Predict Lung Function Research Articles

Predictors of a Minimal Clinically Important Difference Following Omalizumab Treatment in Adult Patients With Severe Allergic Asthma.

Several factors have been found to be predictors of a good response following omalizumab treatment in patients with severe allergic asthma (SAA). However, it remains unclear whether clinical characteristics can predict a minimal clinically important difference (MCID) following omalizumab treatment in this population. Therefore, the aim of this study was to investigate the features associated with an MCID following omalizumab treatment in adult patients with SAA. Of the 124 participants enrolled in this retrospective, cross-sectional study, 94, 103, 20 and 53 achieved the MCID following treatment with omalizumab and were considered to be responders of exacerbation reduction (no exacerbation during the 1-year follow-up period or ≧50% reduction in exacerbations from baseline), oral corticosteroid (OCS) sparing (no use of OCS to control asthma during the study period or a reduction of the monthly OCS maintenance dose to <50% of baseline), lung function (an increase of ≧230 ml in the forced expiratory volume in 1 s from baseline) and asthma control (an increase of ≧3 points in the asthma control test score from baseline), respectively. Normal weight [<25 vs. ≧30 kg/m2, odds ratio (OR) = 3.86, p = 0.024] was predictive of a responder of reduction in exacerbations following omalizumab treatment while subjects with a blood eosinophil level of <300 cells/μL (<300 vs. ≧300 cells/μL, OR = 5.81, p = 0.001) were more likely to exhibit an MCID in OCS sparing. No factor was found to be a predictor of lung function or asthma control. When choosing treatment for adult patients with SAA, our findings may help to select those who may benefit the most from omalizumab treatment.

Respiratory symptoms and lung function in patients treated for pulmonary tuberculosis in Malawi: a prospective cohort study

RationalePulmonary tuberculosis (PTB) can cause post-TB lung disease (PTLD) associated with respiratory symptoms, spirometric and radiological abnormalities. Understanding of the predictors and natural history of PTLD is limited.ObjectivesTo describe the...

Using chest CT scan and unsupervised machine learning for predicting and evaluating response to lumacaftor-ivacaftor in people with cystic fibrosis.

Lumacaftor-ivacaftor is a cystic fibrosis transmembrane conductance regulator (CFTR) modulator known to improve clinical status in people with cystic fibrosis (CF). This study aimed to assess lung structural changes after one year of lumacaftor-ivacaftor treatment, and to use unsupervised machine learning to identify morphological phenotypes of lung disease that are associated with response to lumacaftor-ivacaftor. Adolescents and adults with CF from the French multicenter real-world prospective observational study evaluating the first year of treatment with lumacaftor-ivacaftor were included if they had pretherapeutic and follow-up chest computed tomography (CT)-scans available. CT scans were visually scored using a modified Bhalla score. A k-mean clustering method was performed based on 120 radiomics features extracted from unenhanced pretherapeutic chest CT scans. A total of 283 patients were included. The Bhalla score significantly decreased after 1 year of lumacaftor-ivacaftor (-1.40±1.53 points compared with pretherapeutic CT; p<0.001). This finding was related to a significant decrease in mucus plugging (-0.35±0.62 points; p<0.001), bronchial wall thickening (-0.24±0.52 points; p<0.001) and parenchymal consolidations (-0.23±0.51 points; p<0.001). Cluster analysis identified 3 morphological clusters. Patients from cluster C were more likely to experience an increase in percent predicted forced expiratory volume in 1 sec (ppFEV1) ≥5 under lumacaftor-ivacaftor than those in the other clusters (54% of responders versus 32% and 33%; p=0.01). One year treatment with lumacaftor-ivacaftor was associated with a significant visual improvement of bronchial disease on chest CT. Radiomics features on pretherapeutic CT scan may help in predicting lung function response under lumacaftor-ivacaftor.

Development of a Blood-based Transcriptional Risk Score for Chronic Obstructive Pulmonary Disease.

