Further validation of computer-based prediction of chemical asthma hazardCitation formats

  • Authors:
  • Martin Seed
  • Raymond Agius

Standard

Further validation of computer-based prediction of chemical asthma hazard. / Seed, Martin; Agius, Raymond.

In: Occupational Medicine, Vol. 60, No. 2, kqp168, 02.12.2009, p. 115-120.

Research output: Contribution to journalArticle

Harvard

Seed, M & Agius, R 2009, 'Further validation of computer-based prediction of chemical asthma hazard' Occupational Medicine, vol. 60, no. 2, kqp168, pp. 115-120. https://doi.org/10.1093/occmed/kqp168

APA

Seed, M., & Agius, R. (2009). Further validation of computer-based prediction of chemical asthma hazard. Occupational Medicine, 60(2), 115-120. [kqp168]. https://doi.org/10.1093/occmed/kqp168

Vancouver

Seed M, Agius R. Further validation of computer-based prediction of chemical asthma hazard. Occupational Medicine. 2009 Dec 2;60(2):115-120. kqp168. https://doi.org/10.1093/occmed/kqp168

Author

Seed, Martin ; Agius, Raymond. / Further validation of computer-based prediction of chemical asthma hazard. In: Occupational Medicine. 2009 ; Vol. 60, No. 2. pp. 115-120.

Bibtex

@article{bab105ab313d4b7792fe32b90b929820,
title = "Further validation of computer-based prediction of chemical asthma hazard",
abstract = "Background There is no agreed protocol for the prediction of low molecular weight (LMW) respiratory sensitizers. This creates challenges for occupational physicians responsible for the health of workforces using novel chemicals and respiratory physicians investigating cases of occupational asthma caused by novel asthmagens. Aims To iterate the external validation of a previously published quantitative structure-activity relationship (QSAR) model for the prediction of novel chemical respiratory sensitizers and to better characterize its predictive accuracy. Methods An external validation set of control chemicals was identified from the Australian Hazardous Substances Information System. An external validation set of asthmagenic chemicals was identified by a thorough search of the peer-reviewed literature from January 1995 onwards using the Medline database. The QSAR model was used to determine an 'asthma hazard index' (between 0 and 1) for each chemical. Results A total of 28 external validation asthmagens and 129 control chemicals were identified. The area under the receiver operating characteristic (ROC) curve for the model's ability to distinguish asthmagens from controls was 0.87 (95{\%} CI 0.76-0.97). Using a cut-off hazard index of 0.5 resulted in sensitivity of 79{\%} and specificity of 93{\%}. For prior probability ranging from 1:300 to 1:100, the negative predictive value (NPV) was 1 and positive predictive value (PPV) 0.04-0.1 while for prior probability ranging from 1:20 to 1:3, the NPV was 0.91-0.99 and PPV 0.39-0.85. Conclusions The ROC curve for this QSAR demonstrates good global predictive power for distinguishing asthmagenic from non-asthmagenic LMW organic compounds. Potential for utilization by occupational and respiratory physicians is evident from its predictive values. {\circledC} The Author 2009. Published by Oxford University Press on behalf of the Society of Occupational Medicine.",
keywords = "Novel asthmagen, Occupational asthma, QSAR, Respiratory sensitizer",
author = "Martin Seed and Raymond Agius",
year = "2009",
month = "12",
day = "2",
doi = "10.1093/occmed/kqp168",
language = "English",
volume = "60",
pages = "115--120",
journal = "Occupational medicine (Oxford, England)",
issn = "0962-7480",
publisher = "Oxford University Press",
number = "2",

}

RIS

TY - JOUR

T1 - Further validation of computer-based prediction of chemical asthma hazard

AU - Seed, Martin

AU - Agius, Raymond

PY - 2009/12/2

Y1 - 2009/12/2

N2 - Background There is no agreed protocol for the prediction of low molecular weight (LMW) respiratory sensitizers. This creates challenges for occupational physicians responsible for the health of workforces using novel chemicals and respiratory physicians investigating cases of occupational asthma caused by novel asthmagens. Aims To iterate the external validation of a previously published quantitative structure-activity relationship (QSAR) model for the prediction of novel chemical respiratory sensitizers and to better characterize its predictive accuracy. Methods An external validation set of control chemicals was identified from the Australian Hazardous Substances Information System. An external validation set of asthmagenic chemicals was identified by a thorough search of the peer-reviewed literature from January 1995 onwards using the Medline database. The QSAR model was used to determine an 'asthma hazard index' (between 0 and 1) for each chemical. Results A total of 28 external validation asthmagens and 129 control chemicals were identified. The area under the receiver operating characteristic (ROC) curve for the model's ability to distinguish asthmagens from controls was 0.87 (95% CI 0.76-0.97). Using a cut-off hazard index of 0.5 resulted in sensitivity of 79% and specificity of 93%. For prior probability ranging from 1:300 to 1:100, the negative predictive value (NPV) was 1 and positive predictive value (PPV) 0.04-0.1 while for prior probability ranging from 1:20 to 1:3, the NPV was 0.91-0.99 and PPV 0.39-0.85. Conclusions The ROC curve for this QSAR demonstrates good global predictive power for distinguishing asthmagenic from non-asthmagenic LMW organic compounds. Potential for utilization by occupational and respiratory physicians is evident from its predictive values. © The Author 2009. Published by Oxford University Press on behalf of the Society of Occupational Medicine.

AB - Background There is no agreed protocol for the prediction of low molecular weight (LMW) respiratory sensitizers. This creates challenges for occupational physicians responsible for the health of workforces using novel chemicals and respiratory physicians investigating cases of occupational asthma caused by novel asthmagens. Aims To iterate the external validation of a previously published quantitative structure-activity relationship (QSAR) model for the prediction of novel chemical respiratory sensitizers and to better characterize its predictive accuracy. Methods An external validation set of control chemicals was identified from the Australian Hazardous Substances Information System. An external validation set of asthmagenic chemicals was identified by a thorough search of the peer-reviewed literature from January 1995 onwards using the Medline database. The QSAR model was used to determine an 'asthma hazard index' (between 0 and 1) for each chemical. Results A total of 28 external validation asthmagens and 129 control chemicals were identified. The area under the receiver operating characteristic (ROC) curve for the model's ability to distinguish asthmagens from controls was 0.87 (95% CI 0.76-0.97). Using a cut-off hazard index of 0.5 resulted in sensitivity of 79% and specificity of 93%. For prior probability ranging from 1:300 to 1:100, the negative predictive value (NPV) was 1 and positive predictive value (PPV) 0.04-0.1 while for prior probability ranging from 1:20 to 1:3, the NPV was 0.91-0.99 and PPV 0.39-0.85. Conclusions The ROC curve for this QSAR demonstrates good global predictive power for distinguishing asthmagenic from non-asthmagenic LMW organic compounds. Potential for utilization by occupational and respiratory physicians is evident from its predictive values. © The Author 2009. Published by Oxford University Press on behalf of the Society of Occupational Medicine.

KW - Novel asthmagen

KW - Occupational asthma

KW - QSAR

KW - Respiratory sensitizer

U2 - 10.1093/occmed/kqp168

DO - 10.1093/occmed/kqp168

M3 - Article

VL - 60

SP - 115

EP - 120

JO - Occupational medicine (Oxford, England)

JF - Occupational medicine (Oxford, England)

SN - 0962-7480

IS - 2

M1 - kqp168

ER -