Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis

In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk mod...

Full description

Saved in:
Bibliographic Details
Published in:Annals of internal medicine Vol. 176; no. 3; pp. 320 - 332
Main Authors: Toumazis, Iakovos, Cao, Pianpian, de Nijs, Koen, Bastani, Mehrad, Munshi, Vidit, Hemmati, Mehdi, Ten Haaf, Kevin, Jeon, Jihyoun, Tammemägi, Martin, Gazelle, G Scott, Feuer, Eric J, Kong, Chung Yin, Meza, Rafael, de Koning, Harry J, Plevritis, Sylvia K, Han, Summer S
Format: Journal Article
Language:English
Published: United States 01-03-2023
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening. To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds. Comparative modeling analysis. National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator. 1960 U.S. birth cohort. 45 years. U.S. health care sector. Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model. Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost. Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%). Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions. Risk models were restricted to age, sex, and smoking-related risk predictors. Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration. National Cancer Institute (NCI).
AbstractList In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening. To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds. Comparative modeling analysis. National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator. 1960 U.S. birth cohort. 45 years. U.S. health care sector. Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model. Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost. Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%). Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions. Risk models were restricted to age, sex, and smoking-related risk predictors. Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration. National Cancer Institute (NCI).
BACKGROUNDIn their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening.OBJECTIVETo evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds.DESIGNComparative modeling analysis.DATA SOURCESNational Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator.TARGET POPULATION1960 U.S. birth cohort.TIME HORIZON45 years.PERSPECTIVEU.S. health care sector.INTERVENTIONAnnual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model.OUTCOME MEASURESIncremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost.RESULTS OF BASE-CASE ANALYSISRisk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%).RESULTS OF SENSITIVITY ANALYSESRisk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions.LIMITATIONRisk models were restricted to age, sex, and smoking-related risk predictors.CONCLUSIONRisk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration.PRIMARY FUNDING SOURCENational Cancer Institute (NCI).
Author Meza, Rafael
Munshi, Vidit
Ten Haaf, Kevin
Hemmati, Mehdi
Jeon, Jihyoun
de Koning, Harry J
Bastani, Mehrad
Tammemägi, Martin
Toumazis, Iakovos
Plevritis, Sylvia K
Han, Summer S
Gazelle, G Scott
Kong, Chung Yin
de Nijs, Koen
Cao, Pianpian
Feuer, Eric J
AuthorAffiliation 8 Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland
2 Department of Epidemiology, University of Michigan, Ann Arbor
4 Feinstein Institute for Medical Research, Northwell Health, New York
7 Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada
5 Department of Radiology, Massachusetts General Hospital, Boston
6 Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California
10 Department of Biomedical Data Sciences, Stanford University, Stanford, California
3 Erasmus MC-University Medical Center, Rotterdam, the Netherlands
9 Division of General Internal Medicine, Department of Medicine, Mount Sinai Hospital, New York, New York
1 Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas
AuthorAffiliation_xml – name: 1 Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas
– name: 4 Feinstein Institute for Medical Research, Northwell Health, New York
– name: 8 Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland
– name: 3 Erasmus MC-University Medical Center, Rotterdam, the Netherlands
– name: 9 Division of General Internal Medicine, Department of Medicine, Mount Sinai Hospital, New York, New York
– name: 7 Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada
– name: 6 Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California
– name: 2 Department of Epidemiology, University of Michigan, Ann Arbor
– name: 5 Department of Radiology, Massachusetts General Hospital, Boston
– name: 10 Department of Biomedical Data Sciences, Stanford University, Stanford, California
Author_xml – sequence: 1
  givenname: Iakovos
  orcidid: 0000-0002-3462-2137
  surname: Toumazis
  fullname: Toumazis, Iakovos
  organization: Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas (I.T., M.H.)
– sequence: 2
  givenname: Pianpian
  orcidid: 0000-0001-8886-9672
  surname: Cao
  fullname: Cao, Pianpian
  organization: Department of Epidemiology, University of Michigan, Ann Arbor, Michigan (P.C., J.J.)
