Association between serum oncofetal antigens CA 19-9 and CA 125 and clinical status in patients with cystic fibrosis

Abstract Background Cystic fibrosis (CF) affects >70,000 people worldwide, yet the microbiologic trigger for pulmonary exacerbations (PExs) remains unknown. The objective of this study was to identify changes in bacterial metabolic pathways associated with clinical status. Methods Respiratory samples were collected at hospital admission for PEx, end of intravenous (IV) antibiotic treatment, and follow-up from 27 hospitalized children with CF. Bacterial DNA was extracted and shotgun DNA sequencing was performed. MetaPhlAn2 and HUMAnN2 were used to evaluate bacterial taxonomic and pathway relative abundance, while DESeq2 was used to evaluate differential abundance based on clinical status. Results The mean age of study participants was 10 years; 85% received combination IV antibiotic therapy (beta-lactam plus a second agent). Long-chain fatty acid (LCFA) biosynthesis pathways were upregulated in follow-up samples compared to end of treatment: gondoate (p = 0.012), oleate (p = 0.048), palmitoleate (p = 0.043), and pathways of fatty acid elongation (p = 0.012). Achromobacter xylosoxidans and Escherichia sp. were also more prevalent in follow-up compared to PEx (p < 0.001). Conclusions LCFAs may be associated with persistent infection of opportunistic pathogens. Future studies should more closely investigate the role of LCFA production by lung bacteria in the transition from baseline wellness to PEx in persons with CF. Impact Increased levels of LCFAs are found after IV antibiotic treatment in persons with CF. LCFAs have previously been associated with increased lung inflammation in asthma. This is the first report of LCFAs in the airway of persons with CF. This research provides support that bacterial production of LCFAs may be a contributor to inflammation in persons with CF. Future studies should evaluate LCFAs as predictors of future PExs.

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The relationship between children's treatment-related behaviour problems, age and clinical status in cystic fibrosis

Journal of Paediatrics and Child Health ◽

10.1111/j.1440-1754.1991.tb02540.x ◽

1991 ◽

Vol 27 (5) ◽

pp. 290-294 ◽

Cited By ~ 11

Author(s):

M. R. SANDERS ◽

F. M. GRAVESTOCK ◽

K. WANSTALL ◽

M. DUNNE

Keyword(s):

Cystic Fibrosis ◽

Clinical Status ◽

Behaviour Problems ◽

The Relationship

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

European Respiratory Journal ◽

10.1183/13993003.01344-2021 ◽

2021 ◽

pp. 2101344

Author(s):

Alienor Campredon ◽

Enzo Battistella ◽

Clémence Martin ◽

Isabelle Durieu ◽

Laurent Mely ◽

...

Keyword(s):

Machine Learning ◽

Cystic Fibrosis ◽

Ct Scan ◽

Structural Changes ◽

Clinical Status ◽

Chest Ct ◽

Ct Scans ◽

Wall Thickening ◽

Unsupervised Machine Learning ◽

One Year

ObjectivesLumacaftor-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.MethodsAdolescents 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.ResultsA 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).ConclusionOne 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.

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Is there a role for CA-125 in monitoring patients with early endometrial cancer?

International Journal of Gynecological Cancer ◽

10.1046/j.1525-1438.1991.01040169.x ◽

1991 ◽

Vol 1 (4) ◽

pp. 169-172

Author(s):

M. Prefontaine ◽

G. J. O'Connell ◽

E. Ryan ◽

K. J. Murphy

Keyword(s):

Endometrial Cancer ◽

Positive Predictive Value ◽

Endometrial Carcinoma ◽

Predictive Value ◽

Clinical Status ◽

Statistical Correlation ◽

Ca 125 ◽

Recurrent Malignancy ◽

Low Prevalence

Elevated CA-125 levels have been reported in some women with endometrial carcinoma. Current follow-up policy for these patients does not involve the use of tumor markers. CA-125 measurements were performed in 28 patients with a diagnosis of endometrial cancer, 14 clinically free of disease and 14 with known disease. Based on the sensitivity (0.64) and specificity (0.93) observed we constructed a model to estimate the predictive value of the assay as a marker in the follow-up of patients who have completed treatment. This model would involve a CA-125 assay every six months for five years in 100 patients with stage I and II disease. Despite the high statistical correlation between the clinical status of the patient and the CA-125 value observed in our study, the positive predictive value would be approximately 24% in such a follow-up protocol where a low prevalence of recurrent malignancy is expected.

