Scan-based competing death risk model for re-evaluating lung cancer computed tomography screening eligibility. Issue 5 (12th May 2022)
- Record Type:
- Journal Article
- Title:
- Scan-based competing death risk model for re-evaluating lung cancer computed tomography screening eligibility. Issue 5 (12th May 2022)
- Main Title:
- Scan-based competing death risk model for re-evaluating lung cancer computed tomography screening eligibility
- Authors:
- 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 - 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 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 (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 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. Lung cancer CT screening participants with a relatively low risk of lung cancer incidence and a high risk of competing death can be identified by applying two respective post-scan risk models, and in turn may benefit from other personalised trajectories https://bit.ly/2ZDe62K … (more)
- Is Part Of:
- European respiratory journal. Volume 59:Issue 5(2022)
- Journal:
- European respiratory journal
- Issue:
- Volume 59:Issue 5(2022)
- Issue Display:
- Volume 59, Issue 5 (2022)
- Year:
- 2022
- Volume:
- 59
- Issue:
- 5
- Issue Sort Value:
- 2022-0059-0005-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-05-12
- Subjects:
- Respiratory organs -- Diseases -- Periodicals
Respiration -- Periodicals
616.2 - Journal URLs:
- http://erj.ersjournals.com ↗
http://www.ersnet.org ↗
http://www.blackwell-synergy.com/member/institutions/issuelist.asp?journal=mrj ↗
http://www.ingenta.com/journals/browse/ers/erj?mode=direct ↗ - DOI:
- 10.1183/13993003.01613-2021 ↗
- Languages:
- English
- ISSNs:
- 0903-1936
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - BLDSS-3PM
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