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C. Berg



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    MTE01 - NLST - Additional Lessons and Future Directions (ID 45)

    • Event: WCLC 2013
    • Type: Meet the Expert (ticketed session)
    • Track: Imaging, Staging & Screening
    • Presentations: 1
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      MTE01.1 - NLST - Additional Lessons and Future Directions (ID 593)

      C. Berg

      • Abstract
      • Presentation
      • Slides

      Abstract
      The United States Preventive Services Task Force (USPSTF) has released a draft recommendation, a “B”, for lung cancer screening. This means that the USPSTF concluded with moderate certainty that there was substantial net benefit for screening healthy individuals (i.e. those able to withstand surgical intervention) with a 30 pack-year of more history of smoking, ages 55 to 79 years of age who have smoked within the past 15 years. This recommendation is based primarily upon the results of the National Lung Screening Trial (NLST)with some consideration of the emerging results from much smaller trials in Europe. While this “B” isreasonable, the criteria for whom to screen may need revision. Tammemagi et al (NEJM 2013; 368:728-736) have serially refined an incidence-based risk model. In the most recent model, PLCO~M2012~, lung cancer risk increases with age, African American race/ethnicity versus white, lower socioeconomic status (education), lower BMI, self-reported history of COPD, personal history of cancer, family history of lung cancer, being a current smoker, increased smoking intensity and duration, and shorter quit-time in former smokers. Applying the NLST criteria to the PLCO intervention arm smokers, 14,144 of 37,332 (37.9%) were eligible. To obtain an equal number of individuals using the PLCO~M2012~, individuals with a lung cancer risk >1.3455% were regarded as positive. Overall the PLCO~M2012~ risk method identified 81 more of the 678 lung cancers (11.9%) than did the NLST criteria (41.3% fewer lung cancers were missed: 115 versus 196). To include 80% of lung cancers in the PLCO control smokers, a PLCO~M2012~ risk probability of 0.016082 or higher would be used (specificity = 67.3%; PPV = 4.1%) and the proportion of smokers to be screened would be 33.6%. A spreadsheet calculator is available online, which calculates lung cancer risk according to PLCO~M2012~ given an individual’s predictor levels. http://www.brocku.ca/lung-cancer-risk-calculator An alternative approach looking at lung cancer mortality was developed by Kovalchik et al (NEJM 2013; 369:245-254). This analysis was limited to individuals who met the NLST entry criteria and used the NLST data for risk development with similar factors as Tammemagi et al. Five-year risk of lung cancer mortality ranged from 0.15-0.55% in the lowest risk group (Q1) to greater than 2% in the highest risk group (Q5). Sixty percent of NLST participants with the highest risk of lung cancer mortality accounted for 88% of LDCT-prevented lung cancer deaths. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of LDCT screening across rounds have now been reported. There is little variation across the rounds. At T0, the sensitivity and specificity were 93.8% and 73.4% for LDCT. In the LDCT arm, the PPV was 52.9% (265/501) for any positive finding that led to a biopsy procedure but only 3.8% (270/7,181) for positive findings overall Overall NPV was 99.9% (19,043/19,061). Among LDCT positive screenees undergoing thoracotomy at T1 and T2, 18.9% and 15.9% did not result in a lung cancer diagnosis, respectively. The frequent need for evaluation of positive screens increases the burdens of LDCT screening. Increasing the minimum size threshold for screen positivity can reduce the frequency of diagnostic work-up. Nodules 4-6 mm diameter accounted for roughly half of LDCT positive screens at T1 and T2, but were associated with lung cancer in less than 1% of cases. The variability in radiologists' interpretations of computed tomography (CT) studies in the NLST (including assessment of false-positive rates [FPRs] and sensitivity), was characterized and factors that contributed to variability, and trade-offs between FPRs and sensitivity among different groups of radiologists were evaluated. One hundred twelve radiologists at 32 screening centers each interpreted 100 or more NLST CT studies, interpreting 72 160 of 75 126 total NLST CT studies in aggregate. The mean FPR for radiologists was 28.7% ± 13.7 (standard deviation), with a range of 3.8%-69.0%. Aggregate sensitivity was 96.5% for radiologists with FPRs higher than the median (27.1%), compared with 91.9% for those with FPRs lower than the median (P = .02). In adjusted analyses, smoking cessation was strongly associated with the amount of abnormality observed in the previous year’s screening (P<0.0001). Compared to those with a normal screen, individuals were less likely to be smokers if their previous year’s screen had a major abnormality that was not suspicious for lung cancer (odds ratio (OR) = 0.790, P<0.001), was suspicious for lung cancer but stable from previous screens (OR = 0.777, P<0.001), or was suspicious for lung cancer and was new or changed from the previous screen (OR 0.593, P<0.001). Integration of effective smoking cessation programs within screening programs should lead to further reduction in smoking-related morbidity and mortality. Estimates suggest that the risk of radiation-induced lung cancer from three annual lung CT screens (average lung dose from a single LDCT estimates at 4 mGY) for older current smokers is likely to be in the range 1-10 deaths per 10,000 screened. However, because of the high probability of a positive screen (>20%) the follow-up procedures could double the risk of radiation-related lung cancer. The observed reduction in lung cancer mortality in the trial due to lung CT screening was 31 deaths prevented per 10,000 screened. The estimated radiation-related risks are therefore considerably smaller than the observed benefit. However, when the follow-up scans are included the benefit for current smokers is reduced by about 30% from 31 to about 20 lung cancer deaths per 10,000 screened. The impact on life-expectancy will be smaller, however, because the lung cancer deaths prevented occur at a younger age than the radiation-related cancer deaths. Estimates of the reduction in life-expectancy from radiation-related cancer were on average only 1-5 days. The advent of improved risk models demonstrates that more efficient criteria for selection of individuals for lung cancer screening than the NLST are feasible and effective. The various medical groups that have developed recommendations for lung cancer screening have primarily settled upon the NLST criteria. These groups should re-evaluate their criteria in light of the findings of these new risk models. This would have the salutary effect of making lung cancer screening more efficient and save more lives.

