Cancer Causes & Control最新文献

Purpose: The prevalence of obesity, a crucial risk factor for breast cancer, is markedly higher among Hispanic women. The interaction between ethnic enclaves and neighborhood socioeconomic status (SES) as a determinant of this disparity warrants further research. We aimed to identify neighborhood profiles based on ethnic enclaves and socioeconomic status to evaluate the association with obesity among Hispanic women in the metropolitan Chicago region.

Methods: We used a convenience sample of 24,884 Hispanic women over age 40 who obtained breast imaging from the largest healthcare organization in Chicago between 2010 and 2017. We conducted LPA to characterize neighborhood composition based on tract indicators of ethnic enclaves, disadvantage, and affluence. Multivariate linear and multinomial logistic regression models were used to evaluate the association of neighborhood profiles with BMI.

Results: The LPA model identified four latent profiles, labeled based on their most significant characteristic as "middling," "disadvantage" "ethnic enclaves," and "affluent". Close to 50% of women in the disadvantage profile were obese and obese class II. Women in the disadvantage profile had the highest relative risk of being obese II (OR: 2.74 CI 95% 2.23, 3.36), compared to women in the middling profile. Women in the ethnic enclave and affluent profile were positively and negatively associated with obesity, respectively.

Discussion: Using LPA to group individuals according to their combined traits provides empirical evidence to strengthen our understanding of how neighborhoods influence obesity in Hispanic women. The study findings suggest that ethnic enclaves, that are also disadvantage, are associated with obesity in Hispanic women.

Purpose: Studies of healthcare encounters leading to cancer diagnosis have increased over recent years. While some studies examine healthcare utilization before the cancer registry date of diagnosis, relevant pre-diagnosis interactions are not always immediately prior to this date due to date abstraction guidelines. We evaluated agreement of a registry date with a claims-based index and examined Emergency Department (ED) involvement in cancer diagnosis as an example of possible pre-diagnostic healthcare misclassification that could arise from improper date choice.

Methods: We implemented an algorithm to define a claims-based index as the date of the earliest International Classification of Diseases code for the cancer in Medicare and estimated agreement with the date of diagnosis from a North Carolina registry for patients diagnosed aged 66 or older with 16 cancer types from 2008 to 2017 (n = 92,056). We then classified whether each cancer was initially diagnosed through care originating in the ED using each date.

Results: The index date was identical to the cancer registry date for 47% of patients and preceded the registry date for 28%, with extent of agreement varying by cancer- and patient-specific characteristics. Agreement in ED-involved diagnosis classification using each date varied by cancer site, with sensitivity of classifications using the registry date relative to the index having a minimum of 86% for prostate and kidney cancer.

Conclusion: Studies assessing healthcare utilization proximal to cancer diagnosis should carefully consider the relevant assessment window and be aware that the use of cancer registry versus claims-based dates may impact variable classification.

Purpose: Oncological treatments, such as radiotherapy, which requires consistent electricity, the presence of specialized clinical teams, and daily patient access to treatment facilities, are frequently disrupted by extreme weather events, posing several health hazards to patients. This study explores the association between declared wildfire disasters during radiotherapy and overall survival among patients with non-small cell lung cancer (NSCLC).

Methods: The study population consisted of 202,935 adults with inoperable Stage III NSCLC, who initiated radiotherapy from 2004 through 2019. Exposure was defined as a wildfire disaster declaration in the county of the treatment facility within 12 weeks of initiating radiotherapy. Overall survival was defined as the interval (months) between age at diagnosis and age at death, date of last contact, or study end. Cox proportional hazards was used to estimate crude and adjusted hazard ratios and 95% confidence intervals with inverse probability weighting.

Results: Patients exposed to a wildfire disaster declaration during radiation treatment had worse overall survival (HR, 1.03; 95% CI 1.00-1.06; p = 0.02), compared to unexposed patients in adjusted models.

