Cancer Survivor Study Research Articles

Racial and ethnic disparities in disease progression and subsequent survival among patients with ovarian cancer in the Kaiser Permanente Research on Ovarian Cancer Survival (KP ROCS) Study

Racial and ethnic disparities in disease progression and subsequent survival among patients with ovarian cancer in the Kaiser Permanente Research on Ovarian Cancer Survival (KP ROCS) Study

Diet and Survival in Black Women With Epithelial Ovarian Cancer

Ovarian cancer survival among Black women is the lowest across all racial and ethnic groups. Poor dietary quality also disproportionately affects Black populations, but its association with ovarian cancer survival in this population remains largely unknown. To examine associations between dietary patterns and survival among Black women diagnosed with epithelial ovarian cancer (EOC). This prospective cohort study was conducted among self-identified Black women aged 20 to 79 years newly diagnosed with histologically confirmed EOC in the African American Cancer Epidemiology Study (AACES) between December 2010 and December 2015, with follow-up until October 2022. AACES is a population-based study of ovarian cancer risk and survival among Black women in 11 US regions. Data were analyzed from March 2023 to June 2024. Dietary patterns were assessed by the Healthy Eating Index-2020 (HEI-2020) and Alternative Healthy Eating Index-2010 (AHEI-2010), with scores calculated based on dietary intake in the year prior to diagnosis and collected via the validated Block 2005 Food Frequency Questionnaire. Higher scores indicate better dietary quality. Hazard ratios (HRs) and 95% CIs were estimated from multivariable Cox models for the association between adherence to dietary recommendations and overall mortality among all participants and those with high-grade serous ovarian cancer (HGSOC). Among 483 Black women with EOC (mean [SD] age, 58.1 [10.5] years), 310 deaths were recorded during a median (IQR) follow-up of 4.3 (2.0-8.2) years. No association of dietary patterns with mortality was found among women with EOC overall. However, among 325 women with HGSOC, better adherence to HEI-2020 was associated with decreased mortality in later quartiles compared with the first quartile (HR, 0.63; 95% CI, 0.44-0.92 for quartile 2; HR, 0.67; 95% CI, 0.46-0.97 for quartile 3; HR, 0.63; 95% CI, 0.44-0.91 for quartile 4 ). Similar results were observed with AHEI-2010 among women with HGSOC for the second (HR, 0.62; 95% CI, 0.43-0.89) and fourth (HR, 0.67; 95% CI, 0.45-0.98) quartiles compared with quartile 1. In this study, women with moderate and high prediagnosis dietary quality had significantly lower mortality rates from HGSOC compared with women with the lowest prediagnosis dietary quality. These findings suggest that even moderate adherence to dietary guidelines prior to diagnosis may be associated with improved survival among Black women with HGSOC, the most lethal form of ovarian cancer.

Multi-metric comparison of machine learning imputation methods with application to breast cancer survival

Handling missing data in clinical prognostic studies is an essential yet challenging task. This study aimed to provide a comprehensive assessment of the effectiveness and reliability of different machine learning (ML) imputation methods across various analytical perspectives. Specifically, it focused on three distinct classes of performance metrics used to evaluate ML imputation methods: post-imputation bias of regression estimates, post-imputation predictive accuracy, and substantive model-free metrics. As an illustration, we applied data from a real-world breast cancer survival study. This comprehensive approach aimed to provide a thorough assessment of the effectiveness and reliability of ML imputation methods across various analytical perspectives. A simulated dataset with 30% Missing At Random (MAR) values was used. A number of single imputation (SI) methods - specifically KNN, missMDA, CART, missForest, missRanger, missCforest - and multiple imputation (MI) methods - specifically miceCART and miceRF - were evaluated. The performance metrics used were Gower’s distance, estimation bias, empirical standard error, coverage rate, length of confidence interval, predictive accuracy, proportion of falsely classified (PFC), normalized root mean squared error (NRMSE), AUC, and C-index scores. The analysis revealed that in terms of Gower’s distance, CART and missForest were the most accurate, while missMDA and CART excelled for binary covariates; missForest and miceCART were superior for continuous covariates. When assessing bias and accuracy in regression estimates, miceCART and miceRF exhibited the least bias. Overall, the various imputation methods demonstrated greater efficiency than complete-case analysis (CCA), with MICE methods providing optimal confidence interval coverage. In terms of predictive accuracy for Cox models, missMDA and missForest had superior AUC and C-index scores. Despite offering better predictive accuracy, the study found that SI methods introduced more bias into the regression coefficients compared to MI methods. This study underlines the importance of selecting appropriate imputation methods based on study goals and data types in time-to-event research. The varying effectiveness of methods across the different performance metrics studied highlights the value of using advanced machine learning algorithms within a multiple imputation framework to enhance research integrity and the robustness of findings.

