Ohio Cancer Incidence Surveillance System Research Articles

Abstract 853: Assessment of racial and ethnic disparities in environmental exposure-related cancer burden

Abstract The United States Environmental Protection Agency designates superfund sites as regions contaminated with hazardous waste. These sites have previously been associated with adverse health outcomes, including an increased incidence of cancer. Historically, communities with racial and ethnic minorities and people of low socioeconomic status have served as prime locations for these sites, as these communities have lacked the ability to advocate against this land use. Here, we ask whether racial and ethnic minorities are disproportionately exposed to these sites or other regions of hazardous waste in our catchment area at the Case Comprehensive Cancer Center, and in the state of Ohio. Further, we are examining whether areas of high exposure are associated with adverse health outcomes including higher cancer incidence and mortality. We utilized the Environmental Justice Index (EJI) database from the Centers for Disease Control and Prevention to assess, on a census tract level, the percent of racial and ethnic minorities in a region, defined as all persons except white, non-Hispanic individuals. We also queried hazardous and toxic waste sites including regions with a national priority list site, a toxic release inventory site, treatment, storage, and disposal sites, risk management plan sites, coal mines, and lead mines. We intersected these data and found that census tracts with a higher percentage of minority persons were more likely to be exposed to hazardous and toxic sites. Our current studies are assessing whether this high environmental burden is contributing to disproportionately worse cancer burden for these individuals. We will test this by comparing EJI data with data from the Ohio Cancer Incidence Surveillance System database to assess cancer incidence and mortality in Ohio. This will also provide an avenue for identifying specific exposures that may contribute to different cancer types. Further, we plan to assess if persons with low socioeconomic status or those living with disabilities are disproportionately affected by environmental burden. Overall, understanding environmental burden and health outcomes will facilitate the prioritization of communities at greatest need, contributing to greater health equity. Citation Format: Jessica R. Bobbitt, Fangzhou Liu, Jennifer Cullen, Ruth A. Keri. Assessment of racial and ethnic disparities in environmental exposure-related cancer burden [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 853.

Treatment Patterns and Survival Outcomes in Patients With Breast Cancer on Medicaid, Pre- and Post-Expansion.

The objective of this study was to evaluate the impact of Medicaid expansion on breast cancer treatment and survival among Medicaid-insured women in Ohio, accounting for the timing of enrollment in Medicaid relative to their cancer diagnosis and post-expansion heterogeneous Medicaid eligibility criteria, thus addressing important limitations in previous studies. Using 2011-2017 Ohio Cancer Incidence Surveillance System data linked with Medicaid claims data, we identified women aged 18 to 64 years diagnosed with local-stage or regional-stage breast cancer (n=876 and n=1,957 pre-expansion and post-expansion, respectively). We accounted for women's timing of enrollment in Medicaid relative to their cancer diagnosis, and flagged women post-expansion as Affordable Care Act (ACA) versus non-ACA, based on their income eligibility threshold. Study outcomes included standard treatment based on cancer stage and receipt of lumpectomy, mastectomy, chemotherapy, radiation, hormonal treatment, and/or treatment for HER2-positive tumors; time to treatment initiation (TTI); and overall survival. We conducted multivariable robust Poisson and Cox proportional hazards regression analysis to evaluate the independent associations between Medicaid expansion and our outcomes of interest, adjusting for patient-level and area-level characteristics. Receipt of standard treatment increased from 52.6% pre-expansion to 61.0% post-expansion (63.0% and 59.9% post-expansion in the ACA and non-ACA groups, respectively). Adjusting for potential confounders, including timing of enrollment in Medicaid, being diagnosed in the post-expansion period was associated with a higher probability of receiving standard treatment (adjusted risk ratio, 1.14 [95% CI, 1.06-1.22]) and shorter TTI (adjusted hazard ratio, 1.14 [95% CI, 1.04-1.24]), but not with survival benefits (adjusted hazard ratio, 1.00 [0.80-1.26]). Medicaid expansion in Ohio was associated with improvements in receipt of standard treatment of breast cancer and shorter TTI but not with improved survival outcomes. Future studies should elucidate the mechanisms at play.

Abstract A127: Comparing outcomes in breast cancer treatment between fee-for-service and Medicare Advantage patients

