Emotional and functional well-being in long-term breast cancer survivorship.

PURPOSE: Emotional and functional well-being (EWB and FWB) are important components of mental health and quality of life. This study aims to evaluate long-term EWB and FWB in breast cancer (BC) survivors. METHODS: The Carolina Breast Cancer Study Phase 3 oversampled Black and younger (< 50 years in age) women so that they each represent approximately 50% of the study population and assessed participants' EWB and FWB with the Functional Assessment of Cancer Therapy-Breast (FACT-B) at 5- (baseline), 25-, and 84-months post diagnosis. Multinomial logit models were used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for associations between demographic and clinical characteristics and well-being change relative to baseline. RESULTS: Among 2,781 participants with BC, average EWB and FWB improved with time since diagnosis. Persistent FWB decrements were associated with Black race [OR 1.4 (95% CI 1.2-1.7) and 1.3 (95% CI 1.1-1.6), at 25-months and 84-months respectively], older age [OR 1.4 (95% CI 1.1-1.7) and 1.5 (95% CI 1.2-1.8), respectively], no chemotherapy, and recurrence [OR 2.9 (95% CI 1.8-4.8) and 3.1 (95% CI 2.1-4.6), respectively]. EWB decrements were associated with advanced stage and recurrence. Decrements in combined (FWB+EWB) well-being were associated with recurrence at both follow-up survey timepoints [ORs 4.7 (95% CI 2.7-8.0) and 4.3 (95% CI 2.8-6.6), respectively]. CONCLUSIONS: Long-term well-being varies by demographics and clinical features, with Black women and women with aggressive disease at greatest risk of long-term decrements.

BIRC5 expression by race, age and clinical factors in breast cancer patients.

PURPOSE: Survivin/BIRC5 is a proliferation marker that is associated with poor prognosis in breast cancer and an attractive therapeutic target. However, BIRC5 has not been well studied among racially diverse populations where aggressive breast cancers are prevalent. EXPERIMENTAL DESIGN: We studied BIRC5 expression in association with clinical and demographic variables and as a predictor of recurrence in 2174 participants in the Carolina Breast Cancer Study (CBCS), a population-based study that oversampled Black (n = 1113) and younger (< 50 years; n = 1137) participants with breast cancer. For comparison, similar analyses were conducted in The Cancer Genome Atlas [TCGA N = 1094, Black (n = 183), younger (n = 295)]. BIRC5 was evaluated as a continuous and categorical variable (highest quartile vs. lower three quartiles). RESULTS: Univariate, continuous BIRC5 expression was higher in breast tumors from Black women relative to non-Black women in both estrogen receptor (ER)-positive and ER-negative tumors and in analyses stratified by stage (i.e., within Stage I, Stage II, and Stage III/IV tumors). Within CBCS and TCGA, BIRC5-high was associated with young age (< 50 years) and Black race, as well as hormone receptor-negative tumors, non-Luminal A PAM50 subtypes, advanced stage, and larger tumors (> 2 cm). Relative to BIRC5-low, BIRC5-high tumors were associated with poor 5-year recurrence-free survival (RFS) among ER-positive tumors, both in unadjusted models [HR (95% CI): 2.7 (1.6, 4.6)] and after adjustment for age and stage [Adjusted HR (95% CI): 1.87 (1.07, 3.25)]. However, this relationship was not observed among ER-negative tumors [Crude HR (95% CI): 0.7 (0.39, 1.2); Adjusted HR (95% CI): 0.67 (0.37, 1.2)]. CONCLUSION: Black and younger women with breast cancer have a higher burden of BIRC5-high tumors than older and non-Black women. Emerging anti-survivin treatment strategies may be an important future direction for equitable breast cancer outcomes.

Diffsig: Associating Risk Factors With Mutational Signatures.