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    MTE09 - Cost Effectiveness of CT Screening (ID 53)

    • Event: WCLC 2013
    • Type: Meet the Expert (ticketed session)
    • Track: Imaging, Staging & Screening
    • Presentations: 1
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      MTE09.1 - Cost Effectiveness of CT Screening (ID 602)

      C. Berg

      • Abstract
      • Presentation
      • Slides

      Abstract
      Background The National Lung Screening Trial (NLST) demonstrated that screening with low-dose CT compared to screening with chest radiography reduced lung cancer mortality. Several cost-effectiveness analyses of lung cancer screening have been performed and will be reviewed in the presentation. A team of investigators from the NLST developed detailed data collection instruments to prospectively collect information about the entire screening process and cost expenditures while the trial was ongoing with the specific intention of performing a cost-effectiveness analysis after conclusion of the study. The team has concluded this research and now reports the cost-effectiveness of CT screening within the setting of the NLST. Methods Mean life-years, quality-adjusted life-years (QALYs), and mean costs per person and incremental cost effectiveness ratios for three alternative screening strategies using the societal perspective were estimated. CT screening was compared to chest radiographic and no screening, assuming that chest radiographic screening was ineffective and only contributed costs directly related to screening, not lung cancer treatment. Life-years were based on all observed deaths within the trial and projected survival of those alive at the end. Quality adjustments were derived from a subset of participants selected for quality of life surveys. Costs were based on utilization rates, derived from a subset of participants selected for medical record abstraction, and Medicare reimbursements. Life-years, QALYs, and costs were discounted at 3% per year. Uncertainty was assessed using bootstrap sampling of participants, subset analyses based on age, gender, smoking history, and lung cancer risk, and one-way sensitivity analyses on several assumptions. Results In the base case, the CXR screening strategy was dominated. Compared to no screening, CT screening costs $1441 per person and provided an additional 0.0217 QALYs per person; the incremental cost effectiveness ratio was $67,000 per QALY gained. Conclusions CT screening for lung cancer as performed in the NLST appears to be cost effective under a wide range of assumptions. Whether screening outside the trial will be cost effective will depend on who is selected for screening, how screening is performed, and how screenees are subsequently managed. As the United States Preventive Services Task Force has given a draft recommendation of “B” for lung cancer screening, it will need to be covered without a deductible by insurance companies upon implementation of the Patient Protection and Affordable Care Act. Therefore, appropriate implementation of screening is critical. (Funded by the National Cancer Institute; National Lung Screening Trial ClinicalTrials.gov number, NCT00047385.)

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    PL03 - Presidential Symposium Including Top Rated Abstracts (ID 85)

    • Event: WCLC 2013
    • Type: Plenary Session
    • Track:
    • Presentations: 1
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      PL03.02 - DISCUSSANT (ID 3884)

      C. Berg

      • Abstract
      • Slides

      Abstract not provided

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