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Background and purpose: We report outcomes following spine stereotactic body radiotherapy (SBRT) in metastatic non-small cell lung cancer (NSCLC) and the significance of programmed death-ligand 1 (PD-L1) status, epidermal growth factor receptor (EGFR) mutation and timing of immune check point inhibitors (ICI) on local failure (LF). Materials and methods: 165 patients and 389 spinal segments were retrospectively reviewed from 2009 to 2021. Baseline patient characteristics, treatment and outcomes were abstracted. Primary endpoint was LF and secondary, overall survival (OS) and vertebral compression fracture (VCF). Multivariable analysis (MVA) evaluated factors predictive of LF and VCF. Results: The median follow-up and OS were: 13.0 months (range, 0.5–95.3 months) and 18.4 months (95% CI 11.4–24.6). 52.1% were male and 76.4% had adenocarcinoma. Of the 389 segments, 30.3% harboured an EGFR mutation and 17.0% were PD-L1 ≥ 50%. The 24 months LF rate in PD-L1 ≥ 50% vs PD-L1 < 50% was 10.7% vs. 38.0%, and in EGFR-positive vs. negative was 18.1% vs. 30.0%. On MVA, PD-L1 status of ≥ 50% (HR 0.32, 95% CI 0.15–0.69, p = 0.004) significantly predicted for lower LF compared to PD-L1 < 50%. Lower LF trend was seen with ICI administration peri and post SBRT (HR 0.41, 95% CI 0.16–1.05, p = 0.062). On MVA, polymetastatic disease (HR 3.28, 95% CI 1.84–5.85, p < 0.0001) and ECOG ≥ 2 (HR 1.87, 95% CI 1.16–3.02, p = 0.011) significantly predicted for worse OS and absence of baseline VCF predicted for lower VCF rate (HR 0.20, 95% CI 0.10–0.39, p < 0.0001). Conclusion: We report a significant association of PD-L1 ≥ 50% status on improved LC rates from spine SBRT in NSCLC patients. [ABSTRACT FROM AUTHOR]

Antimicrobial susceptibility testing (AST) is essential for detecting resistance in Pseudomonas aeruginosa and other bacterial pathogens. Here we evaluated the performance of broth microdilution (BMD) panels created using a semi-automated liquid handler, the D300e Digital Dispenser (Tecan Group Ltd., CH) that relies on inkjet printing technology. Microtitre panels (96-well) containing nine twofold dilutions of 12 antimicrobials from five classes (β-lactams, β-lactam/β-lactamase inhibitors, aminoglycosides, fluoroquinolones, polymyxins) were prepared in parallel using the D300e Digital Dispenser and standard methods described by CLSI/ISO. To assess performance, panels were challenged with three well characterized quality control organisms and 100 clinical P. aeruginosa isolates. Traditional agreement and error measures were used for evaluation. Essential (EA) and categorical (CA) agreements were 92.7% and 98.0% respectively for P. aeruginosa isolates with evaluable on-scale results. The majority of minor errors that fell outside acceptable EA parameters (≥ ± 1 dilution, 1.9%) were seen with aztreonam (5%) and ceftazidime (4%), however all antimicrobials displayed acceptable performance in this situation. Differences in MIC were often log2 dilution lower for D300e dispensed panels. Major and very major errors were noted for aztreonam (2.6%) and cefepime (1.7%) respectively. The variable performance of D300e panels suggests that further testing is required to confirm their diagnostic utility for P. aeruginosa. [ABSTRACT FROM AUTHOR]

109 pathologically proven subsolid nodules (SSN) were segmented by 2 readers on non-thin section chest CT with a lung nodule analysis software followed by extraction of CT attenuation histogram and geometric features. Functional data analysis of histograms provided data driven features (FPC1,2,3) used in further model building. Nodules were classified as pre-invasive (P1, atypical adenomatous hyperplasia and adenocarcinoma in situ), minimally invasive (P2) and invasive adenocarcinomas (P3). P1 and P2 were grouped together (T1) versus P3 (T2). Various combinations of features were compared in predictive models for binary nodule classification (T1/T2), using multiple logistic regression and non-linear classifiers. Area under ROC curve (AUC) was used as diagnostic performance criteria. Inter-reader variability was assessed using Cohen's Kappa and intra-class coefficient (ICC). Three models predicting invasiveness of SSN were selected based on AUC. First model included 87.5 percentile of CT lesion attenuation (Q.875), interquartile range (IQR), volume and maximum/minimum diameter ratio (AUC:0.89, 95%CI:[0.75 1]). Second model included FPC1, volume and diameter ratio (AUC:0.91, 95%CI:[0.77 1]). Third model included FPC1, FPC2 and volume (AUC:0.89, 95%CI:[0.73 1]). Inter-reader variability was excellent (Kappa:0.95, ICC:0.98). Parsimonious models using histogram and geometric features differentiated invasive from minimally invasive/pre-invasive SSN with good predictive performance in non-thin section CT. [ABSTRACT FROM AUTHOR]

Chronic airway infections caused by Pseudomonas aeruginosa contribute to the progression of pulmonary disease in individuals with cystic fibrosis (CF). In the setting of CF, within-patient adaptation of a P. aeruginosa strain generates phenotypic diversity that can complicate microbiological analysis of patient samples. We investigated within- and between- sample diversity of 34 phenotypes among 235 P. aeruginosa isolates cultured from sputum samples collected from a single CF patient over the span of one year, and assessed colony morphology as a screening tool for predicting phenotypes, including antimicrobial susceptibilities. We identified 15 distinct colony morphotypes that varied significantly in abundance both within and between sputum samples. Substantial within sample phenotypic heterogeneity was also noted in other phenotypes, with morphotypes being unreliable predictors of antimicrobial susceptibility and other phenotypes. Emergence of isolates with reduced susceptibility to β-lactams was observed during periods of clinical therapy with aztreonam. Our findings confirm that the P. aeruginosa population in chronic CF lung infections is highly dynamic, and that intra-sample phenotypic diversity is underestimated if only one or few colonies are analyzed per sample. [ABSTRACT FROM AUTHOR]

Understanding the significance of bacterial species that colonize and persist in cystic fibrosis (CF) airways requires a detailed examination of bacterial community structure across a broad range of age and disease stage. We used 16S ribosomal RNA sequencing to characterize the lung microbiota in 269 CF patients spanning a 60 year age range, including 76 pediatric samples from patients of age 4-17, and a broad cross-section of disease status to identify features of bacterial community structure and their relationship to disease stage and age. The CF lung microbiota shows significant inter-individual variability in community structure, composition and diversity. The core microbiota consists of five genera - Streptococcus, Prevotella, Rothia, Veillonella and Actinomyces. CF-associated pathogens such as Pseudomonas, Burkholderia, Stenotrophomonas and Achromobacter are less prevalent than core genera, but have a strong tendency to dominate the bacterial community when present. Community diversity and lung function are greatest in patients less than 10 years of age and lower in older age groups, plateauing at approximately age 25. Lower community diversity correlates with worse lung function in a multivariate regression model. Infection by Pseudomonas correlates with age-associated trends in community diversity and lung function. [ABSTRACT FROM AUTHOR]