Response to Drs. Igor Burstyn and George Luta’s letter: Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias)
We want to thank Drs. Burstyn & Luta (1) for their recognition of our recent study (2) suggesting that estimates of breast cancer risk following retrospective self-reported night shift work are inflated by recall bias. The main strength of the study was a gold standard based on individual, prosp...
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Nordic Association of Occupational Safety and Health (NOROSH)
2025-07-01
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| Series: | Scandinavian Journal of Work, Environment & Health |
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https://www.sjweh.fi/article/4232
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| author | Henrik A Kolstad Jesper Medom Vestergaard Jens Peter Bonde Sadie Costello Annett Dalbøge Åse Marie Hansen Ann Dyreborg Larsen Anne Helene Garde |
| author_facet | Henrik A Kolstad Jesper Medom Vestergaard Jens Peter Bonde Sadie Costello Annett Dalbøge Åse Marie Hansen Ann Dyreborg Larsen Anne Helene Garde |
| author_sort | Henrik A Kolstad |
| collection | DOAJ |
| description | We want to thank Drs. Burstyn & Luta (1) for their recognition of our recent study (2) suggesting that estimates of breast cancer risk following retrospective self-reported night shift work are inflated by recall bias. The main strength of the study was a gold standard based on individual, prospective, objective and detailed information on night shift work that allowed validation of self-reported night shift work obtained after breast cancer was diagnosed – the usual situation for case–control studies (3). The study confirmed what textbooks have long taught but rarely documented empirically (4–6). We also want to thank Drs. Burstyn & Luta for their advice on how we could have utilized this precious dataset not only for simple but also probabilistic and Bayesian quantitative bias analyses. Even if highly instructive, this may still require strong statistical involvement. Using data provided in our paper, Drs. Burstyn & Luta’s bias-corrected odds ratio (OR) estimate of breast cancer following night shift work was centered around 1.0 (95% credible interval 0.3–1.7) and suggests that recall bias could completely, and not only partly as in our analysis (OR 1.05; correctly computed 95% confidence interval 0.88–1.27), explain the observed associations between night shift work and breast cancer found in case–control studies with retrospective self-reported exposure information. This finding strengthens our concern that breast cancer studies based on retrospective self-reports of night shifts may not provide convincing evidence. The gold standard of this validation study was based on a cohort of healthcare workers with day-by-day night shift information from a pay roll register and has earlier been used for breast cancer risk assessment showing no increased risk (7). A recent Swedish study using comparable data neither showed an overall increased risk (8). However, these studies included only information on recent night shift work. The next step should be a follow up of the cohorts when information on more distant night shift work becomes available with an emphasis on analyses that explore the timing of shift work on breast cancer risk. References 1. Burstyn I, Luta G. Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias). Scand J Work Environ Health – online first. https://doi.org/10.5271/sjweh.4226 2. Vestergaard JM, Haug JN, Dalbøge A, Bonde JP, Garde AH, Hansen J et al. Validity of self-reported night shift work among women with and without breast cancer. Scand J Work Environ Health. 2024;50(3):152–7. https://doi.org/10.5271/sjweh.4142. 3. Cordina-Duverger E, Menegaux F, Popa A, Rabstein S, Harth V, Pesch B et al. Night shift work and breast cancer: a pooled analysis of population-based case-control studies with complete work history. Eur J Epidemiol. 2018; 33(4):369–79. https://doi.org/10.1007/s10654-018-0368-x. 4. Berrington de González A, Richardson DB, Schubauer-Berigan MK. Statistical methods in cancer research, Volume V. Bias assessment in case–control and cohort studies for hazard identification. Lyon, France: International Agency for Research on Cancer; 2024. 5. Checkoway H, Pearce N, Kriebel D. Research Methods in Occupational Epidemiology. New York: Oxford University Press 2004. p372. 