BACKGROUND: Somatic mutational signatures elucidate molecular vulnerabilities to therapy and therefore detecting signatures and classifying tumors with respect to signatures has clinical value. However, identifying the etiology of the mutational signatures remains a statistical challenge, with both small sample sizes and high variability in classification algorithms posing barriers. As a result, few signatures have been strongly linked to particular risk factors. METHODS: Here we develop a statistical model, Diffsig, for estimating the association of one or more continuous or categorical risk factors with DNA mutational signatures. Diffsig takes into account the uncertainty associated with assigning signatures to samples as well as multiple risk factors' simultaneous effect on observed DNA mutations. RESULTS: We applied Diffsig to breast cancer data to assess relationships between five established breast-relevant mutational signatures and etiologic variables, confirming known mechanisms of cancer development. In simulation, our model was capable of accurately estimating expected associations in a variety of contexts. CONCLUSIONS: Diffsig allows researchers to quantify and perform inference on the associations of risk factors with mutational signatures. IMPACT: We expect Diffsig to provide more robust associations of risk factors with signatures to lead to better understanding of the tumor development process and improved models of tumorigenesis.

Disparities in OncotypeDx Testing and Subsequent Chemotherapy Receipt by Geography and Socioeconomic Status.

BACKGROUND: OncotypeDx is a prognostic and predictive genomic assay used in early-stage hormone receptor positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer. It is used to inform adjuvant chemotherapy decisions, but not all eligible women receive testing. We aimed to assess variation in testing by demographics and geography, and to determine whether testing was associated with chemotherapy. METHODS: For 1,615 women in the Carolina Breast Cancer Study with HR+/HER2-, Stage I-II tumors, we estimated prevalence differences (PDs) and 95% CIs for receipt of OncotypeDx genomic testing in association with and sociodemographic characteristics. We assessed associations between testing and chemotherapy receipt overall and by race. Finally, we calculated the proportion of eligible women receiving OncotypeDx by county-level rurality, census tract-level socioeconomic status, and Area Health Education Center (AHEC) regions. RESULTS: 38% (N=609) of potentially eligible women were tested, with lower testing prevalences in Black (31%; PD = -11%, 95% CI: -16%, 6%) and low-income women (24%; PD = -20%, 95% CI: -29%, -11%) relative to non-Black and higher income women. Urban participants were less likely to be tested than rural participants, though this association varied by region. Among women with low genomic risk tumors, tested participants were 29% less likely to receive chemotherapy than untested participants (95% CI: -40%, -17%). Racial differences in chemotherapy were restricted to untested women. CONCLUSIONS: Both individual and area-level socioeconomics predict likelihood of OncotypeDx testing. IMPACT: Variable adoption of OncotypeDx by socioeconomics and across geographic settings may contribute to excess chemotherapy among HR+/HER2- patients.

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.

A systematic scoping review of latent class analysis applied to accelerometry-assessed physical activity and sedentary behavior.

BACKGROUND: Latent class analysis (LCA) identifies distinct groups within a heterogeneous population, but its application to accelerometry-assessed physical activity and sedentary behavior has not been systematically explored. We conducted a systematic scoping review to describe the application of LCA to accelerometry. METHODS: Comprehensive searches in PubMed, Web of Science, CINHAL, SPORTDiscus, and Embase identified studies published through December 31, 2021. Using Covidence, two researchers independently evaluated inclusion criteria and discrepancies were resolved by consensus. Studies with LCA applied to accelerometry or combined accelerometry/self-reported measures were selected. Data extracted included study characteristics and both accelerometry and LCA methods. RESULTS: Of 2555 papers found, 66 full-text papers were screened, and 12 papers (11 cross-sectional, 1 cohort) from 8 unique studies were included. Study sample sizes ranged from 217-7931 (mean 2249, standard deviation 2780). Across 8 unique studies, latent class variables included measures of physical activity (100%) and sedentary behavior (75%). About two-thirds (63%) of the studies used accelerometry only and 38% combined accelerometry and self-report to derive latent classes. The accelerometer-based variables in the LCA model included measures by day of the week (38%), weekday vs. weekend (13%), weekly average (13%), dichotomized minutes/day (13%), sex specific z-scores (13%), and hour-by-hour (13%). The criteria to guide the selection of the final number of classes and model fit varied across studies, including Bayesian Information Criterion (63%), substantive knowledge (63%), entropy (50%), Akaike information criterion (50%), sample size (50%), Bootstrap likelihood ratio test (38%), and visual inspection (38%). The studies explored up to 5 (25%), 6 (38%), or 7+ (38%) classes, ending with 3 (50%), 4 (13%), or 5 (38%) final classes. CONCLUSIONS: This review explored the application of LCA to physical activity and sedentary behavior and identified areas of improvement for future studies leveraging LCA. LCA was used to identify unique groupings as a data reduction tool, to combine self-report and accelerometry, and to combine different physical activity intensities and sedentary behavior in one LCA model or separate models.