Conclusion: Exposure to a wildfire disaster during radiotherapy is associated with worse overall survival among patients with stage III non-operable NSCLC. This finding underscores the critical need for developing adaptation strategies within the healthcare sector, especially in oncology.

Purpose: To examine incidence trends and patterns for early- and late-onset liver cancer.

Methods: Liver and intrahepatic bile duct (IBD) cancers diagnosed between 2000 and 2019 were acquired from 22 SEER registries. Variables included early-onset (20-49) vs. late-onset (50+), anatomic subsite, histologic type (hepatocellular carcinoma [HCC] and IBD cholangiocarcinoma [ICC]), sex, and race/ethnicity. Age-standardized incidence rates were calculated using SEER*Stat. Jointpoint regression analysis was employed to estimate the annual percent change (APC) and the average APC (AAPC) with pairwise comparisons for trend by sex and by race/ethnicity stratified by age and subsite.

Results: Liver cancer incidence decreased among early-onset (AAPC [95% CI] - 2.39 [- 2.74, - 2.07]) but increased among late-onset patients (2.85 [2.71, 3.01]), primarily driven by HCC (3.60 [3.50, 3.71]). IBD incidence increased for both ages with ICC incidence annually increasing 7.92% (6.84, 9.26) for early-onset and 6.32% (5.46, 8.86) for late-onset patients. Early-onset liver cancer displayed comparable trends across racial/ethnic groups; however, late-onset liver cancer showed more variation, particularly among American Indian/Alaska Native/Asian Pacific Islander (AI/AN/API) populations, which experienced a significant decrease in incidence, thereby narrowing the gap with other racial/ethnic groups. For IBD, an identical pattern of early-onset IBD among non-Hispanic Blacks (NHBs) compared to Hispanics was showed with coincidence test p = 0.1522, and a parallel pattern was observed among late-onset patients for both sexes (p = 0.5087).

Conclusion: Late-onset HCC continues to rise, except for NHB and AI/AN/API, where incidence rates have started to decrease over the past 4-5 years. Early and late-onset ICC incidence continues to increase across all racial/ethnic groups.

Purpose: The National Breast and Cervical Cancer Early Detection Program (NBCCEDP) provides access to timely breast and cervical cancer screening and diagnostic services to women who have low incomes and are uninsured or underinsured. Documenting the number of women eligible and the proportion of eligible women who receive NBCCEDP-funded services is important for identifying opportunities to increase screening and diagnostic services among those who would not otherwise have access.

Methods: Using the Census Bureau's Small Area Health Insurance Estimates data, we estimated the number of women who met the NBCCEDP eligibility criteria based on age, income, and insurance status. We used these estimates along with the number of women served by the NBCCEDP to calculate the percent of women served by race/ethnicity and state. We calculated the percent of eligible women who are up to date with screening using the 2019 National Health Interview Survey.

Results: The NBCCEDP served 15.0% of women ages 40-64 eligible for breast cancer services in 2018-2019 and 5.6% of women ages 21-64 eligible for cervical cancer services in 2018-2020. The NBCCEDP served 13.5% of women ages 40-64 eligible for breast cancer services in 2020-2021 and 5.9% of women ages 21-64 eligible for cervical cancer services in 2019-2021. The percent of women ages 40-64 who received breast cancer services declined by 1.5 percentage points between 2018-2019 and 2020-2021. The percent of women ages 21-64 who received cervical cancer services increased by 0.3 percentage points between 2018-2020 and 2019-2021. The percent of eligible women served varied among states. The state interquartile ranges of the percent of women served were 12.3-27.7% for breast cancer services in 2018-2019 and 3.9-14.7% for cervical cancer services in 2018-2020. Among women eligible for the NBCCEDP, 61.4% are not up to date with breast cancer screening and 40.6% are not up to date with cervical cancer screening.