Population-Based Study of Gastric Cancer Survival and Associations in Rural Western Honduras.

Two-thirds of global cancers occur in low/middle income countries (LMIC). Northern Central America is the largest LMIC region in the Western Hemisphere and lack cancer registries to guide cancer control. We conducted a gastric cancer survival study in rural Western Honduras, characterized as having among the highest gastric cancer incidence rates in Latin America. The cohort of incident gastric cancer diagnosed between 2002 and 2015 was studied with active follow-up with household visits. The regional gastric cancer registry was primary for case identification, with completeness examination with hospital data and national death certificates. Cox regression models were used for survival calculations. Survival follow-up was achieved in 741/774 patients (95.7%). Household interviews were conducted in 74.1% (n = 549); 65.7% were male, median age at diagnosis was 64 years, 24.5% were <55 years; 43.9% of tumors had pyloric obstruction; 45.2%, 43.2%, and 7.3% of histology was intestinal, diffuse, and mixed, respectively. A total of 24.7% patients received treatment. The 5-year survival rates were 9.9% for both males and females, 7.7% for age <45, and 7.9% for diffuse gastric cancer. Median survival time was 4.8 months [95% confidence interval (CI), 4.2-5.6]. In the final Cox regression model including age, sex, Lauren subtype, and poverty index, only treatment was significantly associated with survival (hazard ratio = 2.43, 95% CI, 1.8-3.2). Markedly low gastric cancer 5-year survival rates are observed in rural Central America. The majority of patients present with advanced disease and a minority have access to therapy. The findings have implications for cancer control in the Central America LMICs and for US Latino populations. See related commentary by Riquelme and Abnet, p. 1550.

Cancer survivorship in low-middle income countries - Does quality of life matter?

Cancer survivorship has improved in the recent years due to screening facilities, modernized treatment options and advanced cancer care in specialized centers globally. However, in low-middle-income countries cancer survivorship is not yet improved to that stature. There are multifaceted issues including delay in diagnosis, financial burden and in certain situations in appropriate treatment creates long term effects not only on patients but also on their families. Multidisciplinary approach is a limitation in the LMIC and the mental health aspects are least studies in cancer survivors. Therefore, a revised more focused and evidence based management plan along with long term quality of life issues needs to be focused in patients from LMIC.

Effects of a pilot 12-week exercise program on breast cancer survivors’ quality of life.

e12525 Background: Previous studies have demonstrated that breast cancer survivors commonly experience a decrease in quality of life including an increased risk of depression, insomnia, cancer-related fatigue, and negative body image. Several studies have shown that exercise interventions, such as yoga, Pilates, water aerobics, and strengthening exercises can improve survivors’ quality of life. We implemented a 12-week exercise program in breast cancer survivors and evaluated quality of life changes. Here we discuss our findings evaluating 13 quality of life questionnaires. Methods: We evaluated 46 participants who completed a baseline and post 12-week questionnaire assessment. All participants underwent an exercise program 3 times/week for 90 minutes/session. We calculated differences in baseline and post 12-week quality of life through 13 questionnaires: Functional Assessment of Cancer Therapy - General (FACT-G) Physical, Social/Family, Emotional, and Functional, Social Support, Insomnia Severity Index, Brief Fatigue Inventory, Patient Health Questionnaire, and Body Image after Breast Cancer (BIBCQ) Vulnerability Scale (VS), Body Stigma Scale (BSS), Limitations Scale (LS), Body Concerns Scale (BCS), Transparency Scale (TS), and Arm Concerns Scale (ACS) and assessed the intervention's efficacy by comparing the baseline and post 12-week scores using paired t-tests. Results: The difference between baseline and post 12-week quality of life are presented in the Table. 7/13 questionnaires showed statistical significance: FACT-G Physical and Functional, Insomnia Severity Index, Brief Fatigue Inventory, Patient Health Questionnaire, and BIBCQ LS and BCS. Conclusions: Our study showed improvement in metrics evaluated in breast cancer survivors who underwent the personalized exercise program. Specifically, body image was improved with exercise which further exemplifies the impact of lifestyle changes on quality of life measures and is an important adjunct to future cancer survivorship studies. Clinical trial information: NCT04013568 . [Table: see text]

The association of body composition phenotypes before chemotherapy with epithelial ovarian cancer mortality.