Understanding mechanisms of racial disparities in breast cancer: an assessment of screening and regular care in the Carolina Breast Cancer Study.

PURPOSE: Screening history influences stage at detection, but regular preventive care may also influence breast tumor diagnostic characteristics. Few studies have evaluated healthcare utilization (both screening and primary care) in racially diverse screening-eligible populations. METHODS: This analysis included 2,058 women age 45-74 (49% Black) from the Carolina Breast Cancer Study, a population-based cohort of women diagnosed with invasive breast cancer between 2008 and 2013. Screening history (threshold 0.5 mammograms per year) and pre-diagnostic healthcare utilization (i.e. regular care, based on responses to "During the past ten years, who did you usually see when you were sick or needed advice about your health?") were assessed as binary exposures. The relationship between healthcare utilization and tumor characteristics were evaluated overall and race-stratified. RESULTS: Among those lacking screening, Black participants had larger tumors (5 + cm) (frequency 19.6% vs 11.5%, relative frequency difference (RFD) = 8.1%, 95% CI 2.8-13.5), but race differences were attenuated among screening-adherent participants (10.2% vs 7.0%, RFD = 3.2%, 0.2-6.2). Similar trends were observed for tumor stage and mode of detection (mammogram vs lump). Among all participants, those lacking both screening and regular care had larger tumors (21% vs 8%, RR = 2.51, 1.76-3.56) and advanced (3B +) stage (19% vs 6%, RR = 3.15, 2.15-4.63) compared to the referent category (screening-adherent and regular care). Under-use of regular care and screening was more prevalent in socioeconomically disadvantaged areas of North Carolina. CONCLUSIONS: Access to regular care is an important safeguard for earlier detection. Our data suggest that health equity interventions should prioritize both primary care and screening.

Patterns of chemotherapy receipt among patients with hormone receptor-positive, HER2-negative breast cancer.

BACKGROUND: Breast cancer chemotherapy utilization not only may differ by race and age, but also varies by genomic risk, tumor characteristics, and patient characteristics. Studies in demographically diverse populations with both clinical and genomic data are necessary to understand potential disparities by race and age. METHODS: In the Carolina Breast Cancer Study Phase 3 (2008-2013), chemotherapy receipt (yes/no) and regimen type were assessed in association with age and race among hormone receptor (HR) positive and HER2-negative tumors (n = 1862). Odds ratios were estimated for the association between demographic factors and chemotherapy receipt. RESULTS: Monotonic decreases in frequency of adjuvant chemotherapy receipt were observed over time during the study period, while neoadjuvant chemotherapy was stable. Younger age was associated with chemotherapy receipt (OR [95% CI]: 2.9 [2.4, 3.6]) and with anthracycline-based regimens (OR [95% CI]: 1.7 [1.3, 2.4]). Participants who had Medicaid (OR [95% CI]: 1.8 [1.3, 2.5]), lived in rural settings (OR [95% CI]: 1.4 [1.0, 2.0]), or were Black (OR [95% CI]: 1.5 [1.2, 1.8]) had slightly higher odds of chemotherapy, but these associations were non-significant with adjustment for stage and grade. Associations between younger age and chemotherapy receipt were strongest among women who did not receive genomic testing. CONCLUSIONS: While race was not strongly associated with chemotherapy receipt, younger age remains a strong predictor of chemotherapy receipt, even with adjustment for clinical factors and among women who receive genomic testing.