Rationale: The ability of peripheral blood biomarkers to assess chronic obstructive pulmonary disease (COPD) risk and progression is unknown. Genetics and gene expression may capture important aspects of COPD-related biology that predict disease activity. Objectives: Develop a transcriptional risk score (TRS) for COPD and assess the contribution of the TRS and a polygenic risk score (PRS) for disease susceptibility and progression. Methods: We randomly split 2,569 COPDGene (Genetic Epidemiology of COPD) participants with whole-blood RNA sequencing into training (n = 1,945) and testing (n = 624) samples and used 468 ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points) COPD cases with microarray data for replication. We developed a TRS using penalized regression (least absolute shrinkage and selection operator) to model FEV1/FVC and studied the predictive value of TRS for COPD (Global Initiative for Chronic Obstructive Lung Disease 2-4), prospective FEV1 change (ml/yr), and additional COPD-related traits. We adjusted for potential confounders, including age and smoking. We evaluated the predictive performance of the TRS in the context of a previously derived PRS and clinical factors. Measurements and Main Results: The TRS included 147 transcripts and was associated with COPD (odds ratio, 3.3; 95% confidence interval [CI], 2.4-4.5; P < 0.001), FEV1 change (β, -17 ml/yr; 95% CI, -28 to -6.6; P = 0.002), and other COPD-related traits. In ECLIPSE cases, we replicated the association with FEV1 change (β, -8.2; 95% CI, -15 to -1; P = 0.025) and the majority of other COPD-related traits. Models including PRS, TRS, and clinical factors were more predictive of COPD (area under the receiver operator characteristic curve, 0.84) and annualized FEV1 change compared with models with one risk score or clinical factors alone. Conclusions: Blood transcriptomics can improve prediction of COPD and lung function decline when added to a PRS and clinical risk factors.

Fast decliner phenotype of chronic obstructive pulmonary disease (COPD): applying machine learning for predicting lung function loss

BackgroundChronic obstructive pulmonary disease (COPD) is a heterogeneous group of lung conditions challenging to diagnose and treat. Identification of phenotypes of patients with lung function loss may allow early intervention...

Efficacy of the Segment-Counting Method in Predicting Lung Function and Volume Following Stapler-Based Thoracoscopic Segmentectomy.

Purpose: To investigate the accuracy of a segment-counting method in predicting lung function and volume after stapler-based thoracoscopic segmentectomy in comparison with lobectomy.Methods: Between 2014 and 2018, patients who underwent these procedures were retrospectively reviewed. Thoracic computed tomography and spirometry data before and 1 year after the surgery were assessed. We evaluated the differences between the predicted values using a segment-counting method and the actual postoperative values for lung function and volume in each group. Sub-analyses were also performed to assess the impact of the number of staples and resected segments in predicting patient outcomes.Results: We included 116 patients (segmentectomy, 69; lobectomy, 47). Actual postoperative lung function and volume values matched the predicted values in the stapler-based segmentectomy group, and significantly exceeded the predictions in the lobectomy group (P <0.01). Sub-analyses revealed lower postoperative lung function values than predicted existed after single segmentectomy, with an odds ratio of 3.29 (95% confidence interval: 1.02–10.70, P = 0.04) in a multivariable analysis. The degree of predicted error regarding lung function was negligible.Conclusions: The segment-counting method was useful in predicting lung function after stapler-based thoracoscopic segmentectomy. Segmentectomy rarely yielded lower- than-predicted lung function and volume values.

New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project.

