Nonspesific bronchial hyperresponsiveness and eosinophilic airway inflammation predict occupational asthma to HMW agents but not to LMW agents

<bold>Background:</bold> Specific inhalation challenge (SIC) is used to differentiate occupational asthma (OA) from work-exacerbated asthma (WEA). Clinical differences between these two conditions are not fully recognized. <bold>Methods:</bold> We reviewed medical records of 616 asthma patients who were examined with SIC test in 2010-2020 because of OA suspicion. We compared clinical baseline characteristics between OA and WEA patients and identified predictive markers for OA. <bold>Results:</bold> Altogether 264 patients had positive SIC (OA) and 352 patients had negative SIC (WEA) (Table). Nonspecific bronchial hyperresponsiveness (NSBHR) (OR 3.22 (CI 1.59-6.52) and Fractional exhaled nitric oxide (FeNO) ≥25 (5.45 (2.25-13.24) predicted OA in patients exposed to high molecular weight (HMW) agents after adjusting for age, BMI, sex and current smoking. However, there were no difference between OA and WEA among those exposed to low molecular weight (LMW) agents: NSBHR OR 1.21 (0.74-1.99), FeNO ≥ 25 OR 0.89 (0.50-1.60). <bold>Conclusions:</bold> NSBHR and eosinophilic airway inflammation seem to increase likelihood of OA in patients exposed to HMW agents but not in patients exposed to LMW agents. <table-wrap><object-id>erj;64/suppl_68/PA3112/TB1</object-id><object-id>T1</object-id><object-id>TB1</object-id><table><colgroup><col></col><col></col><col></col><col></col><col></col></colgroup><tbody><tr><td></td><td>All<break></break>n=616</td><td>OA<break></break>n=264</td><td>WEA<break></break>n=352</td><td>p-value</td></tr><tr><td>Age, mean (SD)</td><td>41.6(11.4)</td><td>40.7(11.4)</td><td>42.3(11.5)</td><td>0.457</td></tr><tr><td>Male (%)</td><td>306(50.5)</td><td>127(48.7)</td><td>179(51.9)</td><td>0.432</td></tr><tr><td>BMI, mean (SD)</td><td>27.54(5.35)</td><td>27.7(5.47)</td><td>27.4(5.27)</td><td>0.396</td></tr><tr><td>Current smoking (%)</td><td>134(22.2)</td><td>68(26.2)</td><td>66(19.2)</td><td>0.041</td></tr><tr><td>FEV1 % predicted, mean (SD)</td><td>87.3(11.8)</td><td>87.8(11.9)</td><td>87.0(11.8)</td><td>0.367</td></tr><tr><td>Atopy (%)</td><td>251(44.7)</td><td>128(54.0)</td><td>123(42.9)</td><td><0.001</td></tr><tr><td>Antigen type LMW (%)</td><td>380(61.9)</td><td>106(40.3)</td><td>274(78.1)</td><td><0.001</td></tr><tr><td>FeNO ≥ 25 (%)</td><td>145(26.3)</td><td>76(32.6)</td><td>69(21.7)</td><td>0.004</td></tr><tr><td>NSBHR (%)</td><td>247(40.1)</td><td>126(43.1)</td><td>121(43.1)</td><td>0.002</td></tr></tbody></table></table-wrap>

Authors

Institutions

Publication Details

Published
2024-09-14
DOI
https://doi.org/10.1183/13993003.congress-2024.pa3112
Primary Topic
Occupational exposure and asthma
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nonspesific bronchial hyperresponsiveness and eosinophilic airway inflammation predict occupational asthma to HMW agents but not to LMW agents

Jussi Lantto, Hille Suojalehto, Irmeli Lindström, Ollipekka Kailari
Occupational exposure and asthma
article

Nonspesific bronchial hyperresponsiveness and eosinophilic airway inflammation predict occupational asthma to HMW agents but not to LMW agents

Jussi Lantto, Hille Suojalehto, Irmeli Lindström, Ollipekka Kailari
article en

Abstract

<bold>Background:</bold> Specific inhalation challenge (SIC) is used to differentiate occupational asthma (OA) from work-exacerbated asthma (WEA). Clinical differences between these two conditions are not fully recognized. <bold>Methods:</bold> We reviewed medical records of 616 asthma patients who were examined with SIC test in 2010-2020 because of OA suspicion. We compared clinical baseline characteristics between OA and WEA patients and identified predictive markers for OA. <bold>Results:</bold> Altogether 264 patients had positive SIC (OA) and 352 patients had negative SIC (WEA) (Table). Nonspecific bronchial hyperresponsiveness (NSBHR) (OR 3.22 (CI 1.59-6.52) and Fractional exhaled nitric oxide (FeNO) ≥25 (5.45 (2.25-13.24) predicted OA in patients exposed to high molecular weight (HMW) agents after adjusting for age, BMI, sex and current smoking. However, there were no difference between OA and WEA among those exposed to low molecular weight (LMW) agents: NSBHR OR 1.21 (0.74-1.99), FeNO ≥ 25 OR 0.89 (0.50-1.60). <bold>Conclusions:</bold> NSBHR and eosinophilic airway inflammation seem to increase likelihood of OA in patients exposed to HMW agents but not in patients exposed to LMW agents. <table-wrap><object-id>erj;64/suppl_68/PA3112/TB1</object-id><object-id>T1</object-id><object-id>TB1</object-id><table><colgroup><col></col><col></col><col></col><col></col><col></col></colgroup><tbody><tr><td></td><td>All<break></break>n=616</td><td>OA<break></break>n=264</td><td>WEA<break></break>n=352</td><td>p-value</td></tr><tr><td>Age, mean (SD)</td><td>41.6(11.4)</td><td>40.7(11.4)</td><td>42.3(11.5)</td><td>0.457</td></tr><tr><td>Male (%)</td><td>306(50.5)</td><td>127(48.7)</td><td>179(51.9)</td><td>0.432</td></tr><tr><td>BMI, mean (SD)</td><td>27.54(5.35)</td><td>27.7(5.47)</td><td>27.4(5.27)</td><td>0.396</td></tr><tr><td>Current smoking (%)</td><td>134(22.2)</td><td>68(26.2)</td><td>66(19.2)</td><td>0.041</td></tr><tr><td>FEV1 % predicted, mean (SD)</td><td>87.3(11.8)</td><td>87.8(11.9)</td><td>87.0(11.8)</td><td>0.367</td></tr><tr><td>Atopy (%)</td><td>251(44.7)</td><td>128(54.0)</td><td>123(42.9)</td><td><0.001</td></tr><tr><td>Antigen type LMW (%)</td><td>380(61.9)</td><td>106(40.3)</td><td>274(78.1)</td><td><0.001</td></tr><tr><td>FeNO ≥ 25 (%)</td><td>145(26.3)</td><td>76(32.6)</td><td>69(21.7)</td><td>0.004</td></tr><tr><td>NSBHR (%)</td><td>247(40.1)</td><td>126(43.1)</td><td>121(43.1)</td><td>0.002</td></tr></tbody></table></table-wrap>

Finnish Institute of Occupational Health (FI)
Zero hunger
Openalex Percentile: Top 70%
Occupational exposure and asthma
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.