Look local: the value of cancer surveillance and reporting by American Indian clinics

Assessment of Racial Misclassification Among American Indian and Alaska Native Identity in Cancer Surveillance Data in the United States and Considerations for Oral Health: A Systematic Review

Introduction

Misclassification of American Indian and Alaska Native (AI/AN) peoples exists across various databases in research and clinical practice. Oral health is associated with cancer incidence and survival; however, misclassification adds another layer of complexity to understanding the impact of poor oral health. The objective of this literature review was to systematically evaluate and analyze publications focused on racial misclassification of AI/AN racial identities among cancer surveillance data.

Methods

The PRISMA Statement and the CONSIDER Statement were used for this systematic literature review. Studies involving the racial misclassification of AI/AN identity among cancer surveillance data were screened for eligibility. Data were analyzed in terms of the discussion of racial misclassification, methods to reduce this error, and the reporting of research involving Indigenous peoples.

Results

A total of 66 articles were included with publication years ranging from 1972 to 2022. A total of 55 (83%) of the 66 articles discussed racial misclassification. The most common method of addressing racial misclassification among these articles was linkage with the Indian Health Service or tribal clinic records (45 articles or 82%). The average number of CONSIDER checklist domains was three, with a range of zero to eight domains included. The domain most often identified was Prioritization (60), followed by Governance (47), Methodologies (31), Dissemination (27), Relationships (22), Participation (9), Capacity (9), and Analysis and Findings (8).

Conclusion

To ensure equitable representation of AI/AN communities, and thwart further oppression of minorities, specifically AI/AN peoples, is through accurate data collection and reporting processes.

Misracialization of Indigenous people in population health and mortality studies: a scoping review to establish promising practices

Indigenous people are often misracialized as other racial or ethnic identities in population health research. This misclassification leads to underestimation of Indigenous-specific mortality and health metrics, and subsequently, inadequate resource allocation. In recognition of this problem, investigators around the world have devised analytic methods to address racial misclassification of Indigenous people. We carried out a scoping review based on searches in PubMed, Web of Science, and the Native Health Database for empirical studies published after 2000 that include Indigenous-specific estimates of health or mortality and that take analytic steps to rectify racial misclassification of Indigenous people. We then considered the weaknesses and strengths of implemented analytic approaches, with a focus on methods used in the US context. To do this, we extracted information from 97 articles and compared the analytic approaches used. The most common approach to address Indigenous misclassification is to use data linkage; other methods include geographic restriction to areas where misclassification is less common, exclusion of some subgroups, imputation, aggregation, and electronic health record abstraction. We identified 4 primary limitations of these approaches: (1) combining data sources that use inconsistent processes and/or sources of race and ethnicity information; (2) conflating race, ethnicity, and nationality; (3) applying insufficient algorithms to bridge, impute, or link race and ethnicity information; and (4) assuming the hyperlocality of Indigenous people. Although there is no perfect solution to the issue of Indigenous misclassification in population-based studies, a review of this literature provided information on promising practices to consider.

Formative Assessment to Improve Cancer Screenings in American Indian Men: Native Patient Navigator and mHealth Texting

Cancer screening rates among American Indian men remain low, without programs specifically designed for men. This paper describes the Community-Based Participatory Research processes and assessment of cancer screening behavior and the appropriateness of the mHealth approach for Hopi men's promotion of cancer screenings. This Community-Based Participatory Research included a partnership with H.O.P.I. (Hopi Office of Prevention and Intervention) Cancer Support Services and the Hopi Community Advisory Committee. Cellular phone usage was assessed among male participants in a wellness program utilizing text messaging. Community surveys were conducted with Hopi men (50 years of age or older). The survey revealed colorectal cancer screening rate increased from 51% in 2012 to 71% in 2018, while prostate cancer screening rate had not changed (35% in 2012 and 37% in 2018). Past cancer screening was associated with having additional cancer screening. A cellular phone was commonly used by Hopi men, but not for healthcare or wellness. Cellular phone ownership increased odds of prostate cancer screening in the unadjusted model (OR 9.00, 95% CI: 1.11-73.07), but not in the adjusted model. Cellular phones may be applied for health promotion among Hopi men, but use of cellular phones to improve cancer screening participation needs further investigation.

