The role of radiation therapy in the management of cutaneous malignancies. Part I: Diagnostic modalities and applications.

Radiation therapy offers distinct advantages over other currently available treatments for cutaneous malignancies in certain circumstances. Dermatologists and dermatologic surgeons should be familiar with the available radiation therapy techniques as well as their value and potential limitations in a variety of clinical scenarios. The first article in this 2-part continuing medical education series highlights the mechanisms, modalities, and applications of the most commonly used radiotherapy treatments as they relate to cutaneous oncology. We review the current indications for the use of radiation in the treatment of various cutaneous malignancies, the techniques commonly employed in modern radiotherapy, and the associated complications.

The role of radiation therapy in the management of cutaneous malignancies. Part II: When is radiation therapy indicated?

Radiation therapy may be performed for a variety of cutaneous malignancies, depending on patient health status, tumor clinical and histologic features, patient preference, and resource availability. Dermatologists should be able to recognize the clinical scenarios in which radiation therapy is appropriate, as this may reduce morbidity, decrease risk of disease recurrence, and improve quality of life. The second article in this 2-part continuing medical education series focuses on the most common indications for radiation therapy in the treatment of basal cell carcinoma, cutaneous squamous cell carcinoma, dermatofibrosarcoma protuberans, Merkel cell carcinoma, Kaposi sarcoma, angiosarcoma, cutaneous lymphoma, melanoma, undifferentiated pleomorphic sarcoma, and sebaceous carcinoma.

Predicting future cancer incidence by age, race, ethnicity, and sex.

INTRODUCTION: Cancer remains a substantial burden on society. Our objective was to update projections on the number of new cancer diagnoses in the United States by age, race, ethnicity, and sex through 2040. MATERIALS AND METHODS: Population-based cancer incidence data were obtained using Surveillance, Epidemiology, and End Results (SEER) data. Population estimates were made using the 2010 US Census data population projections to calculate future cancer incidence. Trends in age-adjusted incidence rates for 23 cancer types along with total cancers were calculated and incorporated into a second projection model. RESULTS: If cancer incidence remains stable, annual cancer diagnoses are projected to increase by 29.5% from 1.86 million to 2.4 million between 2020 and 2040. This increase outpaces the projected US population growth of 12.3% over the same period. The population of older adults is projected to represent an increasing proportion of total cancer diagnoses with patients ≥65 years old comprising 69% of all new cancer diagnoses and patients ≥85 years old representing 13% of new diagnoses by 2040. Cancer diagnoses are projected to increase in racial minority groups, with a projected 44% increase in Black Americans (from 222,000 to 320,000 annually), and 86% in Hispanic Americans (from 175,000 to 326,000 annually). DISCUSSION: The landscape of cancer care will continue to change over the next several decades. The burden of disease will remain substantial, and the growing proportion of older and minority patients with cancer remains of particular interest. These projections should help guide future health policy and research priorities.

Independent Predictors for Hospitalization-Associated Radiation therapy Interruptions.

Purpose: Radiation treatment interruption associated with unplanned hospitalization remains understudied. The intent of this study was to benchmark the frequency of hospitalization-associated radiation therapy interruptions (HARTI), characterize disease processes causing hospitalization during radiation, identify factors predictive for HARTI, and localize neighborhood environments associated with HARTI at our academic referral center. Methods and Materials: This retrospective review of electronic health records provided descriptive statistics of HARTI event rates at our institutional practice. Uni- and multivariable logistic regression models were developed to identify significant factors predictive for HARTI. Causes of hospitalization were established from primary discharge diagnoses. HARTI rates were mapped according to patient residence addresses. Results: Between January 1, 2015, and December 31, 2017, 197 HARTI events (5.3%) were captured across 3729 patients with 727 total missed treatments. The 3 most common causes of hospitalization were malnutrition/dehydration (n = 28; 17.7%), respiratory distress/infection (n = 24; 13.7%), and fever/sepsis (n = 17; 9.7%). Factors predictive for HARTI included African-American race (odds ratio [OR]: 1.48; 95% confidence interval [CI], 1.07-2.06; P = .018), Medicaid/uninsured status (OR: 2.05; 95% CI, 1.32-3.15; P = .0013), Medicare coverage (OR: 1.7; 95% CI, 1.21-2.39; P = .0022), lung (OR: 5.97; 95% CI, 3.22-11.44; P < .0001), and head and neck (OR: 5.6; 95% CI, 2.96-10.93; P < .0001) malignancies, and prescriptions >20 fractions (OR: 2.23; 95% CI, 1.51-3.34; P < .0001). HARTI events clustered among Medicaid/uninsured patients living in urban, low-income, majority African-American neighborhoods, and patients from middle-income suburban communities, independent of race and insurance status. Only the wealthiest residential areas demonstrated low HARTI rates. Conclusions: HARTI disproportionately affected socioeconomically disadvantaged urban patients facing a high treatment burden in our catchment population. A complementary geospatial analysis also captured the risk experienced by middle-income suburban patients independent of race or insurance status. Confirmatory studies are warranted to provide scale and context to guide intervention strategies to equitably reduce HARTI events.

Location as Destiny: Identifying Geospatial Disparities in Radiation Treatment Interruption by Neighborhood, Race, and Insurance.

PURPOSE: Radiation therapy interruption (RTI) worsens cancer outcomes. Our purpose was to benchmark and map RTI across a region in the United States with known cancer outcome disparities. METHODS AND MATERIALS: All radiation therapy (RT) treatments at our academic center were cataloged. Major RTI was defined as ≥5 unplanned RT appointment cancellations. Univariate and multivariable logistic and linear regression analyses identified associated factors. Major RTI was mapped by patient residence. A 2-sided P value <.0001 was considered statistically significant. RESULTS: Between 2015 and 2017, a total of 3754 patients received RT, of whom 3744 were eligible for analysis: 962 patients (25.8%) had ≥2 RT interruptions and 337 patients (9%) had major RTI. Disparities in major RTI were seen across Medicaid versus commercial/Medicare insurance (22.5% vs 7.2%; P < .0001), low versus high predicted income (13.0% vs 5.9%; P < .0001), Black versus White race (12.0% vs 6.6%; P < .0001), and urban versus suburban treatment location (12.0% vs 6.3%; P < .0001). On multivariable analysis, increased odds of major RTI were seen for Medicaid patients (odds ratio [OR], 3.35; 95% confidence interval [CI], 2.25-5.00; P < .0001) versus those with commercial/Medicare insurance and for head and neck (OR, 3.74; 95% CI, 2.56-5.46; P < .0001), gynecologic (OR, 3.28; 95% CI, 2.09-5.15; P < .0001), and lung cancers (OR, 3.12; 95% CI, 1.96-4.97; P < .0001) compared with breast cancer. Major RTI was mapped to urban, majority Black, low-income neighborhoods and to rural, majority White, low-income regions. CONCLUSIONS: Radiation treatment interruption disproportionately affects financially and socially vulnerable patient populations and maps to high-poverty neighborhoods. Geospatial mapping affords an opportunity to correlate RT access on a neighborhood level to inform potential intervention strategies.