Asthma and risk of glioma

A population-based case-control study

Harsheen Kaur, Daniel H Lachance, Conor S. Ryan, Youn Ho Sheen, Hee Yun Seol, Chung Il Wi, Sunghwan Sohn, Katherine S. King, Euijung Ryu, Young J Juhn

Research output: Contribution to journalArticle

Abstract

Objectives Literature suggests an inconsistent, but largely inverse, association between asthma and risk of glioma, which is primarily due to methodological inconsistency in sampling frame and ascertainment of asthma. The objective of the study was to clarify the association between asthma and risk of glioma by minimising methodological biases (eg, recall and detection bias). Design A population-based case-control study. Setting General population in Olmsted County, Minnesota, USA. Participants All eligible biopsy-proven incident glioma cases (1995-2014) and two sets of controls among residents matched to age and sex (first set: community controls without glioma; second set: MRI-negative controls from the same community). Methods The predetermined asthma criteria via medical record review were applied to ascertain asthma status of cases and controls. History of asthma prior to index date was compared between glioma cases and their matched controls using conditional logistic regression models. Propensity score for asthma status was adjusted for multivariate analysis. Results We enrolled 135 glioma cases (median age at index date: 53 years) and 270 controls. Of the cases, 21 had a history of asthma (16%), compared with 36 of MRI controls (27%) (OR (95% CI) 0.48 (0.26 to 0.91), p=0.03). With MRI controls, an inverse association between asthma and risk of glioma persisted after adjusting for the propensity score for asthma status, but did not reach statistical significance probably due to the lack of statistical power (OR (95% CI) 0.48 (0.21 to 1.09); p=0.08). Based on comparison of characteristics of controls and cases, community controls seem to be more susceptible to a detection bias. Conclusions While differential detection might account for the association between asthma and risk of glioma, asthma may potentially pose a protective effect on risk of glioma. Our study results need to be replicated by a larger study.

Original languageEnglish (US)
Article numbere025746
JournalBMJ open
Volume9
Issue number6
DOIs
StatePublished - Jun 1 2019

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Glioma
Case-Control Studies
Asthma
Population
Propensity Score
Logistic Models
Medical Records
Multivariate Analysis
Biopsy

Keywords

  • allergy
  • asthma
  • epidemiology

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Asthma and risk of glioma : A population-based case-control study. / Kaur, Harsheen; Lachance, Daniel H; Ryan, Conor S.; Sheen, Youn Ho; Seol, Hee Yun; Wi, Chung Il; Sohn, Sunghwan; King, Katherine S.; Ryu, Euijung; Juhn, Young J.

In: BMJ open, Vol. 9, No. 6, e025746, 01.06.2019.

Research output: Contribution to journalArticle

Kaur, Harsheen ; Lachance, Daniel H ; Ryan, Conor S. ; Sheen, Youn Ho ; Seol, Hee Yun ; Wi, Chung Il ; Sohn, Sunghwan ; King, Katherine S. ; Ryu, Euijung ; Juhn, Young J. / Asthma and risk of glioma : A population-based case-control study. In: BMJ open. 2019 ; Vol. 9, No. 6.
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abstract = "Objectives Literature suggests an inconsistent, but largely inverse, association between asthma and risk of glioma, which is primarily due to methodological inconsistency in sampling frame and ascertainment of asthma. The objective of the study was to clarify the association between asthma and risk of glioma by minimising methodological biases (eg, recall and detection bias). Design A population-based case-control study. Setting General population in Olmsted County, Minnesota, USA. Participants All eligible biopsy-proven incident glioma cases (1995-2014) and two sets of controls among residents matched to age and sex (first set: community controls without glioma; second set: MRI-negative controls from the same community). Methods The predetermined asthma criteria via medical record review were applied to ascertain asthma status of cases and controls. History of asthma prior to index date was compared between glioma cases and their matched controls using conditional logistic regression models. Propensity score for asthma status was adjusted for multivariate analysis. Results We enrolled 135 glioma cases (median age at index date: 53 years) and 270 controls. Of the cases, 21 had a history of asthma (16{\%}), compared with 36 of MRI controls (27{\%}) (OR (95{\%} CI) 0.48 (0.26 to 0.91), p=0.03). With MRI controls, an inverse association between asthma and risk of glioma persisted after adjusting for the propensity score for asthma status, but did not reach statistical significance probably due to the lack of statistical power (OR (95{\%} CI) 0.48 (0.21 to 1.09); p=0.08). Based on comparison of characteristics of controls and cases, community controls seem to be more susceptible to a detection bias. Conclusions While differential detection might account for the association between asthma and risk of glioma, asthma may potentially pose a protective effect on risk of glioma. Our study results need to be replicated by a larger study.",
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AU - Ryan, Conor S.