Several predictive models have been proposed to understand the microbial risk factors associated with cystic fibrosis (CF) progression. Very few have integrated fungal airways colonisation, which is increasingly recognized as a key player regarding CF progression. To assess the association between the percent predicted forced expiratory volume in 1 s (ppFEV1) change and the fungi or bacteria identified in the sputum, 299 CF patients from the “MucoFong” project were included and followed-up with over two years. The relationship between the microorganisms identified in the sputum and ppFEV1 course of patients was longitudinally analysed. An adjusted linear mixed model analysis was performed to evaluate the effect of a transient or chronic bacterial and/or fungal colonisation at inclusion on the ppFEV1 change over a two-year period. Pseudomonas aeruginosa, Achromobacter xylosoxidans, Stenotrophomonas maltophilia, and Candida albicans were associated with a significant ppFEV1 decrease. No significant association was found with other fungal colonisations. In addition, the ppFEV1 outcome in our model was 11.26% lower in patients presenting with a transient colonisation with non-pneumoniae Streptococcus species compared to other patients. These results confirm recently published data and provide new insights into bacterial and fungal colonisation as key factors for the assessment of lung function decline in CF patients.

Prognostic implications of differences in forced vital capacity in black and white US adults: Findings from NHANES III with long-term mortality follow-up.

BackgroundBecause Forced Vital Capacity (FVC) is reduced in Black relative to White Americans of the same age, sex, and height, standard lung function prediction equations assign a lower "normal" range for Black patients. The prognostic implications of this race correction are uncertain.MethodsWe analyzed 5,294 White and 3,743 Black participants age 20–80 in NHANES III, a nationally-representative US survey conducted 1988–94, which we linked to the National Death Index to assess mortality through December 31, 2015. We calculated the FVC-percent predicted among Black and White participants, first applying NHANES III White prediction equations to all persons, and then using standard race-specific prediction equations. We used Cox proportional hazard models to calculate the association between race and all-cause mortality without and with adjustment for FVC (using each FVC metric), smoking, socioeconomic factors, and comorbidities.FindingsBlack participants’ age- and sex-adjusted mortality was greater than White participants (HR 1.46; 95%CI:1.29, 1.65). With adjustment for FVC in liters (mean 3.7 L for Black participants, 4.3 L for White participants) or FVC percent-predicted using White equations for everyone, Black race was no longer independently predictive of higher mortality (HR∼1.0). When FVC-percent predicted was “corrected” for race, Black individuals again showed increased mortality hazard. Deaths attributed to chronic respiratory disease were infrequent for both Black and White individuals.InterpretationLower FVC in Black people is associated with elevated risk of all-cause mortality, challenging the standard assumption about race-based normal limits. Black-White disparities in FVC may reflect deleterious social/environmental exposures, not innate differences.FundingNo funding.

Nutritional status and intake in patients with non-cystic fibrosis bronchiectasis (NCFB) - a cross sectional study

Bronchiectasis is a heterogeneous, chronic respiratory condition, in which the role of nutrition remains unclear and nutritional guidance is lacking. Few studies have explored the role of nutrition in disease management, and little is known about nutritional requirements during periods of stability or metabolic stress. The aim of this study was to characterise nutritional status and intakes in a cohort of patients and identify potential associations with body composition and functional capacity. A prospective observational cohort study was undertaken in an adult population (>17 years). Bronchiectasis was confirmed by high-resolution computerised tomography (HRCT). Anthropometric (weight, height, Body Mass Index (BMI), triceps skinfold thickness (TSF), mid upper-arm circumference (MUAC) and mid arm muscle circumference (MAMC)] lung function and nutritional intakes were measured. Results were analysed as a whole and by disease aetiology [primary ciliary dyskinesia (PCD), Idiopathic cause (IC), bronchiectasis in association with asthma and other] and associations tested. In total, 128 participants (65.5% female) completed the study. Median handgrip strength (HGS) in the total sample was only 66.5% (IQR 60.5-89.8) of reference population norms and was low for those with PCD [58.0% (IQR 43.5-70.0))]. Univariate regression indicated that BMI was a statistically significant predictor of lung function in the whole population with HGS and weight identified as statistically significant predictors of lung function in PCD. The total population and each sub-group failed to meet estimated average requirements for energy but exceeded the Reference nutrient intake (RNI) for protein. Vitamin D was consistently <35% of the RNI. BMI lay within normal to overweight ranges within the whole population and sub-groups, but masked important functional, body composition and nutritional deficits. This was particularly so within a younger sub-group with PCD, who had impaired muscle function, when compared to other causal and associative diseases.

