Pamela M Marcus1, Vincent Paul Doria-Rose2, Ilana F Gareen3, Brenda Brewer4, Kathy Clingan4, Kristen Keating4, Jennifer Rosenbaum4, Heather M Rozjabek5, Joshua Rathmell6, JoRean Sicks7, Anthony B Miller8. 1. National Cancer Institute, Bethesda, MD, USA marcusp@mail.nih.gov. 2. National Cancer Institute, Bethesda, MD, USA. 3. Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, USA. 4. Westat, Inc., Rockville, MD, USA. 5. Drexel University School of Public Health, Philadelphia, PA, USA. 6. Information Management Systems, Inc., Rockville, MD, USA. 7. Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, USA. 8. Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Abstract
BACKGROUND/AIMS: Randomized controlled trials frequently use death review committees to assign a cause of death rather than relying on cause of death information from death certificates. The National Lung Screening Trial, a randomized controlled trial of lung cancer screening with low-dose computed tomography versus chest X-rayfor heavy and/or long-term smokers ages 55-74 years at enrollment, used a committee blinded to arm assignment for a subset of deaths to determine whether cause of death was due to lung cancer. METHODS: Deaths were selected for review using a pre-determined computerized algorithm. The algorithm, which considered cancers diagnosed during the trial, causes and significant conditions listed on the death certificate, and the underlying cause of death derived from death certificate information by trained nosologists, selected deaths that were most likely to represent a death due to lung cancer (either directly or indirectly) and deaths that might have been erroneously assigned lung cancer as the cause of death. The algorithm also selected deaths that might be due to adverse events of diagnostic evaluation for lung cancer. Using the review cause of death as the gold standard and lung cancer cause of death as the outcome of interest (dichotomized as lung cancer versus not lung cancer), we calculated performance measures of the death certificate cause of death. We also recalculated the trial primary endpoint using the death certificate cause of death. RESULTS: In all, 1642 deaths were reviewed and assigned a cause of death (42% of the 3877 National Lung Screening Trial deaths). Sensitivity of death certificate cause of death was 91%; specificity, 97%; positive predictive value, 98%; and negative predictive value, 89%. About 40% of the deaths reclassified to lung cancer cause of death had a death certificate cause of death of a neoplasm other than lung. Using the death certificate cause of death, the lung cancer mortality reduction was 18% (95% confidence interval: 4.2-25.0), as compared with the published finding of 20% (95% confidence interval: 6.7-26.7). CONCLUSION: Death review may not be necessary for primary-outcome analyses in lung cancer screening trials. If deemed necessary, researchers should strive to streamline the death review process as much as possible.
RCT Entities:
BACKGROUND/AIMS: Randomized controlled trials frequently use death review committees to assign a cause of death rather than relying on cause of death information from death certificates. The National Lung Screening Trial, a randomized controlled trial of lung cancer screening with low-dose computed tomography versus chest X-ray for heavy and/or long-term smokers ages 55-74 years at enrollment, used a committee blinded to arm assignment for a subset of deaths to determine whether cause of death was due to lung cancer. METHODS: Deaths were selected for review using a pre-determined computerized algorithm. The algorithm, which considered cancers diagnosed during the trial, causes and significant conditions listed on the death certificate, and the underlying cause of death derived from death certificate information by trained nosologists, selected deaths that were most likely to represent a death due to lung cancer (either directly or indirectly) and deaths that might have been erroneously assigned lung cancer as the cause of death. The algorithm also selected deaths that might be due to adverse events of diagnostic evaluation for lung cancer. Using the review cause of death as the gold standard and lung cancer cause of death as the outcome of interest (dichotomized as lung cancer versus not lung cancer), we calculated performance measures of the death certificate cause of death. We also recalculated the trial primary endpoint using the death certificate cause of death. RESULTS: In all, 1642 deaths were reviewed and assigned a cause of death (42% of the 3877 National Lung Screening Trial deaths). Sensitivity of death certificate cause of death was 91%; specificity, 97%; positive predictive value, 98%; and negative predictive value, 89%. About 40% of the deaths reclassified to lung cancer cause of death had a death certificate cause of death of a neoplasm other than lung. Using the death certificate cause of death, the lung cancer mortality reduction was 18% (95% confidence interval: 4.2-25.0), as compared with the published finding of 20% (95% confidence interval: 6.7-26.7). CONCLUSION:Death review may not be necessary for primary-outcome analyses in lung cancer screening trials. If deemed necessary, researchers should strive to streamline the death review process as much as possible.
Authors: Denise R Aberle; Christine D Berg; William C Black; Timothy R Church; Richard M Fagerstrom; Barbara Galen; Ilana F Gareen; Constantine Gatsonis; Jonathan Goldin; John K Gohagan; Bruce Hillman; Carl Jaffe; Barnett S Kramer; David Lynch; Pamela M Marcus; Mitchell Schnall; Daniel C Sullivan; Dorothy Sullivan; Carl J Zylak Journal: Radiology Date: 2010-11-02 Impact factor: 11.105
Authors: V Paul Doria-Rose; Pamela M Marcus; Anthony B Miller; Eric J Bergstralh; Jack S Mandel; Melvyn S Tockman; Philip C Prorok Journal: Clin Trials Date: 2010-02 Impact factor: 2.486
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Authors: Pamela M Marcus; Ilana F Gareen; Anthony B Miller; Jennifer Rosenbaum; Kristen Keating; Denise R Aberle; Christine D Berg Journal: Contemp Clin Trials Date: 2011-07-18 Impact factor: 2.226
Authors: Asha Bonney; Reem Malouf; Corynne Marchal; David Manners; Kwun M Fong; Henry M Marshall; Louis B Irving; Renée Manser Journal: Cochrane Database Syst Rev Date: 2022-08-03
Authors: Joel R Wilkie; Rachel Lipson; Matthew C Johnson; Christina Williams; Drew Moghanaki; David Elliott; Dawn Owen; Namratha Atluri; Shruti Jolly; Christina Hunter Chapman Journal: Adv Radiat Oncol Date: 2021-04-20
Authors: Jatinderpal K Kalsi; Andy Ryan; Aleksandra Gentry-Maharaj; Danielle Margolin-Crump; Naveena Singh; Matthew Burnell; Elizabeth Benjamin; Sophia Apostolidou; Mariam Habib; Susan Massingham; Chloe Karpinskyj; Robert Woolas; Martin Widschwendter; Lesley Fallowfield; Stuart Campbell; Steven Skates; Alistair McGuire; Max Parmar; Ian Jacobs; Usha Menon Journal: Trials Date: 2021-01-25 Impact factor: 2.279