Indigenous health equity in health register ascertainment and data quality: a narrative review

Background

Health registers play an important role in monitoring distribution of disease and quality of care; however, benefit is limited if ascertainment (i.e., the process of finding and recruiting people on to a register) and data quality (i.e., the accuracy, completeness, reliability, relevance, and timeliness of data) are poor. Indigenous peoples experience significant health inequities globally, yet health data for, and about, Indigenous peoples is often of poor quality. This narrative review aimed to (i) identify perceived barriers for the ascertainment of Indigenous peoples on health registers, and (ii) collate strategies identified and used by health registers to support comprehensive ascertainment and high-quality data for Indigenous peoples.

Methods

A Kaupapa Māori theoretical framework was utilized to guide this work. Four electronic databases were systematically searched for original articles and screened for eligibility. Studies involving health registers with Indigenous population(s) identified were included if either ascertainment or data quality strategies were described. Data extraction focused on the reporting of research involving Indigenous peoples using the CONSIDER checklist domains, ascertainment, and data quality.

Results

Seventeen articles were included spanning publication between 1992 and 2020. Aspects of four of eight CONSIDER domains were identified to be included in the reporting of studies. Barriers to ascertainment were themed as relating to ‘ethnicity data collection and quality’, ‘systems and structures’, ‘health services/health professionals’, and ‘perceptions of individual and community-level barriers’. Strategies to support ascertainment were categorized as ‘collaboration’, ‘finding people’, and ‘recruitment processes’. Categorized strategies to support data quality were ‘collaboration’, ‘ethnicity data collection and quality’, ‘systems-level strategies’, and ‘health service/health professional-level strategies’.

Conclusions

Poor-quality data for Indigenous peoples in health registers prevents the achievement of health equity and exemplifies inaction in the face of need. When viewed through a critical structural determinants lens, there are visible gaps in the breadth of strategies, particularly relating to the inclusion of Indigenous peoples in health register and research governance, and actions to identify and address institutional racism. Indigenous led research, meaningful collaboration, and a sharing of knowledge and experiences between health registers is recommended to enable research and health registers that support Indigenous self-determination and health equity.

Cancer mortality in a population-based cohort of American Indians - The strong heart study

BACKGROUND

Cancer mortality among American Indian (AI) people varies widely, but factors associated with cancer mortality are infrequently assessed.

METHODS

Cancer deaths were identified from death certificate data for 3516 participants of the Strong Heart Study, a population-based cohort study of AI adults ages 45-74 years in Arizona, Oklahoma, and North and South Dakota. Cancer mortality was calculated by age, sex and region. Cox proportional hazards model was used to assess independent associations between baseline factors in 1989 and cancer death by 2010.

RESULTS

After a median follow-up of 15.3 years, the cancer death rate per 1000 person-years was 6.33 (95 % CI 5.67-7.04). Cancer mortality was highest among men in North/South Dakota (8.18; 95 % CI 6.46-10.23) and lowest among women in Arizona (4.57; 95 % CI 2.87-6.92). Factors independently associated with increased cancer mortality included age, current or former smoking, waist circumference, albuminuria, urinary cadmium, and prior cancer history. Factors associated with decreased cancer mortality included Oklahoma compared to Dakota residence, higher body mass index and total cholesterol. Sex was not associated with cancer mortality. Lung cancer was the leading cause of cancer mortality overall (1.56/1000 person-years), but no lung cancer deaths occurred among Arizona participants. Mortality from unspecified cancer was relatively high (0.48/100 person-years; 95 % CI 0.32-0.71).

CONCLUSIONS

Regional variation in AI cancer mortality persisted despite adjustment for individual risk factors. Mortality from unspecified cancer was high. Better understanding of regional differences in cancer mortality, and better classification of cancer deaths, will help healthcare programs address cancer in AI communities.

