Number of Pages: 4 (Double Spaced) Number of sources: 8 Writing Style: APA Type of document: Coursework Category: Healthcare Order Instructions: Comprehensive Article Review Caverly, T.J., Fagerlin, A, & Wiener, R.S. (2018, January 22). Comparison of observed harms and expected mortality benefit for persons in the Veterans Health Affairs Lung Cancer Screening Demonstration Project. JAMA Internal Medicine. 1. What research questions are addressed in this study and what is their purpose (5 points)? 2. What type of research design was used (experimental, quasi-experimental, correlational) in this study and what led you to your decision (5 points)? 3. Are the instruments in this study valid and reliable, why or why not (10 points)? 4. Discuss the specific results of each of the ANCOVAs (analysis of covariance) done in this study. What was the purpose of"each" of the ANCOVAs? What was the covariate in each and why did they do an ANCOVA in each case (5 points)? 5. In the Tables, results are presented, Please explain the tables and summarize the results (15 points). 6. Explain, in simple language, any significant results of this study (25 points)? 7. Identify and discuss any threats to internal and/or external validity in this study (10 points). 8. If you could redesign this study correcting anything you have found wrong with the research, what would you correct and how would you do it (20 points)? Opinion EDITORIAL Reducing Harms in Lung Cancer Screening­ Bach to the Future Michael ln cze, MD, MSEd: Rita F. Redberg, MD, MSc TbeUS PreventativeServices Task Force cmrcntly recom­ mends si:;ree ning (grade Brecommendation)for lung canc er witha nnuallow-dose computed tomo graph}' for high-risk in­ dividuals ages55 to 80 years, defined as those having greate r gLblefor LCS using the Bach risk tool,11 a vaJidatcd risk model usingsex,age, smokingduration, durationof abstinence from smoking and number of cigarettes smoked per day as inpu ts. The asto undingly high ratesof false-pos itiveresults in the low­ =Related attid e than a 30 pack-year cumula­ tivesmoking historyand h av• ing quit with in the past 15 years.1 The evide nce to sup­ est risk quintiles (eg, 2221false-positive resul ts per lung ca n­ cer death averted and a NNS of nearly 5600 in quintile1), as well as extremelylow ratesoflungcancerincidencein the low­ est-risk groups, confirm trends illustrated in previous stud­ port thisrecommendation overwhelminglycomes rrom the Na­ tional Lung CancerScreenfngTrial(NL ST). While3 other large randomized clinical trials failed to show any mortality ben­ efit tolung cancer screening (LCS), the NLST demonstrateda 20% reduction in lungcan ce r mortality,a lo ng with a 6.7% re­ duction in .ill-ca use mortality, when compared with an an­ nual chest radiograph, witb a number needed toscreen (NNS} of256to prevent I lung-cancerassociated death over3years.-2 5 Real-worldapplication ofLCS has been particularly .

1. Number of Pages: 4 (Double Spaced)
Number of sources: 8
Writing Style: APA
Type of document: Coursework
Category: Healthcare
Order Instructions:
Comprehensive Article Review
Caverly, T.J., Fagerlin, A, & Wiener, R.S. (2018, January 22).
Comparison of observed harms and expected mortality benefit
for persons in the Veterans Health Affairs Lung Cancer
Screening Demonstration Project. JAMA Internal Medicine.
1. What research questions are addressed in this study and
what is their purpose (5 points)?
2. What type of research design was used (experimental,
quasi-experimental, correlational) in this study and what led
you to your decision (5 points)?

2. 3. Are the instruments in this study valid and reliable, why or
why not (10 points)?
4. Discuss the specific results of each of the ANCOVAs
(analysis of covariance) done in this study. What was the
purpose of"each" of the ANCOVAs? What was the covariate in
each and why did they do an ANCOVA in each case (5 points)?
5. In the Tables, results are presented, Please explain the
tables and summarize the results (15 points).
6. Explain, in simple language, any significant results of this
study (25 points)?
7. Identify and discuss any threats to internal and/or external
validity in this study (10 points).
8. If you could redesign this study correcting anything you
have found wrong with the research, what would you correct
and how would you do it (20 points)?
Opinion