– sequence: 3
  givenname: Koen
  orcidid: 0000-0003-1451-0557
  surname: de Nijs
  fullname: de Nijs, Koen
  organization: Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.)
– sequence: 4
  givenname: Mehrad
  surname: Bastani
  fullname: Bastani, Mehrad
  organization: Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York (M.B.)
– sequence: 5
  givenname: Vidit
  surname: Munshi
  fullname: Munshi, Vidit
  organization: Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (V.M., G.S.G.)
– sequence: 6
  givenname: Mehdi
  orcidid: 0000-0002-0560-3893
  surname: Hemmati
  fullname: Hemmati, Mehdi
  organization: Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas (I.T., M.H.)
– sequence: 7
  givenname: Kevin
  orcidid: 0000-0001-5006-6938
  surname: Ten Haaf
  fullname: Ten Haaf, Kevin
  organization: Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.)
– sequence: 8
  givenname: Jihyoun
  orcidid: 0000-0001-7003-3412
  surname: Jeon
  fullname: Jeon, Jihyoun
  organization: Department of Epidemiology, University of Michigan, Ann Arbor, Michigan (P.C., J.J.)
– sequence: 9
  givenname: Martin
  orcidid: 0000-0002-4989-5058
  surname: Tammemägi
  fullname: Tammemägi, Martin
  organization: Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada (M.T.)
– sequence: 10
  givenname: G Scott
  surname: Gazelle
  fullname: Gazelle, G Scott
  organization: Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (V.M., G.S.G.)
– sequence: 11
  givenname: Eric J
  orcidid: 0000-0003-4842-7751
  surname: Feuer
  fullname: Feuer, Eric J
  organization: Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland (E.J.F.)
– sequence: 12
  givenname: Chung Yin
  orcidid: 0000-0001-6431-7830
  surname: Kong
  fullname: Kong, Chung Yin
  organization: Division of General Internal Medicine, Department of Medicine, Mount Sinai Hospital, New York, New York (C.Y.K.)
– sequence: 13
  givenname: Rafael
  orcidid: 0000-0002-1076-5037
  surname: Meza
  fullname: Meza, Rafael
  organization: Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, and Department of Integrative Oncology, BC Cancer Research Institute, British Columbia, Canada (R.M.)
– sequence: 14
  givenname: Harry J
  orcidid: 0000-0003-4682-3646
  surname: de Koning
  fullname: de Koning, Harry J
  organization: Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.)
– sequence: 15
  givenname: Sylvia K
  surname: Plevritis
  fullname: Plevritis, Sylvia K
  organization: Department of Biomedical Data Sciences, Stanford University, Stanford, California (S.K.P.)
– sequence: 16
  givenname: Summer S
  orcidid: 0000-0002-2013-6883
  surname: Han
  fullname: Han, Summer S
  organization: Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California (S.S.H.)
BackLink https://www.ncbi.nlm.nih.gov/pubmed/36745885$$D View this record in MEDLINE/PubMed