The association of body composition with epithelial ovarian carcinoma (EOC) mortality is poorly understood. To date, evidence suggests that high adiposity is associated with decreased mortality (an obesity paradox), but the impact of muscle on this association has not been investigated. Herein, we define associations of muscle and adiposity joint-exposure body composition phenotypes with EOC mortality. Body composition from 500 women in the Body Composition and Epithelial Ovarian Cancer Survival Study was dichotomized as normal or low skeletal muscle index (SMI), a proxy for sarcopenia, and high or low adiposity. Four phenotypes were classified as fit (normal SMI and low adiposity; reference; 16.2%), overweight or obese (normal SMI and high adiposity; 51.2%), sarcopenia and overweight or obese (low SMI and high adiposity; 15.6%), and sarcopenia or cachexia (low SMI and low adiposity; 17%). We used multivariable Cox models to estimate associations of each phenotype with mortality for EOC overall and high-grade serous ovarian carcinoma (HGSOC). Overweight or obesity was associated with up to 51% and 104% increased mortality in EOC and HGSOC [Hazard Ratio (HR)] = 1.51, 95% CI = 1.05 to 2.19 and HR = 2.04, 95% CI = 1.29 to 3.21). Sarcopenia and overweight or obesity was associated with up to 66% and 67% increased mortality in EOC and HGSOC (HR = 1.66, 95% CI = 1.13 to 2.45 and HR = 1.67, 95% CI = 1.05 to 2.68). Sarcopenia or cachexia was associated with up to 73% and 109% increased mortality in EOC and HGSOC (HR = 1.73, 95% CI = 1.14 to 2.63 and HR = 2.09, 95% CI = 1.25 to 3.50). Overweight or obesity, sarcopenia and overweight or obesity, and sarcopenia or cachexia phenotypes were each associated with increased mortality in EOC and HGSOC. Exercise and dietary interventions could be leveraged as ancillary treatment strategies for improving outcomes in the most fatal gynecological malignancy with no previously established modifiable prognostic factors.

Differences in Rural Versus Urban Patients With Prostate Cancer in Diagnosis and Treatment: An Analysis of a Population-Based Cohort.

Patients living in rural communities have greater barriers to cancer care and poorer outcomes. We hypothesized that rural patients with prostate cancer have less access and receive different treatments compared with urban patients. We used a population-based prospective cohort, the North Carolina Prostate Cancer Comparative Effectiveness and Survivorship Study, to compare differences in prostate cancer diagnosis, access to care, and treatment in patients by geographic residence. The 2013 rural-urban continuum code (RUCC) was used to determine urban (RUCC 1-3) versus rural (RUCC 4-9) location of residence. Patients with rural residence comprised 25% of the cohort (364 of 1,444); they were less likely to be White race and had lower income and educational attainment. Rural patients were more likely to have <12 cores on biopsy (47.1% v 35.7%; P < .001) and less likely (40.8% v 47.6%; P = .04) to receive multidisciplinary consultation. We observed significant differences in treatment between urban and rural patients, including rural patients receiving less active surveillance or observation (22.6% v 28.7%), especially in low-risk cancer (33.2% v 40.7%). On multivariable analysis that adjusted for patient and diagnostic factors, rural residence was associated with less use of active surveillance or observation over radical treatment (ie, surgery or radiation therapy; odds ratio, 0.49 v urban; P < .001) in patients with low-risk cancer. Patients with prostate cancer who live in rural versus urban areas experience several differences in care that are likely clinically meaningful, including fewer cores in the diagnostic biopsy, less utilization of multidisciplinary consultation, less use of active surveillance, or observation for low-risk disease. Future studies are needed to assess the efficacy of interventions in mitigating these disparities.

Avanzando Caminos (Leading Pathways): design and procedures of the Hispanic/Latino Cancer Survivorship Study.

