Comparing patient-reported outcomes and lifestyle factors before and after the COVID-19 pandemic among Black and Hispanic breast cancer survivors in New Jersey.

PURPOSE: The impact of the COVID-19 pandemic restrictions in the US since March 2020 on cancer survivorship among Black and Hispanic breast cancer (BC) survivors remains largely unknown. We aimed to evaluate associations of the pandemic with participant characteristics, patient-reported outcomes (PROs), and lifestyle factors among Black and Hispanic BC survivors in the Women's Circle of Health Follow-Up Study and the New Jersey BC Survivors Study. METHODS: We included 447 Black (npre = 364 and npost = 83) and 182 Hispanic (npre = 102 and npost = 80) BC survivors who completed a home interview approximately 24 months post-diagnosis between 2017 and 2023. The onset of the pandemic was defined as March 2020. The association of the pandemic with binary outcomes was estimated using robust Poisson regression models. RESULTS: Hispanic and Black BC survivors recruited after the onset of the pandemic reported higher socioeconomic status and fewer comorbidities. Black women in the post-pandemic group reported a higher prevalence of clinically significant sleep disturbance (prevalence ratio (PR) 1.43, 95% CI 1.23, 1.68), lower sleep efficiency, and lower functional well-being, compared to the pre-pandemic group. Hispanic women were less likely to report low health-related quality of life (vs. high; PR 0.62, 95% CI 0.45, 0.85) after the onset of the pandemic. CONCLUSIONS: Ongoing research is crucial to untangle the impact of the pandemic on racial and ethnic minorities participating in cancer survivorship research, as well as PROs and lifestyle factors. IMPLICATIONS FOR CANCER SURVIVORS: This study highlights the importance of considering the impact of the pandemic in all aspects of research, including the interpretation of findings.

Methodology for Using Real-World Data From Electronic Health Records to Assess Chemotherapy Administration in Women With Breast Cancer.

PURPOSE: Identification of patients' intended chemotherapy regimens is critical to most research questions conducted in the real-world setting of cancer care. Yet, these data are not routinely available in electronic health records (EHRs) at the specificity required to address these questions. We developed a methodology to identify patients' intended regimens from EHR data in the Optimal Breast Cancer Chemotherapy Dosing (OBCD) study. METHODS: In women older than 18 years, diagnosed with primary stage I-IIIA breast cancer at Kaiser Permanente Northern California (2006-2019), we categorized participants into 24 drug combinations described in National Comprehensive Cancer Network guidelines for breast cancer treatment. Participants were categorized into 50 guideline chemotherapy administration schedules within these combinations using an iterative algorithm process, followed by chart abstraction where necessary. We also identified patients intended to receive nonguideline administration schedules within guideline drug combinations and nonguideline drug combinations. This process was adapted at Kaiser Permanente Washington using abstracted data (2004-2015). RESULTS: In the OBCD cohort, 13,231 women received adjuvant or neoadjuvant chemotherapy, of whom 10,213 (77%) had their intended regimen identified via the algorithm, 2,416 (18%) had their intended regimen identified via abstraction, and 602 (4.5%) could not be identified. Across guideline drug combinations, 111 nonguideline dosing schedules were used, alongside 61 nonguideline drug combinations. A number of factors were associated with requiring abstraction for regimen determination, including: decreasing neighborhood household income, earlier diagnosis year, later stage, nodal status, and human epidermal growth factor receptor 2 (HER2)+ status. CONCLUSION: We describe the challenges and approaches to operationalize complex, real-world data to identify intended chemotherapy regimens in large, observational studies. This methodology can improve efficiency of use of large-scale clinical data in real-world populations, helping answer critical questions to improve care delivery and patient outcomes.

Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk.

Background: Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). Methods: We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan. Results: Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that TP53 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10-9). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). Conclusions: This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.

Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia.

BACKGROUND: Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs. METHODS: We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG). RESULTS: In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16). CONCLUSION: The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.

Assessment of breast cancer chemotherapy dose reduction in an integrated healthcare delivery system.