Abstract Introduction: Relative to Medicare beneficiaries receiving care through the traditional fee-for-service system (FFS), the percentage of Americans covered by Medicare Advantage (MA) plans has increased over the last decade. As more patients enroll in MA plans, the comparison of outcomes between FFS and MA groups has gained renewed importance. Ohio has a high penetration of MA plans, but differences in outcomes between FFS and MA plans in Ohio is under-studied. Breast cancer is the second most common type of cancer among women, therefore understanding nuances in breast cancer treatment outcomes has broad applicability. In this study, we compare receipt of standard care, time to treatment initiation (TTI), and overall survival (OS) between FFS and MA women diagnosed with incident breast cancer. Methods: We used the Ohio Cancer Incidence Surveillance System (OCISS) cancer registry data linked with Medicare enrollment files and identified patients diagnosed with local and regionally staged breast cancer between 2011-2016. All variables except for FFS and MA enrollment were derived from the OCISS. We developed logistic regression (for analysis of receipt of standard treatment) and Cox regression models (for analysis of TTI and OS) to evaluate the independent association between FFS/MA status and our outcomes of interest, adjusting for age, race, marital status, type of county of residence, neighborhood poverty level, stage at diagnosis, hormone receptor status, and Medicaid dual enrollment. Standard care was defined as receipt of breast-conserving surgery (BCS) or mastectomy, radiotherapy if BCS was received; chemotherapy if regionally staged; and hormone therapy if hormone receptor positive. Results: 12,349 patients were identified that met our inclusion criteria, with 6,801 and 5,548 patients in the FFS and MA groups at the time of diagnosis, respectively. A slightly higher percentage of MA patients were identified as Black (10.3 vs 8.0% on FFS plans). FFS Medicare patients were found to have similar odds of receiving standard care as patients on MA plans (adjusted odds ratio 0.95 [95% CI: 0.88, 1.03]). We detected no difference in TTI between FFS and MA patients, (adjusted hazard ratio (aHR) 0.98 [95% confidence interval (CI): 0.94, 1.01]), or in OS (aHR 1.06 [95% CI: 0.95, 1.18]). No difference was found in receipt of standard care between Black and White patients (aOR 0.88 [95% CI: 0.76, 1.03]). An interaction term with race found that FFS Black patients had significantly lower odds of receiving standard care than their MA counterparts (aOR 0.70 [95% CI: 0.54, 0.92]). We did not find any significant interaction between MA status and race for OS or TTI. Conclusions: MA plans were not associated with any difference in TTI, OS, nor odds of receiving standard treatment for breast cancer compared to FFS Medicare plans. These findings are reassuring given the growing market share of privately administered MA plans, but raise questions with the notable disparity in receipt of standard care between Black FFS enrollees versus Black MA enrollees. Citation Format: Galen Shearn-Nance, Rishi Sachdev, Long Vu, Weichuan Dong, Johnie Rose, Siran Koroukian. Comparing outcomes in breast cancer treatment between fee-for-service and Medicare Advantage patients [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A127.

Abstract C125: Prostate specific antigen testing patterns and prostate cancer stage at diagnosis in Ohio cancer patients

Abstract Summary Statement This study aims to: 1) examine patterns of prostate specific antigen (PSA) testing — diagnostic or screening — across subgroups of prostate cancer (PCa) patients; and 2) analyze patterns of PSA testing in relation to PCa stage at diagnosis. Background Recommendations for PSA tests, blood-based screenings used for PCa detection, are issued by the United States Preventive Services Task Force. Changes in national recommendations, as well as demographic and clinical information can influence the likelihood of an individual receiving a PSA test, and the subsequent PCa diagnosis. Methods Using data from the 2014-2016 linked Ohio Cancer Incidence Surveillance System (OCISS) and Medicare database, we categorized PSA testing  as diagnostic or screening, based on diagnosis and procedure codes. Bivariate analyses were conducted on several factors, including patient demographics, claims-based frailty measures, and certain social determinants of health, to evaluate their association with receipt of screening PSA and stage of PCa diagnosis. Two multivariable logistic regression models were created to identify factors associated with receipt of screening PSA test, and subsequently, of being diagnosed with distant stage PCa. Results After excluding individuals identified without any PSA testing in the three years prior to diagnosis (n = 964) and those with unknown staged cancer (n = 446), our final study population included 3034 Ohio men diagnosed with PCa between 2014-2016. The median age was 73 years. Being of older age at the time of PCa diagnosis (adjusted odds ratio (aOR): 0.95 [95% confidence interval: 0.94, 0.97]) was associated with significantly lower odds of being screened.  Compared to non-frail men, pre-frail patients (aOR: 0.69 [0.57, 0.84]) and patients with mild to severe frailty (aOR: 0.54 [0.39, 0.75]) also had decreased odds of being screened. History of receipt of screening PSA tests was associated with lower odds of being diagnosed with distant stage disease (aOR: 0.55 [0.42, 0.72]). On the other hand, being of older age at the time of PCa diagnosis (aOR: 1.14 [1.12, 1.17]), having moderate to severe frailty (compared to non-frailty) (aOR: 4.30 [2.38, 8.02]), and being separated or divorced (compared to being married) (aOR: 1.75 [1.06, 2.78]), were associated with increased odds of being diagnosed with distant stage disease. Conclusions Younger age and lower gradients of frailty were strongly associated with receipt of screening PSA.  In turn, receipt of screening PSA was associated with early stage PCa, while being older, having higher degrees of frailty, and being divorced or separated from a spouse, were associated with elevated odds of distant stage PCa. This study adds to existing evidence suggesting that PSA-based screening may promote earlier detection of prostate cancer in a real-world setting and challenges preexisting beliefs on the usefulness of PSA testing in older populations.   Citation Format: Sajan Patel, Siran Koroukian, Johnie Rose, Long Vu, Holly Hartman. Prostate specific antigen testing patterns and prostate cancer stage at diagnosis in Ohio cancer patients [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C125.

Individual-level home values and cancer mortality in a statewide registry.

Prior work assessing disparities in cancer outcomes has relied on regional socioeconomic metrics. These metrics average data across many individuals, resulting in a loss of granularity and confounding with other regional factors. Using patients' addresses at the time of diagnosis from the Ohio Cancer Incidence Surveillance System, we retrieved individual home price estimates from an online real estate marketplace. This individual-level estimate was compared with the Area Deprivation Index (ADI) at the census block group level. Multivariable Cox proportional hazards models were used to determine the relationship between home price estimates and all-cause and cancer-specific mortality. A total of 667 277 patients in Ohio Cancer Incidence Surveillance System were linked to individual home prices across 16 cancers. Increasing home prices, adjusted for age, stage at diagnosis, and ADI, were associated with a decrease in the hazard of all-cause and cancer-specific mortality (hazard ratio [HR] = 0.92, 95% confidence interval [CI] = 0.92 to 0.93, and HR = 0.95, 95% CI = 0.94 to 0.95, respectively). Following a cancer diagnosis, individuals with home prices 2 standard deviations above the mean had an estimated 10-year survival probability (7.8%, 95% CI = 7.2% to 8.3%) higher than those with home prices 2 standard deviations below the mean. The association between home price and mortality was substantially more prominent for patients living in less deprived census block groups (Pinteraction < .001) than for those living in more deprived census block groups. Higher individual home prices were associated with improved all-cause and cancer-specific mortality, even after accounting for regional measures of deprivation.