Avanzando Caminos (Leading Pathways): The Hispanic/Latino Cancer Survivorship Cohort Study aims to examine the influence of sociocultural, medical, stress-related, psychosocial, lifestyle, behavioral, and biological factors on symptom burden, health-related quality of life, and clinical outcomes among Hispanics/Latinos who have been previously treated for cancer. Avanzando Caminos is a prospective, cohort-based study of 3000 Hispanics/Latinos who completed primary cancer treatment within the past 5 years that is representative of the general Hispanic/Latino population in the United States. Participants will complete self-report measures at baseline (time [T] 1), 6months (T2), 1year (T3), 2years (T4), 3years (T5), 4years (T6), and 5years (T7). Blood samples drawn for assessment of leukocyte gene expression, cardiometabolic markers, and genetic admixture will be collected at baseline (T1), 1year (T3), 3years (T5), and 5years (T7). Medical and cancer characteristics and clinical outcomes will be extracted from the electronic medical record and/or state cancer registry at each time point. Data analysis will include general latent variable modeling and latent growth modeling. Avanzando Caminos will fill critical gaps in knowledge in order to guide future secondary and tertiary prevention efforts to mitigate cancer disparities and optimize health-related quality of life among Hispanic/Latino cancer survivors.

St. Jude Survivorship Portal: Sharing and Analyzing Large Clinical and Genomic Datasets from Pediatric Cancer Survivors.

Childhood cancer survivorship studies generate comprehensive datasets comprising demographic, diagnosis, treatment, outcome, and genomic data from survivors. To broadly share this data, we created the St. Jude Survivorship Portal (https://survivorship.stjude.cloud), the first data portal for sharing, analyzing, and visualizing pediatric cancer survivorship data. More than 1,600 phenotypic variables and 400 million genetic variants from more than 7,700 childhood cancer survivors can be explored on this free, open-access portal. Summary statistics of variables are computed on-the-fly and visualized through interactive and customizable charts. Survivor cohorts can be customized and/or divided into groups for comparative analysis. Users can also seamlessly perform cumulative incidence and regression analyses on the stored survivorship data. Using the portal, we explored the ototoxic effects of platinum-based chemotherapy, uncovered a novel association between mental health, age, and limb amputation, and discovered a novel haplotype in MAGI3 strongly associated with cardiomyopathy specifically in survivors of African ancestry. Significance: The St. Jude Survivorship Portal is the first data portal designed to share and explore clinical and genetic data from childhood cancer survivors. The portal provides both open- and controlled-access features and will fulfill a wide range of data sharing needs of the survivorship research community and beyond. See co-corresponding author Xin Zhou discuss this research article, published simultaneously at the AACR Annual Meeting 2024: https://vimeo.com/932617204/7d99fa4958.

The choice of diagnostic modality influences the proportion of low muscle strength, low muscle mass, and sarcopenia in colorectal cancer patients

Low muscle strength, low muscle mass, and sarcopenia have a negative impact on health outcomes in colorectal cancer (CRC) patients. Different diagnostic modalities are used to identify these conditions but it is unknown how well the modalities agree. The aim of this study was to compare different diagnostic modalities by means of calculating the proportion of low muscle strength, low muscle mass, and sarcopenia in CRC patients, and to investigate the agreement for sarcopenia between the various modalities. Men and women participating in the Norwegian Dietary Guidelines and colorectal cancer Survival (CRC-NORDIET) study were included in the analyses. Cut-off values for low muscle strength, low muscle mass, and sarcopenia were defined according to the second consensus set by the European Working Group on Sarcopenia in Older People (EWGSOP2). The diagnostic modalities used to assess muscle strength were handgrip strength and the sit-to-stand test. For muscle mass, computed tomography, dual-energy X-ray absorptiometry (DXA), multi-frequency bioelectrical impedance analysis (MF-BIA), and single-frequency BIA (SF-BIA) were applied. Cohen's kappa was calculated to determine the agreement for low muscle strength and confirmed sarcopenia between diagnostic modalities. Five hundred and three men and women (54% men, mean age of 66 (range 50-80) years old) were included in the analysis. As much as 99% (n=70) of the population was identified with low muscle mass by MF-BIA, while the other modalities identified 9-49% as having low muscle mass. Handgrip strength identified a lower proportion of low muscle strength as compared with the sit-to-stand test (4% vs. 8%). When applying various combinations of diagnostic modalities for low muscle strength and low muscle mass, the proportion of sarcopenia was found to be between 0.3 and 11.4%. There was relatively poor agreement between the different diagnostic modalities with Cohen's Kappa ranging from 0.0 to 0.55, except for the agreement between SF-BIASergi and MF-BIASergi, which was 1. The proportion of low muscle strength, low muscle mass, and sarcopenia in CRC patients varied considerably depending on the diagnostic modalities used. Further studies are needed to provide modality-specific cut-off values, adjusted to sex, age and body size.