3. EDITORIAL
Reducing Harms in Lung Cancer Screening-
Bach to the Future
Michael ln cze, MD, MSEd: Rita F. Redberg, MD, MSc
TbeUS PreventativeServices Task Force cmrcntly recom- mends
si:;ree ning (grade Brecommendation)for lung canc er witha
nnuallow-dose computed tomo graph}' for high-risk in-
dividuals ages55 to 80 years, defined as those having greate r
gLblefor LCS using the Bach risk tool,11 a vaJidatcd risk model
usingsex,age, smokingduration, durationof abstinence from
smoking and number of cigarettes smoked per day as inpu ts.
The asto undingly high ratesof false-pos itiveresults in the low-
=Related attid e
than a 30 pack-year cumula­ tivesmoking historyand h av• ing
quit with in the past 15 years.1 The evide nce to sup-
est risk quintiles (eg, 2221false-positive resul ts per lung ca n-
cer death averted and a NNS of nearly 5600 in quintile1), as
well as extremelylow ratesoflungcancerincidencein the low- est-
risk groups, confirm trends illustrated in previous stud-
port thisrecommendation overwhelminglycomes rrom the Na-
tional Lung CancerScreenfngTrial(NL ST). While3 other large
randomized clinical trials failed to show any mortality ben- efit
tolung cancer screening (LCS), the NLST demonstrateda 20%
reduction in lungcan ce r mortality,a lo ng with a 6.7% re-
duction in .ill-ca use mortality, when compared with an an- nual
chest radiograph, witb a number needed toscreen (NNS} of256to
prevent I lung-cancerassociated death over3years.-2 5 Real-

4. worldapplication ofLCS has been particularly chal- lenging, w
ith evidence of inappropriate U.% in low-risk per- sonsalong
with very high rates.o fincidental lindings a.nd false - positive
resultsleadiag to a muchhigher harm o benefit ratio than what
was seen in randomized clinical trials.·2 7 The most robust
implementation data to date,conducted on alargehigh- risk
population through the Veterans Health Administration system,
dcmonstr.itc-0 that 56% of those screened had nod- ules
requiring follow-up with repeated imaging and/or inva-
siveprocedures, and 40%ha.d incidentalfindings,such asem-
physema and coronary arte ry calcificatio, 11 with a relatively
!ow cm ce r detection rate of 1.5% (even lower for early-stage
(
-
)cancers tbat mostbenefit fro m sc;r,eening).GTncreasing l y,
there has beenconcern aboutboth the cost-effectiven
essofLCSand the harms associated with screening, including
high rates of incidentalfindings (resulting in unnecessary
i.nvasive proce- dures and emotionalstress), as well as radiation
ex posure (pos - sibly leading tosecondar y malignant
neop!asm.7 9 1 hese flild- ings raise the question of whethe r a
more targeted inclusion criteria maydecrease the total
numberofpatientsscreened and the false-posi tivity ra te
withoutsacrificingt.he mortality ben- efit seen in the NLST.
It is against this background that Caverly ct al10 examine
the impact of riskstratifying a real-world cohort of patientseli·
ies and make lhe case for refined guidelines for LCS.1 .n This
is es pecially salienti n light of recent evi dence suggesting t ha
t bl,gh numbers oflow-riskindividuals arebeingscreenedin.real·
world practice.7
Unfortunately, the useof LDCTscreeningevenin the high- est -
risk quintiles isstill associated with alarm ingly high rates of
false-positive results-302 false-positive resqJts for every lung
cancer death prevented (NNS, 552), in addition to high rates
ofincidental findingspotentiaUy req uiringinterven lion as noted

