with specific cognitive deficits in individuals with a history of depression and with progressively worsening working memory over time. Adolescents who participated in a prospective, longitudinal study of adolescent-onset depression were recruited to complete a follow-up cognitive assessment. The sample was comprised of 82 participants (52.4% female; 37.8% white; 42.7% low socioeconomic status) who were aged 22.61 years (SD = 1.50) at the time of the follow-up cognitive assessment. Prior to the follow-up cognitive assessment, they had completed an average of 6.24 (SD = 1.80) prior annual assessments over 6.24 years (SD = 2.08) as part of the parent longitudinal study in which C-reactive protein (CRP), depressive symptoms, and working memory were assessed repeatedly. First, using linear regression, we tested whether individuals exhibiting inflammation (CRP ≥3 mg/L) at multiple timepoints and a history of likely depression (Children's Depression Inventory ≥19) exhibited differentially worse executive functioning, episodic memory, or psychomotor speed. Second, using hierarchical linear modeling, we tested whether the combination of inflammation and likely past depression was associated with poorer working memory over time. Chronic inflammation was associated with worsening working memory over time, but no significant associations were observed in cross-sectional analyses. These preliminary data indicate that chronic inflammation may lead to progressive decline in working memory over time.

Market making and the production of nurses for export: a case study of India-UK health worker migration.

BACKGROUND: High-income countries increasingly look to the international recruitment of health workers to address domestic shortages, especially from low-income and middle-income countries. We adapt conceptual frameworks from migration studies to examine the networked and commercialised nature of the Indian market for nurse migration to the UK. METHODS: We draw on data from 27 expert interviews conducted with migration intermediaries, healthcare providers and policymakers in India and the UK. FINDINGS: India-UK nurse migration occurs within a complex and evolving market encompassing ways to educate, train and recruit nursing candidates. For-profit actors shape the international orientation of nursing curricula, broker on-the-job training and offer language, exam and specialised clinical training. Rather than merely facilitate travel, these brokers produce both generic, emigratory nurses as well as more customised nurses ready to meet specific shortages in the UK. DISCUSSION: The dialectic of producing emigratory and customised nurses is similar to that seen in the Post-Fordist manufacturing model characterised by flexible specialisation and a networked structure. As the commodity in this case are people attempting to improve their position in life, these markets require attention from health policy makers. Nurse production regimes based on international market opportunities are liable to change, subjecting nurses to the risk of having trained for a market that can no longer accommodate them. The commercial nature of activities further entrenches existing socioeconomic inequalities in the Indian nurse force. Negative repercussions for the source healthcare system can be anticipated as highly qualified, specialised nurses leave to work in healthcare systems abroad.

τ $$ \tau $$ -Inflated beta regression model for censored recurrent events.

This research introduces a multivariate τ $$ \tau $$ -inflated beta regression ( τ $$ \tau $$ -IBR) modeling approach for the analysis of censored recurrent event data that is particularly useful when there is a mixture of (a) individuals who are generally less susceptible to recurrent events and (b) heterogeneity in duration of event-free periods amongst those who experience events. The modeling approach is applied to a restructured version of the recurrent event data that consists of censored longitudinal times-to-first-event in τ $$ \tau $$ length follow-up windows that potentially overlap. Multiple imputation (MI) and expectation-solution (ES) approaches appropriate for censored data are developed as part of the model fitting process. A suite of useful analysis outputs are provided from the τ $$ \tau $$ -IBR model that include parameter estimates to help interpret the (a) and (b) mixture of event times in the data, estimates of mean τ $$ \tau $$ -restricted event-free duration in a τ $$ \tau $$ -length follow-up window based on a patient's covariate profile, and heat maps of raw τ $$ \tau $$ -restricted event-free durations observed in the data with censored observations augmented via averages across MI datasets. Simulations indicate good statistical performance of the proposed τ $$ \tau $$ -IBR approach to modeling censored recurrent event data. An example is given based on the Azithromycin for Prevention of COPD Exacerbations Trial.

Change in motivational bias during treatment predicts outcome in anorexia nervosa.

