Behzad Heibati , Jo S. Stenehjem , Elisabeta Pletea , Michelle C. Turner , Eva S. Schernhammer , Damien M. McElvenny , Tom Loney , Kurt Straif , Irina Guseva Canu
{"title":"Indirect adjustment of tobacco smoking in occupational studies of lung cancer: A systematic review of the available methods and their applications","authors":"Behzad Heibati , Jo S. Stenehjem , Elisabeta Pletea , Michelle C. Turner , Eva S. Schernhammer , Damien M. McElvenny , Tom Loney , Kurt Straif , Irina Guseva Canu","doi":"10.1016/j.canep.2025.102820","DOIUrl":null,"url":null,"abstract":"<div><div>Tobacco smoking is an important risk factor and potentially a major confounding factor in occupational lung cancer studies. However, as individual information on tobacco smoking is often not available, indirect adjustment methods may be used to account for potential confounding from smoking. Therefore, we aimed at providing an overview of the available indirect adjustment methods for smoking in studies of occupational exposures and lung cancer risk. We conducted a systematic search of relevant studies that applied statistical methods for indirect adjustment of tobacco smoking and were published between 1-Jan-2000 and 2-Apr-2025 to capture developments in recent decades. Studies were retrieved from Embase, MEDLINE, and Web of Science. Fifteen studies fulfilled our inclusion criteria and were included. We grouped the studies into four methods of indirect smoking adjustment: (1) without distributions for adjusted data; (2) distributions for adjusted data; (3) negative control outcomes; (4) factor analysis models. For studies with an external comparison group, percentage change in estimates from before to after indirect adjustment ranged −36.1 %_to_+ 17.3 %, while the corresponding range for those with internal comparison was −16.2 %_to_+ 47.8 %. The choice of indirect adjustment method depends on the use of reference group (external vs. internal) and the data available. Adjustment methods 1 and 2 use partial cohort data or ancillary data from other similar workers and may be preferable over methods 3 and 4, if such data are available. Methods 3 and 4 may be well suited if such data are lacking but have stronger assumptions.</div></div>","PeriodicalId":56322,"journal":{"name":"Cancer Epidemiology","volume":"97 ","pages":"Article 102820"},"PeriodicalIF":2.4000,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1877782125000803","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Tobacco smoking is an important risk factor and potentially a major confounding factor in occupational lung cancer studies. However, as individual information on tobacco smoking is often not available, indirect adjustment methods may be used to account for potential confounding from smoking. Therefore, we aimed at providing an overview of the available indirect adjustment methods for smoking in studies of occupational exposures and lung cancer risk. We conducted a systematic search of relevant studies that applied statistical methods for indirect adjustment of tobacco smoking and were published between 1-Jan-2000 and 2-Apr-2025 to capture developments in recent decades. Studies were retrieved from Embase, MEDLINE, and Web of Science. Fifteen studies fulfilled our inclusion criteria and were included. We grouped the studies into four methods of indirect smoking adjustment: (1) without distributions for adjusted data; (2) distributions for adjusted data; (3) negative control outcomes; (4) factor analysis models. For studies with an external comparison group, percentage change in estimates from before to after indirect adjustment ranged −36.1 %_to_+ 17.3 %, while the corresponding range for those with internal comparison was −16.2 %_to_+ 47.8 %. The choice of indirect adjustment method depends on the use of reference group (external vs. internal) and the data available. Adjustment methods 1 and 2 use partial cohort data or ancillary data from other similar workers and may be preferable over methods 3 and 4, if such data are available. Methods 3 and 4 may be well suited if such data are lacking but have stronger assumptions.
期刊介绍:
Cancer Epidemiology is dedicated to increasing understanding about cancer causes, prevention and control. The scope of the journal embraces all aspects of cancer epidemiology including:
• Descriptive epidemiology
• Studies of risk factors for disease initiation, development and prognosis
• Screening and early detection
• Prevention and control
• Methodological issues
The journal publishes original research articles (full length and short reports), systematic reviews and meta-analyses, editorials, commentaries and letters to the editor commenting on previously published research.