PURPOSE: Most cytotoxic drugs are dosed using body surface area (BSA), yet not all cancer patients receive the full BSA-determined dose. Prior work suggests that breast cancer patients who are obese are more likely to experience dose reduction than normal weight patients. However, the factors driving dose reduction remain unclear. METHODS: In 452 women diagnosed with stage I-IIIA primary breast cancer at Kaiser Permanente Northern California, we evaluated the association between obesity and dose reduction, and further explored other factors in relation to dose reduction, including various sociodemographic characteristics, tumor characteristics, and comorbidities. Study participants were a part of the Pathways Study, diagnosed between 2006 and 2013 and treated with cyclophosphamide + doxorubicin, followed by paclitaxel (ACT). Dose reduction was assessed using first cycle dose proportion (FCDP) and average relative dose intensity (ARDI), a metric of dose intensity over the course of chemotherapy. RESULTS: Overall, 8% of participants received a FCDP < 90% and 21.2% had an ARDI < 90%, with dose reduction increasing with body mass index. In adjusted logistic regression models, obese women had 4.1-fold higher odds of receiving an ARDI < 90% than normal weight women (95% CI: 1.9-8.9; p-trend = 0.0006). Increasing age was positively associated with an ADRI < 90%, as was the presence of comorbidity. Dose reduction was less common in later calendar years. CONCLUSION: Results offer insight on factors associated with chemotherapy dosing for a common breast cancer regimen. Larger studies are required to evaluate relevance to other regimens, and further work will be needed to determine whether dose reductions impact outcomes in obese women.

Evaluation of Algorithms Using Automated Health Plan Data to Identify Breast Cancer Recurrences.

BACKGROUND: We updated algorithms to identify breast cancer recurrences from administrative data, extending previously developed methods. METHODS: In this validation study, we evaluated pairs of breast cancer recurrence algorithms (vs. individual algorithms) to identify recurrences. We generated algorithm combinations that categorized discordant algorithm results as no recurrence [High Specificity and PPV (positive predictive value) Combination] or recurrence (High Sensitivity Combination). We compared individual and combined algorithm results to manually abstracted recurrence outcomes from a sample of 600 people with incident stage I-IIIA breast cancer diagnosed between 2004 and 2015. We used Cox regression to evaluate risk factors associated with age- and stage-adjusted recurrence rates using different recurrence definitions, weighted by inverse sampling probabilities. RESULTS: Among 600 people, we identified 117 recurrences using the High Specificity and PPV Combination, 505 using the High Sensitivity Combination, and 118 using manual abstraction. The High Specificity and PPV Combination had good specificity [98%, 95% confidence interval (CI): 97-99] and PPV (72%, 95% CI: 63-80) but modest sensitivity (64%, 95% CI: 44-80). The High Sensitivity Combination had good sensitivity (80%, 95% CI: 49-94) and specificity (83%, 95% CI: 80-86) but low PPV (29%, 95% CI: 25-34). Recurrence rates using combined algorithms were similar in magnitude for most risk factors. CONCLUSIONS: By combining algorithms, we identified breast cancer recurrences with greater PPV than individual algorithms, without additional review of discordant records. IMPACT: Researchers should consider tradeoffs between accuracy and manual chart abstraction resources when using previously developed algorithms. We provided guidance for future studies that use breast cancer recurrence algorithms with or without supplemental manual chart abstraction.

Advancing Social and Environmental Research in Cancer Registries Using Geomasking for Address-Level Data.

Understanding the social and environmental causes of cancer in the United States, particularly in marginalized communities, is a major research priority. Population-based cancer registries are essential for advancing this research, given their nearly complete capture of incident cases within their catchment areas. Most registries limit the release of address-level geocodes linked to cancer outcomes to comply with state health departmental regulations. These policies ensure patient privacy, uphold data confidentiality, and enhance trust in research. However, these restrictions also limit the conduct of high-quality epidemiologic studies on social and environmental factors that may contribute to cancer burden. Geomasking refers to computational algorithms that distort locational data to attain a balance between effectively "masking" the original address location while faithfully maintaining the spatial structure in the data. We propose that the systematic deployment of scalable geomasking algorithms could accelerate research on social and environmental contributions across the cancer continuum by reducing measurement error bias while also protecting privacy. We encourage multidisciplinary teams of registry officials, geospatial analysts, cancer researchers, and others engaged in this form of research to evaluate and apply geomasking procedures based on feasibility of implementation, accuracy, and privacy protection to accelerate population-based research on social and environmental causes of cancer.