Clustering of uveal melanoma: County wide analysis within Ohio.

To determine if a greater than expected number of cases (clustering) of uveal melanoma occurred within Ohio for any specific region or time period as compared to others. Analysis of population database. Ohio Cancer Incidence Surveillance System (OCISS) database (2000-2019) was accessed for the diagnosis of uveal melanoma using the International Classification of Disease for Oncology codes: C69.3 (choroid), C69.4 (ciliary body and iris). Counties within Ohio were grouped by geographic regions (7) and socioeconomic variables. Age- and race-standardized incidence ratios (SIR) were calculated to determine temporal or geographic clustering. Over the twenty-year period, the total number of uveal melanoma cases reported within Ohio were 1,617 with the overall age-adjusted annual incidence of 6.72 cases per million population (95% CI 6.30-7.16). There was an increase in the incidence of uveal melanoma over 20 years (p<0.001) across seven geographic regions, but no significant difference in incidence rates between the regions. There was no difference in incidence based on county classification by age composition (p = 0.14) or education level (p = 0.11). Counties with a low median household income (p<0.001), those classified as urban (p = 0.004), and those with a greater minority population (p = 0.004) had lower incidence. Less populated counties had a higher incidence of uveal melanoma (p<0.001). There is no evidence of geographic or temporal clustering of uveal melanoma within Ohio from 2000 to 2019.

Twenty-year patterns in area deprivation index and risk of metastatic prostate cancer at initial diagnosis among men in Ohio.

10526 Background: Men diagnosed with prostate cancer (PCa) have a 5-year overall survival (OS) rate of 98%. However, this rate plummets to approximately 30% for men diagnosed with metastatic PCa. Furthermore, PCa exerts a greater burden on African American men with a higher incidence and a higher mortality rate than other races. These disparities have been contributed to a result of interactions among genes, health behaviors, and access to care. In our study, we examined Social Determinants of Health (SDoH) – social risk factors that contribute to disparities in cancer mortality. Area deprivation index (ADI) is one of the assessments used to measure these social risk factors. ADI can assess a geographic area’s level of socioeconomic deprivation and is associated with health outcomes on the census block level. Variables used in ADI are grouped into 4 domains – education, income, employment, and housing quality. Most of the communities will fall between a standardized score of 40 to 160. In this study, we used a large population-based cancer database to examine the impact of ADI on risk of metastatic PCa at diagnosis in Ohio. Methods: The Ohio Cancer Incidence Surveillance System (OCISS) data were examined for the period 1996 to 2016 to predict the odds of distant stage at diagnosis. Generalized additive models were constructed with age and year of cancer diagnosis, area deprivation index, race, and Hispanic ethnicity as predictors. The relationship between continuous variables and odds of distant diagnosis was modeled via penalized cubic splines. Odds ratios were calculated for race and Hispanic ethnicity. To summarize the results for variables modeled via splines, predicted probabilities were calculated with other variables held at their average or reference values. Results: We identified 112,023 men with PCa in OCISS database. The median age was 67 (IQR 61-67) years old. Subjects were 85.3% White, 13.8% Black, and 0.9% other races. Only 0.6% of men were Hispanic. By stage, 84.6% (N=94753) had localized PCa, 10.4% (N=11640) had regional PCa, and 5.0% (N=5571) had distant PCa. The median ADI was 93.9 (IQR 83.6-106.5). Our analysis showed that Black men had 41.8% higher odds of having metastatic PCa at diagnosis than White men. Furthermore, our analysis showed similar risk of metastatic PCa at diagnosis in lower ADI values but higher risk at higher ADI values (Table). Conclusions: Higher ADI values were associated with higher risk of metastatic PCa at diagnosis. Interventions should target populations with socioeconomic deprivation and aim to improve patient access to prostate cancer prevention, screening, and treatment services. [Table: see text]

Abstract 4218: Cancer prevalence among Ohio firefighters: data from the Ohio Cancer Incidence Surveillance System (OCISS) 1996-2019