Predicting early breast cancer recurrence from histopathological images in the Carolina Breast Cancer Study.

Approaches for rapidly identifying patients at high risk of early breast cancer recurrence are needed. Image-based methods for prescreening hematoxylin and eosin (H&E) stained tumor slides could offer temporal and financial efficiency. We evaluated a data set of 704 1-mm tumor core H&E images (2-4 cores per case), corresponding to 202 participants (101 who recurred; 101 non-recurrent matched on age and follow-up time) from breast cancers diagnosed between 2008-2012 in the Carolina Breast Cancer Study. We leveraged deep learning to extract image information and trained a model to identify recurrence. Cross-validation accuracy for predicting recurrence was 62.4% [95% CI: 55.7, 69.1], similar to grade (65.8% [95% CI: 59.3, 72.3]) and ER status (66.3% [95% CI: 59.8, 72.8]). Interestingly, 70% (19/27) of early-recurrent low-intermediate grade tumors were identified by our image model. Relative to existing markers, image-based analyses provide complementary information for predicting early recurrence.

From Race to Racism and Disparities to Equity: An Actionable Biopsychosocial Approach to Breast Cancer Outcomes.

PURPOSE: Racial disparities in outcomes of breast cancer in the United States have widened over more than 3 decades, driven by complex biologic and social factors. In this review, we summarize the biological and social narratives that have shaped breast cancer disparities research across different scientific disciplines in the past, explore the underappreciated but crucial ways in which these 2 strands of the breast cancer story are interwoven, and present 5 key strategies for creating transformative interdisciplinary research to achieve equity in breast cancer treatment and outcomes. DESIGN: We first review the key differences in tumor biology in the United States between patients racialized as Black versus White, including the overrepresentation of triple-negative breast cancer and differences in tumor histologic and molecular features by race for hormone-sensitive disease. We then summarize key social factors at the interpersonal, institutional, and social structural levels that drive inequitable treatment. Next, we explore how biologic and social determinants are interwoven and interactive, including historical and contemporary structural factors that shape the overrepresentation of triple-negative breast cancer among Black Americans, racial differences in tumor microenvironment, and the complex interplay of biologic and social drivers of difference in outcomes of hormone receptor positive disease, including utilization and effectiveness of endocrine therapies and the role of obesity. Finally, we present 5 principles to increase the impact and productivity of breast cancer equity research. RESULTS: We find that social and biologic drivers of breast cancer disparities are often cyclical and are found at all levels of scientific investigation from cells to society. To break the cycle and effect change, we must acknowledge and measure the role of structural racism in breast cancer outcomes; frame biologic, psychosocial, and access factors as interwoven via mechanisms of cumulative stress, inflammation, and immune modulation; take responsibility for the impact of representativeness (or the lack thereof) in genomic and decision modeling on the ability to accurately predict the outcomes of Black patients; create research that incorporates the perspectives of people of color from inception to implementation; and rigorously evaluate innovations in equitable cancer care delivery and health policies. CONCLUSIONS: Innovative, cross-disciplinary research across the biologic and social sciences is crucial to understanding and eliminating disparities in breast cancer outcomes.

Molecular features of androgen-receptor low, estrogen receptor-negative breast cancers in the Carolina breast cancer study.