5. in theoriginalcohort study.6 Furthem1ore, while the author co
rrectly poi.n,t out large differences in sc ree ning ef- ficacy and
benefit to risk ratio between the highest and low- est risk
quintiles, thedata are murkier in between, with greater than 500
false-positive res ults per lung cancer death pre- vented foraII b
ut the highest-risk quintile, mea.ning th at most participants are
exposed to an unfavorable benefit to risk ra- tio.
Caverly et a.110 have made the important contribution of
applying a validated risk stratification tool toa real-world co-
hort to improve sc reening c rite ria. Other groups have retro-
spectively demonstrated reduced hamis in stu dy popula- tions
with novel1iskstratificationtoolsusingeasilyobtainable patient
infomiation, such as em physema diag1l0s is, s moking
history,age,sex,and family history.'2·' 3 However,dearly more
work is needed to minimizethe harms of radiation eiq,osure,
invasive procedure,sand emotionalstressundercurrentguide-
Jines , while preservingbenefit for those whose livescould be
saved by the early detection oflung cancer. Ifand howwe will
get there has yet to be deterrni.necl, but one thing is d ear: the
future of LCSdepends on our ability to reexamine and refine our
approach to patient selection and clearly commun.icate risks
and benefits of screening.
ARTICLE INF ORMATION
Author Afffliatlons: partmellt of Medicine, Uniot!rsityof C
lifomia,S/ln Francisco. Schoolcl Medicine.SanFrancis.co
(rncre,Redberg}:l:di tor,
JAMA lntemcl Medi6ne (Re<Jberg).
Corrcspondnl g Author: AltaF.Re<lbcrg, MO, MSc, Departm I
of Medicine, Universrtyof Calirorni a, Sa11Fralldsm,5d1oolof
Medicine, 505 f>amassus, M i l 80 , SanFrancisco, CA9414
3·0124-(r it a.redberg
@ucsf.edu).

6. f>ubllshedOnHnc : January22. 20 18 .
doi:10.1001/ Jan; ainternrni:d.20T7.8217
Conflict ofl nterest Di.sdosur : Nooe l'<!p<,rted.
Jamaintemalmedidne.comJAMA l llt .ern alMed[dnc
Publishedonline Janua1y 22,2018 El
© 2018 American Medical Association. All rights reserve,d.
Letters
RESEARCHLETTER
LESSISMOREComparison of Observed Harms
and Expected Mortality Benefit for Persons
in the Veterans Health Affairs Lung Cancer Screening
Demonstration Project
The Veterans Health Affairs (VHA) lungcancer screening (LCS)
demonstration project identified a much higher false- positive
rate following initial low-dose computed tomo-
graphic screening than did the National Lung Screening Trial
Next, we separated patients into risk quintiles and as- sessed for
each: number of LC cases observed; screening ef- fectiveness
(number needed to screen[NNS] per LC death pre- vented); and
screening efficiency (number of false-positive result s and
downstream diagnostic procedures [eg, ad- vanced imaging,
bronchoscopies,biopsies] per LC death pre- vented). Following

7. VHA policy and as part of the VA Quality Enhancement
Research Initiative, thisevaluation was not con- sidered to be
researchand wasdeclared to benonresearch qual- ity
improvement activities by the VHA National Center for
Health Promotion and Disease Prevention , and the Ann Ar -
=Editorial
(58.2% VS 26.3%).1•2 Most
false -positive result s (nod- ules not confirmed to belung
bor Veterans Affairs Medical Center institutional review board.
Asa quality improvement activity, patient consent was not re-
quired. Patient data were deidentified in analyses.
cancer [LC]after follow-up) resulted in repeated imaging, but
2.0% of people screened also required nonbeneficial down-
stream diagnostic evaluation to determine these noduleswere not
cancer.2 We sought to put these findings into context by
examining how this high false-positive rate influences the harm-
to-benefit ratio for higher- vs lower-risk patients.
Methods I From March 31, 2015, through June 30, 2015, 2106
patients were screened across 8 academic VAs. Screening
processes and population-average outcomes for this project have
been reported.2 In trials, LCS's 20% relative risk reduc- tion
(RRR) in LC mortality did not vary by baseline LC risk,3 so we
estimated each patient's absolute risk reduction (ARR) by
multiplying the 20% RRR by their baseline LC mortality risk
(ARR = Baseline Risk x RRR). We estimated annual baseline
LC mortality risk using the Bach risk model. 4 Unlike other
models, the Bach mo del's inputs are obtainable in VHA's
Corporate Data Warehouse. In addition, a recent analysis
indicates it is one of the best performing models.s
Results I Patients in higher quintiles of LC risk had signifi-