Abstract Firefighting is classified as a Group 1 carcinogen or “carcinogenic to humans” by the International Agency for Research on Cancer. Compared to the general population, firefighters have a 9% increased risk of cancer incidence and a 14% increased risk of cancer mortality. Although there have been previous studies of cancer incidence among firefighters in Florida and Massachusetts, there have been no studies examining cancer incidence among firefighters in the state of Ohio. Therefore, this is the first study to examine cancer prevalence among Ohio firefighters. The study utilized data from the Ohio Cancer Incidence Surveillance System (OCISS), the Ohio state cancer registry. This study examined data from 1996-2019, including a total of 1,314,318 people. Occupation was classified as firefighter, police, or general population. The odds of being a firefighter versus a police officer or the general population was calculated for specific cancer types. In addition, this analysis was stratified by gender. Police were used as a comparison group because it is an occupation similar to firefighters with the exception of exposure. There was a total of 3,397 firefighters, 3,341 police, and 1,307,580 people in the general population. Among firefighters, they were mostly male (86.8%), White (92.7%), Non-Hispanic (3.4%), married (67.7%), and never used tobacco (19.8%). The mean age at cancer diagnosis among firefighters was 66 years and most of them were diagnosed between 2010 and 2014. A similar distribution was seen among police except the mean age at cancer diagnosis was 63 years and most of them were current tobacco users (18.5%). The distribution was similar among the general population except the majority of them were female (51.6%). Firefighters had increased odds of esophageal cancer, cancers of the soft tissue including the heart, skin, prostate, testis, bladder, and brain compared to the general population. Cancer of the oral cavity, pharynx, and kidney were also increased among firefighters; however, they did not reach statistical significance. Compared to police, firefighters had increased odds of breast, uterine, prostate, brain, and thyroid cancer. In addition, they had decreased odds of pancreatic and bladder cancer. When stratified by gender, among the 2,948 male firefighters, there were increased odds of cancer of the soft tissue including heart, prostate, brain, cranial nerves, and thyroid cancer compared to the general population. They also had decreased odds of cancer of the larynx, lung &amp; bronchus, and bladder. Number of female firefighters was small generating unstable odds ratios. We observed increased prevalence of several types of cancer among Ohio firefighters, similar to previous studies. Although there were limitations present due to many people lacking data on occupation, the current study supports that Ohio firefighters have an increased risk of many different types of cancer. Citation Format: Susan E. Olivo-Marston, Shashank Singh, Robert B. Hood, Olorunfemi Adetona. Cancer prevalence among Ohio firefighters: data from the Ohio Cancer Incidence Surveillance System (OCISS) 1996-2019. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4218.

Understanding Disparities in Receipt of Complex Gastrointestinal Cancer Surgery at a Small Geographic Scale.

To define neighborhood-level disparities in the receipt of complex cancer surgery. Little is known about the geographic variation of receipt of surgery among patients with complex gastrointestinal (GI) cancers, especially at a small geographic scale. This study included individuals diagnosed with 5 invasive, nonmetastatic, complex GI cancers (esophagus, stomach, pancreas, bile ducts, liver) from the Ohio Cancer Incidence Surveillance System during 2009 and 2018. To preserve patient privacy, we combined US census tracts into the smallest geographic areas that included a minimum number of surgery cases (n=11) using the Max-p-regions method and called these new areas "MaxTracts." Age-adjusted surgery rates were calculated for MaxTracts, and the Hot Spot analysis identified clusters of high and low surgery rates. US Census and CDC PLACES were used to compare neighborhood characteristics between the high- and low-surgery clusters. This study included 33,091 individuals with complex GI cancers located in 1006 MaxTracts throughout Ohio. The proportion in each MaxTract receiving surgery ranged from 20.7% to 92.3% with a median (interquartile range) of 48.9% (42.4-56.3). Low-surgery clusters were mostly in urban cores and the Appalachian region, whereas high-surgery clusters were mostly in suburbs. Low-surgery clusters differed from high-surgery clusters in several ways, including higher rates of poverty (23% vs. 12%), fewer married households (40% vs. 50%), and more tobacco use (25% vs. 19%; all P <0.01). This improved understanding of neighborhood-level variation in receipt of potentially curative surgery will guide future outreach and community-based interventions to reduce treatment disparities. Similar methods can be used to target other treatment phases and other cancers.

Abstract A061: Receipt of standard treatment by breast cancer patients on Medicaid, pre- and post-expansion

Abstract Background: Medicaid expansion in Ohio went into effect in 2014. While prior studies have shown earlier breast cancer stages at diagnosis post-expansion, its impact relative to receipt of standard treatment remains understudied. Here, we examined changes in stage-appropriate standard treatment by women with invasive incident breast cancer pre- and post-expansion, and by their timing of enrollment in Medicaid relative to cancer diagnosis – a key marker of inadequate access to care. Methods: We used 2011-2017 Ohio Cancer Incidence Surveillance System (OCISS) data linked with Medicaid enrollment and claims files. Our study population included women 18-65 years of age diagnosed with local- or regional-stage cancer (n=1,053 and n=2,264 women in the pre- and post-expansion periods, respectively). We identified women as Previously Enrolled if they enrolled in Medicaid at least 3 months prior to cancer diagnosis and remained continuously enrolled for 4 months post-diagnosis, and as Newly Enrolled if they enrolled in Medicaid in the 3 months before or after cancer diagnosis. We used the OCISS for sociodemographic and treatment data. We defined standard treatment as the receipt of mastectomy, or lumpectomy and radiation in all women. In those with regional-stage cancer, we required standard treatment to also include chemotherapy; and for those with positive hormonal status, we required hormonal therapy. From claims data, we identified comorbid conditions, grouped as none, physical conditions only, mental conditions only, and physical and mental conditions, with or without substance abuse. In addition to descriptive analysis, we conducted multivariable logistic regression analysis to evaluate the independent association between Medicaid expansion and receipt of standard treatment, after adjusting for patient demographics, tumor characteristics, and comorbid conditions. Results: The median age was 50.6 years and 51.8 years in the pre- and post-expansion periods. The percent of Newly Enrolled women relative to the total decreased from 24.8% to 18.9%. Women in this group were healthier than those in the Previously Enrolled group, as evidenced by the higher percent of women with no comorbid conditions (43.3% and 42.4% vs. 21.7% and 22.5%, Pre- and Post-expansion, respectively). From Pre- to Post-Expansion, receipt of standard treatment increased from 52.3% to 58.8% and from 58.6% to 61.6% among the Previously and Newly Enrolled, respectively. Results from the multivariable logistic regression analysis showed that compared to women diagnosed in the pre-expansion period, those diagnosed in the post-expansion period had 10% higher odds to receive standard treatment, after adjusting for patient covariates. Conversely, the timing of enrollment in Medicaid relative to cancer diagnosis was not associated with our outcome of interest. Conclusion: Medicaid expansion in Ohio was associated with improvements in receipt of stage-appropriate standard treatment for breast cancer. Future studies should elucidate the mechanisms at play. Citation Format: Siran M. Koroukian, Weichuan Dong, Kirsten Eom, Uriel M. Kim, Johnie Rose, Jeffrey Albert, Cynthia Owusu, Kristine Zanotti, Gregory S. Cooper, Jennifer Tsui. Receipt of standard treatment by breast cancer patients on Medicaid, pre- and post-expansion [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A061.