PURPOSE: Androgen receptor (AR) expression is absent in 40-90% of estrogen receptor (ER)-negative breast cancers. The prognostic value of AR in ER-negative patients and therapeutic targets for patients absent in AR remains poorly explored. METHODS: We used an RNA-based multigene classifier to identify AR-low and AR-high ER-negative participants in the Carolina Breast Cancer Study (CBCS; N = 669) and The Cancer Genome Atlas (TCGA; N = 237). We compared AR-defined subgroups by demographics, tumor characteristics, and established molecular signatures [PAM50 risk of recurrence (ROR), homologous recombination deficiency (HRD), and immune response]. RESULTS: AR-low tumors were more prevalent among younger (RFD = + 10%, 95% CI = 4% to 16%) participants in CBCS and were associated with HER2 negativity (RFD = - 35%, 95% CI = - 44% to - 26%), higher grade (RFD = + 17%, 95% CI = 8% to 26%), and higher risk of recurrence scores (RFD = + 22%, 95% CI = 16.1% to 28%), with similar results in TCGA. The AR-low subgroup was strongly associated with HRD in CBCS (RFD = + 33.3%, 95% CI = 23.8% to 43.2%) and TCGA (RFD = + 41.5%, 95% CI = 34.0% to 48.6%). In CBCS, AR-low tumors had high adaptive immune marker expression. CONCLUSION: Multigene, RNA-based low AR expression is associated with aggressive disease characteristics as well as DNA repair defects and immune phenotypes, suggesting plausible precision therapies for AR-low, ER-negative patients.

Identifying patient profiles of disparate care in resectable pancreas cancer using latent class analysis.

BACKGROUND AND OBJECTIVES: Disparities in pancreas cancer care are multifactorial, but factors are often examined in isolation. Research that integrates these factors in a single conceptual framework is lacking. We use latent class analysis (LCA) to evaluate the association between intersectionality and patterns of care and survival in patients with resectable pancreas cancer. METHODS: LCA was used to identify demographic profiles in resectable pancreas cancer (n = 140 344) diagnosed from 2004 to 2019 in the National Cancer Database (NCDB). LCA-derived patient profiles were used to identify differences in receipt of minimum expected treatment (definitive surgery), optimal treatment (definitive surgery and chemotherapy), time to treatment, and overall survival. RESULTS: Minimum expected treatment (hazard ratio [HR] 0.69, 95% confidence interval [CI]: 0.65, 0.75) and optimal treatment (HR 0.58, 95% CI: 0.55, 0.62) were associated with improved overall survival. Seven latent classes were identified based on age, race/ethnicity, and socioeconomic status (SES) attributes (zip code-linked education and income, insurance, geography). Compared to the referent group (≥65 years + White + med/high SES), the ≥65 years + Black profile had the longest time-to-treatment (24 days vs. 28 days) and lowest odds of receiving minimum (odds ratio [OR] 0.67, 95% CI: 0.64, 0.71) or optimal treatment (OR 0.76, 95% CI: 0.72, 0.81). The Hispanic patient profile had the lowest median overall survival-55.3 months versus 67.5 months. CONCLUSIONS: Accounting for intersectionality in the NCDB resectable pancreatic cancer patient cohort identifies subgroups at higher risk for inequities in care. LCA demonstrates that older Black patients and Hispanic patients are at particular risk for being underserved and should be prioritiz for directed interventions.

Reproducibility and intratumoral heterogeneity of the PAM50 breast cancer assay.

