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Julie Barberio,1 Thomas P Ahern,2 Richard F MacLehose,3 Lindsay J Collin,1 Deirdre P Cronin-Fenton,4 Per Damkier,5 Henrik Toft Sørensen,4 Timothy L Lash1 1Rollins School of Public Health, Emory University, Atlanta, GA, USA; 2The Robert Larner College of Medicine, University of Vermont, Burlington, VT, USA; 3University of Minnesota, Minneapolis, MN, USA; 4Aarhus University Hospital, Aarhus, Denmark; 5Odense University Hospital, Odense, DenmarkCorrespondence: Julie BarberioRollins School of Public Health, Emory University, Atlanta, GA, USAEmail julie.barberio@emory.eduPurpose: To compare the magnitude of bias due to unmeasured confounding estimated from various techniques in an applied example.Patients and Methods: We examined the association between dibutyl phthalate (DBP) and incident estrogen receptor (ER)-positive breast cancer in a Danish nationwide cohort (N=1,122,042). Cox regression analyses were adjusted for age and active drug compounds contributing to DBP exposure. We estimated the hazard ratios (HRs) that would have been observed had one of the DBP sources been unmeasured and calculated the strength of confounding by comparing to the fully adjusted HR. We performed a quantitative bias analysis (QBA) of the “unmeasured” confounder, using external information to specify the bias parameters. Upper bounds on the bias were estimated and E-values were calculated.Results: The adjusted HR for incident ER-positive breast cancer among women with high-level (≥ 10,000 cumulative milligrams) versus no DBP exposure was 2.12 (95% confidence interval 1.12 to 4.05). Removing each DBP source in isolation resulted in negligible change in the HR. The bias estimates from the QBA ranged from 1.00 to 1.01. The estimated maximum impact of unmeasured confounding ranged from 1.01 to 1.51. E-values ranged from 3.46 to 3.68.Conclusion: The impact of bias due to simulated unmeasured confounding was negligible, in part, because the unmeasured variable was not independent of controlled variables. When a suspected confounder cannot be measured in the study data, our exercise suggests that QBA is the most informative method for assessing the impact. E-values may best be reserved for situations where uncontrolled confounding emanates from an unknown confounder.Keywords: bias analysis, unmeasured confounding, the E-value

Lindsay J Collin,1,2 Anders H Riis,2 Richard F MacLehose,3 Thomas P Ahern,4 Rune Erichsen,2,5 Ole Thorlacius-Ussing,6 Timothy L Lash1 1Department of Epidemiology, Emory University, Atlanta, GA, USA; 2Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; 3Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA; 4Department of Surgery, The Robert Larner, M.D. College of Medicine at the University of Vermont, Burlington, VT, USA; 5Department of Surgery, Randers Regional Hospital, Randers, Denmark; 6Department of Gastrointestinal Surgery, Aalborg University Hospital, Aalborg, DenmarkCorrespondence: Lindsay J CollinDepartment of Epidemiology, Emory University, 1518 Clifton RoadNE, Atlanta, GA 30322, USATel +1 530-386-3341Email lindsay.jane.collin@emory.eduBackground: Among men and women diagnosed with colorectal cancer (CRC), 20– 50% will develop a cancer recurrence. Cancer recurrences are not routinely captured by most population-based registries; however, linkage across Danish registries allows for the development of predictive models to detect recurrence. Successful application of such models in population-based settings requires validation against a gold standard to ensure the accuracy of recurrence identification.Objective: We apply a recently developed validation study design for prospectively collected validation data to validate predicted CRC recurrences against gold standard diagnoses from medical records in an actively followed cohort of CRC patients in Denmark.Methods: We use a Bayesian monitoring framework, traditionally used in clinical trials, to iteratively update classification parameters (positive and negative predictive values, and sensitivity and specificity) in an adaptive validation substudy design. This design allows determination of the sample size necessary to estimate the corresponding parameters and to identify when validation efforts can cease based on predefined criteria for parameter values and levels of precision.Results: Among 355 men and women diagnosed with CRC in Denmark and actively followed semi-annually, there were 63 recurrences diagnosed by active follow-up and 70 recurrences identified by a predictive algorithm. The adaptive validation design met stopping criteria for the classification parameters after 120 patients had their recurrence information validated. This stopping point yielded parameter estimates for the classification parameters similar to those obtained when the entire cohort was validated, with 66% less patients needed for the validation study.Conclusion: In this proof of concept application of the adaptive validation study design for outcome misclassification, we demonstrated the ability of the method to accurately determine when sufficient validation data have been collected. This method serves as a novel validation substudy design for prospectively collected data with simultaneous implementation of a validation study.Keywords: validation study design, colorectal cancer recurrence

