Outcomes of Initial Low-DoseComputed Tomography Screening According to Risk Quintile

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Table. Outcomes of Initial Low-DoseComputed Tomography Screening According to Risk Quintile

 

No.(%) Predicted’ LC Deaths Efficiency Calculation

(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 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) 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 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.

 

 

 

 

 

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

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 (tcaverly@med

.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.

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

 

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