BACKGROUND: The PAM50 assay is used routinely in clinical practice to determine breast cancer prognosis and management; however, research assessing how technical variation and intratumoral heterogeneity contribute to misclassification and reproducibility of these tests is limited. METHODS: We evaluated the impact of intratumoral heterogeneity on the reproducibility of results for the PAM50 assay by testing RNA extracted from formalin-fixed paraffin embedded breast cancer blocks sampled at distinct spatial locations. Samples were classified according to intrinsic subtype (Luminal A, Luminal B, HER2-enriched, Basal-like, or Normal-like) and risk of recurrence with proliferation score (ROR-P, high, medium, or low). Intratumoral heterogeneity and technical reproducibility (replicate assays on the same RNA) were assessed as percent categorical agreement between paired intratumoral and replicate samples. Euclidean distances between samples, calculated across the PAM50 genes and the ROR-P score, were compared for concordant vs. discordant samples. RESULTS: Technical replicates (N = 144) achieved 93% agreement for ROR-P group and 90% agreement on PAM50 subtype. For spatially distinct biological replicates (N = 40 intratumoral replicates), agreement was lower (81% for ROR-P and 76% for PAM50 subtype). The Euclidean distances between discordant technical replicates were bimodal, with discordant samples showing higher Euclidian distance and biologic heterogeneity. CONCLUSION: The PAM50 assay achieved very high technical reproducibility for breast cancer subtyping and ROR-P, but intratumoral heterogeneity is revealed by the assay in a small proportion of cases.

Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population.

Markers of genomic instability, including TP53 status and homologous recombination deficiency (HRD), are candidate biomarkers of immunogenicity and immune-mediated survival, but little is known about the distribution of these markers in large, population-based cohorts of racially diverse patients with breast cancer. In prior clinical trials, DNA-based approaches have been emphasized, but recent data suggest that RNA-based assessment can capture pathway differences conveniently and may be streamlined with other RNA-based genomic risk scores. Thus, we used RNA expression to study genomic instability (HRD and TP53 pathways) in context of the breast cancer immune microenvironment in three datasets (total n = 4,892), including 1,942 samples from the Carolina Breast Cancer Study, a population-based study that oversampled Black (n = 1,026) and younger women (n = 1,032). Across all studies, 36.9% of estrogen receptor (ER)-positive and 92.6% of ER-negative breast cancer had presence of at least one genomic instability signature. TP53 and HRD status were significantly associated with immune expression in both ER-positive and ER-negative breast cancer. RNA-based genomic instability signatures were associated with higher PD-L1, CD8 T-cell marker, and global and multimarker immune cell expression. Among tumors with genomic instability signatures, adaptive immune response was associated with improved recurrence-free survival regardless of ER status, highlighting genomic instability as a candidate marker for predicting immunotherapy response. Leveraging a convenient, integrated RNA-based approach, this analysis shows that genomic instability interacts with immune response, an important target in breast cancer overall and in Black women who experience higher frequency of TP53 and HR deficiency. Significance: Despite promising advances in breast cancer immunotherapy, predictive biomarkers that are valid across diverse populations and breast cancer subtypes are needed. Genomic instability signatures can be coordinated with other RNA-based scores to define immunogenic breast cancers and may have value in stratifying immunotherapy trial participants.

Discrimination between Precancerous Gastric Lesions and Gastritis Using a Gastric Cancer Risk Stratification Model.

BACKGROUND: Seropositivity to certain Helicobacter pylori proteins may affect development of gastric lesions that could become cancerous. Previously, we developed a model of gastric cancer risk including gender, age, HP0305 sero-positivity, HP1564 sero-positivity, UreA antibody titer and serologically defined chronic atrophic gastritis (termed: "Lasso model"). METHODS: We evaluated the Lasso model's ability to discriminate individuals with precancerous gastric lesions (n=320) from individuals with superficial or mild atrophic gastritis (n=226) in Linqu County, China, a population at high risk for gastric cancer. We also compared its performance to the ABC Method, a gastric cancer risk stratification tool currently used in East Asia. RESULTS: For distinguishing precancerous lesions from those with gastritis, the receiver operating characteristic curve had an area under the curve (AUC) of 73.41% (95% CI: 69.10%, 77.71%) and, at Youden's Index, a sensitivity of 78.44% (59.38%, 82.50%) and specificity of 64.72% (95% CI: 58.85%, 81.42%). Positive predictive value (PPV) was 75.38% (72.78%, 82.51%). Specificity, AUC and PPV were significantly greater (p < 0.05) than those of the ABC Method. When specificity was held constant, the Lasso model had greater sensitivity, PPV and negative predictive value (NPV) than the ABC Method. However, adjusting the ABC Method for age and gender negated the Lasso model's significant improvement in AUC. CONCLUSIONS: The Lasso model for gastric cancer risk prediction can classify precancerous lesions with significantly greater AUC than the ABC Method and, at constant specificity, with greater sensitivity, PPV and NPV. However, adding age and gender to the ABC Method, as included in the Lasso model, substantially improved its performance and negated the Lasso model's advantage.