Transcriptome analysis reveals key genes modulated by ALK5 inhibition in a bleomycin model of systemic sclerosis.

ObjectiveSSc is a rheumatic autoimmune disease affecting roughly 20 000 people worldwide and characterized by excessive collagen accumulation in the skin and internal organs. Despite the high morbidity and mortality associated with SSc, there are no approved disease-modifying agents. Our objective in this study was to explore transcriptomic and model-based drug discovery approaches for SSc.MethodsIn this study, we explored the molecular basis for SSc pathogenesis in a well-studied mouse model of scleroderma. We profiled the skin and lung transcriptomes of mice at multiple timepoints, analysing the differential gene expression that underscores the development and resolution of bleomycin-induced fibrosis.ResultsWe observed shared expression signatures of upregulation and downregulation in fibrotic skin and lung tissue, and observed significant upregulation of key pro-fibrotic genes including GDF15, Saa3, Cxcl10, Spp1 and Timp1. To identify changes in gene expression in responses to anti-fibrotic therapy, we assessed the effect of TGF-β pathway inhibition via oral ALK5 (TGF-β receptor I) inhibitor SB525334 and observed a time-lagged response in the lung relative to skin. We also implemented a machine learning algorithm that showed promise at predicting lung function using transcriptome data from both skin and lung biopsies.ConclusionThis study provides the most comprehensive look at the gene expression dynamics of an animal model of SSc to date, provides a rich dataset for future comparative fibrotic disease research, and helps refine our understanding of pathways at work during SSc pathogenesis and intervention.

Complication and lung function impairment prediction using perfusion and computed tomography air trapping (CLIPPCAIR): protocol for the development and validation of a novel multivariable model for the prediction of post-resection lung function.

BackgroundRecent advancements in computed tomography (CT) scanning and post processing have provided new means of assessing factors affecting respiratory function. For lung cancer patients requiring resection, and especially those with respiratory comorbidities such as chronic obstructive pulmonary disease (COPD), the ability to predict post-operative lung function is a crucial step in the lung cancer operability assessment. The primary objective of the CLIPPCAIR study is to use novel CT data to develop and validate an algorithm for the prediction of lung function remaining after pneumectomy/lobectomy.MethodsTwo sequential cohorts of non-small cell lung cancer patients requiring a pre-resection CT scan will be recruited at the Montpellier University Hospital, France: a test population (N=60) on which predictive models will be developed, and a further model validation population (N=100). Enrolment will occur during routine pre-surgical consults and follow-up visits will occur 1 and 6 months after pneumectomy/lobectomy. The primary outcome to be predicted is forced expiratory volume in 1 second (FEV1) six months after lung resection. The baseline CT variables that will be used to develop the primary multivariable regression model are: expiratory to inspiratory ratios of mean lung density (MLDe/i for the total lung and resected volume), the percentage of voxels attenuating at less than ‒950 HU (PVOX‒950 for the total lung and resected volume) and the ratio of iodine concentrations for the resected volume over that of the total lung. The correlation between predicted and real values will be compared to (and is expected to improve upon) that of previously published methods. Secondary analyses will include the prediction of transfer factor for carbon monoxide (TLCO) and complications in a similar fashion. The option to explore further variables as predictors of post-resection lung function or complications is kept open.DiscussionCurrent methods for estimating post-resection lung function are imperfect and can add assessments (such as scintigraphy) to the pre-surgical workup. By using CT imaging data in a novel fashion, the results of the CLIPPCAIR study may not only improve such estimates, it may also simplify patient pathways.Trial registrationClinicaltrials.gov (NCT03885765).

Does peripheral blood eosinophil count predict lung function improvement in adult subjects with asthma?

