TY - JOUR
T1 - Biomarkers in lung cancer screening
T2 - the importance of study design
AU - Baldwin, David R.
AU - Callister, Matthew E.
AU - Crosbie, Philip A.
AU - O'Dowd, Emma L.
AU - Rintoul, Robert C.
AU - Robbins, Hilary A.
AU - Steele, Robert J. C.
N1 - Funding Information:
Support statement: H.A. Robbins was supported in part by the INTEGRAL programme (U19 CA203654). P.A. Crosbie was supported by the NIHR Manchester Biomedical Research Centre. R.C. Rintoul is supported by the NIHR Cambridge Biomedical Research Centre and Cancer Research UK Cambridge Centre.
Conflict of interest: D.R. Baldwin reports personal fees from AstraZeneca, MSD, BMS, Roche and Johnson and Johnson, outside the submitted work. M.E. Callister has nothing to disclose. P.A. Crosbie reports personal fees from AstraZeneca and Novartis, personal fees and other from Everest Detection, outside the submitted work. E.L. O’Dowd has nothing to disclose. R.C. Rintoul reports personal fees from AstraZeneca and Roche, outside the submitted work; and is Chief Investigator of the LuCiD study, sponsored by Owlstone Medical but declares no financial support or financial interest in Owlstone Medical. H.A. Robbins has nothing to disclose. R.J.C. Steele has nothing to disclose.
Publisher Copyright:
Copyright © ERS 2021
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/1
Y1 - 2021/1
N2 - In most randomised controlled trials of low radiation dose computed tomography (LDCT) screening for lung cancer, eligibility has been determined by age and tobacco smoking criteria [1, 2]. A number of multivariable risk prediction models have been developed that are more sensitive and specific, but are still heavily dependent on smoking and age [3]. Some have been used successfully in trials and pilot programmes and have yielded higher detection rates, although they may also select people with more comorbidities [4-6]. Using biomarkers to select people for lung cancer screening is an important area for research because it offers the possibility to identify those at high risk who are not eligible for screening by conventional criteria, while avoiding further investigation in those who do not have malignant disease. This means that the impact of the intervention as a whole could be greater (more lives saved) and harms, due to the screening of low-risk people or those without cancer, could be avoided. Two biomarkers intended for use in lung screening are presented in this issue of the European Respiratory Journal.
AB - In most randomised controlled trials of low radiation dose computed tomography (LDCT) screening for lung cancer, eligibility has been determined by age and tobacco smoking criteria [1, 2]. A number of multivariable risk prediction models have been developed that are more sensitive and specific, but are still heavily dependent on smoking and age [3]. Some have been used successfully in trials and pilot programmes and have yielded higher detection rates, although they may also select people with more comorbidities [4-6]. Using biomarkers to select people for lung cancer screening is an important area for research because it offers the possibility to identify those at high risk who are not eligible for screening by conventional criteria, while avoiding further investigation in those who do not have malignant disease. This means that the impact of the intervention as a whole could be greater (more lives saved) and harms, due to the screening of low-risk people or those without cancer, could be avoided. Two biomarkers intended for use in lung screening are presented in this issue of the European Respiratory Journal.
KW - lung cancer screening
KW - biomarkers
KW - methodology of clinical trials
U2 - 10.1183/13993003.04367-2020
DO - 10.1183/13993003.04367-2020
M3 - Editorial
C2 - 33446580
SN - 0903-1936
VL - 57
JO - European Respiratory Journal
JF - European Respiratory Journal
IS - 1
M1 - 2004367
ER -
