Construction and case study of a novel lung cancer risk index
Abstract Purpose This study constructs a lung cancer risk index (LCRI) that incorporates many modifiable risk factors using an easily reproducible and adaptable method that relies on publicly available data. Methods We used meta-analysis followed by Analytic Hierarchy Process (AHP) to generate a lun...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-12-01
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| Series: | BMC Cancer |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12885-022-10370-4 |
| _version_ | 1828277548486754304 |
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| author | Ali Faghani Lei Guo Margaret E. Wright M. Courtney Hughes Mahdi Vaezi |
| author_facet | Ali Faghani Lei Guo Margaret E. Wright M. Courtney Hughes Mahdi Vaezi |
| author_sort | Ali Faghani |
| collection | DOAJ |
| description | Abstract Purpose This study constructs a lung cancer risk index (LCRI) that incorporates many modifiable risk factors using an easily reproducible and adaptable method that relies on publicly available data. Methods We used meta-analysis followed by Analytic Hierarchy Process (AHP) to generate a lung cancer risk index (LCRI) that incorporates seven modifiable risk factors (active smoking, indoor air pollution, occupational exposure, alcohol consumption, secondhand smoke exposure, outdoor air pollution, and radon exposure) for lung cancer. Using county-level population data, we then performed a case study in which we tailored the LCRI for use in the state of Illinois (LCRIIL). Results For both the LCRI and the LCRIIL, active smoking had the highest weights (46.1% and 70%, respectively), whereas radon had the lowest weights (3.0% and 5.7%, respectively). The weights for alcohol consumption were 7.8% and 14.7% for the LCRI and the LCRIIL, respectively, and were 3.8% and 0.95% for outdoor air pollution. Three variables were only included in the LCRI: indoor air pollution (18.5%), occupational exposure (13.2%), and secondhand smoke exposure (7.6%). The Consistency Ratio (CR) was well below the 0.1 cut point. The LCRIIL was moderate though significantly correlated with age-adjusted lung cancer incidence (r = 0.449, P < 0.05) and mortality rates (r = 0.495, P < 0.05). Conclusion This study presents an index that incorporates multiple modifiable risk factors for lung cancer into one composite score. Since the LCRI allows data comprising the composite score to vary based on the location of interest, this measurement tool can be used for any geographic location where population-based data for individual risk factors exist. Researchers, policymakers, and public health professionals may utilize this framework to determine areas that are most in need of lung cancer-related interventions and resources. |
| first_indexed | 2024-04-13T07:16:19Z |
| format | Article |
| id | doaj.art-0329d36412604f36b382d7a35ff7dbcc |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-04-13T07:16:19Z |
| publishDate | 2022-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-0329d36412604f36b382d7a35ff7dbcc2022-12-22T02:56:44ZengBMCBMC Cancer1471-24072022-12-0122111010.1186/s12885-022-10370-4Construction and case study of a novel lung cancer risk indexAli Faghani0Lei Guo1Margaret E. Wright2M. Courtney Hughes3Mahdi Vaezi4College of Engineering and Engineering Technology, Northern Illinois UniversitySchool of Interdisciplinary Health Professions, Northern Illinois UniversityUniversity of Illinois Cancer CenterSchool of Health Studies, Northern Illinois UniversityCollege of Engineering and Engineering Technology, Northern Illinois UniversityAbstract Purpose This study constructs a lung cancer risk index (LCRI) that incorporates many modifiable risk factors using an easily reproducible and adaptable method that relies on publicly available data. Methods We used meta-analysis followed by Analytic Hierarchy Process (AHP) to generate a lung cancer risk index (LCRI) that incorporates seven modifiable risk factors (active smoking, indoor air pollution, occupational exposure, alcohol consumption, secondhand smoke exposure, outdoor air pollution, and radon exposure) for lung cancer. Using county-level population data, we then performed a case study in which we tailored the LCRI for use in the state of Illinois (LCRIIL). Results For both the LCRI and the LCRIIL, active smoking had the highest weights (46.1% and 70%, respectively), whereas radon had the lowest weights (3.0% and 5.7%, respectively). The weights for alcohol consumption were 7.8% and 14.7% for the LCRI and the LCRIIL, respectively, and were 3.8% and 0.95% for outdoor air pollution. Three variables were only included in the LCRI: indoor air pollution (18.5%), occupational exposure (13.2%), and secondhand smoke exposure (7.6%). The Consistency Ratio (CR) was well below the 0.1 cut point. The LCRIIL was moderate though significantly correlated with age-adjusted lung cancer incidence (r = 0.449, P < 0.05) and mortality rates (r = 0.495, P < 0.05). Conclusion This study presents an index that incorporates multiple modifiable risk factors for lung cancer into one composite score. Since the LCRI allows data comprising the composite score to vary based on the location of interest, this measurement tool can be used for any geographic location where population-based data for individual risk factors exist. Researchers, policymakers, and public health professionals may utilize this framework to determine areas that are most in need of lung cancer-related interventions and resources.https://doi.org/10.1186/s12885-022-10370-4Lung cancerRisk factorsAnalytic hierarchy processesMeta-analysisRisk index |
| spellingShingle | Ali Faghani Lei Guo Margaret E. Wright M. Courtney Hughes Mahdi Vaezi Construction and case study of a novel lung cancer risk index BMC Cancer Lung cancer Risk factors Analytic hierarchy processes Meta-analysis Risk index |
| title | Construction and case study of a novel lung cancer risk index |
| title_full | Construction and case study of a novel lung cancer risk index |
| title_fullStr | Construction and case study of a novel lung cancer risk index |
| title_full_unstemmed | Construction and case study of a novel lung cancer risk index |
| title_short | Construction and case study of a novel lung cancer risk index |
| title_sort | construction and case study of a novel lung cancer risk index |
| topic | Lung cancer Risk factors Analytic hierarchy processes Meta-analysis Risk index |
| url | https://doi.org/10.1186/s12885-022-10370-4 |
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