BookMark eNpVkNtKw0AQhhep2IOCTyC59Ca65yTeSA2tCi2Ch-tluzupq-lGs0mhb2-KterVMDMf_wzfEPV85QGhU4IvEkbl5ZzSmFIiD9CACJbFLMG8hwYYYxbzlGR9NAzhbdumND1CfSYTLtJUDND00YX3aF5ZKOMbHcBGs9Yvo1x7A3X0ZGoA77rBVTSO8io08aQowDRuDR5CiMZel5vgwjE6LHQZ4GRXR-hlOnnO7-LZw-19Pp7FhmHcxBaKQoPEwhYSBNhFxjkjHKQgC55KbbBJZEZwyrUEm4iM2o7OTCq0wJnI2Ahdf-d-tIsVWAO-qXWpPmq30vVGVdqp_xvvXtWyWitCMBWS4i7hfJdQV58thEatXDBQltpD1QZFk4RTmVApf1FTVyHUUOzvEKy23lXnXW29d-jZ37_24I9o9gUDQX40
Cites_doi 10.1001/jama.2016.6255
10.1038/sj.bjc.6605459
10.7326/M20-1392
10.1002/cncr.32026
10.1097/JTO.0b013e31822e59b3
10.1177/0272989X06290497
10.1002/cncr.33835
10.1371/journal.pmed.1001764
10.7326/M18-1250
10.7326/M19-0322
10.7326/M17-2701
10.21037/tlcr-20-753
10.1177/0272989X15570364
10.1016/j.lungcan.2018.05.008
10.1002/cncr.28623
10.1002/cam4.1896
10.1002/cncr.33839
10.1093/jnci/djz165
10.1513/AnnalsATS.202111-1253OC
10.1177/0962280221995972
10.7326/M13-2316
10.1093/jncics/pkz035
10.1016/j.jtho.2020.02.008
10.1016/j.amepre.2013.10.022
10.1001/jama.2013.285112
10.1158/1055-9965.EPI-14-0745
10.7326/M17-2561
10.1007/s10552-017-0907-x
10.1016/j.lungcan.2020.07.007
10.1016/j.jtho.2018.08.1819
10.1258/jms.2011.010127
10.21037/tlcr-20-985
10.1002/ijc.33578
10.1513/AnnalsATS.201810-690RL
10.1001/jamaoncol.2015.2472
10.1001/jama.2021.1117
10.1001/jamanetworkopen.2019.0204
10.1093/jncics/pkab081
10.1016/j.jtho.2017.04.021
10.1016/j.chest.2021.06.066
10.1093/jnci/djaa211
10.1111/j.1539-6924.2011.01652.x
10.1016/j.athoracsur.2020.07.051
10.7326/M17-1401
10.1016/j.lungcan.2018.10.029
10.1371/journal.pmed.1002277
10.7326/M19-1263
10.1007/s10552-011-9866-9
10.1016/j.chest.2020.04.063
10.1093/jnci/djz164
10.1001/jama.2021.1077
10.1001/jamaoncol.2021.4942
10.1056/NEJMoa1211776
10.1093/jnci/djaa013
10.1111/j.1539-6924.2011.01681.x
10.1513/AnnalsATS.201902-102OC
10.1016/j.jtho.2020.08.006
10.1056/NEJMp1405158
10.1093/jnci/djab002
10.1371/journal.pone.0099978
10.1093/jnci/djz041
10.1016/S1470-2045(21)00590-8
10.1002/cncr.28833
10.1136/thoraxjnl-2017-211377
ContentType Journal Article
DBID CGR
CUY
CVF
ECM
EIF
NPM
AAYXX
CITATION
7X8
5PM
DOI 10.7326/M22-2216
DatabaseName Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
CrossRef
MEDLINE - Academic
PubMed Central (Full Participant titles)
DatabaseTitle MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
CrossRef
MEDLINE - Academic
DatabaseTitleList MEDLINE
MEDLINE - Academic
Database_xml – sequence: 1
  dbid: ECM
  name: MEDLINE
  url: https://search.ebscohost.com/login.aspx?direct=true&db=cmedm&site=ehost-live
  sourceTypes: Index Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
EISSN 1539-3704
EndPage 332
ExternalDocumentID 10_7326_M22_2216
36745885
Genre Journal Article
Research Support, N.I.H., Extramural
GrantInformation_xml – fundername: NCI NIH HHS
  grantid: U01 CA253858
– fundername: NCI NIH HHS
  grantid: U01 CA199284
GroupedDBID ---
..I
.55
.GJ
.XZ
08G
1CY
23M
2WC
354
36B
39C
3O-
3V.
4.4
53G
5GY
5RE
5RS
6J9
7RV
7X7
88E
8C1
8F7
8FI
8FJ
8G5
8R4
8R5
AAKAS
AAQOH
AAQQT
AARDX
AAWTL
AAYOK
ABBLC
ABCQX
ABDPE
ABJNI
ABOCM
ABPMR
ABUWG
ACBNA
ACGFO
ACGFS
ADBBV
ADZCM
AEGXH
AENEX
AERZD
AFCHL
AFFNX
AFKRA
AHJKT
AHMBA
AI.