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Unsupervised Phenotypic Clustering for Determining Clinical Status in Children with Cystic Fibrosis

European Respiratory Journal ◽

10.1183/13993003.02881-2020 ◽

2021 ◽

pp. 2002881

Author(s):

Nicole Filipow ◽

Gwyneth Davies ◽

Eleanor Main ◽

Neil J. Sebire ◽

Colin Wallis ◽

...

Keyword(s):

Machine Learning ◽

Cystic Fibrosis ◽

Lung Function ◽

Disease Severity ◽

Learning Algorithm ◽

Severe Disease ◽

Clinical Status ◽

Oral Antibiotics ◽

Multisystem Disease ◽

Street Hospital

BackgroundCystic Fibrosis (CF) is a multisystem disease in which assessing disease severity based on lung function alone may not be appropriate. The aim of the study was to develop a comprehensive machine-learning algorithm to assess clinical status independent of lung function in children.MethodsA comprehensive prospectively collected clinical database (Toronto, Canada) was used to apply unsupervised cluster analysis. The defined clusters were then compared by current and future lung function, risk of future hospitalisation, and risk of future pulmonary exacerbation (PEx) treated with oral antibiotics. A K-Nearest Neighbours (KNN) algorithm was used to prospectively assign clusters. The methods were validated in a paediatric clinical CF dataset from Great Ormond Street Hospital (GOSH).ResultsThe optimal cluster model identified four (A-D) phenotypic clusters based on 12 200 encounters from 530 individuals. Two clusters (A,B) consistent with mild disease were identified with high FEV1, and low risk of both hospitalisation and PEx treated with oral antibiotics. Two clusters (C,D) consistent with severe disease were also identified with low FEV1. Cluster D had the shortest time to both hospitalisation and PEx treated with oral antibiotics. The outcomes were consistent in 3124 encounters from 171 children at GOSH. The KNN cluster allocation error rate was low, at 2.5% (Toronto), and 3.5% (GOSH).ConclusionMachine learning derived phenotypic clusters can predict disease severity independent of lung function and could be used in conjunction with functional measures to predict future disease trajectories in CF patients.

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Staphylococcus aureus Pathogenicity in Cystic Fibrosis Patients—Results from an Observational Prospective Multicenter Study Concerning Virulence Genes, Phylogeny, and Gene Plasticity

Toxins ◽

10.3390/toxins12050279 ◽

2020 ◽

Vol 12 (5) ◽

pp. 279 ◽

Cited By ~ 1

Author(s):

Jonas Lange ◽

Kathrin Heidenreich ◽

Katharina Higelin ◽

Kristina Dyck ◽

Vanessa Marx ◽

...

Keyword(s):

Cystic Fibrosis ◽

Staphylococcus Aureus ◽

Virulence Genes ◽

Clinical Status ◽

Virulence Gene ◽

Clinical Deterioration ◽

Limited Degree ◽

Multi Center Study ◽

The Impact ◽

Specific Virulence

Staphylococcus aureus and cystic fibrosis (CF) are closely interlinked. To date, however, the impact of S. aureus culture in CF airways on lung function and disease progression has only been elucidated to a limited degree. This analysis aims to identify bacterial factors associated to clinical deterioration. Data were collected during an observational prospective multi-center study following 195 patients from 17 centers. The average follow-up time was 80 weeks. S. aureus isolates (n = 3180) were scanned for the presence of 25 virulence genes and agr-types using single and multiplex PCR. The presence of specific virulence genes was not associated to clinical deterioration. For the agr-types 1 and 4, however, a link to the subjects’ clinical status became evident. Furthermore, a significant longitudinal decrease in the virulence gene quantity was observed. Analyses of the plasticity of the virulence genes revealed significantly increased plasticity rates in the presence of environmental stress. The results suggest that the phylogenetic background defines S. aureus pathogenicity rather than specific virulence genes. The longitudinal loss of virulence genes most likely reflects the adaptation process directed towards a persistent and colonizing rather than infecting lifestyle.

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