Post-Affordable Care Act Improvements in Cancer Stage Among Ohio Medicaid Beneficiaries Resulted From an Increase in Stable Coverage.

The mechanisms underlying improvements in early-stage cancer at diagnosis following Medicaid expansion remain unknown. We hypothesized that Medicaid expansion allowed for low-income adults to enroll in Medicaid before cancer diagnosis, thus increasing the number of stably-enrolled relative to those who enroll in Medicaid only after diagnosis (emergently-enrolled). Using data from the 2011-2017 Ohio Cancer Incidence Surveillance System and Medicaid enrollment files, we identified individuals diagnosed with incident invasive breast (n=4850), cervical (n=1023), and colorectal (n=3363) cancer. We conducted causal mediation analysis to estimate the direct effect of pre- (vs. post-) expansion on being diagnosed with early-stage (-vs. regional-stage and distant-stage) disease, and indirect (mediation) effect through being in the stably- (vs. emergently-) enrolled group, controlling for individual-level and area-level characteristics. The percentage of stably-enrolled patients increased from 63.3% to 73.9% post-expansion, while that of the emergently-enrolled decreased from 36.7% to 26.1%. The percentage of patients with early-stage diagnosis remained 1.3-2.9 times higher among the stably-than the emergently-enrolled group, both pre-expansion and post-expansion. Results from the causal mediation analysis showed that there was an indirect effect of Medicaid expansion through being in the stably- (vs. emergently-) enrolled group [risk ratios with 95% confidence interval: 1.018 (1.010-1.027) for breast cancer, 1.115 (1.064-1.167) for cervical cancer, and 1.090 (1.062-1.118) for colorectal cancer. We provide the first evidence that post-expansion improvements in cancer stage were caused by an increased reliance on Medicaid as a source of stable insurance coverage.

Health Disparities in Liver Cancer: An Analysis of the Ohio Cancer Incidence Surveillance System

Background: We explored associations between neighborhood deprivation and tumor characteristics, treatment, and 5-year survival among primary hepatocellular carcinoma (HCC) patients in Ohio diagnosed between 2008 and 2016. Methods: We used data from the Ohio Cancer Incidence Surveillance System and limited our analysis to adult (&gt;18 years of age) HCC patients with known census tract information based on address at diagnosis. Using principal components analysis, we created a neighborhood deprivation index (NDI) using 9 census tract-level variables. We examined associations between tumor characteristics (stage and tumor size) and NDI quintile using chi-square tests and analysis of variance (ANOVA). Associations between guideline-concordant care and NDI using log-binomial regression adjusted for sex, race, age at diagnosis, metropolitan status, cancer stage, and year of diagnosis were conducted. For 5-year survival, we utilized Cox proportional hazards models with a similar adjustment set. Results: Neighborhood deprivation index was not associated with stage or tumor size. Individuals living in the most deprived neighborhoods were 16% less likely to receive guideline-concordant care as compared to individuals living in the least deprived neighborhoods (adjusted prevalence ratio [PR]: 0.84; 95% confidence interval [CI]: 0.74-0.94). Similarly, individuals living in the most deprived neighborhoods were 15% less likely to survive 5 years compared to individuals living in the least deprived neighborhoods (adjusted Hazard Ratio: 1.15; 95% CI: 1.01-1.29). Conclusion: Our results suggest a negative association between neighborhood deprivation on guideline-concordant care and survival among HCC patients. Interventions targeting disparities of HCC should focus not only on individual-level factors but address larger neighborhood level factors as well.

Comparing the association between multiple chronic conditions, multimorbidity, frailty, and survival among older patients with cancer

IntroductionThe high prevalence of multiple chronic conditions (MCC), multimorbidity, and frailty may affect treatment and outcomes for older adults with cancer. The goal of this study was to use three conceptually distinct measures of morbidity to examine the association between these measures and mortality. Materials and MethodsUsing Medicare claims data linked with the 2012–2016 Ohio Cancer Incidence Surveillance System we identified older adults with incident primary cancer sites of breast, colorectal, lung, or prostate (n = 29,140). We used claims data to identify their Elixhauser comorbidities, Multimorbidity-Weighted Index (MWI), and Claims Frailty Index (CFI) as measures of MCC, multimorbidity, and frailty, respectively. We used Cox proportional hazard models to examine the association between these measures and survival time since diagnosis. ResultsLung cancer patients had the highest levels of MCC, multimorbidity, and frailty. There was a positive association between all three measures and a greater hazard of death after adjusting for age, sex (colorectal and lung only), and stage. Breast cancer patients with 5+ comorbidities had an adjusted hazard ratio (aHR) of 1.63 (95% confidence interval [CI]: 1.38, 1.93), and those with mild frailty had an aHR of 3.38 (95% CI; 2.12, 5.41). The C statistics for breast cancer were 0.79, 0.78, and 0.79 for the MCC, MWI, and CFI respectively. Similarly, lung cancer patients who were moderately or severely frail had an aHR of 1.82 (95% CI: 1.53, 2.18) while prostate cancer patients had an aHR of 3.39 (95% CI: 2.12, 5.41) and colorectal cancer patients had an aHR of 4.51 (95% CI: 3.23, 6.29). Model performance was nearly identical across the MCC, multimorbidity, and frailty models within cancer type. The models performed best for prostate and breast cancer, and notably worse for lung cancer. The frailty models showed the greatest separation in unadjusted survival curves. DiscussionThe MCC, multimorbidity, and frailty indices performed similarly well in predicting mortality among a large cohort of older cancer patients. However, there were notable differences by cancer type. This work highlights that although model performance is similar, frailty may serve as a clearer indicator in risk stratification of geriatric oncology patients than simple MCCs or multimorbidity.

