Role of neighborhood context in ovarian cancer survival disparities: current research and future directions

Gomez, Scarlett Lin; Mcguire, Valerie; Collin, Lindsay J.; Dempsey, Lauren F.; Inamdar, Pushkar; Lawson-Michod, Katherine; Peters, Edward S.; Kushi, Lawrence H.; Shariff‐Marco, Salma; Peres, Lauren C.; Terry, P. W.; Bandera, Elisa V.; Schildkraut, Joellen M.; Doherty, Jennifer A.; Lawson, Andrew

doi:10.1016/j.ajog.2023.04.026

Cited by 8 publications

(12 citation statements)

References 104 publications

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“…Zip code was the smallest geographic unit available in the source data; however, census tract–level metrics for the vulnerability measures may be a subject of future research in alternate data sources. Previous studies have found associations between county- and zip code–level factors and disparities in health care access …”

Section: Discussionmentioning

confidence: 99%

“…Racial and ethnic disparities in health reflect structural differences across social factors and resources, including environmental factors and access to health care interventions . Prevailing evidence suggests that disparities in cancer treatment and mortality associated with individuals’ race and ethnicity are not fully accounted for by individual-level, clinical, and demographic factors and that neighborhood factors influencing health and health care access could be contributors …”

Section: Introductionmentioning

confidence: 99%

“…4 Prevailing evidence suggests that disparities in cancer treatment and mortality associated with individuals' race and ethnicity are not fully accounted for by individual-level, clinical, and demographic factors and that neighborhood factors influencing health and health care access could be contributors. [5][6][7][8] There has been growing interest in how area-level measures of socioeconomic status and environment are associated with health outcomes. Area-level measures have been associated with frailty, obesity, and cardiovascular disease as well as access to preventive health care in historically marginalized populations.…”

Section: Introductionmentioning

confidence: 99%

“…[4][5][6]9,10 In regard to cancer-specific outcomes, a higher Social Vulnerability Index (SVI) 11 score has been associated with patients being less likely to receive neoadjuvant chemotherapy or to use high-volume centers for surgical resection and with patients being more likely to encounter fragmented postoperative care. 7,8,11,12 Additionally, area-level factors have been associated with morbidity after controlling for sociodemographic factors among individuals with colorectal and breast cancer. 13 Metrics that are commonly used to quantify social determinants of health at the county and zip code level include the Social Deprivation Index (SDI) 12 and Index of Concentration at the Extremes (ICE), a measure of spatial social polarization that quantifies racial residential segregation.…”

Section: Introductionmentioning

confidence: 99%

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Area Vulnerability and Disparities in Therapy for Patients With Metastatic Renal Cell Carcinoma

Rahman,

Long,

Westvold

et al. 2024

JAMA Netw Open

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ImportanceArea-level measures of sociodemographic disadvantage may be associated with racial and ethnic disparities with respect to receipt of treatment for metastatic renal cell carcinoma (mRCC) but have not been investigated previously, to our knowledge.ObjectiveTo assess the association between area-level measures of social vulnerability and racial and ethnic disparities in the treatment of US Medicare beneficiaries with mRCC from 2015 through 2019.Design, Setting, and ParticipantsThis retrospective cohort study included Medicare beneficiaries older than 65 years who were diagnosed with mRCC from January 2015 through December 2019 and were enrolled in fee-for-service Medicare Parts A, B, and D from 1 year before through 1 year after presumed diagnosis or until death. Data were analyzed from November 22, 2022, through January 26, 2024.ExposuresFive different county-level measures of disadvantage and 4 zip code–level measures of vulnerability or deprivation and segregation were used to dichotomize whether an individual resided in the most vulnerable quartile according to each metric. Patient-level factors included age, race and ethnicity, sex, diagnosis year, comorbidities, frailty, Medicare and Medicaid dual enrollment eligibility, and Medicare Part D low-income subsidy (LIS).Main Outcomes and MeasuresThe main outcomes were receipt and type of systemic therapy (oral anticancer agent or immunotherapy from 2 months before to 1 year after diagnosis of mRCC) as a function of patient and area-level characteristics. Multivariable regression analyses were used to adjust for patient factors, and odds ratios (ORs) from logistic regression and relative risk ratios (RRRs) from multinomial logistic regression are reported.ResultsThe sample included 15 407 patients (mean [SD] age, 75.6 [6.8] years), of whom 9360 (60.8%) were men; 6931 (45.0%), older than 75 years; 93 (0.6%), American Indian or Alaska Native; 257 (1.7%), Asian or Pacific Islander; 757 (4.9%), Hispanic; 1017 (6.6%), non-Hispanic Black; 12 966 (84.2%), non-Hispanic White; 121 (0.8%), other; and 196 (1.3%), unknown. Overall, 8317 patients (54.0%) received some type of systemic therapy. After adjusting for individual factors, no county or zip code–level measures of social vulnerability, deprivation, or segregation were associated with disparities in treatment. In contrast, patient-level factors, including female sex (OR, 0.78; 95% CI, 0.73-0.84) and LIS (OR, 0.48; 95% CI, 0.36-0.65), were associated with lack of treatment, with particularly limited access to immunotherapy for patients with LIS (RRR, 0.25; 95% CI, 0.14-0.43). Associations between individual-level factors and treatment in multivariable analysis were not mediated by the addition of area-level metrics. Disparities by race and ethnicity were consistently and only observed within the most vulnerable areas, as indicated by the top quartile of each vulnerability deprivation index.Conclusions and RelevanceIn this cohort study of older Medicare patients diagnosed with mRCC, individual-level demographics, including race and ethnicity, sex, and income, were associated with receipt of systemic therapy, whereas area-level measures were not. However, individual-level racial and ethnic disparities were largely limited to socially vulnerable areas, suggesting that efforts to improve racial and ethnic disparities may be most effective when targeted to socially vulnerable areas.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Area Vulnerability and Disparities in Therapy for Patients With Metastatic Renal Cell Carcinoma

Rahman,

Long,

Westvold

et al. 2024

JAMA Netw Open

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“…Framework for ovarian cancer disparities. 77 high-risk types (46.1% vs. 21.6%) and are more likely to have an advanced disease stage (34.1% vs. 19.8%), with worse outcomes after controlling for stage and treatment. 73 A SEER study (2000-2012) including all uterine sarcomas, another aggressive type, showed worse survival associated with age, Black race, and advanced stage.…”

Section: Differences In Uterine Cancer Histologymentioning

confidence: 99%

Disparities in Gynecologic Cancers

Lee,

Tiro,

Odunsi

2023

Cancer J

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Gynecologic cancer disparities have different trends by cancer type and by sociodemographic/economic factors. We highlight disparities in the United States arising due to poor delivery of cancer care across the continuum from primary prevention, detection, and diagnosis through treatment and identify opportunities to eliminate/reduce disparities to achieve cancer health equity. Our review documents the persistent racial and ethnic disparities in cervical, ovarian, and uterine cancer outcomes, with Black patients experiencing the worst outcomes, and notes literature investigating social determinants of health, particularly access to care. Although timely delivery of screening and diagnostic evaluation is of paramount importance for cervical cancer, efforts for ovarian and uterine cancer need to focus on timely recognition of symptoms, diagnostic evaluation, and delivery of guideline-concordant cancer treatment, including tumor biomarker and somatic/germline genetic testing.

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