Diffsig: Associating Risk Factors With Mutational Signatures.

Somatic mutational signatures elucidate molecular vulnerabilities to therapy and therefore detecting signatures and classifying tumors with respect to signatures has clinical value. However, identifying the etiology of the mutational signatures remains a statistical challenge, with both small sample sizes and high variability in classification algorithms posing barriers. As a result, few signatures have been strongly linked to particular risk factors. Here we present Diffsig, a model and R package for estimating the association of risk factors with mutational signatures, suggesting etiologies for the pre-defined mutational signatures. Diffsig is a Bayesian Dirichlet-multinomial hierarchical model that allows testing of any type of risk factor while taking into account the uncertainty associated with samples with a low number of observations. In simulation, we found that our method can accurately estimate risk factor-mutational signal associations. We applied Diffsig to breast cancer data to assess relationships between five established breast-relevant mutational signatures and etiologic variables, confirming known mechanisms of cancer development. Diffsig is implemented as an R package available at: https://github.com/jennprk/diffsig.

Job loss, return to work, and multidimensional well-being after breast cancer treatment in working-age Black and White women.

PURPOSE: Breast cancer survivorship has improved in recent decades, but few studies have assessed the patterns of employment status following diagnosis and the impact of job loss on long-term well-being in ethnically diverse breast cancer survivors. We hypothesized that post-treatment employment status is an important determinant of survivor well-being and varies by race and age. METHODS: In the Carolina Breast Cancer Study, 1646 employed women with primary breast cancer were longitudinally evaluated for post-diagnosis job loss and overall well-being. Work status was classified as "sustained work," "returned to work," "job loss," or "persistent non-employment." Well-being was assessed by the Functional Assessment of Cancer Therapy (FACT-G) instrument. Analysis of covariance was used to evaluate the association between work status and well-being (physical, functional, social, and emotional). RESULTS: At 25 months post-diagnosis, 882 (53.6%) reported "sustained work," 330 (20.1%) "returned to work," 162 (9.8%) "job loss," and 272 (16.5%) "persistent non-employment." Nearly half of the study sample (46.4%) experienced interruptions in work during 2 years post-diagnosis. Relative to baseline (5-month FACT-G), women who sustained work or returned to work had higher increases in all well-being domains than women with job loss and persistent non-employment. Job loss was more common among Black than White women (adjusted odds ratio = 3.44; 95% confidence interval 2.37-4.99) and was associated with service/laborer job types, lower education and income, later stage at diagnosis, longer treatment duration, and non-private health insurance. However, independent of clinical factors, job loss was associated with lower well-being in multiple domains. CONCLUSIONS: Work status is commonly disrupted in breast cancer survivors, but sustained work is associated with well-being. Interventions to support women's continued employment after diagnosis are an important dimension of breast cancer survivorship. IMPLICATIONS FOR CANCER SURVIVORS: Our findings indicate that work continuation and returning to work may be a useful measure for a range of wellbeing concerns, particularly among Black breast cancer survivors who experience greater job loss.

Gene Expression Profiling Identifies Two Chordoma Subtypes Associated with Distinct Molecular Mechanisms and Clinical Outcomes.