Medicaid Expansion Associated With Reduction in Geospatial Breast Cancer Stage at Diagnosis Disparities.

Prior studies demonstrate that Medicaid expansion has been associated with earlier-stage breast cancer diagnosis among women with low income, likely through increased access to cancer screening services. However, how this policy change has impacted geospatial disparities in breast cancer stage at diagnosis is unclear. To examine whether there were reductions in geospatial disparities in advanced stage breast cancer at diagnosis in Ohio after Medicaid expansion. The study included 33 537 women aged 40 to 64 years diagnosed with invasive breast cancer from the Ohio Cancer Incidence Surveillance System between 2010 and 2017. The space-time scan statistic was used to detect clusters of advanced stage at diagnosis before and after Medicaid expansion. Block group variables from the Census were used to describe the contextual characteristics of detected clusters. The percentage of local stage diagnosis among women with breast cancer increased from 60.2% in the pre-expansion period (2010-2013) to 62.6% in the post-expansion period (2014-2017), while the uninsured rate among those women decreased from 13.7% to 7.5% during the same period. Two statistically significant ( P < .05) and 6 nonsignificant spatial clusters ( P > .05) of advanced stage breast cancer cases were found in the pre-expansion period, while none were found in the post-expansion period. These clusters were in the 4 largest metropolitan areas in Ohio, and individuals inside the clusters were more likely to be disadvantaged along numerous socioeconomic factors. Medicaid expansion has played an important role in reducing geospatial disparities in breast cancer stage at diagnosis, likely through the reduction of advanced stage disease among women living in socioeconomically disadvantaged communities.

Abstract P3-12-30: Impact of medicaid expansion on breast cancer stage at diagnosis: Exploring the mechanisms at play

Abstract Background: Prior studies have shown significant improvements in earlier breast cancer stage at diagnosis following Medicaid expansion. However, the mechanisms behind this finding have not been explored. The timing of Medicaid enrollment among cancer patients has been shown to be associated with cancer stage at diagnosis, with significantly higher percentages of women with late-stage breast cancer enrolling in Medicaid shortly before or after cancer diagnosis (hereafter referred to as the Peri-dx group), compared to those continuously enrolled in Medicaid at least 4 months prior to cancer diagnosis (Pre-dx group). Hence, we conducted a causal mediation study based on a logistic regression model to determine whether the observed improvements in breast cancer stage at diagnosis from Pre- to Post-expansion can be attributed to a decreasing percentage of women in the Peri-dx group, and a corresponding increase in the Pre-dx group. Methods: We used the linked Ohio Cancer Incidence Surveillance System and Medicaid data, and identified women in Ohio age younger than 66 years, diagnosed with incident invasive breast cancer during the period May 2011-December 2017, and enrolled in Medicaid at the time of cancer diagnosis (n=5,880, excluding those with unstaged/unknown-stage cancer). We defined the years 2011-2013 and 2014-2017 as the Pre- and Post-expansion periods, and Month 0 as the month of cancer diagnosis. We identified women enrolled in Medicaid in the -3 to +3-month window in the Peri-dx group, and those continuously enrolled in Medicaid at least 4 months prior to cancer diagnosis in the Pre-dx group. We conducted a causal mediation analysis to estimate the direct, indirect, and total effect of Medicaid expansion on being diagnosed with local-stage disease versus late- (regional- and distant-) stage disease, with the mediator variable being a patient in the Pre-dx group (versus in the Peri-dx group), adjusting for patient- and area-level covariates. Results: The median age of our study population was 53 years; 75.0% were non-Hispanic White. The percent of breast cancer patients diagnosed with late-stage disease was 43.5% and 53.4% in the Pre- and Peri-dx groups, respectively. We observed a clear shift in the distribution of breast cancer patients from the Peri- to the Pre-dx group over time, with an increase in the percentage of women in the Pre-dx group (from 55.2% to 74.2% from the Pre- to Post-Expansion period), and a corresponding decrease in the Peri-dx group (from 44.8% to 25.8%). Findings from our causal mediation analysis, based on a risk difference scale, showed that while the direct effect of Medicaid expansion on being diagnosed with local-stage disease was not significant (coefficient: 0.037, (p=0.297)), both the indirect and total effects were highly significant (0.049 (p &amp;lt; 0.001), and 0.086 (p=0.015)). Conclusion: Our results indicate that the improvements in breast cancer stage at diagnosis from Pre- to Post-Expansion can be attributed to a decrease in the Peri-dx group, and a corresponding increase in the Pre-dx group, which improves access to screening, increases the likelihood of breast cancer patients being engaged with Medicaid providers, and reduces delays in enrollment logistics prior to treatment initiation. Citation Format: Siran M. Koroukian, Weichuan Dong, Jeffrey Albert, Uriel Kim, Johnie Rose, Cynthia Owusu, Kristine Zanotti, Gregory Cooper, Jennifer Tsui. Impact of medicaid expansion on breast cancer stage at diagnosis: Exploring the mechanisms at play [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-12-30.