The INPHOG childhood cancer survivorship (C2S) study: Making of the Indian childhood cancer survivorship cohort

The INPHOG childhood cancer survivorship (C2S) study: Making of the Indian childhood cancer survivorship cohort

Clinically relevant body composition phenotypes are associated with distinct circulating cytokine and metabolomic milieus in epithelial ovarian cancer patients.

Preclinical evidence suggests that host obesity is associated with tumor progression due to immuno-metabolic dysfunction, but the impact of obesity on immunity and clinical outcomes in patients is poorly understood, with some studies suggesting an obesity paradox. We recently reported that high-adiposity and low-muscle body composition phenotypes are associated with striking increases in epithelial ovarian cancer (EOC) mortality and we observed no evidence of an obesity paradox. However, whether at-risk versus optimal body composition phenotypes are associated with distinct immuno-metabolic milieus remains a fundamental gap in knowledge. Herein, we defined differentially abundant circulating immuno-metabolic biomarkers according to body composition phenotypes in EOC. Muscle and adiposity cross-sectional area (cm2) was assessed using CT images from 200 EOC patients in The Body Composition and Epithelial Ovarian Cancer Survival Study at Roswell Park. Adiposity was dichotomized as low versus high; patients with skeletal muscle index (SMI) <38.5 (muscle cm2/height m2) were classified as low SMI (sarcopenia). Joint-exposure phenotypes were categorized as: Fit (normal SMI/low-adiposity), Overweight/Obese (normal SMI/high-adiposity), Sarcopenia/Obese (low SMI/high adiposity), and Sarcopenia/Cachexia (low SMI/low-adiposity). Treatment-naïve serum samples were assessed using Biocrates MxP Quant 500 for targeted metabolomics and commercially available Luminex kits for adipokines and Th1/Th2 cytokines. Limma moderated T-tests were used to identify differentially abundant metabolites and cytokines according to body composition phenotypes. Patients with 'risk' phenotypes had significantly increased abundance of metabolites and cytokines that were unique according to body composition phenotype. Specifically, the metabolites and cytokines in increased abundance in the at-risk phenotypes are implicated in immune suppression and tumor progression. Conversely, increased abundance of lauric acid, IL-1β, and IL-2 in the Fit phenotype was observed, which have been previously implicated in tumor suppression and anti-tumor immunity. In this pilot study, we identified several significantly differentially abundant metabolites according to body composition phenotypes, confirming that clinically significant joint-exposure body composition phenotypes are also biologically distinct. Although we observed evidence that at-risk phenotypes were associated with increased abundance of immuno-metabolic biomarkers indicated in immune suppression, additional confirmatory studies focused on defining the link between body composition and immune cell composition and spatial relationships in the EOC tumor microenvironment are warranted.

Abstract B068: Predictors of estrogen receptor staining levels in African American women with ER+ breast cancer in the Detroit Research on Cancer Survivors study