8. cantly more lung cancers diagnosed during the project, sup-
porting the Bach model's ability to risk stratify in this popu-
lation (Figure, A: 4.8 LCs per 1000 in quintile 1 vs 29.7 per
1000 in quintile 5). Initial screens were least effective for
veterans in quintile 1 (lowest LC risk) (NNS of 6903) and most
effective for vete rans in quintile 5 (NNS of 687) (Figure).
Rates of false-positive results and downstream evaluations did
not differ significantly across risk quint iles (P= .52 and P = .15
for trend, respectively). That is, the over- all 56.2% rate of
false-positive results requiring tracking remain ed relatively
stable across risk quintiles (95% CI, 53.1%-62.6% in quintile 1
vs 51.9%-61.5% in quintile 5), as did the overall 2.0% rate of
false-positive results requiring downstream diagnostic
evaluations (95% CI, 0.3%-2.6 % in quintile 1 vs 1.7%-5.2 %).
This relationship of increasing absolute benefit and relatively
stable harms enhances the favorable harm vs benefit balance for
higher-risk vs lower- risk per so ns. The initial screen was leas t
efficient for
Figure. Observed Rateof Lung cancer Diagnosis and Predicted
Effectiveness WithInitial Low-Dose Computed Tomography
Screening
0 Observedrate of lung cancer diagnoses
[!} Screeningeffectiveness
(
50
P
=
.004
z
ci

9. 40
0
0
0
30
0.
§
20
.
"
3
'
10
u
T,i
) (
P
<
.001
)8000
"' 7000
6000
u
5000
40 00
Ql Q2 Q3 Q4 QS

10. li_ 3000
0
;:,:; 2 000
z
z 10 0 0
0
QI Q2 Q3 Q4 Q5
A.Observed rateof lungcancer diagnoses (per 1000persons
screenedonce). B. Screening effectiveness: number needed to
BaselineLung Cancer Risi< Quintile BaselineRisk Quintile
screen(NNS) to prevent1lungcancer
death. Error barsindicate 95% Os.
jamainternalmedicine.com JAMA Internal Medicine
Published online January 22.2018 El
© 2018 American Medical Association. All rights reserved.
Downloaded From: by donna hammaker on 02/17/2018
Letters
Table. Outcomes of Initial Low-DoseComputed Tomography
Screening According to Risk Quintile
No.(%) Predicted' LC Deaths Efficiency Calculation

11. (No. of Harms per LCDeath
Observed (During VHA Demonstratio n Project) Prevented)
(
Quintile
of Risk
FPs Requiring
Nonbeneficial
FPS
per
LC
Diagnostic
Risk LC
'
)
Participants•
Casesb,c
Tracking
Diagnostic
Evalua
ti
on
Total,
No.'
P
revented,No.'
De
a
h
t
Prevented
'
Evaluations per

12. LC
Allquintiles
2084 (100)
31 (100)
11
7
5
(100)
42 (100)
7.97
1.59
737
26
Quintile 1
420
(20.2)
2 (6.5)
243 (20.7)
6
(14.3)
0.45
0.09
2749
68
Q
u
n
i
til
e
2
459 (22.0)
2 (6.5)
249 (21.2)

13. 5 (11.9)
1.07
0.22
1152
23
Quintile
3
379 (18.2)
5
(
16
.1)
205 (17.4)
8
(19.0)
1.29
0.26
793
31
Quintile 4
422 (20.3)
10 (32.3)
249 (21.2)
9 (21.4)
2.0
0.40
622
22
Quintile 5
404 (19.4)
12 (38.7)
229 (19.5)
14
(33.3)
3.16
0.63

14. 36
3
22
)(1-y Cumu lative Observed LC FPs Requiring
DeathPrevented'
Abbreviations: FP, false-positive screening result; LC.
lungcancer; VHA, Veterans Health Administration.
· Based on lung cancer risk prediction model of Bach etal.4
which uses the followinginputs to calculate anindi vidual's1-
year cumulative risk of LC: sex, age, smoking status
(current/formersmoker), years since quitting if former smoker.
mean number cigarettes per day while smoking, andasbestos
exposure. Asbestos exposure wasnot available for participants
and wasnot considered in these calculations. The Bach model
has been shown to have
excellent predictivenesswithout this variable.3·5 For example.
theBach model (in the absence of asbestos exposure
information) showed satisfactory calibration and excellent
discriminativeability inarecent external validation study (areas
under curves of O 68 to 0.8for predictingLCdeath ).5
bTwenty-two of the 2106 participants
hadincompletesmokinghistory and wereexcluded fr om
thisanalysis.
'P < .05 by linear test of trend for continuousoutcomes.

