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1.
Clin Lymphoma Myeloma Leuk ; 22(12): e1092-e1099, 2022 12.
Article in English | MEDLINE | ID: mdl-36109323

ABSTRACT

BACKGROUND: Prevalence is reflective of disease incidence and survival, and defined as the number of patients living with active disease. In diseases such as diffuse large B-cell lymphoma (DLBCL) with treatments with curative potential, a proportion of patients are cured, leading to a need for accurate, contemporary estimates of DLBCL prevalence to gauge the impact of the rapidly emerging treatment landscape. METHODS: Data from Surveillance, Epidemiology, and End Results (SEER) from 2000-2018 were utilized to develop an epidemiological model of incidence, survival, and cure, to estimate the current prevalent DLBCL population requiring active management in the United States (US). A variety of estimates were explored regarding cure rate and timing, based on a companion analysis of MarketScan data for treatment patterns and survival in incident DLBCL patients, and conditional survival analysis of SEER data. RESULTS: Across scenarios, with estimated cure ranging from 52.8% and 68.9%, and timing of cure ranging from 1 and 20 years post diagnosis, the estimated prevalence ranged from 63,883 to 142,889. With an assumption of no cure, estimated prevalence was 179,475. DISCUSSION: Prevalence estimates of DLBCL varied almost 3-fold, depending on specific cure adjustments made. Further understanding of DLBCL prevalence, for newly diagnosed and relapsed and/or refractory disease, is important to characterize the impact of emerging treatment options and related health care burden.


Subject(s)
Epidemiological Models , Lymphoma, Large B-Cell, Diffuse , United States/epidemiology , Humans , SEER Program , Prevalence , Lymphoma, Large B-Cell, Diffuse/epidemiology , Lymphoma, Large B-Cell, Diffuse/therapy , Lymphoma, Large B-Cell, Diffuse/diagnosis , Survival Analysis
2.
Article in English | MEDLINE | ID: mdl-30154333

ABSTRACT

In 2010, Patient-Centered Outcomes Research Institute (PCORI) was authorized by Congress to improve the quality and relevance of evidence available to help patients, caregivers, employers, insurers, and policy makers make better-informed health decisions. We conducted a qualitative analysis of behavioral health trials in the PCORI Addressing Disparities portfolio to examine cultural tailoring strategies across the following priority populations: racial and ethnic minorities, rural populations, people with low-income or low socioeconomic status, individuals with disabilities, people with low health literacy, and lesbian, gay, bisexual, and transgender (LGBT) communities. The Common Strategies for Enhancing Cultural Appropriateness model was used to examine cultural tailoring strategies within trials. We hypothesized increased intersectionality within a patient population at risk for disparities would correlate with the dosage and type of cultural tailoring strategies applied. Thirty-three behavioral health trials applied cultural tailoring strategies and a majority of trials (n = 30) used three or more strategies. Trends in cultural tailoring were associated with certain racial and ethnic groups; however, increased use of tailoring was not associated with the number of priority populations included in a trial. The PCORI Addressing Disparities portfolio demonstrates how a range of cultural tailoring strategies are used, within comparative clinical effectiveness research trials, to address the needs and intersectionality of patients to reduce health and healthcare disparities.


Subject(s)
Ethnicity , Healthcare Disparities , Minority Groups , Health Services Accessibility , Humans , Rural Population , Sexuality , United States
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