AIAGR
ALIPV
ALMA_UNASSIGNED_HOLDINGS
AQUVI
ASPBG
AVWKF
AZFZN
AZQEC
BCR
BCU
BEC
BENPR
BKEYQ
BKNYI
BLC
BPHCQ
BTJBQ
BVXVI
BZLQD
C1A
C45
CCPQU
CGR
CUY
CVF
DWQXO
E3Z
EBS
ECM
EIF
EJD
EMB
EMOBN
EX3
F5P
FEDTE
FYUFA
GNUQQ
GUQSH
H13
HMCUK
HVGLF
H~9
IH2
J5H
K-O
K9-
L7B
LPU
M0R
M0T
M1P
M2O
M5~
MV1
MVM
N4W
NAPCQ
NPM
OBH
OCB
OFXIZ
OGEVE
OHH
OHT
OVD
OVIDX
P2P
PCD
PQQKQ
PROAC
PSQYO
Q2X
RWL
RXW
S0X
SJFOW
SJN
SV3
TAE
TEORI
TPH
TR2
TWZ
UKHRP
UKR
VH1
VVN
WH7
WOQ
WOW
X6Y
X7M
XOL
YFH
YOC
YQJ
YYP
ZGI
ZXP
ZY1
~H1
AAYXX
CITATION
7X8
5PM
ID FETCH-LOGICAL-c300t-deffae605df6e5edb944314e651b486ac0c7691084a6ed7592de609c85a509593
ISSN 0003-4819
IngestDate Tue Sep 17 21:28:27 EDT 2024
Sat Aug 17 05:23:37 EDT 2024
Thu Nov 21 21:53:57 EST 2024
Sat Nov 02 12:05:59 EDT 2024
IsPeerReviewed true
IsScholarly true
Issue 3
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c300t-deffae605df6e5edb944314e651b486ac0c7691084a6ed7592de609c85a509593
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
equal contribution
ORCID 0000-0003-4842-7751
0000-0001-7003-3412
0000-0002-0560-3893
0000-0001-6431-7830
0000-0003-1451-0557
0000-0001-8886-9672
0000-0001-5006-6938
0000-0002-1076-5037
0000-0002-3462-2137
0000-0002-4989-5058
0000-0003-4682-3646
0000-0002-2013-6883
PMID 36745885
PQID 2774267266
PQPubID 23479
PageCount 13
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_11025620
proquest_miscellaneous_2774267266
crossref_primary_10_7326_M22_2216
pubmed_primary_36745885
PublicationCentury 2000
PublicationDate 2023-03-01
PublicationDateYYYYMMDD 2023-03-01
PublicationDate_xml – month: 03
  year: 2023
  text: 2023-03-01
  day: 01
PublicationDecade 2020
PublicationPlace United States
PublicationPlace_xml – name: United States
PublicationTitle Annals of internal medicine
PublicationTitleAlternate Ann Intern Med
PublicationYear 2023
References 36745888 - Ann Intern Med. 2023 Mar;176(3):413-414
r26-M222216
r71-M222216
r11-M222216
r39-M222216
r24-M222216
r7-M222216
r41-M222216
r67-M222216
r20-M222216
r37-M222216
r35-M222216
r22-M222216
r9-M222216
r52-M222216
r62-M222216
r49-M222216
r18-M222216
r31-M222216
r1-M222216
r16-M222216
r33-M222216
r50-M222216
r47-M222216
r3-M222216
r45-M222216
r43-M222216
r5-M222216
r60-M222216
r28-M222216
r12-M222216
r59-M222216
r8-M222216
r55-M222216
r70-M222216
r25-M222216
r40-M222216
r57-M222216
r23-M222216
r72-M222216
r42-M222216
r6-M222216
r10-M222216
r38-M222216
r66-M222216
r68-M222216
r51-M222216
r53-M222216
r36-M222216
r21-M222216
r48-M222216
r63-M222216
r17-M222216
r34-M222216
r46-M222216
r65-M222216
r15-M222216
r2-M222216
r30-M222216
r58-M222216
r4-M222216
r13-M222216
r27-M222216
r44-M222216
r61-M222216
References_xml – ident: r12-M222216
  doi: 10.1001/jama.2016.6255
– ident: r59-M222216
  doi: 10.1038/sj.bjc.6605459
– ident: r53-M222216
  doi: 10.7326/M20-1392
– ident: r65-M222216
  doi: 10.1002/cncr.32026
– ident: r49-M222216
  doi: 10.1097/JTO.0b013e31822e59b3
– ident: r47-M222216
  doi: 10.1177/0272989X06290497
– ident: r13-M222216
  doi: 10.1002/cncr.33835
– ident: r34-M222216
  doi: 10.1371/journal.pmed.1001764