OBJECTIVE: Reward and punishment sensitivity are known to be altered in anorexia nervosa (AN). Most research has examined these constructs separately although motivated behavior is influenced by considering both the potential for reward and risk of punishment. The present study sought to compare the relative balance of reward and punishment sensitivity in AN versus healthy controls (HCs) and examine whether motivational bias is associated with AN symptoms and treatment outcomes. METHODS: Adolescents and adults with AN (n = 262) in a partial hospitalization program completed the Eating Disorders Examination Questionnaire (EDE-Q), Behavioral Inhibition System/Behavioral Activation System (BIS/BAS) scales, and Sensitivity to Punishment/Sensitivity to Reward Questionnaire (SPSRQ) at admission and discharge. HCs (HC; n = 90) completed the BIS/BAS and SPSRQ. Motivational Bias Scores were calculated to reflect the dominance of reward versus punishment sensitivity. RESULTS: Individuals with AN demonstrated significantly greater bias toward punishment sensitivity than HC. In AN, a bias toward punishment was associated with higher EDE-Q Global score at admission. Change in motivational bias during treatment predicted EDE-Q Global scores, but not BMI, at discharge, with greater increases in reward sensitivity or greater decreases in punishment sensitivity during treatment predicting lower eating pathology. Similar findings were observed using the BIS/BAS and SPSRQ. DISCUSSION: Change in motivational bias during treatment is associated with improved outcomes in AN. However, it appears that much of the change in motivational bias can be attributed to changes in punishment sensitivity, rather than reward sensitivity. Future research should examine the mechanisms underlying punishment sensitivity decreases during treatment. PUBLIC SIGNIFICANCE: Sensitivity to reward and punishment may be important treatment targets for individuals with anorexia nervosa (AN). To date, most research has considered reward and punishment sensitivity separately, rather than examining their relationship to each other. We found that the balance of reward and punishment sensitivity (i.e., motivational bias) differs between healthy controls and those with AN and that this bias is associated with eating disorder symptoms and treatment outcome.

Machine Learning of Plasma Proteomics Classifies Diagnosis of Interstitial Lung Disease.

RATIONALE: Distinguishing connective tissue disease associated interstitial lung disease (CTD-ILD) from idiopathic pulmonary fibrosis (IPF) can be clinically challenging. OBJECTIVES: Identify proteins that separate and classify CTD-ILD from IPF patients. METHODS: Four registries with 1247 IPF and 352 CTD-ILD patients were included in analyses. Plasma samples were subjected to high-throughput proteomics assays. Protein features were prioritized using Recursive Feature Elimination (RFE) to construct a proteomic classifier. Multiple machine learning models, including Support Vector Machine, LASSO regression, Random Forest (RF), and imbalanced-RF, were trained and tested in independent cohorts. The validated models were used to classify each case iteratively in external datasets. MEASUREMENT AND MAIN RESULTS: A classifier with 37 proteins (PC37) was enriched in biological process of bronchiole development and smooth muscle proliferation, and immune responses. Four machine learning models used PC37 with sex and age score to generate continuous classification values. Receiver-operating-characteristic curve analyses of these scores demonstrated consistent Area-Under-Curve 0.85-0.90 in test cohort, and 0.94-0.96 in the single-sample dataset. Binary classification demonstrated 78.6%-80.4% sensitivity and 76%-84.4% specificity in test cohort, 93.5%-96.1% sensitivity and 69.5%-77.6% specificity in single-sample classification dataset. Composite analysis of all machine learning models confirmed 78.2% (194/248) accuracy in test cohort and 82.9% (208/251) in single-sample classification dataset. CONCLUSIONS: Multiple machine learning models trained with large cohort proteomic datasets consistently distinguished CTD-ILD from IPF. Identified proteins involved in immune pathways. We further developed a novel approach for single sample classification, which could facilitate honing the differential diagnosis of ILD in challenging cases and improve clinical decision-making.

Topologic Parametric Response Mapping Identifies Tissue Subtypes Associated with Emphysema Progression.

RATIONALE AND OBJECTIVES: Small airways disease (SAD) and emphysema are significant components of chronic obstructive pulmonary disease (COPD), a heterogenous disease where predicting progression is difficult. SAD, a principal cause of airflow obstruction in mild COPD, has been identified as a precursor to emphysema. Parametric Response Mapping (PRM) of chest computed tomography (CT) can help distinguish SAD from emphysema. Specifically, topologic PRM can define local patterns of both diseases to characterize how and in whom COPD progresses. We aimed to determine if distribution of CT-based PRM of functional SAD (fSAD) is associated with emphysema progression. MATERIALS AND METHODS: We analyzed paired inspiratory-expiratory chest CT scans at baseline and 5-year follow up in 1495 COPDGene subjects using topological analyses of PRM classifications. By spatially aligning temporal scans, we mapped local emphysema at year five to baseline lobar PRM-derived topological readouts. K-means clustering was applied to all observations. Subjects were subtyped based on predominant PRM cluster assignments and assessed using non-parametric statistical tests to determine differences in PRM values, pulmonary function metrics, and clinical measures. RESULTS: We identified distinct lobar imaging patterns and classified subjects into three radiologic subtypes: emphysema-dominant (ED), fSAD-dominant (FD), and fSAD-transition (FT: transition from healthy lung to fSAD). Relative to year five emphysema, FT showed rapid local emphysema progression (-57.5% ± 1.1) compared to FD (-49.9% ± 0.5) and ED (-33.1% ± 0.4). FT consisted primarily of at-risk subjects (roughly 60%) with normal spirometry. CONCLUSION: The FT subtype of COPD may allow earlier identification of individuals without spirometrically-defined COPD at-risk for developing emphysema.

