Search

There is increased interest in eliminating health disparities in the United States and worldwide. Broadly defined, health disparities refer to preventable inequalities in health status, such as cancer to ethnicity, socioeconomic status, gender, education, environment, and geographic locations. To make informed health policy decisions, it is essential to precisely measure the magnitude of disparities and assess trends over time. The Health Disparities Calculator (HD*Calc) is free statistical software that calculates 11 commonly used measures of health disparities and provides corresponding 95% CIs for the 11 measures using either an analytic method or a Monte Carlo simulation-based method; however, the derivation of SEs and coverage properties of the CIs have not been formally evaluated. We used simulation studies to assess the coverage properties of these CIs. We have also conducted bias analyses for measures implemented in HD*Calc using age-adjusted cancer incidence rates from national, state, and county level SEER data. The results of these analyses indicate that HD*Calc should be used with caution to construct CIs for some health disparity measures when the proportion of zero event counts is greater than 25%.

Purpose To estimate cancer population-based reference values in the United States for eight PROMIS (Patient-Reported Outcomes Measurement Information System) domains by age and stage of disease. Patients and Methods For the Measuring Your Health (MY-Health) study, persons newly diagnosed with cancer (prostate, colorectal, non-small-cell lung, non-Hodgkin lymphoma, breast, uterine, or cervical) from 2010 to 2012 (N = 5,284) were recruited through the National Cancer Institute's SEER Program. Participants were mailed surveys 6 to 13 months after diagnosis. Raking by race/ethnicity, age, and stage generated weighted average PROMIS scores for pain interference, fatigue, anxiety, depression, sleep disturbance, physical function, ability to participate in social roles, and cognitive function. PROMIS measures are standardized to a T-score metric, with a score of 50 representing the general US population mean. Clinically meaningful differences were defined as a 3-point difference in scores. Results Several reference values (means) for patients with cancer were worse than the general United States population norms of 50. These include pain interference (52.4), fatigue (52.2), and physical function (44.1). Reference values were highest (ie, showed greatest symptom burden) in lung cancer (pain interference, 55.5; fatigue, 57.3; depression, 51.4) and cervical cancer (anxiety, 53.2; sleep disturbance, 53.4). Reference values for patients age 65 to 84 years reported lower sleep disturbance, anxiety, and depression, and better cognitive function than younger patients. Cancer reference values were poorer among those with advanced disease compared with patients with limited or no evidence of disease, specifically physical function (41.1 v 46.6, respectively), fatigue (55.8 v 50.2, respectively), and pain interference (55.2 v 50.9, respectively). Conclusion In a large, population-based sample of patients with recently diagnosed cancer, we observed symptom severity and functional deficits by age, stage, and cancer type consistent with the expected impact of cancer diagnosis and treatment. These United States cancer reference values can help facilitate interpretation of the PROMIS domain scores in research studies or in clinical applications that measure and evaluate the symptom and functional burden patients with cancer experience after initial treatment.