15. patients in quintile 1 (2749 false-positive results and 68 non-
beneficial diagnostic procedures per LC death prevented) and
most efficient for t hose in quintile 5 (eg, 363 false- positive
results and 22 nonbeneficial diagnostic procedures per death
prevented) (Table).
Discussion I The high rate of false-positive resultsidentified in
the VHA's LCSdemonstration project hascaused concern about
whether LCS sho uld be implemented in this population. We
reex amined these data and found that the high false-positive
rateresults ina more concerning harm-to-benefitratiofor those
eligible persons at lower LC risk, but a much better harm -to-
benefit ratiofor high-risk patients (Table). Wefound that even
given these very high false-posit ive rates, the overall balance
of prosand consamong patients at highLC riskstillsurpasses
those of most established cancer screening programs.
These results should be interpreted with several caveats in
mind.The high rateoffalse-positive results found in the VA
demonstration project may represent a substantial overesti- mate
offuture ratesfor 2 reasons: (1) initial screens likely have more
false-positive resu lts than recurrent screening, and (2) newer
nodulemanagement guidelines areshowing great prom- ise in
loweringfalse-positiverates.6 Reducing the rateoffalse- positive
findings would improve the harm-to-benefit balance for all
quintiles. However, our analysis did not include all po- tential
harms ofLCS, such as overdiagnosis and psychologi- cal effects
from false-positive results. In addition, effective- nessstudies
arestill needed to confirm the extent towhich the mortality
benefit observed in the National Lung Screening Trial, a 20.0%
reduction in lung cancer and a 6.7% reduction in all- cause
mortality,1 applies in actual practice.
These real-world findings reinfo rce the need to risk- stratify
patients for LCS and provide support for personal- ized, risk-
based harm-benefit estimates for all eligible per- sons during
LCS de cision-making.
Tanner J. Caverly, MD, MPH

16. Angela Fagerlin, PhD
Renda Soylemez Wiener, MD, MPH Christopher G. Slatore,
MD, MS Nichole T. Tanner, MD, MSCR
Shira Yun, MD Rodney Hayward, MD
Author Affiliations: VACenter for Clinical Management
Research. Ann Arbor. Michigan (Caverly, Yun. Hayward):
University of Michigan Medical School. Ann Arbor (Caverly.
Yun. Hayward);Institutefor HealthPolicy Innovation. University
ofMichigan. AnnArbor (Caverly, Hayward); VASalt Lake Oty
Center for Informatics Decision Enhancement and Surveillance
(IDEAS). Salt Lake City.
Utah(Fagerlin); University ofUtah Schoolof Medicine. Salt Lake
City (Fagerlin); Center for Healthcare Organization and
Implementation Research. Edith Nourse Rogers Memorial
Veterans Affairs Hospital, Bedford, Massachusetts (Wiener);
Boston University School of Medicine, Boston. Massachusetts
(Wiener); VA PortlandHealth Care System Center to Improve
Veteran Involvement in Ca,re Portland. Oregon
(Slatore);Oregon Health & Science University School of
Medicine. Portland(Slatore); Health Equity and Rural
OutreachInnovation Center (HEROIC). Ralph H. Johnson
Veterans Affairs Hospital,Charleston,South Carolina (Tanner);
Medical University of South Carolina. Medicine. Charleston
(Tanner).
Corresponding Author: Tanner J. Caverly. MD.MPH. VACenter
for Clinical Management Research and Universityof Michigan
MedicalSchool. 2800 Plymouth Rd. Building 16. Room 321.
Ann Arbor. Ml 48109 ([email protected]
.umich.edu).
Accepted for Publication: November 27, 2017.
Published Online: January 22,2018.
doi:10.1001/jamainternmed.20178. 170
Author Contributions:DrCaveryl had fullaccess to allof the data
in thestudy and takes responsibility for theintegrity of thedata
and the accuracy of the data analysis.