Previous studies have investigated the contribution of the eosinophilic phenotype, as defined by the peripheral blood eosinophil count, in predicting asthma outcomes. There is evidence that the eosinophilic phenotype predicts uncontrolled symptoms and asthma exacerbations.1,2 We are aware of no prospective study evaluating whether the eosinophilic phenotype is a useful biomarker for predicting lung function trends in subjects with asthma who have used maintenance therapy. This is an important issue, because predicting loss of lung function is a meaningful goal of asthma monitoring, as lung function decline leads to irreversible airway obstruction and worse clinical outcomes.

Lung function decline is associated with serum uric acid in Korean health screening individuals

We performed a retrospective cohort study of 19,237 individuals who underwent at least three health screenings with follow-up periods of over 5 years to find a routinely checked serum marker that predicts lung function decline. Using linear regression models to analyze associations between the rate of decline in the forced expiratory volume in 1 s (FEV1) and the level of 10 serum markers (calcium, phosphorus, uric acid, total cholesterol, total protein, total bilirubin, alkaline phosphatase, aspartate aminotransferase, creatinine, and C-reactive protein) measured at two different times (at the first and third health screenings), we found that an increased uric acid level was significantly associated with an accelerated FEV1 decline (P = 0.0014 and P = 0.037, respectively) and reduced FEV1 predicted % (P = 0.0074 and P = 8.64 × 10–7, respectively) at both visits only in non-smoking individuals. In addition, we confirmed that accelerated forced vital capacity (FVC) and FEV1/FVC ratio declines were observed in non-smoking individuals with increased serum uric acid levels using linear mixed models. The serum uric acid level thus potentially predicts an acceleration in lung function decline in a non-smoking general population.

Association Between Body Composition and Pulmonary Function Tests Among Health Care Workers in Iran

Background: Why is bodyweight not a predictor of lung function, while height, sex, race, and age are predictors of lung capacity and function? In this study, we want to investigate the association between body composition and pulmonary function. And, as much as possible, answer the question of why bodyweight is not predictive of lung function. Methods: This cross-sectional study was performed among 2967 employees of Tehran University of Medical Sciences (TUMS) who participated in the TUMS Employees Cohort (TEC) study. The body composition of the participants was measured using the Bioelectrical Impedance Analysis (BIA) method. Anthropometric variables were also measured as a confounder. The pulmonary function of participants was assessed by a forced spirometry test. Results: The correlation of BIA values including fat-free mass and total body water with a pulmonary function such as FEV1, FVC, and FEF25-75is higher than most anthropometric values such as weight, wrist circumference, and the waist to hip ratio. Also, in regression analysis, age and sex had an association with pulmonary function, but the weight did not show a significant relationship. On the other hand, fat-free mass and visceral fat were significantly associated with pulmonary function. One is direct and the other is inverse. Conclusion: We observed a negative association between visceral fat and pulmonary function tests and a direct association between Fat-free mass pulmonary function tests (FEV1 and FVC) adjusted for age, sex, and anthropometric indices.

Sex-specific longitudinal association of DNA methylation with lung function.

Investigating whether DNA methylation (DNA-M) at an earlier age is associated with lung function at a later age and whether this relationship differs by sex could enable prediction of future lung function deficit.A training/testing-based technique was used to screen 402 714 cytosine-phosphate-guanine dinucleotide sites (CpGs) to assess the longitudinal association of blood-based DNA-M at ages 10 and 18 years with lung function at 18 and 26 years, respectively, in the Isle of Wight birth cohort (IOWBC). Multivariable linear mixed models were applied to the CpGs that passed screening. To detect differentially methylated regions (DMRs), DMR enrichment analysis was conducted. Findings were further examined in the Avon Longitudinal Study of Parents and Children (ALSPAC). Biological relevance of the identified CpGs was assessed using gene expression data.DNA-M at eight CpGs (five CpGs with forced expiratory volume in 1 s (FEV1) and three CpGs with FEV1/forced vital capacity (FVC)) at an earlier age was associated with lung function at a later age regardless of sex, while at 13 CpGs (five CpGs with FVC, three with FEV1 and five with FEV1/FVC), the associations were sex-specific (pFDR<0.05) in IOWBC, with consistent directions of association in ALSPAC (IOWBC-ALSPAC consistent CpGs). cg16582803 (WNT10A) and cg14083603 (ZGPAT) were replicated in ALSPAC for main and sex-specific effects, respectively. Among IOWBC-ALSPAC consistent CpGs, DNA-M at cg01376079 (SSH3) and cg07557690 (TGFBR3) was associated with gene expression both longitudinally and cross-sectionally. In total, 57 and 170 DMRs were linked to lung function longitudinally in males and females, respectively.CpGs showing longitudinal associations with lung function have the potential to serve as candidate markers in future studies on lung function deficit prediction.