AU - Sheen, Youn Ho

AU - Seol, Hee Yun

AU - Wi, Chung Il

AU - Sohn, Sunghwan

AU - King, Katherine S.

AU - Ryu, Euijung

AU - Juhn, Young J

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N2 - Objectives Literature suggests an inconsistent, but largely inverse, association between asthma and risk of glioma, which is primarily due to methodological inconsistency in sampling frame and ascertainment of asthma. The objective of the study was to clarify the association between asthma and risk of glioma by minimising methodological biases (eg, recall and detection bias). Design A population-based case-control study. Setting General population in Olmsted County, Minnesota, USA. Participants All eligible biopsy-proven incident glioma cases (1995-2014) and two sets of controls among residents matched to age and sex (first set: community controls without glioma; second set: MRI-negative controls from the same community). Methods The predetermined asthma criteria via medical record review were applied to ascertain asthma status of cases and controls. History of asthma prior to index date was compared between glioma cases and their matched controls using conditional logistic regression models. Propensity score for asthma status was adjusted for multivariate analysis. Results We enrolled 135 glioma cases (median age at index date: 53 years) and 270 controls. Of the cases, 21 had a history of asthma (16%), compared with 36 of MRI controls (27%) (OR (95% CI) 0.48 (0.26 to 0.91), p=0.03). With MRI controls, an inverse association between asthma and risk of glioma persisted after adjusting for the propensity score for asthma status, but did not reach statistical significance probably due to the lack of statistical power (OR (95% CI) 0.48 (0.21 to 1.09); p=0.08). Based on comparison of characteristics of controls and cases, community controls seem to be more susceptible to a detection bias. Conclusions While differential detection might account for the association between asthma and risk of glioma, asthma may potentially pose a protective effect on risk of glioma. Our study results need to be replicated by a larger study.

AB - Objectives Literature suggests an inconsistent, but largely inverse, association between asthma and risk of glioma, which is primarily due to methodological inconsistency in sampling frame and ascertainment of asthma. The objective of the study was to clarify the association between asthma and risk of glioma by minimising methodological biases (eg, recall and detection bias). Design A population-based case-control study. Setting General population in Olmsted County, Minnesota, USA. Participants All eligible biopsy-proven incident glioma cases (1995-2014) and two sets of controls among residents matched to age and sex (first set: community controls without glioma; second set: MRI-negative controls from the same community). Methods The predetermined asthma criteria via medical record review were applied to ascertain asthma status of cases and controls. History of asthma prior to index date was compared between glioma cases and their matched controls using conditional logistic regression models. Propensity score for asthma status was adjusted for multivariate analysis. Results We enrolled 135 glioma cases (median age at index date: 53 years) and 270 controls. Of the cases, 21 had a history of asthma (16%), compared with 36 of MRI controls (27%) (OR (95% CI) 0.48 (0.26 to 0.91), p=0.03). With MRI controls, an inverse association between asthma and risk of glioma persisted after adjusting for the propensity score for asthma status, but did not reach statistical significance probably due to the lack of statistical power (OR (95% CI) 0.48 (0.21 to 1.09); p=0.08). Based on comparison of characteristics of controls and cases, community controls seem to be more susceptible to a detection bias. Conclusions While differential detection might account for the association between asthma and risk of glioma, asthma may potentially pose a protective effect on risk of glioma. Our study results need to be replicated by a larger study.

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