Experiences and lessons learned from community-engaged recruitment for the South Asian breast cancer study in New Jersey during the COVID-19 pandemic.

BACKGROUND: South Asians are a rapidly growing population in the United States. Breast cancer is a major concern among South Asian American women, who are an understudied population. We established the South Asian Breast Cancer (SABCa) study in New Jersey during early 2020 to gain insights into their breast cancer-related health attitudes. Shortly after we started planning for the study, the COVID-19 disease spread throughout the world. In this paper, we describe our experiences and lessons learned from recruiting study participants by partnering with New Jersey's community organizations during the COVID-19 pandemic. METHODS: We used a cross-sectional design. We contacted 12 community organizations and 7 (58%) disseminated our study information. However, these organizations became considerably busy with pandemic-related needs. Therefore, we had to pivot to alternative recruitment strategies through community radio, Rutgers Cancer Institute of New Jersey's Community Outreach and Engagement Program, and Rutgers Cooperative Extension's community health programs. We recruited participants through these alternative strategies, obtained written informed consent, and collected demographic information using a structured survey. RESULTS: Twenty five women expressed interest in the study, of which 22 (88%) participated. Nine (41%) participants learned about the study through the radio, 5 (23%) through these participants, 1 (4.5%) through a non-radio community organization, and 7 (32%) through community health programs. Two (9%) participants heard about the study from their spouse. All participants were born outside the US, their average age was 52.4 years (range: 39-72 years), and they have lived in the US for an average of 26 years (range: 5-51 years). CONCLUSION: Pivoting to alternative strategies were crucial for successful recruitment. Findings suggest the significant potential of broadcast media for community-based recruitment. Family dynamics and the community's trust in our partners also encouraged participation. Such strategies must be considered when working with understudied populations.

Menopausal hormone therapy use and risk of ovarian cancer by race: the ovarian cancer in women of African ancestry consortium.

BACKGROUND: Most studies examining post-menopausal menopausal hormone therapy (MHT) use and ovarian cancer risk have focused on White women and few have included Black women. METHODS: We evaluated MHT use and ovarian cancer risk in Black (n = 800 cases, 1783 controls) and White women (n = 2710 cases, 8556 controls), using data from the Ovarian Cancer in Women of African Ancestry consortium. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association of MHT use with ovarian cancer risk, examining histotype, MHT type and duration of use. RESULTS: Long-term MHT use, ≥10 years, was associated with an increased ovarian cancer risk for White women (OR = 1.38, 95%CI: 1.22-1.57) and the association was consistent for Black women (OR = 1.20, 95%CI: 0.81-1.78, pinteraction = 0.4). For White women, the associations between long-term unopposed estrogen or estrogen plus progesterone use and ovarian cancer risk were similar; the increased risk associated with long-term MHT use was confined to high-grade serous and endometroid tumors. Based on smaller numbers for Black women, the increased ovarian cancer risk associated with long-term MHT use was apparent for unopposed estrogen use and was predominately confined to other epithelial histotypes. CONCLUSION: The association between long-term MHT use and ovarian cancer risk was consistent for Black and White women.

The Association between Mediated Deprivation and Ovarian Cancer Survival among African American Women.

BACKGROUND: Deprivation indices are often used to adjust for socio-economic disparities in health studies. Their role has been partially evaluated for certain population-level cancer outcomes, but examination of their role in ovarian cancer is limited. In this study, we evaluated a range of well-recognized deprivation indices in relation to cancer survival in a cohort of self-identified Black women diagnosed with ovarian cancer. This study aimed to determine if clinical or diagnostic characteristics lie on a mediating pathway between socioeconomic status (SES) and deprivation and ovarian cancer survival in a minority population that experiences worse survival from ovarian cancer. METHODS: We used mediation analysis to look at the direct and indirect causal effects of deprivation indices with main mediators of the SEER stage at diagnosis and residual disease. The analysis employed Bayesian structural equation models with variable selection. We applied a joint Bayesian structural model for the mediator, including a Weibull mixed model for the vital outcome with deprivation as exposure. We selected modifiers via a Monte Carlo model selection procedure. RESULTS: The results suggest that high SES-related indices, such as Yost, Kolak urbanicity (URB), mobility (MOB) and SES dimensions, and concentrated disadvantage index (CDI), all have a significant impact on improved survival. In contrast, area deprivation index (ADI)/Singh, and area level poverty (POV) did not have a major impact. In some cases, the indirect effects have very wide credible intervals, so the total effect is not well estimated despite the estimation of the direct effect. CONCLUSIONS: First, it is clear that commonly used indices such as Yost, or CDI both significantly impact the survival experience of Black women diagnosed with epithelial ovarian cancer. In addition, the Kolak dimension indices (URB, MOB, mixed immigrant: MICA and SES) also demonstrate a significant association, depending on the mediator. Mediation effects differ according to the mediator chosen.