'Not in it for huge profits but because it's right': The contested moral economies of UK-India exports in health worker education and training.

While the growth of global markets in health-related services may have significant consequences for healthcare provisioning and training, it has received relatively little attention from the social sciences. This article examines UK-India, and specifically England-India, exports in health worker education and training as one such global market, drawing on sociological scholarship on moral economies to understand how trading in this field is constructed and legitimated by the individuals and organisations involved, what tensions evolve, and what is at stake in them. We employ a qualitative mixed methods approach using publicly available materials on existing UK-India collaborations and primary data from interviews with key stakeholders in India and the UK, including government departments, arms-length bodies, NHS Trusts, trade associations and private providers. Our analysis illustrates the key discursive strategies used to legitimate engagement in these markets, and the complex and contested moral economies unfolding between and across these stakeholders and contexts. Not least, we demonstrate the conflicting moral sentiments and the boundary work required to realise commodification. Situating cross-border trade in health worker education and training in a moral economy framework thus illuminates the social context and moral worlds in which this evolving trade is embedded.

Risk Factors for Chronic Obstructive Pulmonary Disease Exacerbations among Individuals without a History of Recent Exacerbations: A COPDGene Analysis.

Rationale: Acute exacerbations of chronic obstructive pulmonary disease (AE-COPD) are detrimental events in the natural history of COPD, but the risk factors associated with future exacerbations in the absence of a history of recent exacerbations are not fully understood. Objectives: To identify risk factors for COPD exacerbations among participants in the Genetic Epidemiology of COPD Study (COPDGene) without a history of exacerbation in the previous year. Methods: We identified participants with a smoking history enrolled in COPDGene who had COPD (defined as forced expiratory volume in 1 second [FEV1]/forced vital capacity < 0.70), no exacerbation in the year before their second study site visit, and who completed at least one longitudinal follow-up questionnaire in the following 36 months. We used univariable and multivariable zero-inflated negative binomial regression models to identify risk factors associated with increased rates of exacerbation. Each risk factor's regression coefficient (ß) was rounded to the nearest 0.25 and incorporated into a graduated risk score. Results: Among the 1,528 participants with a smoking history and COPD enrolled in COPDGene without exacerbation in the year before their second study site visit, 508 participants (33.2%) had at least one moderate or severe exacerbation in the 36 months studied. Gastroesophageal reflux disease, chronic bronchitis, high symptom burden (as measured by Modified Medical Research Council Dyspnea Scale and COPD Assessment Test), and lower FEV1% predicted were associated with an increased risk of exacerbation. Each 1-point increase in our graduated risk score was associated with a 25-30% increase in exacerbation rate in the 36 months studied. Conclusions: In patients with COPD without a recent history of exacerbations, gastroesophageal reflux disease, chronic bronchitis, high symptom burden, and lower lung function are associated with increased risk of future exacerbation using a simple risk score that can be used in clinical practice.

Calcium and Phosphate Disorders: Core Curriculum 2024.

Maintaining normal calcium and phosphate homeostasis is essential for optimal cellular, metabolic, and organ function. Parathyroid hormone, fibroblast growth factor 23, and 1,25-dihydroxyvitamin D regulate calcium and phosphate homeostasis via multiple interlinked feedback loops, receptors, ion channels, and transporters. Following an initial overview of the stimuli and effects of the different hormonal regulators, this installment of AJKD's Core Curriculum in Nephrology reviews the physiology and pathophysiology of calcium and phosphate disorders through the lens of a series of illustrative cases. The cases span clinical conundrums commonly encountered by nephrologists in their daily clinical practice and other less common disorders. Some of the cases present in the outpatient clinic setting and others in the inpatient hospital setting. Patients with normal kidney function, chronic kidney disease, kidney failure, and acute kidney injury are all represented. Some of the disorders are iatrogenic, and some are due to native disease. All demonstrate key aspects of pathophysiology that are essential knowledge for nephrology clinicians of all career stages.

Comparison of Pirfenidone and Nintedanib: Post Hoc Analysis of the CleanUP-IPF Study.

