Predictors of Colorectal Cancer Screening in Two Underserved U.S. Populations: A Parallel Analysis

BackgroundDespite declining colorectal cancer (CRC) incidence and mortality rates in the U.S., significant geographic and racial disparities in CRC death rates remain. Differences in guideline-concordant CRC screening rates may explain some of these disparities. We aim to assess individual and neighborhood-level predictors of guideline-concordant CRC screening within two cohorts of individuals located within CRC mortality geographic hotspot regions in the U.S.MethodsA total of 36,901 participants from the Southern Community Cohort Study and 4,491 participants from the Ohio Appalachia CRC screening study were included in this study. Self-reported date of last CRC screening was used to determine if the participant was within guidelines for screening. Logistic regression models were utilized to determine the association of individual-level predictors, neighborhood deprivation, and residence in hotspot regions on the odds of being within guidelines for CRC screening.ResultsLower household income, lack of health insurance, and being a smoker were each associated with lower odds of being within guidelines for CRC screening in both cohorts. Area-level associations were less evident, although up to 15% lower guideline adherence was associated with residence in neighborhoods of greater deprivation and in the Lower Mississippi Delta, one of the identified CRC mortality hotspots.ConclusionThese results reveal the adverse effects of lower area-level and individual socioeconomic status on adherence to CRC guideline screening

Multilevel Interventions To Address Health Disparities Show Promise In Improving Population Health

Multilevel interventions are those that affect at least two levels of influence—for example, the patient and the health care provider. They can be experimental designs or natural experiments caused by changes in policy, such as the implementation of the Affordable Care Act or local policies. Measuring the effects of multilevel interventions is challenging, because they allow for interaction among levels, and the impact of each intervention must be assessed and translated into practice. We discuss how two projects from the National Institutes of Health’s Centers for Population Health and Health Disparities used multilevel interventions to reduce health disparities. The interventions, which focused on the uptake of the human papillomavirus vaccine and community-level dietary change, had mixed results. The design and implementation of multilevel interventions are facilitated by input from the community, and more advanced methods and measures are needed to evaluate the impact of the various levels and components of such interventions

Promoting patient engagement in cancer genomics research programs: An environmental scan

Background: A national priority in the United States is to promote patient engagement in cancer genomics research, especially among diverse and understudied populations. Several cancer genomics research programs have emerged to accomplish this priority, yet questions remain about the meaning and methods of patient engagement. This study explored how cancer genomics research programs define engagement and what strategies they use to engage patients across stages in the conduct of research.Methods: An environmental scan was conducted of cancer genomics research programs focused on patient engagement. Research programs were identified and characterized using materials identified from publicly available sources (e.g., websites), a targeted literature review, and interviews with key informants. Descriptive information about the programs and their definitions of engagement, were synthesized using thematic analysis. The engagement strategies were synthesized and mapped to different stages in the conduct of research, including recruitment, consent, data collection, sharing results, and retention.Results: Ten research programs were identified, examples of which include the Cancer Moonshot Biobank, the MyPART Network, NCI-CONNECT, and the Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. All programs aimed to include understudied or underrepresented populations. Based on publicly available information, four programs explicitly defined engagement. These definitions similarly characterized engagement as being interpersonal, reciprocal, and continuous. Five general strategies of engagement were identified across the programs: 1) digital (such as websites) and 2) non-digital communications (such as radio broadcasts, or printed brochures); 3) partnering with community organizations; 4) providing incentives; and 5) affiliating with non-academic medical centers. Digital communications were the only strategy used across all stages of the conduct of research. Programs tailored these strategies to their study goals, including overcoming barriers to research participation among diverse populations.Conclusion: Programs studying cancer genomics are deeply committed to increasing research participation among diverse populations through patient engagement. Yet, the field needs to reach a consensus on the meaning of patient engagement, develop a taxonomy of patient engagement measures in cancer genomics research, and identify optimal strategies to engage patients in cancer genomics. Addressing these needs could enable patient engagement to fulfill its potential and accelerate the pace of cancer genomic discoveries

Family history of prostate and colorectal cancer and risk of colorectal cancer in the Women's health initiative.