Persistence of both reversible airway obstruction and higher blood eosinophils may predict lung function decline in severe asthma.

This study analysed whether the persistence of both reversible airway obstruction (RAO) and elevated BE counts was associated to reduced asthma control and accelerated lung function decline in treated severe asthmatics. About 202 severe asthmatics were studied after 12-120months of step-5 treatment associated to anti-IgE therapy. Following treatments, reversibility tests, after inhaling 400 mcg of Salbutamol, were performed. FEV1 >12% or ≤12% changes differentiated RAO+ from RAO- subjects. Blood eosinophil (BE) counts after treatment were considered. Pre-/post-treatment bronchodilator FEV1 % and ACT were lower (61% [50-71], 74.4% [62.5-83.7] and 20[18-22]), whereas BE were higher (380 cells/µl [170-590]) in RAO+ compared to RAO- subjects (77% [64-88], p=0.0001, 81.8% [66.1-94.3], p=0.0001, 21[18-23], p=0.045 and 230 cells/µl [80-360], p=0.003). A negative relationship between SABA-induced FEV1 % changes and pre-bronchodilator FEV1 % (β=-0.551%; p=0.0001) and ACT (β=-0.059; p=0.038) was found. Conversely, post-treatment BE levels were positively related (β=145.565 cells/µl; p=0.003) to FEV1 >12% increases. A rising trend of pre-/post-bronchodilator FEV1 % in time was observed in RAO- subjects with BE<300 cells/µl. Conversely, we highlighted significant declining tendencies of pre/post-bronchodilator FEV1 % in RAO+ patients with BE>300 cells/µl reaching lower values after more than 36months of step-5 treatment (59.6% [39.9-72.1] vs 74[66.5-89.2] of RAO+ individuals with BE<300 cells/µl [p=0.026] and 81.6% [66.1-91.8] of RAO-subjects with BE>300 cells/µl [p=0.009]). Persistent SABA-induced FEV1 >12%, especially when associated to BE>300 cells/ml, may be a marker of accelerated lung function decline in severe asthmatics despite maximal step-5 treatment. The highest bronchodilation associated to the lowest BE levels should be the main goal of asthma treatment to prevent such decline.

Relative influence of overall and central body adiposity on lung function and development of lung function predictive model for adolescents in Tripura

