Scan-based competing death risk model for re-evaluating lung cancer computed tomography screening eligibility
Schreuder, Anton; Jacobs, Colin; Lessmann, Nikolas; Broeders, Mireille J.M.; Silva, Mario; Išgum, Ivana; de Jong, Pim A.; van den Heuvel, Michel M.; Sverzellati, Nicola; Prokop, Mathias; Pastorino, Ugo; Schaefer-Prokop, Cornelia M.; van Ginneken, Bram
(2022) The European respiratory journal, volume 59, issue 5, pp. 1 - 12
(Article)
Abstract
BACKGROUND: A baseline computed tomography (CT) scan for lung cancer (LC) screening may reveal information indicating that certain LC screening participants can be screened less, and instead require dedicated early cardiac and respiratory clinical input. We aimed to develop and validate competing death (CD) risk models using CT information to
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identify participants with a low LC risk and a high CD risk. METHODS: Participant demographics and quantitative CT measures of LC, cardiovascular disease and chronic obstructive pulmonary disease were considered for deriving a logistic regression model for predicting 5-year CD risk using a sample from the National Lung Screening Trial (n=15 000). Multicentric Italian Lung Detection data were used to perform external validation (n=2287). RESULTS: Our final CD model outperformed an external pre-scan model (CD Risk Assessment Tool) in both the derivation (area under the curve (AUC) 0.744 (95% CI 0.727-0.761) and 0.677 (95% CI 0.658-0.695), respectively) and validation cohorts (AUC 0.744 (95% CI 0.652-0.835) and 0.725 (95% CI 0.633-0.816), respectively). By also taking LC incidence risk into consideration, we suggested a risk threshold where a subgroup (6258/23 096 (27%)) was identified with a number needed to screen to detect one LC of 216 (versus 23 in the remainder of the cohort) and ratio of 5.41 CDs per LC case (versus 0.88). The respective values in the validation cohort subgroup (774/2287 (34%)) were 129 (versus 29) and 1.67 (versus 0.43). CONCLUSIONS: Evaluating both LC and CD risks post-scan may improve the efficiency of LC screening and facilitate the initiation of multidisciplinary trajectories among certain participants.
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Keywords: Early Detection of Cancer/methods, Humans, Lung, Lung Neoplasms/diagnosis, Mass Screening, Risk Assessment/methods, Tomography, X-Ray Computed/methods, Pulmonary and Respiratory Medicine, Journal Article, Research Support, N.I.H., Extramural
ISSN: 0903-1936
Publisher: European Respiratory Society
Note: Funding Information: Acknowledgements: The authors thank Gabriel Humpire Mamani (Radboud University Medical Center, Nijmegen, The Netherlands), Jean-Paul Charbonnier and Leticia Gallardo-Estrella (Thirona, Nijmegen, The Netherlands) for their technical support in obtaining quantitative CT measures, and Claudio Jacomelli and Frederica Sabia (Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy) for extracting the requested Multicentric Italian Lung Detection (MILD) trial data. The authors also thank the MILD research teams for access to MILD data and the National Cancer Institute (NCI) for access to the NCI’s data collected by the National Lung Screening Trial (NLST) under project number NLST-437. The statements contained herein are solely those of the authors and do not represent or imply concurrence or endorsement by the NCI. Funding Information: Conflict of interest: A. Schreuder has nothing to disclose. C. Jacobs reports grants from MeVis Medical Solutions AG, Bremen, Germany, outside the submitted work. N. Lessmann has nothing to disclose. M.J.M. Broeders has nothing to disclose. M. Silva has nothing to disclose. I. Išgum has nothing to disclose. P.A. de Jong reports departmental research support from Philips Healthcare, during the conduct of the study. M.M. van den Heuvel has nothing to disclose. N. Sverzellati has nothing to disclose. M. Prokop reports personal fees for lectures from Bracco, Bayer, Toshiba and Siemens, grants from Toshiba, other (departmental spin-off with no personal financial interest) from Thiroux, outside the submitted work. U. Pastorino has nothing to disclose. C.M. Schaefer-Prokop has nothing to disclose. B. van Ginneken reports royalties from MeVis Medical Solutions and Delft Imaging Systems, and is co-founder and shareholder of Thirona, outside the submitted work. Funding Information: The authors thank Gabriel Humpire Mamani (Radboud University Medical Center, Nijmegen, The Netherlands), Jean-Paul Charbonnier and Leticia Gallardo-Estrella (Thirona, Nijmegen, The Netherlands) for their technical support in obtaining quantitative CT measures, and Claudio Jacomelli and Frederica Sabia (Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy) for extracting the requested Multicentric Italian Lung Detection (MILD) trial data. The authors also thank the MILD research teams for access to MILD data and the National Cancer Institute (NCI) for access to the NCI’s data collected by the National Lung Screening Trial (NLST) under project number NLST-437. The statements contained herein are solely those of the authors and do not represent or imply concurrence or endorsement by the NCI. Publisher Copyright: Copyright ©The authors 2022. For reproduction rights and permissions contact permissions@ersnet.org.
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