Neighborhood Disadvantage, African Genetic Ancestry, Cancer Subtype, and Mortality Among Breast Cancer Survivors.

Importance: Racial disparities in breast cancer (BC) survival arise from multilevel causes, which may exert influence at different stages of BC progression. Clarifying the importance of genetic and social factors could help prioritize interventions. Objective: To jointly examine associations between African genetic ancestry, social environment, and mortality from any cause and BC in Black BC survivors. Design, Setting, and Participants: This population-based cohort study enrolled self-identified Black women aged 20 to 75 years with histologically confirmed BC from June 2005 to May 2019 and followed them up until death or censoring in September 2021. Participants lived in 10 New Jersey counties. Data were analyzed between December 2022 and April 2023. Exposures: A neighborhood socioeconomic status (nSES) index composed of census tract measures (education, income, wealth, employment status, and occupation) was linked to residential addresses at diagnosis. Percentage African ancestry was estimated using the ADMIXTURE program. Main Outcomes and Measures: Sequentially adjusted (age adjusted: age and interview year; fully adjusted: age adjusted with individual SES, lifestyle factors, and comorbidities) logistic regression models were fit to estimate associations with tumor subtypes (estrogen receptor-negative [ER-] vs estrogen receptor-positive [ER+]; triple-negative breast cancer [TNBC] vs luminal A), and Cox models were fit for associations with all-cause mortality (ACM) and breast cancer-specific mortality (BCSM). Models for BCSM were fit using Fine-Gray competing risks models, and robust standard errors were used to account for census tract-level clustering. Results: Among 1575 participants, median (IQR) African ancestry was 85% (76%-90%), and median (IQR) age was 55 (46-63) years. A 10-percentage point increase in African ancestry was associated with higher odds of ER- vs ER+ (adjusted odds ratio [aOR], 1.08; 95% CI, 0.98-1.18) and TNBC vs luminal (aOR, 1.15; 95% CI, 1.02-1.31) tumors, but not with ACM or BCSM. A 1-IQR increase in nSES was associated with lower ACM (adjusted hazard ratio [aHR], 0.76; 95% CI, 0.63-0.93), and the HR for BCSM was less than 1 but not statistically significant (aHR, 0.81; 95% CI, 0.62-1.04) in age-adjusted models, but associations attenuated following further adjustment for potential mediators (individual SES, lifestyles, comorbidities). Conclusions and Relevance: In this cohort study of Black female BC survivors, higher African ancestry was associated with aggressive tumor subtypes. Compared with genetic ancestry, mediating pathways related to social environments may be more important for survival in these patients.

Association of inflammation-related exposures and ovarian cancer survival in a multi-site cohort study of Black women.

BACKGROUND: An association was observed between an inflammation-related risk score (IRRS) and worse overall survival (OS) among a cohort of mostly White women with invasive epithelial ovarian cancer (EOC). Herein, we evaluated the association between the IRRS and OS among Black women with EOC, a population with higher frequencies of pro-inflammatory exposures and worse survival. METHODS: The analysis included 592 Black women diagnosed with EOC from the African American Cancer Epidemiology Study (AACES). Cox proportional hazards models were used to compute hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of the IRRS and OS, adjusting for relevant covariates. Additional inflammation-related exposures, including the energy-adjusted Dietary Inflammatory Index (E-DIITM), were evaluated. RESULTS: A dose-response trend was observed showing higher IRRS was associated with worse OS (per quartile HR: 1.11, 95% CI: 1.01-1.22). Adding the E-DII to the model attenuated the association of IRRS with OS, and increasing E-DII, indicating a more pro-inflammatory diet, was associated with shorter OS (per quartile HR: 1.12, 95% CI: 1.02-1.24). Scoring high on both indices was associated with shorter OS (HR: 1.54, 95% CI: 1.16-2.06). CONCLUSION: Higher levels of inflammation-related exposures were associated with decreased EOC OS among Black women.