Conclusion: There is wide variation between states in the share of eligible women served for breast and cervical cancer screening services. We found that both the number and the percentage of eligible women who received NBCCEDP breast cancer services declined during a period that overlapped with the COVID-19 pandemic. A large proportion of eligible women did not receive breast or cervical cancer screening.

Purpose: Respondent-driven sampling (RDS) is a sampling method that relies on social networks to recruit hard-to-reach populations, and reduces the bias from non-random selection. This study aimed to assess the efficacy of RDS in collecting health assessment data from underrepresented populations not captured by traditional sampling techniques.

Methods: An RDS study was conducted in Hawai'i between 2017 and 2018 of Native Hawaiians, Chuukese, and Marshallese participants. 1006 cases consisting of 352 seeds and 654 recruits were analyzed in conjunction with data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS), filtered to include Native Hawaiian/Other Pacific Islander participants (n = 1564). Missing network size data was imputed by RDSAnalyst and determined by the sample median network size. Weighted samples were compared for differences.

Results: Chi-square testing revealed significant differences between the RDS and BRFSS weighted samples across sex, age, education, income, and colon/cervical cancer screening variables. Only BMI group and smoking status exhibited no significant differences. RDS methods recruited participants efficiently within one year.

Conclusion: The findings indicate that RDS offers an effective sampling methodology when trying to reach hidden populations and provides more insight into the social networks of underserved communities as the transfer/utilization of health information may be linked to social connectedness.

Purpose: Oral cavity (OC) and oropharyngeal (OP) cancer rates have increased annually rising in the U.S. and Texas. Dental providers could play a key role in lowering OC/OP cancer rates through prevention and screening, but Texas faces a significant shortage of dental health professionals, affecting access to dental care, including OC/OP cancer prevention and early detection. This study aims to explore the link between OC/OP cancer rates and these dental shortage areas in Texas.

Methods: We analyzed OC/OP cancer incidence in Texas using SEER-Medicare data for patients aged 65 and over from 2012 to 2017. Rates per 100,000 were stratified by age, gender, and dental health provider shortage area (DHPSA) status (yes/no). Zero-Inflated Poisson Regression models were used to adjust for patient characteristics in studying cancer incidence, Late-stage diagnoses were assessed using logistic regression.

Results: The incidence rate was 27.3 per 100,000 people in Texas. DHPSA counties had lower incidence rates (24.3 per 100,000) compared to non-DHPSA counties (29.8 per 100,000; p = 0.0423). Among patients with OC/OP diagnoses, those living in a DHPSA county had lower odds of advanced stage diagnoses (aOR: 0.79; CI: 0.64-0.96) than those in non-DHPSA counties.

Conclusion: The findings highlight the complex link between dental providers and OC/OP cancer diagnoses, noting differences in indicators of need based on DHPSA location. Limited local dental services may lead to underreported cancer cases. Further research on dental service usage could improve OC/OP outcomes by prioritizing interventions from dental professionals.

Purpose: Obesity in mid-life is a well-established risk factor for developing renal cell carcinoma (RCC); however, patients with RCC who are obese at the time of diagnosis have more favorable survival outcomes. To get better insight into the obesity paradox and determine the extent to which weight around diagnosis is stable, we examined pre- and post-diagnosis weight changes in patients with localized RCC.

Methods: We included 334 patients with localized RCC from the prospective cohort ReLife who self-reported body weight at multiple time points ranging from 2 years before to 2 years after diagnosis. Multivariable linear mixed-effects regression models were used to compare weight at each timepoint to weight at diagnosis for the overall study population, as well as stratified by BMI at diagnosis, tumor stage, and tumor grade.

Results: Most patients were classified as overweight (38.3%) or obese (29.6%) at diagnosis. Overall, patients experienced on average 1.45 kg (95% confidence interval (CI) 0.84, 2.06) weight loss in the 2 years before diagnosis. Pre-diagnosis weight loss was higher in patients who were non-obese at diagnosis, and who presented with higher tumor stage and grade. On average, pre-diagnosis weight loss was at least partially regained within two years after diagnosis.