Abstract Introduction: Breast cancer incidence in African American women (AAW) in the U.S. is now equal to that in European American women (EAW). Despite having the highest survival rates of all breast cancer subtypes, AAW are nearly twice as likely to die from hormone receptor-positive (HR+) disease compared to EAW. ER+/HER2- breast cancer is a heterogeneous subtype, with tumors showing anywhere from 1-100% ER staining by immunohistochemistry. AAW are also more likely to have a lower proportion of HR+ cells within their breast tumor compared to EAW, and tumors with lower proportions of HR+ cells are associated with worse survival. While this is consistent with the fact that AAW are more likely to have aggressive breast cancer subtypes like triple negative breast cancer, our understanding of epidemiologic risk factors associated with various levels of ER staining is limited particularly among scientifically underrepresented populations. Therefore, our objective was to identify predictors associated with estrogen receptor staining levels in AAW. Methods: Questionnaire and population-based registry data from 748 female HR+ breast cancer survivors enrolled in the Detroit Research on Cancer Survivors (ROCS) study were analyzed. Risk factors of interest included self-reported demographics, socioeconomic characteristics, and health behaviors. Individual and combined estrogen receptor (ER) and progesterone (PR) percent staining levels were obtained from medical record review. A combined hormone report (HR) staining level variable was created based on the maximum percent staining among ER and PR. Associations between risk factors and HR staining levels were evaluated using chi-squared tests, and univariable and multivariable linear regression. An alpha value of 0.05 was set to determine statistical significance. Results: In our cohort, a majority of patients (86.6%), had tumors that were characterized as high HR staining (&amp;gt;90% of tumor cells HR+). A small percentage of tumors were found to be in the low (1-10% HR+: 6.6%) or medium (11-90% HR+: 6.8%) staining categories. When looking at each variable individually, we saw that demographic and medical history variables were associated with percent HR staining levels, including, age at diagnosis (beta=0.038,p&amp;lt;0.001), diabetes (beta=0.052,p= 0.03), high blood pressure (beta=0.060,p= 0.0037) and high cholesterol (beta=0.052,p= 0.028). When stratified by HER2 status, these associations remained similar in effect size and statistical significance only among HER2- patients. In a multivariable model, percent HR staining was associated with age at diagnosis (beta=0.002,p= 0.031), HER2+ status (beta= -0.15, p&amp;lt;0.001), marital status (beta= -0.016,p= 0.084) and nulliparity (b=0.073,p=0.012). Conclusions: Our findings identify multiple risk factors that are associated with weakly positive ER tumors. As AAW die more frequently from ER+/HER- weak breast cancers, these findings have potential application in improving future screenings and providing optimal therapeutics, resulting in a better prognosis among this cohort. Citation Format: Abigail M. Fielder, Jaclyn Kyko, Mrudula Nair, Julie Ruterbusch, David Gorski, Michael Simon, Lauren Hamel, Ann G. Schwartz, Kristen S. Purrington. Predictors of estrogen receptor staining levels in African American women with ER+ breast cancer in the Detroit Research on Cancer Survivors study [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 B068.

Housing instability and psychological distress in African American cancer survivors: findings from the Detroit Research on Cancer Survivors study.

As health care systems seek to screen for and address housing instability in patient populations, robust evidence linking unstable housing to patient-reported outcomes is needed. Housing instability may increase psychological distress in cancer survivors, potentially more so among African American cancer survivors who are also likely to experience disproportionate burden of housing instability. The purpose of this analysis was to estimate associations between housing instability and psychological distress in African Americans diagnosed with cancer. We included survey responses from 2875 African American cancer survivors in the Detroit Research on Cancer Survivors (ROCS) study. We examined how housing instability at enrollment, using an item adapted from the Health Leads Screening Toolkit, related to psychological distress at enrollment, using Patient Reported Outcomes Measurement System (PROMIS) 4-item anxiety and depression short forms. Linear regression models adjusted for sociodemographic factors were used to estimate associations overall and stratified by stage at diagnosis. Approximately 12% of participants reported being unstably housed. Housing instability was associated with significant differences in PROMIS scores for both anxiety (difference: 6.79; 95% CI: 5.57-8.01) and depression (difference: 6.16; 95% CI: 4.99-7.34). We did not find meaningful differences stratifying by disease stage. Housing instability was experienced by over a tenth of this cohort of African American cancer survivors and was related to statistically and clinically meaningful differences in psychological distress even following adjustment for sociodemographics. These findings provide evidence supporting screening of housing instability in cancer survivors, especially those from medically underserved populations.

Breast Cancer: 20-Year Comparative Mortality and Survival Analysis by Age, Sex, Race/Ethnicity, Stage, Grade, Disease Duration, Selected ICD-O-3 Oncophenotypes, and Cohort Entry Time-Period.

Breast cancer remains the most common non-cutaneous malignancy in women in both Europe and the United States and the second leading cause of cancer-related deaths. In this breast cancer mortality and survival study, a US retrospective population-based analysis of 656,501 microscopically confirmed breast cancer cases, 1975-2019, data is derived from the NCI Surveillance Epidemiology & End Results Program, SEER*Stat 8.4.0.1.

Association between chronic pain and quality of life in long-term breast cancer survivors: a prospective analysis.