– ident: r43-M222216
  doi: 10.7326/M18-1250
– ident: r23-M222216
  doi: 10.7326/M19-0322
– ident: r11-M222216
  doi: 10.7326/M17-2701
– ident: r31-M222216
  doi: 10.21037/tlcr-20-753
– ident: r48-M222216
  doi: 10.1177/0272989X15570364
– ident: r24-M222216
  doi: 10.1016/j.lungcan.2018.05.008
– ident: r42-M222216
  doi: 10.1002/cncr.28623
– ident: r51-M222216
  doi: 10.1002/cam4.1896
– ident: r66-M222216
  doi: 10.1002/cncr.33839
– ident: r8-M222216
  doi: 10.1093/jnci/djz165
– ident: r57-M222216
  doi: 10.1513/AnnalsATS.202111-1253OC
– ident: r55-M222216
  doi: 10.1177/0962280221995972
– ident: r35-M222216
  doi: 10.7326/M13-2316
– ident: r22-M222216
  doi: 10.1093/jncics/pkz035
– ident: r70-M222216
  doi: 10.1016/j.jtho.2020.02.008
– ident: r45-M222216
  doi: 10.1016/j.amepre.2013.10.022
– ident: r44-M222216
  doi: 10.1001/jama.2013.285112
– ident: r36-M222216
  doi: 10.1158/1055-9965.EPI-14-0745
– ident: r50-M222216
  doi: 10.7326/M17-2561
– ident: r39-M222216
  doi: 10.1007/s10552-017-0907-x
– ident: r3-M222216
  doi: 10.1016/j.lungcan.2020.07.007
– ident: r63-M222216
  doi: 10.1016/j.jtho.2018.08.1819
– ident: r62-M222216
  doi: 10.1258/jms.2011.010127
– ident: r67-M222216
  doi: 10.21037/tlcr-20-985
– ident: r5-M222216
  doi: 10.1002/ijc.33578
– ident: r72-M222216
  doi: 10.1513/AnnalsATS.201810-690RL
– ident: r68-M222216
  doi: 10.1001/jamaoncol.2015.2472
– ident: r1-M222216
  doi: 10.1001/jama.2021.1117
– ident: r6-M222216
  doi: 10.1001/jamanetworkopen.2019.0204
– ident: r25-M222216
  doi: 10.1093/jncics/pkab081
– ident: r28-M222216
  doi: 10.1016/j.jtho.2017.04.021
– ident: r20-M222216
  doi: 10.1016/j.chest.2021.06.066
– ident: r7-M222216
  doi: 10.1093/jnci/djaa211
– ident: r37-M222216
  doi: 10.1111/j.1539-6924.2011.01652.x
– ident: r16-M222216
  doi: 10.1016/j.athoracsur.2020.07.051
– ident: r26-M222216
  doi: 10.7326/M17-1401
– ident: r27-M222216
  doi: 10.1016/j.lungcan.2018.10.029
– ident: r30-M222216
  doi: 10.1371/journal.pmed.1002277
– ident: r9-M222216
  doi: 10.7326/M19-1263
– ident: r38-M222216
  doi: 10.1007/s10552-011-9866-9
– ident: r61-M222216
  doi: 10.1016/j.chest.2020.04.063
– ident: r4-M222216
  doi: 10.1093/jnci/djz164
– ident: r2-M222216
  doi: 10.1001/jama.2021.1077
– ident: r21-M222216
  doi: 10.1001/jamaoncol.2021.4942
– ident: r46-M222216
  doi: 10.1056/NEJMoa1211776
– ident: r60-M222216
  doi: 10.1093/jnci/djaa013
– ident: r40-M222216
  doi: 10.1111/j.1539-6924.2011.01681.x
– ident: r17-M222216
  doi: 10.1513/AnnalsATS.201902-102OC
– ident: r33-M222216
  doi: 10.1016/j.jtho.2020.08.006
– ident: r52-M222216
  doi: 10.1056/NEJMp1405158
– ident: r71-M222216
  doi: 10.1093/jnci/djab002
– ident: r41-M222216
  doi: 10.1371/journal.pone.0099978
– ident: r10-M222216
  doi: 10.1093/jnci/djz041
– ident: r15-M222216
  doi: 10.1016/S1470-2045(21)00590-8
– ident: r58-M222216
  doi: 10.1002/cncr.28833
– ident: r18-M222216
  doi: 10.1136/thoraxjnl-2017-211377
SSID ssj0003828
Score 2.546714
Snippet In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on...