Background: Population-specific reference values are necessary for maintaining the reliability of pulmonary function evaluation. There are very few studies that have included body adiposity markers as the predictors of lung function, instead of age and height. Objectives: A gender-specific lung function predictive model of adolescents was developed using overall and central adiposity markers. The relative influences of both markers on pulmonary functions were also evaluated. Methods: Anthropometric and pulmonary function parameters of the subjects were recorded. The percentage body fat, fat mass (FM), fat-free mass (FFM), and body density were calculated. Statistical analysis was done using SPSS 16.0. Results: Significant differences between sexes for anthropometric measures were observed. The mean values of waist circumference (71.94 ± 2.33 mm for female vs. 71.37 ± 2.25 mm for male; P < 0.0005), body composition (5.83 ± 1.27 mm for female vs. 4.71 ± 0.83 mm for male; P < 0.0005), and sum of skinfolds (35.71 ± 4.48 mm for female vs. 34.66 ± 3.01 mm for male; P < 0.0005) were higher in female in comparison to male. Males had significantly higher subscapular skinfold thickness (9.39 ± 1.05 mm, compared with 9.17 ± 1.05 mm for females; P = 0.003). Mean values of central adiposity markers such as waist-hip-ratio (0.88 ± 0.01 for female vs. 0.87 ± 0.01, for male; P < 0.0005) and waist-to-height ratio (0.47 ± 0.004 for female vs. 0.47 ± 0.01, for male; P = 0.002) as well as overall adiposity markers such as percentage body fat (23.81 ± 1.11 for female vs. 18.98 ± 1.20, for male; P = 0.001) and FM (11.27 ± 1.83 kg for female vs. 8.94 ± 1.16, kg for male; P < 0.0005) were significantly higher in female compared to male. Mean FFM (38.17 ± 4.38 mm for male vs. 35.81 ± 3.93 mm for female; P < 0.0005) was significantly higher in male. All the pulmonary function parameters were significantly higher in male compared to female. Results showed the existence of significant mean differences in pulmonary function measures across the three body fat percentage groups in both sexes, with linear decrease of mean values of lung function with the increase of body fat percentage. Post hoc pair-wise multiple comparisons were done to compare the lung function between groups. Conclusion: Overall adiposity marker would explain variation in the pulmonary function parameters better than central adiposity markers in adolescents of both sexes.

Novel non-invasive particles in exhaled air method to explore the lining fluid of small airways—a European population-based cohort study

IntroductionRespiratory tract lining fluid of small airways mainly consists of surfactant that can be investigated by collection of the particles of exhaled aerosol (PExA) method. This offers an exciting prospect...

Microbiome Data Enhances Predictive Models of Lung Function in People With Cystic Fibrosis.

Microbiome sequencing has brought increasing attention to the polymicrobial context of chronic infections. However, clinical microbiology continues to focus on canonical human pathogens, which may overlook informative, but nonpathogenic, biomarkers. We address this disconnect in lung infections in people with cystic fibrosis (CF). We collected health information (lung function, age, and body mass index [BMI]) and sputum samples from a cohort of 77 children and adults with CF. Samples were collected during a period of clinical stability and 16S rDNA sequenced for airway microbiome compositions. We use ElasticNet regularization to train linear models predicting lung function and extract the most informative features. Models trained on whole-microbiome quantitation outperformed models trained on pathogen quantitation alone, with or without the inclusion of patient metadata. Our most accurate models retained key pathogens as negative predictors (Pseudomonas, Achromobacter) along with established correlates of CF disease state (age, BMI, CF-related diabetes). In addition, our models selected nonpathogen taxa (Fusobacterium, Rothia) as positive predictors of lung health. These results support a reconsideration of clinical microbiology pipelines to ensure the provision of informative data to guide clinical practice.

In Silico Ventilation Within the Dose-Volume is Predictive of Lung Function Post-radiation Therapy in Patients with Lung Cancer

Lung cancer is a leading cause of death worldwide. Radiation therapy (RT) is one method to treat this disease. A common side effect of RT for lung cancer is radiation-induced lung damage (RILD) which leads to loss of lung function. RILD often compounds pre-existing smoking-related regional lung function impairment. It is difficult to predict patient outcomes due to large variability in individual response to RT. In this study, the capability of image-based modelling of regional ventilation in lung cancer patients to predict lung function post-RT was investigated. Twenty-five patient-based models were created using CT images to define the airway geometry, size and location of tumour, and distribution of emphysema. Simulated ventilation within the 20 Gy isodose volume showed a statistically significant negative correlation with the change in forced expiratory volume in 1 s 12-months post-RT (p = 0.001, R = − 0.61). Patients with higher simulated ventilation within the 20 Gy isodose volume had a greater loss in lung function post-RT and vice versa. This relationship was only evident with the combined impact of tumour and emphysema, with the location of the emphysema relative to the dose-volume being important. Our results suggest that model-based ventilation measures can be used in the prediction of patient lung function post-RT.