Research
Print page Print page
Switch language
The Capital Region of Denmark - a part of Copenhagen University Hospital
Published

Can secretory immunoglobulin A in saliva predict a change in lung infection status in patients with cystic fibrosis? A prospective pilot study

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

APA

CBE

MLA

Vancouver

Author

Bibtex

@article{b44526d9419849c589d8fb284a4da6d0,
title = "Can secretory immunoglobulin A in saliva predict a change in lung infection status in patients with cystic fibrosis?: A prospective pilot study",
abstract = "Background: Chronic lung infection with Pseudomonas aeruginosa is the main cause of mortality in patients with cystic fibrosis (CF). Sinus colonization with P. aeruginosa often precedes intermittent lung colonization, and intermittent colonization precedes chronic infection.When P. aeruginosa colonizes the sinuses, elevated immunoglobulin A (IgA) levels specific against P. aeruginosa can be detected in saliva. Therefore, we hypothesized that increasing levels of IgA in saliva can be detected before P. aeruginosa lung colonization.Methods: Forty-nine CF patients free from lung colonization with P. aeruginosa or other Gram-negative bacteria (GNB) were included in this prospective study. Saliva and serum samples were collected and examined for IgA antibodies against P. aeruginosa with at least 6-month intervals between sequential samples.Results: A total of 110 measurements of IgA in saliva were included. During a median of 8.5-month follow-up, 25 patients changed their lung infection status. We were able to construct a statistical model that for a given value of IgA in saliva, could predict the probability of a change in lung infection status within the next 8.5 months (median): p = 1 / (1 + exp(-(-0.9582 + 1.6518*IgA)). The model includes a prediction band where 95{\%} of new measurements are predicted to fall within. The model, however, failed to reach statistical significance (P = 0.056 1-tailed), probably because of lack of power.Conclusion: The saliva IgA model may predict a worsening in lung infection status presumably acting as a surrogate marker of P. aeruginosa bacterial sinusitis. The model may identify patients at risk of subsequent lung colonization and, thus, be a helpful clinical tool, but it should be tested in studies with larger sample sizes to evaluate its utility.",
author = "Alanin, {Mikkel Christian} and Tania Pressler and Kasper Aanaes and Ekstr{\o}m, {Claus Thorn} and Marianne Skov and Johansen, {Helle Krogh} and Nielsen, {Kim G} and {von Buchwald}, Christian and Niels H{\o}iby",
year = "2018",
month = "8",
doi = "10.1002/hsr2.52",
language = "English",
volume = "1",
pages = "e52--e56",
journal = "Health Science Reports",
issn = "2398-8835",
publisher = "Wiley",
number = "8",

}

RIS

TY - JOUR

T1 - Can secretory immunoglobulin A in saliva predict a change in lung infection status in patients with cystic fibrosis?

T2 - A prospective pilot study

AU - Alanin, Mikkel Christian

AU - Pressler, Tania

AU - Aanaes, Kasper

AU - Ekstrøm, Claus Thorn

AU - Skov, Marianne

AU - Johansen, Helle Krogh

AU - Nielsen, Kim G

AU - von Buchwald, Christian

AU - Høiby, Niels

PY - 2018/8

Y1 - 2018/8

N2 - Background: Chronic lung infection with Pseudomonas aeruginosa is the main cause of mortality in patients with cystic fibrosis (CF). Sinus colonization with P. aeruginosa often precedes intermittent lung colonization, and intermittent colonization precedes chronic infection.When P. aeruginosa colonizes the sinuses, elevated immunoglobulin A (IgA) levels specific against P. aeruginosa can be detected in saliva. Therefore, we hypothesized that increasing levels of IgA in saliva can be detected before P. aeruginosa lung colonization.Methods: Forty-nine CF patients free from lung colonization with P. aeruginosa or other Gram-negative bacteria (GNB) were included in this prospective study. Saliva and serum samples were collected and examined for IgA antibodies against P. aeruginosa with at least 6-month intervals between sequential samples.Results: A total of 110 measurements of IgA in saliva were included. During a median of 8.5-month follow-up, 25 patients changed their lung infection status. We were able to construct a statistical model that for a given value of IgA in saliva, could predict the probability of a change in lung infection status within the next 8.5 months (median): p = 1 / (1 + exp(-(-0.9582 + 1.6518*IgA)). The model includes a prediction band where 95% of new measurements are predicted to fall within. The model, however, failed to reach statistical significance (P = 0.056 1-tailed), probably because of lack of power.Conclusion: The saliva IgA model may predict a worsening in lung infection status presumably acting as a surrogate marker of P. aeruginosa bacterial sinusitis. The model may identify patients at risk of subsequent lung colonization and, thus, be a helpful clinical tool, but it should be tested in studies with larger sample sizes to evaluate its utility.

AB - Background: Chronic lung infection with Pseudomonas aeruginosa is the main cause of mortality in patients with cystic fibrosis (CF). Sinus colonization with P. aeruginosa often precedes intermittent lung colonization, and intermittent colonization precedes chronic infection.When P. aeruginosa colonizes the sinuses, elevated immunoglobulin A (IgA) levels specific against P. aeruginosa can be detected in saliva. Therefore, we hypothesized that increasing levels of IgA in saliva can be detected before P. aeruginosa lung colonization.Methods: Forty-nine CF patients free from lung colonization with P. aeruginosa or other Gram-negative bacteria (GNB) were included in this prospective study. Saliva and serum samples were collected and examined for IgA antibodies against P. aeruginosa with at least 6-month intervals between sequential samples.Results: A total of 110 measurements of IgA in saliva were included. During a median of 8.5-month follow-up, 25 patients changed their lung infection status. We were able to construct a statistical model that for a given value of IgA in saliva, could predict the probability of a change in lung infection status within the next 8.5 months (median): p = 1 / (1 + exp(-(-0.9582 + 1.6518*IgA)). The model includes a prediction band where 95% of new measurements are predicted to fall within. The model, however, failed to reach statistical significance (P = 0.056 1-tailed), probably because of lack of power.Conclusion: The saliva IgA model may predict a worsening in lung infection status presumably acting as a surrogate marker of P. aeruginosa bacterial sinusitis. The model may identify patients at risk of subsequent lung colonization and, thus, be a helpful clinical tool, but it should be tested in studies with larger sample sizes to evaluate its utility.

U2 - 10.1002/hsr2.52

DO - 10.1002/hsr2.52

M3 - Journal article

VL - 1

SP - e52-e56

JO - Health Science Reports

JF - Health Science Reports

SN - 2398-8835

IS - 8

ER -

ID: 56201934