Cancer Screening Rates in Individuals With Different Life Expectancies

Abstract

IMPORTANCE Routine cancer screening has unproven net benefit for patients with limited life expectancy.OBJECTIVE To examine the patterns of prostate, breast, cervical, and colorectal cancer screening in the United States in individuals with different life expectancies. DESIGN, SETTING, AND PARTICIPANTS Data from the population-based National HealthInterview Survey (NHIS) from 2000 through 2010 were used and included 27 404 participants aged 65 years or older. Using a validated mortality index specific for NHIS, participants were grouped into those with low (<25%), intermediate (25%-49%), high (50%-74%), and very high (Ն75%) risks of 9-year mortality.MAIN OUTCOMES AND MEASURES Rates of prostate, breast, cervical, and colorectal cancer screening. RESULTSIn participants with very high mortality risk, 31% to 55% received recent cancer screening, with prostate cancer screening being most common (55%). For women who had a hysterectomy for benign reasons, 34% to 56% had a Papanicolaou test within the past 3 years. On multivariate analysis, very high vs low mortality risk was associated with less screening for prostate (odds ratio [OR], 0.65 [95% CI, 0.50-0.85]), breast (OR, 0.43 [95% CI, 0.35-0.53]), and cervical (OR, 0.50 [95% CI, 0.36-0.70]) cancers. There was less screening for prostate and cervical cancers in more recent years compared with 2000, and there was no significant interaction between calendar year and mortality risk for any cancer screening (P> .05 for all cancers). Our sensitivity analysis showed that screening was also common in individuals with less than 5-year life expectancy. CONCLUSIONS AND RELEVANCEA substantial proportion of the US population with limited life expectancy received prostate, breast, cervical, and colorectal cancer screening that is unlikely to provide net benefit. These results suggest that overscreening is common in both men and women, which not only increases health care expenditure but can lead to net patient harm.

Receipt of Cancer Screening Is a Predictor of Life Expectancy

“…5 Other published methods include information on functional and emotional status, but these methods cannot be used with administrative data. 6,8 …”

“…[2][3][4] One example of over-testing is the case of a patient with limited life expectancy receiving a screening test for cancer. [5][6][7][8][9][10][11] There is a lag between when a cancer is diagnosed by screening and when it would be diagnosed through symptoms, and a further lag before screening lowers the risk of death from the cancer. 12 Thus, patients with limited life expectancy who undergo cancer screening are at risk of diagnosis and treatment of a cancer that would not otherwise have affected their health.…”

“…12 Thus, patients with limited life expectancy who undergo cancer screening are at risk of diagnosis and treatment of a cancer that would not otherwise have affected their health. [8][9][10] Therefore, such Bover-screening^could be used as a quality indicator, where physicians would be evaluated based on the percentage of patients with low life expectancy who are overscreened, similar to measuring the percentage with normal life expectancy who do not receive screening (under-screened). [2][3][4] We have conducted preliminary work on developing quality measures for over-screening using Medicare data and estimating the life expectancy of individual patients.…”

Understanding disparity: Researchers strive to recruit more African Americans and other minorities to studies

“…1 Researchers analyzed the rates of these cancer screenings among patients aged 65 years or older using data from the National Health Interview Survey from 2000 through 2010. The 27,404 participants were grouped by low to very high risk of 9-year mortality.…”

Capsule Commentary on Hoffman et al., Self-Reported Health Status Predicts Other-Cause Mortality in Men with Localized Prostate Cancer: Results from the Prostate Cancer Outcomes Study

“…1 Despite the consensus from specialty societies and clinical practice guidelines, these tests are commonly performed in individuals with high risk of mortality within 5 years. 2 The frequency with which these tests are overused speaks to the challenge of estimating life expectancy in clinical practice. To address this challenge, Hoffman and colleagues 3 offer an important contribution to the growing literature on how to best target clinical services based on life expectancy estimates.…”