BACKGROUNDIn their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people...
SourceID pubmedcentral
proquest
crossref
pubmed
SourceType Open Access Repository
Aggregation Database
Index Database
StartPage 320
SubjectTerms Aged, 80 and over
Cost-Benefit Analysis
Cost-Effectiveness Analysis
Early Detection of Cancer - methods
Humans
Lung
Lung Neoplasms - diagnostic imaging
Mass Screening - methods
Middle Aged
Quality-Adjusted Life Years
Title Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis
URI https://www.ncbi.nlm.nih.gov/pubmed/36745885
https://search.proquest.com/docview/2774267266
https://pubmed.ncbi.nlm.nih.gov/PMC11025620
Volume 176
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://sdu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwELfYkBAviG86PmQk3qZAajtxwtsYrQa0BbFM2lvkxGdtsCVT2_DAX885zldXHsYDL1bluk51v8v57mz_jpA3GpdxFZrMU8qXnsixiRRkXgjCsmNBxI3Ndxwdy8Vp9HEiJv11xb7vvyKNfYi1vTn7D2h3k2IHfkbMsUXUsb0R7t_tWXFb4ezC-4ArlN6fVXZn34K7xDfZHrOpswPNjfTV2nMExq3Va1lKhl5rz7J87hKIF1t78klZXarfjrDgk_pZ_io7Z_1Q1enYb6iIVwNl1IBq-KP-wZeyv5CGf3rt6kztz-FsqfQwL8F4fzDrLbS2NEb75aoLd8bWVXtptIoPTCdn_mAV5i7red3AS16XpJxjBM3Y-C8c2ouv6fRkNkuTyWmyQ24zND_W-h1_XnTrM8cg09EQ29netXNtOiZb0cb1Q7MDLyS5T-414QM9cLg_ILegeEjuzBswHpGphZ8O4KcWfurgpx389D09oNvg0xb8x-RkOkkOj7ymVIaXc99fexqMUYChqTYhBKCzWKBnKCAMxpmIQpX7uQzRM4yECkHLIGYaR8c5vqhBzU39hOwWZQHPCNWZYkZwLTPDhGQ8VoYpkEaO4yjLFYzI61ZO6ZVjREkxkrSyTFGWqZUljmkFmKK5sntQqoCyWqUMww0WSnQLR-SpE2g3Cw-lvTcdjEi0IepugKVC3_ymOD-rKdHRiUXfnfl7N3jwc3K319cXZHe9rOAl2Vnp6lWtKH8AzeZ9mg
link.rule.ids 230,315,782,786,887,27933,27934
linkProvider Multiple Vendors
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Risk+Model-Based+Lung+Cancer+Screening+%3A+A+Cost-Effectiveness+Analysis&rft.jtitle=Annals+of+internal+medicine&rft.au=Toumazis%2C+Iakovos&rft.au=Cao%2C+Pianpian&rft.au=de+Nijs%2C+Koen&rft.au=Bastani%2C+Mehrad&rft.date=2023-03-01&rft.eissn=1539-3704&rft.volume=176&rft.issue=3&rft.spage=320&rft.epage=332&rft_id=info:doi/10.7326%2FM22-2216&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0003-4819&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0003-4819&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0003-4819&client=summon