Gery P. Guy

Prevalence and Costs of Skin Cancer Treatment in the U.S., 2002−2006 and 2007−2011

BACKGROUND Skin cancer, the most common cancer in the U.S., is a major public health problem. The incidence of nonmelanoma and melanoma skin cancer is increasing; however, little is known about the economic burden of treatment. PURPOSE To examine trends in the treated prevalence and treatment costs of nonmelanoma and melanoma skin cancers. METHODS This study used data on adults from the 2002-2011 Medical Expenditure Panel Survey full-year consolidated files and information from corresponding medical conditions and medical event files to estimate the treated prevalence and treatment cost of nonmelanoma skin cancer, melanoma skin cancer, and all other cancer sites. Analyses were conducted in January 2014. RESULTS The average annual number of adults treated for skin cancer increased from 3.4 million in 2002-2006 to 4.9 million in 2007-2011 (p<0.001). During this period, the average annual total cost for skin cancer increased from

Economic Burden of Cancer Survivorship Among Adults in the United States

3.6 billion to

Vital Signs: Changes in Opioid Prescribing in the United States, 2006–2015

8.1 billion (p=0.001), representing an increase of 126.2%, while the average annual total cost for all other cancers increased by 25.1%. During 2007-2011, nearly 5 million adults were treated for skin cancer annually, with average treatment costs of

Years of Potential Life Lost and Indirect Costs of Melanoma and Non-Melanoma Skin Cancer: A Systematic Review of the Literature

8.1 billion each year. CONCLUSIONS These findings demonstrate that the health and economic burden of skin cancer treatment is substantial and increasing. Such findings highlight the importance of skin cancer prevention efforts, which may result in future savings to the healthcare system.

The health burden and economic costs of cutaneous melanoma mortality by race/ethnicity–United States, 2000 to 2006

PURPOSE To present nationally representative estimates of the impact of cancer survivorship on medical expenditures and lost productivity among adults in the United States. METHODS Using the 2008 to 2010 Medical Expenditure Panel Survey, we identified 4,960 cancer survivors and 64,431 individuals without a history of cancer age ≥ 18 years. Direct medical costs were measured using annual health care expenditures and examined by source of payment and service type. Indirect morbidity costs were estimated from lost productivity as a result of employment disability, missed work days, and lost household productivity. We evaluated the economic burden of cancer survivorship by estimating excess costs among cancer survivors, stratified by time since diagnosis (recently diagnosed [≤ 1 year] and previously diagnosed [> 1 year]), compared with individuals without a history of cancer using multivariable regression models stratified by age (18 to 64 and ≥ 65 years), controlling for age, sex, race/ethnicity, education, and comorbidities. RESULTS In 2008 to 2010, the annual excess economic burden of cancer survivorship among recently diagnosed cancer survivors was

Financial Hardship Associated With Cancer in the United States: Findings From a Population-Based Sample of Adult Cancer Survivors

16,213 per survivor age 18 to 64 years and

Melanoma Treatment Costs: A Systematic Review of the Literature, 1990–2011

16,441 per survivor age ≥ 65 years. Among previously diagnosed cancer survivors, the annual excess burden was

Indoor Tanning Among Young Non-Hispanic White Females

4,427 per survivor age 18 to 64 years and

The association between demographic and behavioral characteristics and sunburn among U.S. adults - National Health Interview Survey, 2010.

4,519 per survivor age ≥ 65 years. Excess medical expenditures composed the largest share of the economic burden among cancer survivors, particularly among those recently diagnosed. CONCLUSION The economic impact of cancer survivorship is considerable and is also high years after a cancer diagnosis. Efforts to reduce the economic burden caused by cancer will be increasingly important given the growing population of cancer survivors.

State Indoor Tanning Laws and Adolescent Indoor Tanning

Background Prescription opioid–related overdose deaths increased sharply during 1999–2010 in the United States in parallel with increased opioid prescribing. CDC assessed changes in national-level and county-level opioid prescribing during 2006–2015. Methods CDC analyzed retail prescription data from QuintilesIMS to assess opioid prescribing in the United States from 2006 to 2015, including rates, amounts, dosages, and durations prescribed. CDC examined county-level prescribing patterns in 2010 and 2015. Results The amount of opioids prescribed in the United States peaked at 782 morphine milligram equivalents (MME) per capita in 2010 and then decreased to 640 MME per capita in 2015. Despite significant decreases, the amount of opioids prescribed in 2015 remained approximately three times as high as in 1999 and varied substantially across the country. County-level factors associated with higher amounts of prescribed opioids include a larger percentage of non-Hispanic whites; a higher prevalence of diabetes and arthritis; micropolitan status (i.e., town/city; nonmetro); and higher unemployment and Medicaid enrollment. Conclusions and Implications for Public Health Practice Despite reductions in opioid prescribing in some parts of the country, the amount of opioids prescribed remains high relative to 1999 levels and varies substantially at the county-level. Given associations between opioid prescribing, opioid use disorder, and overdose rates, health care providers should carefully weigh the benefits and risks when prescribing opioids outside of end-of-life care, follow evidence-based guidelines, such as CDC’s Guideline for Prescribing Opioids for Chronic Pain, and consider nonopioid therapy for chronic pain treatment. State and local jurisdictions can use these findings combined with Prescription Drug Monitoring Program data to identify areas with prescribing patterns that place patients at risk for opioid use disorder and overdose and to target interventions with prescribers based on opioid prescribing guidelines.