BackgroundEvidence suggests that risk of colorectal and prostate cancer is increased among those with a family history of the same disease, particularly among first-degree relatives. However, the aggregation of colorectal and prostate cancer within families has not been well investigated.MethodsAnalyses were conducted among participants of the Women's Health Initiative (WHI) observational cohort, free of cancer at the baseline examination. Subjects were followed for colorectal cancer through August 31st, 2009. A Cox-proportional hazards regression modeling approach was used to estimate risk of colorectal cancer associated with a family history of prostate cancer, colorectal cancer and both cancers among first-degree relatives of all participants and stratified by race (African American vs. White).ResultsOf 75,999 eligible participants, there were 1122 colorectal cancer cases diagnosed over the study period. A family history of prostate cancer alone was not associated with an increase in colorectal cancer risk after adjustment for confounders (aHR =0.94; 95% CI =0.76, 1.15). Separate analysis examining the joint impact, a family history of both colorectal and prostate cancer was associated with an almost 50% increase in colorectal cancer risk (aHR = 1.48; 95% CI = 1.04, 2.10), but similar to those with a family history of colorectal cancer only (95% CI = 1.31; 95% CI = 1.11, 1.54).ConclusionsOur findings suggest risk of colorectal cancer is increased similarly among women with colorectal cancer only and among those with both colorectal and prostate cancer diagnosed among first-degree family members. Future studies are needed to determine the relative contribution of genes and shared environment to the risk of both cancers

Distributed Cognition in Cancer Treatment Decision Making: An Application of the DECIDE Decision-Making Styles Typology

Distributed cognition occurs when cognitive and affective schemas are shared between two or more people during interpersonal discussion. Although extant research focuses on distributed cognition in decision making between health care providers and patients, studies show that caregivers are also highly influential in the treatment decisions of patients. However, there are little empirical data describing how and when families exert influence. The current article addresses this gap by examining decisional support in the context of cancer randomized clinical trial (RCT) decision making. Data are drawn from in-depth interviews with rural, Appalachian cancer patients (N = 46). Analysis of transcript data yielded empirical support for four distinct models of health decision making. The implications of these findings for developing interventions to improve the quality of treatment decision making and overall well-being are discussed

Cancer-related Disparities among Residents of Appalachia Ohio

The authors sought to identify cancer-related disparities in Appalachia Ohio and better understand reasons for the disparities. Data from the Ohio Cancer Incidence Surveillance System, among other sources, were used to examine potential cancer disparities among residents of Appalachia Ohio. Using Ohio census data, the authors examined contributions of household income, educational attainment and population density to disparities in cancer incidence. Results suggest the following disparities in Appalachia Ohio (compared to non-Appalachia Ohio): greater cancer incidence and mortality rates for cancers of the cervix, colon and rectum, lung and bronchus and melanoma of the skin; a later stage at diagnosis of melanoma of the skin; lower prevalence of cancer screening behaviors of mammography, Pap smears, and sigmoidoscopy/colonoscopy; and less favorable cancer-related behaviors of obesity, physical activity, diet and especially tobacco smoking. Disparities in Appalachia Ohio may be associated with differences in household income, educational attainment and population density

Distributed Cognition in Cancer Treatment Decision Making: An Application of the DECIDE Decision-Making Styles Typology

Distributed cognition occurs when cognitive and affective schemas are shared between two or more people during interpersonal discussion. Although extant research focuses on distributed cognition in decision making between health care providers and patients, studies show that caregivers are also highly influential in the treatment decisions of patients. However, there are little empirical data describing how and when families exert influence. The current article addresses this gap by examining decisional support in the context of cancer randomized clinical trial (RCT) decision making. Data are drawn from in-depth interviews with rural, Appalachian cancer patients (N = 46). Analysis of transcript data yielded empirical support for four distinct models of health decision making. The implications of these findings for developing interventions to improve the quality of treatment decision making and overall well-being are discussed

Measuring cervical cancer risk: development and validation of the CARE Risky Sexual Behavior Index

To develop and validate a risky sexual behavior index specific to cervical cancer research