Deprivation and segregation in ovarian cancer survival among African American women: a mediation analysis.

PURPOSE: Deprivation and segregation indices are often examined as possible explanations for observed health disparities in population-based studies. In this study, we assessed the role of recognized deprivation and segregation indices specifically as they affect survival in a cohort of self-identified Black women diagnosed with ovarian cancer who enrolled in the African American Cancer Epidemiology Study. METHODS: Mediation analysis was used to examine the direct and indirect effects between deprivation or segregation and overall survival via a Bayesian structural equation model with Gibbs variable selection. RESULTS: The results suggest that high socioeconomic status-related indices have an association with increased survival, ranging from 25% to 56%. In contrast, index of concentration at the extremes-race does not have a significant impact on overall survival. In many cases, the indirect effects have very wide credible intervals; consequently, the total effect is not well estimated despite the estimation of the direct effect. CONCLUSIONS: Our results show that Black women living in higher socioeconomic status neighborhoods are associated with increased survival with ovarian cancer using area-level economic indices such as Yost or index of concentration at the extremes-income. In addition, the Kolak urbanization index has a similar impact and highlights the importance of area-level deprivation and segregation as potentially modifiable social factors in ovarian cancer survival.

A framework for assessing interactions for risk stratification models: the example of ovarian cancer.

Generally, risk stratification models for cancer use effect estimates from risk/protective factor analyses that have not assessed potential interactions between these exposures. We have developed a 4-criterion framework for assessing interactions that includes statistical, qualitative, biological, and practical approaches. We present the application of this framework in an ovarian cancer setting because this is an important step in developing more accurate risk stratification models. Using data from 9 case-control studies in the Ovarian Cancer Association Consortium, we conducted a comprehensive analysis of interactions among 15 unequivocal risk and protective factors for ovarian cancer (including 14 non-genetic factors and a 36-variant polygenic score) with age and menopausal status. Pairwise interactions between the risk/protective factors were also assessed. We found that menopausal status modifies the association among endometriosis, first-degree family history of ovarian cancer, breastfeeding, and depot-medroxyprogesterone acetate use and disease risk, highlighting the importance of understanding multiplicative interactions when developing risk prediction models.

Factors associated with health-related quality of life in a cohort of cancer survivors in New Jersey.

BACKGROUND: Although there is extensive literature on correlates of health-related quality of life (HRQoL) among cancer survivors, there has been less attention paid to the role of socioeconomic disadvantage and survivorship care transition experiences in HRQoL. There are few large cohort studies that include a comprehensive set of correlates to obtain a full picture of what is associated with survivors' HRQ0L. This cohort study of recent cancer survivors in New Jersey aimed to explore the association between social determinants of health, health history, health behaviors, survivorship care experiences, and psychosocial factors in HRQoL. METHODS: Eligible survivors were residents of New Jersey diagnosed with genitourinary, female breast, gynecologic, colorectal, lung, melanoma, or thyroid cancers. Participants completed measures of social determinants, health behaviors, survivorship care experiences, psychosocial factors, and HRQoL. Separate multiple regression models predicting HRQoL were conducted for each of the five domains (social determinants, health history, health behaviors, survivorship care experiences, psychosocial factors). Variables attaining statistical significance were included in a hierarchical multiple regression arranged by the five domains. RESULTS: 864 cancer survivors completed the survey. Lower global HRQoL was associated with being unemployed, more comorbidities, a less healthy diet, lower preparedness for survivorship, more unmet support needs, and higher fear about cancer recurrence. Two psychosocial factors, unmet support needs and fear of recurrence, played the most important role in HRQoL, accounting for more than 20% of the variance. Both unmet support needs and fear of recurrence were significant correlates of physical, functional, and emotional HRQoL domains. CONCLUSIONS: Interventions seeking to improve cancer survivors' HRQoL may benefit from improving coordinated management of comorbid medical problems, fostering a healthier diet, addressing unmet support needs, and reducing survivors' fears about cancer recurrence.