BACKGROUND: Antifibrotics are effective in slowing FVC decline in idiopathic pulmonary fibrosis (IPF). However, whether antifibrotic type is differentially associated with FVC decline remains inconclusive. RESEARCH QUESTION: Are there significant differences in 12-month FVC decline between pirfenidone and nintedanib? STUDY DESIGN AND METHODS: A post hoc analysis was performed using the Clinical Efficacy of Antimicrobial Therapy Strategy Using Pragmatic Design in IPF (CleanUP-IPF) trial (No. NCT02759120). Participants who reported using pirfenidone or nintedanib on enrollment into the trial were in the primary analysis. Spirometry was scheduled at baseline and the 12- and 24-month study visits. Linear mixed-effects models with random intercept and slope were used to examine changes in FVC over time. Models were adjusted for age, sex, smoking history, coronary artery disease history, baseline FVC, and 12-month spline term. Survival and nonelective respiratory hospitalization by antifibrotic type were determined using Cox regression models with adjustment for age, sex, smoking history, coronary artery disease history, and baseline FVC and diffusing capacity for carbon monoxide. RESULTS: Out of the 513 participants with IPF randomized in the CleanUP-IPF trial, 407 reported using pirfenidone (n = 264, 65%) or nintedanib (n = 143, 35%). The pirfenidone group had more participants with a history of coronary artery disease than the nintedanib group (34.1% vs 20.3%, respectively). Patients treated with nintedanib had a higher 12-month visit FVC than patients treated with pirfenidone (mean difference, 106 mL; 95% CI, 34-178). This difference was attenuated at the 24-month study visit. There were no significant differences in overall survival and nonelective respiratory hospitalization between the pirfenidone- and nintedanib-treated groups. INTERPRETATION: Patients with IPF who used nintedanib had a slower 12-month FVC decline than pirfenidone in a post hoc analysis of a clinical trial.

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. OBJECTIVE: 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 used to derive a proteomic signature of TFS. MAIN RESULTS: Of 2921 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 combining cohorts, validated proteins with strongest TFS association were latent-transforming growth factor beta-binding protein 2 (HR 2.43, 95% CI 2.09-2.82), collagen alpha-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 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.

Establishing links between safety culture, climate, behaviors, and outcomes of long-haul truck drivers.

INTRODUCTION: This paper examines the safety relationships between safety culture, safety influences, safety climate, and safety outcomes for long-haul truck drivers. The relationships focus on the intersection of the electronic logging device (ELD) technology, regulations, and truck drivers that fall into the lone-worker category. RESULTS: Through research questions, links between safety culture and safety climate were established with links between the layers. CONCLUSIONS: The implementation of the ELD system was associated with safety outcomes.

Quantitative CT of Normal Lung Parenchyma and Small Airways Disease Topologies are Associated With COPD Severity and Progression.

Objectives: Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients, and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline. Materials and Methods: PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n=8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model. Results: Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (ß of 0.106, p<0.001) and VfSAD (ß of 0.065, p=0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69. Conclusions: We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Machine learning for screening of at-risk, mild and moderate COPD patients at risk of FEV1 decline: results from COPDGene and SPIROMICS.

Purpose: The purpose of this study was to train and validate machine learning models for predicting rapid decline of forced expiratory volume in 1 s (FEV1) in individuals with a smoking history at-risk-for chronic obstructive pulmonary disease (COPD), Global Initiative for Chronic Obstructive Lung Disease (GOLD 0), or with mild-to-moderate (GOLD 1-2) COPD. We trained multiple models to predict rapid FEV1 decline using demographic, clinical and radiologic biomarker data. Training and internal validation data were obtained from the COPDGene study and prediction models were validated against the SPIROMICS cohort. Methods: We used GOLD 0-2 participants (n = 3,821) from COPDGene (60.0 ± 8.8 years, 49.9% male) for variable selection and model training. Accelerated lung function decline was defined as a mean drop in FEV1% predicted of > 1.5%/year at 5-year follow-up. We built logistic regression models predicting accelerated decline based on 22 chest CT imaging biomarker, pulmonary function, symptom, and demographic features. Models were validated using n = 885 SPIROMICS subjects (63.6 ± 8.6 years, 47.8% male). Results: The most important variables for predicting FEV1 decline in GOLD 0 participants were bronchodilator responsiveness (BDR), post bronchodilator FEV1% predicted (FEV1.pp.post), and CT-derived expiratory lung volume; among GOLD 1 and 2 subjects, they were BDR, age, and PRMlower lobes fSAD. In the validation cohort, GOLD 0 and GOLD 1-2 full variable models had significant predictive performance with AUCs of 0.620 ± 0.081 (p = 0.041) and 0.640 ± 0.059 (p < 0.001). Subjects with higher model-derived risk scores had significantly greater odds of FEV1 decline than those with lower scores. Conclusion: Predicting FEV1 decline in at-risk patients remains challenging but a combination of clinical, physiologic and imaging variables provided the best performance across two COPD cohorts.