Purpose

Measuring the effect of cancer interventions must take into account rising cancer incidence now that people live longer because of declines in mortality from cardiovascular disease (CVD). Cancer mortality rates in the population do not accomplish this objective. We sought a measure that would reveal the effects of changing mortality rates from other diseases.

Methods

We obtained annual breast, colorectal, lung, and prostate cancer mortality rates from the Surveillance, Epidemiology, and End Results registries; we obtained noncancer mortality rates from national death certificates, 1975 to 2005. We used life-table methods to calculate the burden of cancer mortality as the average person-years of life lost (PYLL) as a result of cancer (cancer-specific PYLL) and quantify individual-and perhaps offsetting-contributions of the two factors that affect cancer-specific PYLL: mortality rates as a result of cancer and other-cause mortality.

Results

Falling cancer mortality rates reduced the burden of mortality from leading cancers, but increasing cancer incidence as a result of decreasing other-cause mortality rates partially offset this progress. Between 1985 and 1989 and between 2000 and 2004, the burden of lung cancer in males declined by 0.1 year of life lost. This decline reflects the sum of two effects: decreasing lung cancer mortality rates that reduced the average burden of lung cancer mortality by 0.33 years of life lost and declining other-cause mortality rates that raised it by 0.23 years. Other common cancers showed similar patterns.

Conclusion

By using a measure that accounts for increased cancer incidence as a result of improvements in CVD mortality, we find that prior assessments have underestimated the impact of cancer interventions.

Comparative effectiveness research (CER) in genomic medicine (GM) measures the clinical utility of using genomic information to guide clinical care in comparison to appropriate alternatives. We summarized findings of high-quality systematic reviews that compared the analytic and clinical validity and clinical utility of GM tests. We focused on clinical utility findings to summarize CER-derived evidence about GM and identify evidence gaps and future research needs. We abstracted key elements of study design, GM interventions, results, and study quality ratings from 21 systematic reviews published in 2010 through 2015. More than half (N = 13) of the reviews were of cancer-related tests. All reviews identified potentially important clinical applications of the GM interventions, but most had significant methodological weaknesses that largely precluded any conclusions about clinical utility. Twelve reviews discussed the importance of patient-centered outcomes, although few described evidence about the impact of genomic medicine on these outcomes. In summary, we found a very limited body of evidence about the effect of using genomic tests on health outcomes and many evidence gaps for CER to address.Genet Med advance online publication 13 April 2017.