6. Rothman KJ. Modern Epidemiology. Boston/Toronto: Little, Brown and Company; 1986. p358. 7. Vistisen HT, Garde AH, Frydenberg M, Christiansen P, Hansen AM, Hansen J et al. Short-term effects of night shift work on breast cancer risk: a cohort study of payroll data. Scand J Work Environ Health. 2017;43(1):59–67. https://doi.org/10.5271/sjweh.3603. 8. Gustavsson P, Bigert C, Andersson T, Kader M, Härmä M, Selander J et al. Night work and breast cancer risk in a cohort of female healthcare employees in Stockholm, Sweden. Occup Environ Med. 2023;80(7):372–6. https://doi.org/10.1136/oemed-2022-108673. Henrik Albert Kolstad, MD,1, 2 Jesper Medom Vestergaard, MIT,1 Jens Peter Bonde, MD,3 Sadie Costello, PhD,4 Annett Dalbøge, PhD,1 Åse Marie Hansen, PhD,5, 6 Ann Dyreborg Larsen, PhD,6 Anne Helene Garde, PhD 5, 6 1 Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark. 2 Department of Clinical Medicine, Aarhus University, Denmark. 3 Department of Occupational and Environmental Medicine, Bispebjerg and Frederiksberg Hospital, Denmark. 4 Environmental Health Science, School of Public Health, University of California, Berkeley, USA. 5 The National Research Centre for the Working Environment, Denmark. 6 Department of Public Health, University of Copenhagen, Denmark. Correspondence to: Henrik Kolstad, Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark. [E-mail: kolstad@clin.au.dk] |
| format | Article |
| id | doaj-art-3d63d73cb0c748839f23bb1a5ba05fc5 |
| institution | Matheson Library |
| issn | 0355-3140 1795-990X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nordic Association of Occupational Safety and Health (NOROSH) |
| record_format | Article |
| series | Scandinavian Journal of Work, Environment & Health |
| spelling | doaj-art-3d63d73cb0c748839f23bb1a5ba05fc52025-06-27T09:09:00ZengNordic Association of Occupational Safety and Health (NOROSH)Scandinavian Journal of Work, Environment & Health0355-31401795-990X2025-07-0151434734810.5271/sjweh.42324232Response to Drs. Igor Burstyn and George Luta’s letter: Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias)Henrik A Kolstad0Jesper Medom Vestergaard1Jens Peter Bonde2Sadie Costello3Annett Dalbøge4Åse Marie Hansen5Ann Dyreborg Larsen6Anne Helene Garde7Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark.Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark.Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark.Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark.Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark.Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark.Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark.Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark.We want to thank Drs. Burstyn & Luta (1) for their recognition of our recent study (2) suggesting that estimates of breast cancer risk following retrospective self-reported night shift work are inflated by recall bias. The main strength of the study was a gold standard based on individual, prospective, objective and detailed information on night shift work that allowed validation of self-reported night shift work obtained after breast cancer was diagnosed – the usual situation for case–control studies (3). The study confirmed what textbooks have long taught but rarely documented empirically (4–6). We also want to thank Drs. Burstyn & Luta for their advice on how we could have utilized this precious dataset not only for simple but also probabilistic and Bayesian quantitative bias analyses. Even if highly instructive, this may still require strong statistical involvement. Using data provided in our paper, Drs. Burstyn & Luta’s bias-corrected odds ratio (OR) estimate of breast cancer following night shift work was centered around 1.0 (95% credible interval 0.3–1.7) and suggests that recall bias could completely, and not only partly as in our analysis (OR 1.05; correctly computed 95% confidence interval 0.88–1.27), explain the observed associations between night shift work and breast cancer found in case–control studies with retrospective self-reported exposure information. This finding strengthens our concern that breast cancer studies based on retrospective self-reports of night shifts may not provide convincing evidence. The gold standard of this validation study was based on a cohort of healthcare workers with day-by-day night shift information from a pay roll register and has earlier been used for breast cancer risk assessment showing no increased risk (7). A recent Swedish study using comparable data neither showed an overall increased risk (8). However, these studies included only information on recent night shift work. The next step should be a follow up of the cohorts when information on more distant night shift work becomes available with an emphasis on analyses that explore the timing of shift work on breast cancer risk. References 1. Burstyn I, Luta G. Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias). Scand J Work Environ Health – online first. https://doi.org/10.5271/sjweh.4226 2. Vestergaard JM, Haug JN, Dalbøge A, Bonde JP, Garde AH, Hansen J et al. Validity of self-reported night shift work among women with and without breast cancer. Scand J Work Environ Health. 2024;50(3):152–7. https://doi.org/10.5271/sjweh.4142. 3. Cordina-Duverger E, Menegaux F, Popa A, Rabstein S, Harth V, Pesch B et al. Night shift work and breast cancer: a pooled analysis of population-based case-control studies with complete work history. Eur J Epidemiol. 2018; 33(4):369–79. https://doi.org/10.1007/s10654-018-0368-x. 4. Berrington de González A, Richardson DB, Schubauer-Berigan MK. Statistical methods in cancer research, Volume V. Bias assessment in case–control and cohort studies for hazard identification. Lyon, France: International Agency for Research on Cancer; 2024. 5. Checkoway H, Pearce N, Kriebel D. Research Methods in Occupational Epidemiology. New York: Oxford University Press 2004. p372. 6. Rothman KJ. Modern Epidemiology. Boston/Toronto: Little, Brown and Company; 1986. p358. 7. Vistisen HT, Garde AH, Frydenberg M, Christiansen P, Hansen AM, Hansen J et al. Short-term effects of night shift work on breast cancer risk: a cohort study of payroll data. Scand J Work Environ Health. 2017;43(1):59–67. https://doi.org/10.5271/sjweh.3603. 8. Gustavsson P, Bigert C, Andersson T, Kader M, Härmä M, Selander J et al. Night work and breast cancer risk in a cohort of female healthcare employees in Stockholm, Sweden. Occup Environ Med. 2023;80(7):372–6. https://doi.org/10.1136/oemed-2022-108673. Henrik Albert Kolstad, MD,1, 2 Jesper Medom Vestergaard, MIT,1 Jens Peter Bonde, MD,3 Sadie Costello, PhD,4 Annett Dalbøge, PhD,1 Åse Marie Hansen, PhD,5, 6 Ann Dyreborg Larsen, PhD,6 Anne Helene Garde, PhD 5, 6 1 Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark. 2 Department of Clinical Medicine, Aarhus University, Denmark. 3 Department of Occupational and Environmental Medicine, Bispebjerg and Frederiksberg Hospital, Denmark. 4 Environmental Health Science, School of Public Health, University of California, Berkeley, USA. 5 The National Research Centre for the Working Environment, Denmark. 6 Department of Public Health, University of Copenhagen, Denmark. Correspondence to: Henrik Kolstad, Occupational and Environmental Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark. [E-mail: kolstad@clin.au.dk] https://www.sjweh.fi/article/4232 odds ratiorecall biasvalidation studylettervalidation dataexposure misclassification |
| spellingShingle | Henrik A Kolstad Jesper Medom Vestergaard Jens Peter Bonde Sadie Costello Annett Dalbøge Åse Marie Hansen Ann Dyreborg Larsen Anne Helene Garde Response to Drs. Igor Burstyn and George Luta’s letter: Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias) Scandinavian Journal of Work, Environment & Health odds ratio recall bias validation study letter validation data exposure misclassification |
| title | Response to Drs. Igor Burstyn and George Luta’s letter: Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias) |
| title_full | Response to Drs. Igor Burstyn and George Luta’s letter: Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias) |
| title_fullStr | Response to Drs. Igor Burstyn and George Luta’s letter: Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias) |
| title_full_unstemmed | Response to Drs. Igor Burstyn and George Luta’s letter: Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias) |
| title_short | Response to Drs. Igor Burstyn and George Luta’s letter: Advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification (recall bias) |
| title_sort | response to drs igor burstyn and george luta s letter advice on better utilization of validation data to adjust odds ratios for differential exposure misclassification recall bias |
| topic | odds ratio recall bias validation study letter validation data exposure misclassification |
| url |
https://www.sjweh.fi/article/4232
|
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