Data Matching to Support Analysis of Cancer Epidemiology Among Veterans Compared With Non-Veteran Populations-An Exemplar in Brain Tumors.

PURPOSEState and national cancer registries do not systematically include Veteran data, which hinders analysis of the diagnosis patterns, treatment trajectories, and clinical outcomes of Veterans compared with non-Veteran populations. This study used data matching approaches to compare cases included in the Oncology Domain of the Veterans Affairs (VA) Corporate Data Warehouse and the Ohio Cancer Incidence Surveillance System, using brain tumors as an exemplar.METHODSWe used direct data matching, on the basis of protected health information (PHI) common to both databases, to compare primary brain tumors from Veterans and non-Veterans diagnosed from 2000 to 2016. Working with this matched data set, we used six data elements that did not contain PHI, to assess the feasibility of using deterministic data matching to compare Veterans and non-Veterans.RESULTSBetween 2000 and 2016, 223 Veterans from Ohio had a primary brain tumor; of those, 55 (25%) were not included in Ohio Cancer Incidence Surveillance System. Direct data matching showed that Veterans experienced a greater proportion of glioblastomas (41%) compared with non-Veterans (21%). Sex did not account for this difference. Deterministic data matching within the matched data set found that 75% (126 of 168) of Veterans had exact matches for at least five of six non-PHI variables common to both databases.CONCLUSIONThis study indicated that direct and deterministic data matching approaches to compare brain tumors in Veterans and in non-Veterans is feasible. This approach has the potential to promote comparisons of the distribution of tumors, the impact of chemical and environmental exposures, treatment trajectories, and clinical outcomes among Veteran and non-Veteran populations with brain tumors as well as other cancers and rare diseases.

Abstract IA09: Data science techniques for understanding your cancer catchment area

Abstract Clinical and population health researchers have the opportunity to create combined datasets for clinical cancer research that are vastly larger and, therefore, offer the potential to be more accurate and useful than those in traditional clinical research environments. The difficulty in creating these datasets is in cleaning and validating the data from disparate sources into an easily analyzable format. In addition, given the emphasis on cancer catchment, linking these data with other publically available data resources, e.g., census, environmental exposures, is critical for formulation the most accurate picture of your cancer patient population. Through the Cleveland Institute for Computational Biology, we have developed two data science techniques that (1) hash and match patients across systems/registries and (2) geocode patients at the individual address level. Identifying potential duplicate records is an essential step for the data cleansing as it allows for a more accurate count of unique patients, a more accurate picture of disease burden, and a better view of clinical outcomes of care over time. This identification of duplicate records is complicated by privacy rules adopted by many countries, such as the Health Insurance Portability and Accountability Act (HIPAA). Individually identifiable health information must be masked from parties that do not have viewing permission. In order to simplify the process of cleaning duplicate medical records and generating a unique patient identifier, thereby retaining HIPAA protections, we have created an easy-to-use software tool called “The De Duplicate and De Identify Research Engine” or “DeDeRE,” which includes 4 services: hashing, matching, reporting, and optimization. The DeDeRE software was developed to provide a solution for integrating and de-duplicating patient records across disparate datasets in order to allow the resulting datasets to be combined into larger sets while still protecting patient privacy. The DeDeRE software was developed in 2018 and used specifically as a test platform for the purpose of determining duplicate patients in multiple U.S. state cancer registries participating in the Surveillance, Epidemiology and End Results (SEER) program. Specifically, by hashing and matching millions of records of multiple state cancer registries, duplicate cases both intrastate and interstate were identified and adjudicated. Cancer health disparities are associated with many factors, including one’s location of residence. Location of residence can be associated with access to healthy food, transportation, access to health services, etc., some of which are known risk factors for specific types of cancer. In Ohio, we have obtained individual-level identified information from the Ohio Cancer Incidence Surveillance System (OCISS) allowing us to geocode all cancer patients in Ohio by individual address. We focus our analysis on the Cleveland Metro area and layer in other available data for our area in order to better understand differences in cancer incidence by location. Both of the data science approaches presented here are being applied in the Cleveland Metro area, allowing us to investigate important questions related to our Cleveland area cancer catchment population. Citation Format: Jill S. Barnholtz-Sloan. Data science techniques for understanding your cancer catchment area [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA09.

Gender Disparities in Bladder Cancer-Specific Survival in High Poverty Areas Utilizing Ohio Cancer Incidence Surveillance System (OCISS)

ObjectiveTo better understand the interplay of socioeconomic and demographic traits on bladder cancer outcomes utilizing the Ohio state cancer registry, Ohio Cancer Incidence Surveillance System (OCISS). MethodsWe obtained demographic, clinical and outcome data on 47,182 bladder cancer cases diagnosed from 1996 to 2016 from OCISS. Multivariable Cox proportional hazards regression to calculate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the association between sex, race and poverty and survival, adjusting age, stage, and primary treatment. ResultsWithin the OCISS database, there were 47,182 patients with a diagnosis of bladder cancer identified, with females representing 12,056 (26%) of the population. There were a total of 9255(35.2%) deaths due to bladder cancer, with median follow-up time of 4.4 years. After adjusting for confounding variables, women were statistically significantly less likely to die from any cause (HR: 0.94, 95% CI: 0.91-0.96), compared with men, but more likely to die from bladder cancer (HR: 1.21, 95% CI: 1.15-1.27). We also found that after adjusting for confounding variables, including sex and poverty, black race was statistically significantly associated with a higher risk of overall (HR: 1.12, 95% CI: 1.06-1.18) and bladder cancer-specific mortality (HR: 1.25, 95% CI: 1.15-1.36). ConclusionUsing the OCISS database, female gender, self-reported black race, and neighborhood poverty level were associated with worse bladder cancer-specific survival. By recognizing these disparities, we can prospectively address risk factors in efforts to improve survival among these patient populations.