Clinical parameters affecting survival outcomes in patients with low-grade serous ovarian carcinoma: an international multicentre analysis.

BACKGROUND: Women with low-grade ovarian serous carcinoma (LGSC) benefit from surgical treatment; however, the role of chemotherapy is controversial. We examined an international database through the Ovarian Cancer Association Consortium to identify factors that affect survival in LGSC. METHODS: We performed a retrospective cohort analysis of patients with LGSC who had had primary surgery and had overall survival data available. We performed univariate and multivariate analyses of progression-free survival and overall survival, and generated Kaplan-Meier survival curves. RESULTS: Of the 707 patients with LGSC, 680 (96.2%) had available overall survival data. The patients' median age overall was 54 years. Of the 659 patients with International Federation of Obstetrics and Gynecology stage data, 156 (23.7%) had stage I disease, 64 (9.7%) had stage II, 395 (59.9%) had stage III, and 44 (6.7%) had stage IV. Of the 377 patients with surgical data, 200 (53.0%) had no visible residual disease. Of the 361 patients with chemotherapy data, 330 (91.4%) received first-line platinum-based chemotherapy. The median follow-up duration was 5.0 years. The median progression-free survival and overall survival were 43.2 months and 110.4 months, respectively. Multivariate analysis indicated a statistically significant impact of stage and residual disease on progression-free survival and overall survival. Platinum-based chemotherapy was not associated with a survival advantage. CONCLUSION: This multicentre analysis indicates that complete surgical cytoreduction to no visible residual disease has the most impact on improved survival in LGSC. This finding could immediately inform and change practice.

Racial Differences in the Association of Endometriosis and Uterine Leiomyomas With the Risk of Ovarian Cancer.

OBJECTIVE: To evaluate associations between endometriosis and uterine leiomyomas with ovarian cancer risk by race and the effect of hysterectomy on these associations. METHODS: We used data from four case-control studies and two case-control studies nested within prospective cohorts in the OCWAA (Ovarian Cancer in Women of African Ancestry) consortium. The study population included 3,124 Black participants and 5,458 White participants, of whom 1,008 Black participants and 2,237 White participants had ovarian cancer. Logistic regression was used to calculate odds ratios (ORs) and 95% CIs for the associations of endometriosis and leiomyomas with ovarian cancer risk, by race, stratified by histotype and hysterectomy. RESULTS: The prevalences of endometriosis and leiomyomas were 6.4% and 43.2% among Black participants and 7.0% and 21.5% among White participants, respectively. Endometriosis was associated with an increased risk of endometrioid and clear-cell ovarian cancer in both racial groups (eg, OR for endometrioid tumors for Black and White participants 7.06 [95% CI 3.86-12.91] and 2.17 [95% CI 1.36-3.45], respectively, Phetereogeneity =.003). The association between endometriosis and ovarian cancer risk in White participants was stronger in those without hysterectomy, but no difference was observed in Black participants (all Pinteraction ≥.05). Leiomyomas were associated with an elevated risk of ovarian cancer only in those without hysterectomy in both Black (OR 1.34, 95% CI 1.11-1.62) and White (OR 1.22, 95% CI 1.05-1.41) participants (all Pinteraction ≥.05). CONCLUSIONS: Black and White participants with endometriosis had a higher risk of ovarian cancer, and hysterectomy modified this association among White participants. Leiomyomas were associated with an increased risk of ovarian cancer in both racial groups, with hysterectomy modifying the risk in both groups. Understanding how racial differences in access to care and treatment options (eg, hysterectomy) may help guide future risk reduction strategies.

Sociodemographic disparities in targeted therapy in ovarian cancer in a national sample.