Background: A 2013 meta-analysis observed a protective association between overweight BMI (versus normal BMI) and all-cause mortality that was particularly strong in people aged ≥65. Estimates informing this meta-analysis were highly heterogeneous, and critics raised insufficient or inappropriate confounder adjustment in many studies as an explanation for the protective summary association. Using this topic as an example, we demonstrate a novel approach for external adjustment of individual studies for a uniform and sufficient confounder set before meta-analysis., Methods: We abstracted summary data on the 33 associations comprising the age ≥65 stratum of the 2013 meta-analysis. Using an external dataset (NHANES III), we derived covariates used in each study's multivariable model of the overweight-mortality association. We then calculated a bias factor to quantify the direction and magnitude of displacement of the ratio measure of association after changing from the original adjustment set to a sufficient adjustment set. After applying bias factors to adjust original associations, we compared summary results from random effects meta-analyses with and without such adjustment., Results: We reproduced the original meta-analysis of overweight-mortality estimates among older participants and found a protective association similar to that reported in 2013 (summary RR=0.88, 95% CI: 0.84, 0.92, I2=38.4%). After we simulated uniform adjustment of all 33 associations for a minimally sufficient confounder set (age, sex, and smoking status), the meta-analysis showed a similar summary association (summary RR=0.90, 95% CI: 0.86, 0.94), but with reduced heterogeneity (I2=34.6%)., Conclusion: Simulated uniform adjustment for a sufficient confounder set may improve rigor and promote consensus in meta-analysis., Competing Interests: Conflict of interest: No author declares a conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: We evaluated the impact of systematic bias due to loss of heterozygosity (LOH) and incomplete phenotyping in studies examining the relationship between CYP2D6 variants and breast cancer recurrence among women treated with tamoxifen., Methods: We performed a systematic review of the literature on tamoxifen, CYP2D6 variants, and breast cancer recurrence. A quantitative bias analysis was performed to adjust for LOH and incomplete phenotyping. Bias-adjusted results were then combined in a meta-analysis., Results: Thirty-three studies informed the bias analysis and meta-analysis on CYP2D6 variants and breast cancer recurrence and/or mortality. An unadjusted meta-analysis suggested increased risk of recurrence and/or mortality for poor relative to normal metabolizers [RR = 1.28; 95% simulation interval (SI), 1.04-1.58] with substantial heterogeneity (I2 = 27%; P for heterogeneity = 0.07). Adjusting for LOH and incomplete genotyping resulted in a slight change in the effect estimate and a decrease in heterogeneity (RR = 1.34; 95% SI, 1.10-1.63; I2 = 0%; P for heterogeneity = 0.17). Intermediate metabolizers had a slightly increased risk of recurrence and/or mortality relative to normal metabolizers (RR = 1.15; 95% SI, 1.00-1.34; I2 = 0%; P for heterogeneity = 0.89)., Conclusions: Adjusting for biases such as LOH and incomplete genotyping reduced observed heterogeneity between studies. Individuals with poor CYP2D6 phenotypes were at increased risk for breast cancer outcomes compared with those with normal phenotypes., Impact: Reduction in CYP2D6 activity was associated with an increased risk of breast cancer recurrence and/or mortality, and results underscore the importance of quantitatively adjusting for biases when aggregating study results., (©2024 American Association for Cancer Research.)

Background: We examined the association between late-stage diagnosis and individual- and community-level sociodemographic and socioeconomic characteristics among patients with pediatric Hodgkin lymphoma and rhabdomyosarcoma (RMS)., Methods: We obtained Children's Oncology Group data from 1999 to 2021 including summary stage [local (L), regional (R), and distant (D)], tumor subtype, demographics, and ZIP Code at diagnosis. We linked ZIP Codes to county-level redlining scores (C, D = greatest redlining), the Child Opportunity Index, and measures of segregation (racial dissimilarity indices). Logistic regressions calculated odds ratios for late-stage diagnosis and by race within tumor subtype., Results: In total, 5,956 patients with Hodgkin lymphoma and 2,800 patients with RMS were included. Late-stage diagnosis of Hodgkin lymphoma was correlated with Black race [ORDistant(D) vs. regional/local (R&L) = 1.38 (1.13-1.68)], being uninsured [ORD vs. R&L = 1.38 (1.09-1.75)], and subtype [nodular sclerosis vs. Other Hodgkin lymphoma: ORD vs. R&L = 1.64 (1.34-2.01), Untyped: ORD vs. R&L = 1.30 (1.04-1.63)]. Late-stage RMS was correlated with bilingual households [ORDistant/regional(D&R) vs. local(L) = 2.66 (1.03-6.91)] and tumor type [alveolar vs. embryonal ORD vs. R&L = 6.16 (5.00-7.58)]. Community-level factors associated with late-stage Hodgkin lymphoma were greater Black (OR80-100% = 1.83; 95% CI = 1.11-3.02) and Hispanic (OR60-79% = 1.30; 95% CI = 1.05-1.60) dissimilarity indices. Late-stage diagnosis for RMS was associated with more redlined census tracts within counties (OR = 1.54; 95% CI = 1.02-2.35) and low/very low Child Opportunity Index (OR = 1.21; 95% CI = 1.02-1.45)., Conclusions: Novel markers of community deprivation, such as redlining and racial segregation, were correlated with cancer outcomes for children with Hodgkin lymphoma and RMS in this first disparities study using Children's Oncology Group registries., Impact: The interplay of multilevel risk factors provides important consideration for efforts to improve early detection of pediatric cancer diagnosis., (©2024 American Association for Cancer Research.)