17. Study concept and design: Caverly,Fageriln, Siatore, Yun,
Hayward. Acquisition. analysis. orinterpretation o
fdata:Caverly. Wiener. Tanner. Yun. Hayward.
Drafting of themanuscript:Caverly.
Criticalrevisionof the manuscript forimportant intellectual
content: All authors.
Statistical analysis:Caverly.Hayward. Obtained funding:
Caverly.
Administrative.technical, or material support: Caverly,Yun.
Studysupervision:Caverly. Fagerlin.
Conflict of Interest Disclosures: Nonereported.
Funding/Support:Funding for thisstudy was provided by the US
Department of Veterans Affairs (VA) Quality Enhancement
Research Initiative.Dr caverly is
E2 JAMA InternalMedicine Published online January 22, 2018
© 2018 American Medical Association. All rights reserved.
jamainternalmedicine.com
Downloaded From: by donna hammaker on 02/17/2018
Comprehensive Article Review
Caverly, T.J., Fagerlin, A, & Wiener, R.S. (2018, January 22).
Comparison of observed harms and expected mortality benefit
for persons in the Veterans Health Affairs Lung Cancer
Screening Demonstration Project. JAMA Internal Medicine.
1. What research questions are addressed in this study and what
is their purpose (5 points)?

18. 2. What type of research design was used (experimental, quasi-
experimental, correlational) in this study and what led you to
your decision (5 points)?
3. Are the instruments in this study valid and reliable, why or
why not (10 points)?
4. Discuss the specific results of each of the ANCOVAs
(analysis of covariance) done in this study. What was the
purpose of"each" of the ANCOVAs? What was the covariate in
each and why did they do an ANCOVA in each case (5 points)?
5. In the Tables, results are presented, Please explain the tables
and summarize the results (15 points).
6. Explain, in simple language, any significant results of this
study (25 points)?
7. Identify and discuss any threats to internal and/or external
validity in this study (10 points).
8. If you could redesign this study correcting anything you have
found wrong with the research, what would you correct and how
would you do it (20 points)?
Risks of Lung Screening Seen Outweighing Benefits in Many
with Smoking History Very high false-positive screening rate
seen in Veterans Affairs study
Real-world findings from a Veterans Affairs (VA) population
reinforce the need for personalized decision-making about lung
cancer screening using validated risk-stratification models.
Using the Bach risk tool for assessing lung cancer risk in
veterans screened at eight academic VA centers (MSKCC,
2018), nearly 5,600 veterans in the lowest risk quintile needed

19. to be screened to prevent one lung cancer death. Meanwhile, the
number of false-positive cases per death averted was 2,221. See
generally Caverly, Fagerlin, & Wiener, 2018.
Patients in the highest quintiles of lung cancer risk had
significantly more lung cancers diagnosed supporting the
model's ability to stratify risk in this population. These
findings, recently published in the Journal of the American
Medical Association Internal Medicine (Caverly et al., 2018)
bolster those from a VA screening trial published last March
(Kinsinger et
1
Letters
coinvestigatoronaresearch grant fromGenentech·s Corporate
Giving Scientific Project Support Program that isunrelated to
this study andunrelated to any Genentechor Rocheproducts. No
other disclosures are reported.
Roleof theFunde/rSpon sor: The funding sourceshadnorolein
thedesign and conduct of th e study: colleciton.management.
analysis. and interpretationof the data: preparation. review. or
approval of themanuscript: and decision to submit the
manuscript for publication.
Disclaimer: Allauthors were employees of the VA at the
timethis work was conducted. The viewsexpressed inthis article
are those of the authors and do not necessarily represent the
views of the VA or the US Government.
Meeting Presentation:Anearlier version of this work was anoral
presentation at the 2017 Veterans Affairs Health Services

