Ebell MH, Bentivegna M, Hulme C Cancer-Specific Mortality, All-Cause Mortality, and Overdiagnosis in Lung Cancer Screening Trials: A Meta-Analysis. Ann Fam Med. 2020 Nov;18(6):545-552. doi: 10.1370/afm.2582. (Systematic review)

PURPOSE: Benefit of lung cancer screening using low-dose computed tomography (LDCT) in reducing lung cancer-specific and all-cause mortality is unclear. We undertook a meta-analysis to assess its associations with outcomes.

METHODS: We searched the literature and previous systematic reviews to identify randomized controlled trials comparing LDCT screening with usual care or chest radiography. We performed meta-analysis using a random effects model. The primary outcomes were lung cancer-specific mortality, all-cause mortality, and the cumulative incidence ratio of lung cancer between screened and unscreened groups as a measure of overdiagnosis.

RESULTS: Meta-analysis was based on 8 trials with 90,475 patients that had a low risk of bias. There was a significant reduction in lung cancer-specific mortality with LDCT screening (relative risk = 0.81; 95% CI, 0.74-0.89); the estimated absolute risk reduction was 0.4% (number needed to screen = 250). The reduction in all-cause mortality was not statistically significant (relative risk = 0.96; 95% CI, 0.92-1.01), but the absolute reduction was consistent with that for lung cancer-specific mortality (0.34%; number needed to screen = 294). In the studies with the longest duration of follow-up, the incidence of lung cancer was 25% higher in the screened group, corresponding to a 20% rate of overdiagnosis.

CONCLUSIONS: This meta-analysis showing a significant reduction in lung cancer-specific mortality, albeit with a tradeoff of likely overdiagnosis, supports recommendations to screen individuals at elevated risk for lung cancer with LDCT.

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Comments from MORE raters

Physician rater

Clearly, the authors are at a crossroads of what this study means as based on the discussion section of the paper. They list several unexplained reasons why this screening has not been adopted. This makes the study less impactful.

Physician rater

It is discouraging that the authors use this meta-analysis to rehash data from 9 years ago, using out-dated CT criteria for lung cancer diagnosis, to once again prove that lung cancer screening works. Even with the old criteria for following lung nodules, lung cancer screening, according to the NLST, could save more lives than colon cancer and breast cancer screening combined. Hopefully, we will finally acknowledge this and begin to approach the potential of this screening test.

Physician rater

It's good to put some numbers to the reduction in risk and rate of over-diagnosis. This will inform conversations with patients considering LDCT for lung cancer screening.

Physician rater

While screening will be debated until the cows come home, thankfully this meta-analysis adds credibility. I was not surprised by the findings. I'm not sure doubters will be convinced. We find cases that can be cured now, as opposed to finding too late to cure. There are many false positives but there are algorithms that may have costs, but less harm. It baffles me how “all cause” mortality could be an issue in older population with all smoking related risks of other cancers and morbidities.

Physician rater

As a Radiation Oncologist, I find the results of the article under review establish the role of low dose CT scan of chest in high risk population with consequent decrease in significant relative risk reduction in lung cancer mortality. The study is useful in my clinic to discuss lung screening with asymptomatic, high risk populations.

Physician rater

Clinicians need to read this to be aware of the data that is informing changes in service. However, they also need to read it alongside commentary on the implications of overdiagnosis that is reported, and also why the findings need to be considered in context of Wilson Junger/National SCreening Committee Criteria. It needs to be understood as an incomplete set of data (including beyond the limitations of the specific analysis itself).
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