Pain is a leading cause of disability worldwide and is highly prevalent among breast cancer survivors. Pain and quality of life (QOL) are associated in breast cancer patients undergoing active treatment, but little is known about the relationship between the two in long-term survivors. We evaluated associations between pain information collected during a 5-year post-diagnosis follow-up survey and QOL assessed by the SF-36 during a 10-year post-diagnosis survey for 2828 participants in the Shanghai Breast Cancer Survival Study. The mean overall QOL score was 78.7 for the entire study population and decreased as pain severity and frequency measured at the 5-year timepoint increased (none: 81.9, mild: 75.9, moderate/severe: 70.4, infrequent: 76.7, frequent: 72.3; P < 0.001). Significant inverse associations were found between pain and all QOL domains, including pain at 10-years post-diagnosis after multivariate adjustments. Concurrent pain was significantly and strongly associated with QOL. Most of the associations between 5-years post-diagnosis pain and QOL at 10-years post-diagnosis persisted after further adjustment for concurrent pain. Pain is associated prospectively and concurrently with poor QOL among long-term breast cancer survivors. Programs to manage pain are needed to improve QOL among breast cancer survivors.

Neurocognitive outcomes in adult survivors of neuroblastoma: A report from the Childhood Cancer Survivor Study.

Despite survival improvements, there is a paucity of data on neurocognitive outcomes in neuroblastoma survivors. This study addresses this literature gap. Neurocognitive impairments in survivors were compared to sibling controls from the Childhood Cancer Survivor Study (CCSS) using the CCSS Neurocognitive Questionnaire. Impaired emotional regulation, organization, task efficiency, and memory defined as scores ≥90th percentile of sibling norms. Modified Poisson regression models evaluated associations with treatment exposures, era of diagnosis, and chronic conditions. Analyses were stratified by age at diagnosis (≤1 and>1year) as proxy for lower versus higher risk disease. Survivors (N=837; median [range] age, 25 [17-58] years, age diagnosed, 1 [0-21] years) were compared to sibling controls (N=728; age, 32 [16-43] years). Survivors had higher risk of impaired task efficiency (≤1year relative risk [RR], 1.48; 95% confidence interval [CI], 1.08-2.03; >1year RR, 1.58; 95% CI, 1.22-2.06) and emotional regulation (≤1year RR, 1.51; 95% CI, 1.07-2.12; >1year RR,1.44; 95% CI, 1.06-1.95). Impaired task efficiency associated with platinum exposure (≤1year RR, 1.74; 95% CI, 1.01-2.97), hearing loss (≤1year RR,1.95; 95% CI,1.26-3.00; >1year RR,1.56; 95% CI,1.09-2.24), cardiovascular (≤1year RR,1.83; 95% CI,1.15-2.89; >1year RR,1.74; 95% CI,1.12-2.69), neurologic (≤1year RR,2.00; 95% CI,1.32-3.03; >1year RR,2.29; 95% CI,1.64-3.21), and respiratory (>1year RR,2.35; 95% CI,1.60-3.45) conditions. Survivors ≤1year; female sex (RR,1.54; 95% CI,1.02-2.33), cardiovascular (RR,1.71; 95% CI,1.08-2.70) and respiratory (RR,1.99; 95% CI,1.14-3.49) conditions associated impaired emotional regulation. Survivors were less likely to be employed full-time (p<.0001), graduate college (p=.035), and live independently (p<.0001). Neuroblastoma survivors report neurocognitive impairment impacting adult milestones. Identified health conditions and treatment exposures can be targeted to improve outcomes. Survival rates continue to improve in patients with neuroblastoma. There is a lack of information regarding neurocognitive outcomes in neuroblastoma survivors; most studies examined survivors of leukemia or brain tumors. In this study, 837 adult survivors of childhood neuroblastoma were compared to siblings from the Childhood Cancer Survivorship Study. Survivors had a 50% higher risk of impairment with attention/processing speed (task efficiency) and emotional reactivity/frustration tolerance (emotional regulation). Survivors were less likely to reach adult milestones such as living independently. Survivors with chronic health conditions are at a higher risk of impairment. Early identification and aggressive management of chronic conditions may help mitigate the level of impairment.