PURPOSE: Chordoma is a rare bone tumor with a high recurrence rate and limited treatment options. The aim of this study was to identify molecular subtypes of chordoma that may improve clinical management. EXPERIMENTAL DESIGN: We conducted RNA sequencing in 48 tumors from patients with Chinese skull-base chordoma and identified two major molecular subtypes. We then replicated the classification using a NanoString panel in 48 patients with chordoma from North America. RESULTS: Tumors in one subtype were more likely to have somatic mutations and reduced expression in chromatin remodeling genes, such as PBRM1 and SETD2, whereas the other subtype was characterized by the upregulation of genes in epithelial-mesenchymal transition and Sonic Hedgehog pathways. IHC staining of top differentially expressed genes between the two subtypes in 312 patients with Chinese chordoma with long-term follow-up data showed that the expression of some markers such as PTCH1 was significantly associated with survival outcomes. CONCLUSIONS: Our findings may improve the understanding of subtype-specific tumorigenesis of chordoma and inform clinical prognostication and targeted options.

Healthcare system engagement and algorithm-identified cancer incidence following initiation of a new medication.

PURPOSE: Implausibly high algorithm-identified cancer incidence within a new user study after medication initiation may result from increased healthcare utilization (HU) around initiation ("catch-up care") that increases diagnostic opportunity. Understanding the relationships between HU prior to and around initiation and subsequent cancer rates and timing is important to avoiding protopathic bias. METHODS: We identified a cohort of 417 458 Medicare beneficiaries (2007-2014) aged ≥66 initiating an antihypertensive (AHT) after ≥180 days of non-use. Initiators were stratified into groups of 0, 1, 2-3, and ≥4 outpatient visits (OV) 60-360 days before initiation. We calculated algorithm-identified colorectal cancer (aiCRC) rates stratified by OVs and time since AHT initiation: (0-90, 91-180, 181-365, 366-730, and 731+ days). We summarized HU -360/+60 days around AHT initiation by aiCRC timing: (0-29, 30-89, 90-179, and ≥180 days). RESULTS: AiCRC incidence (311 per 100 000 overall) peaked in the first 0-90 days, was inversely associated with HU before initiation, and stabilized ≥180 days after AHT initiation. Catch-up care was greatest among persons with aiCRCs identified <30 days in follow-up. Catch-up care magnitude decreased as time to the aiCRC date increased, with aiCRCs identified ≥180 days after AHT initiation exhibiting similar HU compared with the full cohort. CONCLUSION: Lower HU before-and increased HU around AHT initiation-seem to drive excess short-term aiCRC incidence. Person-time and case accrual should only begin when incidence stabilizes. When comparison groups within a study differ by HU, outcome-detection bias may exist. Similar observations may exist in other settings when typical HU is delayed (e.g., cancer screening during SARS-CoV-2).

Do Patient-Reported Upper-Body Symptoms Predict Breast Cancer-Related Lymphoedema: Results from a Population-Based, Longitudinal Breast Cancer Cohort Study.

The objectives of this work were to (i) describe upper-body symptoms post-breast cancer; (ii) explore the relationship between symptoms and upper-body function, breast cancer-related lymphoedema (BCRL), physical activity levels, and quality of life; and (iii) determine whether the presence of upper-body symptoms predicts BCRL. Nine symptoms, upper-body function, lymphoedema, physical activity, and quality of life were assessed in women with invasive breast cancer at baseline (2- to 9-months post-diagnosis; n = 2442), and at 2- and 7-years post-diagnosis. Mann−Whitney tests, unpaired t-tests, and chi-squared analyses were used to assess cross-sectional relationships, while regression analyses were used to assess the predictive relationships between symptoms at baseline, and BCRL at 2- and 7-years post-diagnosis. Symptoms are common post-breast cancer and persist at 2- and 7-years post-diagnosis. Approximately two in three women, and one in three women, reported >2 symptoms of at least mild severity, and of at least moderate severity, respectively. The presence of symptoms is associated with poorer upper-body function, and lower physical activity levels and quality of life. One or more symptoms of at least moderate severity increases the odds of developing BCRL by 2- and 7-years post-diagnosis (p < 0.05). Consequently, improved monitoring and management of symptoms following breast cancer have the potential to improve health outcomes.