20. Research &Development (HSR&D)/ Quality Improv
ementEnhancement Initiative (QUERI) National Conference:
July 18-20. 2017: Arlington. Virginia.
1. Aberle DR, Adams AM. BergCD, etal,NationalLungScreening
Trial Research Team.Reduced lung-cancer mortality with low-
dosecomputed tomographic screening. N Engl J Med. 2011:36 5
(5):395· 409.
2.
. Kinsinger LS. Anderson C.Kim J. etal.Implementationof
lungcancer screeningin the VeteransHealth Administration.
JAMA Intern Med. 2017:177(3): 399 -406.
3. Kovalchik SA.TammemagiM.Berg CD. et al. Targeting of
low-dose CT screening according to theriskof lung-cancer
death. NEnglJ Med. 2013:369(3): 245-254.
4. . BachPB, Elkin EB. Pastorino U. et al. Benchmarkin g
lungcancer mortality rates in current andformer smokers. Chest.
2004:126(6):1742-1749.
5. Ten Haaf K, JeonJ. Tammemagi MC. etal. Risk prediction
models for selection of lungcancer screeningcandidates:
aretrospective validation study. PLoS Med.
2017;14(4):e1002277.
6. Pinsky PF.Gierada OS. Black W. et al.Performance of Lung-
RADS in th e National LungScreening Trial:
aretrospectiveassessment. AnnInternMed. 2015:162(7):485-491.

21. jamainternalmedicine.com JAMA Internal Medicine
Published onlineJanuary 22.2018 E3© 2018 American
Medical Association. All rights reserved.
Downloaded From: by donna hammaker on 02/17/2018

22. al., 2017), showing a very high false-positive rate associated
with lung cancer screening. The false-positive rate in that
population was around 58 percent, which was more than twice
the false-positive rate seen in the National Lung Screening Trial
(National Cancer Center, 2014).
The U.S. Preventive Services Task Force recommends lung
cancer screening with low-dose CT for high-risk people between
the ages of 55 and 80, defined as having a greater than 30 pack-
year cumulative smoking history and having quit within the past
15 years for those no longer smoking (grade B
recommendation). In an editorial published with the current VA
study, it was observed that the future oflung cancer screening
"depends on our ability to reexamine and refine our approach to
patient selection and clearly communicate risks and benefits of
screening" (Incze & Redberg, 2018). The study cohort consisted
of 2,106 veterans screened for lung cancer at eight academic
VA centers during a 3-month period in the spring of 2015 as
part of the Veterans Health Affairs Lung Cancer Screening
Demonstration Project.
Annual baseline lung cancer mortality risk was estimated using
the Bach risk model, which is a validated tool calculating sex,
smoking duration, duration of abstinence from smoking, and
number of cigarettes smoked per day to estimate lung cancer
risk. Participants were separated into risk quintiles and assessed
for lung cancer cases observed, number needed to screen (NNS)
per lung cancer death prevented, and number of false-positive
results and downstream diagnostic procedures. The research
found "that even given these very high false-positive rates, the
overall balance of pros and cons among patients at high lung
cancer risk still surpassed those of most established cancer
screening programs" (Caverly et al., 2018).
Supporting References

23. Caverly, T.J., Fagerlin, A., & Wiener, R.S. (2018, January 22).
Comparison of observed harms and expected mortality benefit
for persons in the Veterans Health Affairs Lung Cancer
Screening Demonstration Project. JAMA Internal Medicine.
Retrieved from
https://jamanetwork.com/joumals/jamainternalmedicine/article-
abstract/2599437?redirect=true
Kinsinger, L.S. , Anderson C., Kim, J., Larson, M., King, H.A.,
Rice, K.L.Jackson, G.L. (2017, March 1). Implementation of
lung cancer screening in the Veterans Health Administration.
JAMA Internal Medicine, 1 77(3), 399-406.
Incze, M., & Redberg, R. F. (2018, January 22). Editorial:
Reducing harms in lung cancer screening- Bach to the future.
JAMA Internal Medicine. Retrieved from
https://app.jamanetwork. com/#page=issuesContainer
Memorial Sloan Kettering Cancer Center (MSKCC). (2018).
Lung cancer screening decision tool. New York, NY: MSKCC.
Retrieved from https://www.mskcc.org/cancer-
care/types/lung/screening/lung-screening-decision-tool
National Cancer Center (NCI). (2014). National lung screening
trial. Washington, DC: U.S. Department of Health and Human
Services, National Institutes of Health NCI. Retrieved from
https://www.cancer.gov/types/lung/research/nlst
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