Background: The treatment landscape for ovarian cancer has changed in recent years with the introduction of targeted therapies to treat patients with advanced disease. We investigated patient demographic and clinical factors associated with use of targeted therapies as a part of the first-line treatment for ovarian cancer. Methods: This study included patients diagnosed with stage I-IV ovarian cancer between 2012 and 2019 from the National Cancer Database. Information on demographic and clinical characteristics were collected and described using frequency and percent across receipt of targeted therapy. Logistic regression was used to compute the odds ratios (ORs) and 95% confidence intervals (CI) associating patient demographic and clinical factors with receipt of targeted therapy. Results: Among 99,286 ovarian cancer patients (mean age 62 years), 4.1% received targeted therapy. The rate of targeted therapy receipt across racial and ethnic groups over the study period was fairly similar; however, non-Hispanic Black women were less likely to receive targeted therapy than their non-Hispanic White counterparts (OR=0.87, 95% CI: 0.76-1.00). Patients who received neoadjuvant chemotherapy were more likely to receive targeted therapy than those who received adjuvant chemotherapy (OR=1.26; 95% CI: 1.15-1.38). Moreover, among patients who received targeted therapy, 28% received neoadjuvant targeted therapy, with non-Hispanic Black women being most likely to receive neoadjuvant targeted therapy (34%) compared with other racial and ethnic groups. Conclusions: We observed differences in receipt of targeted therapy by factors such as age at diagnosis, stage, and comorbidities present at diagnosis, as well as factors related to healthcare access-including neighborhood education level and health insurance status. Approximately 28% of patients received targeted therapy in the neoadjuvant setting, which could negatively impact treatment outcomes and survival due to the increased risk of complications associated with targeted therapies that may delay or prevent surgery. These results warrant further evaluation in a cohort of patients with more comprehensive treatment information.

Associations between Etiologic or Prognostic Tumor Tissue Markers and Neighborhood Contextual Factors in Male Health Professionals Diagnosed with Prostate Cancer.

BACKGROUND: There is growing evidence that unfavorable neighborhood contexts may influence prostate cancer progression. Whether these associations may be explained in part by differences in tumor-level somatic alterations remain unclear. METHODS: Data on tumor markers (PTEN, p53, ERG, and SPINK1) were obtained from 1,157 participants with prostate cancer in the Health Professionals Follow-up Study. Neighborhood greenness, socioeconomic status, and the income Index of Concentration at Extremes were obtained from satellite and census data and linked to participants' address at diagnosis and at study enrollment. Exposures were scaled to an interquartile range and modeled as tertiles. Bivariate associations between tertiles of neighborhood factors and tumor markers were assessed in covariate adjusted logistic regression models to estimate ORs and 95% confidence intervals. RESULTS: There was no association between any of the neighborhood contextual factors and PTEN, p53, ERG, or SPINK1 in bivariate or multivariable adjusted models. Results were generally consistent when modeling exposure using exposure at diagnosis or at study enrollment. CONCLUSIONS: In this multilevel study of men with prostate cancer, we found no evidence of associations between neighborhood context and tumor tissue markers. IMPACT: Our results provide some of the first empirical data in support of the hypothesis that prostate cancer risk conferred by tumor tissue markers may arise independently of underlying neighborhood context. Prospective studies in more diverse populations are needed to confirm these findings.

Sociodemographic and Health Correlates of Multiple Health Behavior Adherence among Cancer Survivors: A Latent Class Analysis.

The study aimed to (a) assess current levels of adherence to the National Comprehensive Cancer Network's multiple health behavior guidelines and (b) identify characteristics of cancer survivors associated with different adherence levels. Cancer survivors (N = 661) were identified through the state registry and completed questionnaires. Latent class analysis (LCA) was used to identify patterns of adherence. Associations between predictors with the latent classes were reported as risk ratios. LCA identified three classes: lower- (39.6%), moderate- (52.0%), and high-risk lifestyle (8.3%). Participants in the lower-risk lifestyle class had the highest probability of meeting most of the multiple health behavior guidelines compared to participants in the high-risk lifestyle class. Characteristics associated with membership in the moderate-risk lifestyle class included self-identifying as a race other than Asian/Asian American, being never married, having some college education, and having been diagnosed with later stage colorectal or lung cancer. Those in the high-risk lifestyle class were more likely to be male, never married, have a high school diploma or less, diagnosed with colorectal or lung cancer, and diagnosed with pulmonary comorbidities. Study findings can be used to inform development of future interventions to promote multiple health behavior adherence among higher risk cancer survivors.