Abstract D074: Variations in genomic testing across cancer sites and by demographic characteristics

Abstract Study Objective: Genomic testing is essential to identify the best treatment modalities for certain cancers; yet, its uptake has been relatively low, especially among disadvantaged subgroups of the population. The aim of this study is to identify demographic and clinical factors associated with receipt of genomic testing in Ohioans diagnosed with either incident female breast, kidney, bladder, prostate, colorectal, or lung cancer. Methods: We used data from the 2009 linked Ohio Cancer Incidence Surveillance System and Medicare files, and identified genomic testing using the appropriate procedure codes in claims data. Our study population included 10,945 patients. Independent variables examined were age at diagnosis (&amp;lt; 65, 65-74, 75+), sex, race (White or All Other), dual enrollment in the Medicare and Medicaid program (or ‘dual’) as a marker for low income and heightened vulnerability, and advanced stage at diagnosis (Regional/Distant versus Local stage). We conducted multivariable logistic regression analysis to identify correlates of genomic testing by cancer site. Results: For all cancer sites combined, 11.1% were younger than 65, and 40.6% were older than 75 years of age. Eighty eight percent were White, 47.0% were women, 13.9% were duals, and one third were diagnosed with advanced-stage cancer. Overall, only 19.5% underwent genomic testing, ranging from a low of 6.7% in prostate cancer patients, to a high of 39.3% in breast cancer patients. In addition, we observed considerable variation in genomic testing by age, race, sex, dual status, and cancer stage across cancer sites. Adjusting for the independent variables listed above, being 75 years of age or older was significantly and positively associated with increased likelihood of undergoing genomic testing in breast (adjusted odds ratio: 1.17, 95% confidence interval: 1.04, 1.32), kidney and bladder combined (1.29 (1.09, 1.53)), and prostate cancer patients (1.45 (1.12, 1.89)). Advanced-stage disease was associated with increased likelihood of genomic testing in breast and colorectal cancer patients (1.40 (1.17, 1.67) and 3.07 (2.30, 4.11), respectively), but with decreased likelihood in kidney and bladder cancer patients (0.66 (0.48, 0.91)). Finally, we note that White patients with lung cancer were significantly more likely than others to undergo genomic testing (2.49 (1.29, 4.78)). Conclusion: Our data from 2009 provide baseline statistics on genomic testing uptake in Ohio. Data for subsequent years will help us to assess trends in providing personalized medicine. Citation Format: Siran Koroukian, Weichuan Dong, Johnie Rose, Fredrick Schumacher, Sarah Markt. Variations in genomic testing across cancer sites and by demographic characteristics [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr D074.

Abstract C057: Neighborhood disadvantage is associated with liver cancer treatment and survival

Abstract Liver cancer is the 5th leading cause of cancer mortality in the United States and is predicted to increase in the US as a consequence of the opioid epidemic. Associations between individual-level risk factors, such as socioeconomic status, and liver cancer survival have been explored; however, the role of neighborhood-level factors, such as neighborhood deprivation, are noticeably absent from the literature. We explored the association between greater neighborhood deprivation and disparities in tumor characteristics, treatment and 5-year survival among primary liver cancer patients in Ohio diagnosed between 2003 and 2016 using data from the Ohio Cancer Incidence Surveillance System. We restricted our sample to only patients who were 18 years older and who could be geographically linked to a census tract based on their address at diagnosis. We created a neighborhood deprivation index (NDI) using nine variables at the Census tract level including: % less than high school diploma, % college graduates, % at or below the federal poverty line, % unemployed, median household income, % vacancy, % owner occupied unites, median house/unit value and % African American. We used principal component analysis to create the index and derived quintiles of deprivation with the higher quintiles reflective of areas with higher deprivation. We examined associations between tumor characteristics and NDI quintile using chi-square tests and ANOVA. We examined concordance with treatment guidelines as binary variable using log-binomial regression. For 5-year survival we utilized Cox proportional hazard models. Confounding variables for each regression model were selected using Directed Acyclic Graphs. After exclusion criteria were applied, 8,208 primary liver cancer patients were included in the study. We observed no statistically significant differences in tumor characteristics by quintile of NDI. However, we found a clear gradient between levels of deprivation and decrease likelihood of receiving guideline-concordant care. Specifically, between the most and least deprived areas, a 25% lower risk (Risk ratio [RR]=0.75; 95% Confidence Interval [CI]=0.67, 0.85) of receiving guideline-concordant care was observed in our adjusted log-binomial regression model. In adjusted survival models we observed an increased risk of death comparing the most and least deprived areas (Hazard ratio [HR]=1.14, 95% CI=1.02, 1.27). Our study suggests a potential negative effect of neighborhood deprivation on treatment concordance and liver cancer survival. Interventions targeting disparities in liver cancer should focus on not only individual level factors but address larger neighborhood level factors as well. Future analyses are needed to confirm these disparities observed and determine if similar neighborhood level effects occur in other cancer disparities. This study includes data provide by the Ohio Department of Health which should not be considered an endorsement of this study or its conclusions. Citation Format: Robert B Hood, Ashley Felix. Neighborhood disadvantage is associated with liver cancer treatment and survival [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr C057.