Native American Patients with Chronic Obstructive Pulmonary Disease Exacerbations in a Tertiary Academic Medical Center - A Pilot Study

Purpose

The prevalence of chronic obstructive pulmonary disease (COPD) and comorbidities (eg diabetes and obesity) among Native American (NA) population are higher than among the general US population. However, studies of COPD in NAs are scarce. Oklahoma has the largest NA population affiliated with federally recognized tribes in the country and is an ideal location for such research. A pilot study was designed to investigate the characteristics of NA patients with COPD exacerbations in a tertiary academic medical center.

Patients and Methods

We conducted a retrospective exploratory study of NA adults with COPD exacerbation hospitalizations and/or emergency department visits at the University of Oklahoma Medical Center between July 2001 and June 2020. Medical records were reviewed to confirm COPD exacerbation and outcomes, including death, mechanical ventilation, intensive care unit (ICU) stay, home oxygen, and 30-day readmission. Additional collected data included socio-demographics, body mass index, diabetes, other COPD comorbidities and clinical variables.

Results

Of 630 encounters reviewed, 159 met the inclusion criteria, representing 91 patients. Most patients were female (64%), obese or overweight (68%), and had diabetes (42%) or hypertension (71%). Mean age was 60 years old, but women were 5 years younger than men. Among the 76 patients with COPD hospitalizations, 31 patients (41%) had an intensive care unit (ICU) stay and 19 (25%) were intubated in their last hospitalization. Among 9 patients (10%) with 30-day readmissions, 8 were female. Medicare, Indian Health Service, Tribal health service, or Medicaid were the most frequently used payment sources. Sex, diabetes, and obesity were not associated with hospital length of stay, 30-day readmission or supplemental O2 use.

Conclusion

Hospitalized NA COPD patients at this tertiary care center had multiple comorbidities. Many required ICU care and intubation. Larger studies of the risk and mitigating factors for COPD health outcomes in NA patients are needed.

Racial/ethnic disparities in renal cell carcinoma: Increased risk of early-onset and variation in histologic subtypes

Background

Racial/ethnic minority groups have a higher burden of renal cell carcinoma (RCC), but RCC among Hispanic Americans (HAs) and American Indians and Alaska Natives (AIs/ANs) are clinically not well characterized. We explored variations in age at diagnosis and frequencies of RCC histologic subtypes across racial/ethnic groups and Hispanic subgroups using National Cancer Database (NCDB) and Arizona Cancer Registry Data.

Methods

Adult RCC cases with known race/ethnicity were included. Logistic regression analysis was performed to estimate odds and 95% confidence interval (CI) of early‐onset (age at diagnosis <50 years) and diagnosis with clear cell RCC (ccRCC) or papillary RCC.

Results

A total of 405 073 RCC cases from NCDB and 9751 cases from ACR were identified and included. In both datasets, patients from racial/ethnic minority groups had a younger age at diagnosis than non‐Hispanic White (NHW) patients. In the NCDB, AIs/ANs had twofold increased odds (OR, 2.21; 95% CI, 1.88‐2.59) of early‐onset RCC compared with NHWs. HAs also had twofold increased odds of early‐onset RCC (OR, 2.14; 95% CI, 1.79‐2.55) in the ACR. In NCDB, ccRCC was more prevalent in AIs (86.3%) and Mexican Americans (83.5%) than NHWs (72.5%). AIs/ANs had twofold increased odds of diagnosis with ccRCC (OR, 2.18; 95% CI, 1.85‐2.58) in the NCDB, but the association was stronger in the ACR (OR, 2.83; 95% CI, 2.08‐3.85). Similarly, Mexican Americans had significantly increased odds of diagnosis with ccRCC (OR, 2.00; 95% CI, 1.78‐2.23) in the NCDB.

Conclusions

This study reports younger age at diagnosis and higher frequencies of ccRCC histologic subtype in AIs/ANs and Hispanic subgroups. These variations across racial/ethnic groups and Hispanic subgroups may have potential clinical implications.