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Comparison of Observed Harms and Expected Mortality Benefit for Persons in the Veterans Health Affairs Lung Cancer Screening Demonstration Project

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Comparison 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 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 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

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jamainternalmedicine.com JAMA Internal Medicine Published online January 22.2018 El

© 2018 American Medical Association. All rights reserved.

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