Abstract 1911: Racial and ethnic disparities in comorbidity burden among ovarian cancer patients

Abstract Background: Ovarian cancer is the most lethal gynecologic cancer and the fifth leading cause of cancer-related mortality among women in the US. Racial and ethnic disparities in ovarian cancer outcomes are well-documented, wherein non-Hispanic Black (NHB) women are 40% more likely to die from their disease compared with non-Hispanic White (NHW) women. However, the causes of these disparities are complex and multifactorial. Comorbidities are known to differ by race and ethnicity and have the potential to affect treatment and cancer outcomes. Our objective was to characterize the comorbidity burden by race and ethnicity in a large cohort of ovarian cancer patients. Methods: The electronic health record-based Kaiser Permanente Research on Ovarian Cancer Survival (KP-ROCS) study includes individuals ≥18 years of age diagnosed with ovarian cancer between 2000 and 2018. Comorbidities (e.g., cardiovascular disease, type II diabetes, hypertension, liver disease) were identified using ICD-9/10 and procedural codes in the five years preceding the individual’s ovarian cancer diagnosis. We present the distribution of individual comorbidities as well as the Charlson Comorbidity Index (CCI) across racial and ethnic groups (non-Hispanic Asian, Hispanic, NHB, and NHW). Results: Of 4,910 ovarian cancer patients in the KP-ROCS cohort, 625 (13%) are non-Hispanic Asian, 605 (12%) are Hispanic, 268 (5.5%) are NHB, and 3,321 (74%) are NHW. The mean age at diagnosis was lowest for non-Hispanic Asian (57 years, standard deviation [SD] 14), followed by Hispanic (60 years, SD=13), NHB (63 years, SD=13), and NHW (65 years, SD=13) ovarian cancer patients. At diagnosis, NHB and Hispanic ovarian cancer patients were more likely to present with diabetes than non-Hispanic Asian and NHW women (NHB=21%, Hispanic=21% vs non-Hispanic Asian=16%, NHW=12%). Cardiovascular disease was more common among NHB women compared with other racial and ethnic groups (NHB=41% vs. Hispanic=28%, non-Hispanic Asian=26%, NHW=32%). Moreover, the net burden of comorbidities (CCI=3+) was higher among NHB women compared with other racial and ethnic groups (NHB=30% vs non-Hispanic Asian=17%, Hispanic=23%, NHW=21%). Conclusions: Our preliminary data indicate that NHB ovarian cancer patients are more likely to present with comorbidities at the time of their ovarian cancer diagnosis compared with other racial and ethnic groups. These comorbid conditions may inhibit the ability to tolerate surgery and systemic therapies, contributing to racial and ethnic disparities in outcomes. Future analyses will seek to address these questions. Citation Format: Lindsay Jane Collin, Valerie Lee, Jia Li, Carola Sanchez Diaz, Bethan Powell, Juraj Kavecansky, Scarlett Lin Gomez, Jennifer Doherty, Elisa V. Bandera, Larry Kushi. Racial and ethnic disparities in comorbidity burden among ovarian cancer patients [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 1911.

Comparison of Machine Learning Methods in the Study of Cancer Survivors' Return to Work: An Example of Breast Cancer Survivors with Work-Related Factors in the CONSTANCES Cohort.

Machine learning (ML) methods showed a higher accuracy in identifying individuals without cancer who were unable to return to work (RTW) compared to the classical methods (e.g. logistic regression models). We therefore aim to discuss the value of these methods in relation to RTW for cancer survivors. Breast cancer (BC) survivors who were working at diagnosis within the CONSTANCES cohort were included in the study. RTW was assessed five years after the BC diagnosis (early retirement was considered as non-RTW). Age and occupation at diagnosis, and physical occupational job exposures assessed using the Job Exposure Matrix, JEM-CONSTANCES, were evaluated as predictors of RTW five years after BC diagnosis. The following four ML methods were used: (i) k-nearest neighbors; (ii) random forest; (iii) neural network; and (iv) elastic net. The training sample included 683 BC survivors (RTW: 85.7%), and the test sample 171 (RTW: 85.4%). The elastic net method had the best results despite low sensitivity (accuracy = 76.6%; sensitivity = 31.7%; specificity = 90.8%), and the random forest model was the most accurate (= 79.5%) but also the least sensitive (= 14.3%). This study takes a first step towards opening up new possibilities for identifying the occupational determinants of cancer survivors' RTW. Further work, including a larger sample size, and more predictor variables, is now needed.