Conclusion: Patients who were non-obese and patients with higher stage and grade tumors had higher pre-diagnosis weight loss, which was at least partially regained after treatment. These patterns suggest there are subgroups of patients with localized RCC who experience disease-related weight loss, which could contribute to the obesity paradox.

Purpose: Historical redlining, a 1930s-era form of residential segregation and proxy of structural racism, has been associated with breast cancer risk, stage, and survival, but research is lacking on how known present-day breast cancer risk factors are related to historical redlining. We aimed to describe the clustering of present-day neighborhood-level breast cancer risk factors with historical redlining and evaluate geographic patterning across the US.

Methods: This ecologic study included US neighborhoods (census tracts) with Home Owners' Loan Corporation (HOLC) grades, defined as having a score in the Historic Redlining Score dataset; 2019 Population Level Analysis and Community EStimates (PLACES) data; and 2014-2016 Environmental Justice Index (EJI) data. Neighborhoods were defined as redlined if score ≥ 2.5. Prevalence quintiles of established adverse and protective breast cancer factors relating to behavior, environment, and socioeconomic status (SES) were used to classify neighborhoods as high-risk or not. Factor analysis grouped factors into domains. Overall and domain-specific scores were calculated for each neighborhood according to historical redlining status. Percent difference in score by historical redlining was used to assess differences in average scores, with Wilcoxon-Mann-Whitney test used to estimate significance. Kappa statistic was used to estimate concordance between historical redlining status and high-risk status. Heatmaps of scores were created to compare spatial clustering of high-risk factors to historical redlining.

Results: We identified two domains: (1) behavior + SES; (2) healthcare. Across the US, redlined neighborhoods had significantly more breast cancer factors than non-redlined (redlined neighborhoods = 5.41 average high-risk factors vs. non-redlined = 3.55 average high-risk factors; p < 0.0001). Domain-specific results were similar (percent difference for redlined vs. non-redlined: 39.1% higher for behavior + SES scale; 23.1% higher for healthcare scale). High-scoring neighborhoods tended to spatially overlap with D-grades, with heterogeneity by scale and region.

Conclusion: Breast cancer risk factors clustered together more in historically redlined neighborhoods compared to non-redlined neighborhoods. Our findings suggest there are regional differences for which breast cancer factors cluster by historical redlining, therefore interventions aimed at redlining-based cancer disparities need to be tailored to the community.

Objectives: Automated breast ultrasound imaging (ABUS) results in a reduction in breast cancer stage at diagnosis beyond that seen with mammographic screening in women with increased breast density or who are at a high risk of breast cancer. It is unknown if the addition of ABUS to mammography or ABUS imaging alone, in this population, is a cost-effective screening strategy.

Methods: A discrete event simulation (Monte Carlo) model was developed to assess the costs of screening, diagnostic evaluation, biopsy, and breast cancer treatment. The number of quality-adjusted life years gained through each screening method is assessed using previously published quality of life measures. Incremental cost-effectiveness ratios for screening with the combination of mammographic and ABUS imaging, and for ABUS imaging alone are calculated as compared to standard mammographic imaging.

Results: Combined screening with both mammographic and ABUS imaging results in an incremental cost-effectiveness ratio of $7,071 ($6,332-$7,809) when compared to traditional mammographic imaging (p < 0.05). ABUS screening alone results in an incremental cost-effectiveness ratio of $3,559 ($- 965-$8,082) when compared to mammographic imaging (p < 0.05). ABUS screening alone is more likely to be cost-effective for a willingness-to-pay of less than $7,100.

Conclusions: The addition of ABUS to mammographic imaging is a cost-effective screening strategy in women with increased breast density or who are at a high risk of developing breast cancer. ABUS imaging alone is also a cost-effective strategy in this population, particularly in resource-poor areas.