Background: Approximately one-third of US adults have a tattoo, and the prevalence is increasing. Tattooing can result in long-term exposure to carcinogens and inflammatory and immune responses., Methods: We examined tattooing and risk of hematologic cancers in a population-based case-control study with 820 cases diagnosed 2019-2021 and 8200 frequency-matched controls, ages 18-79 years. We calculated odds ratios (OR) and 95% confidence intervals (CI) using multivariable-adjusted logistic regression models., Results: The prevalence of tattooing was 22% among Hodgkin lymphoma (HL) cases, 11% among non-Hodgkin lymphoma (NHL) cases, 16% among myeloid neoplasm cases, and 15% among controls. Though there were no clear patterns of associations between ever receiving a tattoo and risk of HL, NHL, or myeloid neoplasms overall, in analyses restricted to ages 20-60 years, ever receiving a tattoo (OR 2.06 [95% CI 1.01, 4.20]) and receiving a tattoo 10+ years prior (OR 2.64 [95% CI 1.23, 5.68]) were associated with an aggregated group of rarer mature B-cell NHLs. We also observed elevated risks for a 10+ year latency for myelodysplastic syndromes and chronic myeloid leukemia (OR 1.48 [95% CI 0.40, 5.41], and OR 1.24 [95% CI 0.45, 3.43], respectively)., Conclusions: Though estimates were imprecise, we found some suggestive evidence that tattooing may be associated with an increased risk of certain hematologic cancer subtypes. With an estimated 46% prevalence of tattooing in US individuals ages 30-49, additional studies are needed to understand the degree to which these exposures may be associated with hematologic cancer risk., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Importance: 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., Objective: To examine associations between dietary patterns and survival among Black women diagnosed with epithelial ovarian cancer (EOC)., Design, Setting, and Participants: 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., Exposures: 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., Main Outcomes and Measures: 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)., Results: 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., Conclusions and Relevance: 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.

Mismeasurement of a dichotomous outcome yields an unbiased risk ratio estimate when there are no false positive cases (perfect specificity) and when sensitivity is non-differential with respect to exposure status. In studies where these conditions are expected, quantitative bias analysis may be considered unnecessary. We conducted a simulation study to explore the robustness of this special case to small departures from perfect specificity and stochastic departures from non-differential sensitivity. We observed substantial bias of the risk ratio with specificity values as high at 99.8%. The magnitude of bias increased directly with the true underlying risk ratio and was markedly stronger at lower baseline risk. Stochastic departure from non-differential sensitivity also resulted in substantial bias in most simulated scenarios; downward bias prevailed when sensitivity was higher among unexposed compared with exposed, and upward bias prevailed when sensitivity was higher among exposed compared with unexposed. Our results show that seemingly innocuous departures from perfect specificity (e.g., 0.2%) and from non-differential sensitivity can yield substantial bias of the risk ratio under outcome misclassification. We present a web tool permitting easy exploration of this bias mechanism under user-specifiable study scenarios., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: Breast cancer has an average 10-year relative survival reaching 84%. This favorable survival is due, in part, to the introduction of biomarker-guided therapies. We estimated the population-level effect of the introduction of two adjuvant therapies-tamoxifen and trastuzumab-on recurrence using the trend-in-trend pharmacoepidemiologic study design., Methods: We ascertained data on women diagnosed with nonmetastatic breast cancer who were registered in the Danish Breast Cancer Group clinical database. We used the trend-in-trend design to estimate the population-level effect of the introduction of (1) tamoxifen for postmenopausal women with estrogen receptor (ER)-positive breast cancer in 1982, (2) tamoxifen for premenopausal women diagnosed with ER-positive breast cancer in 1999, and (3) trastuzumab for women <60 years diagnosed with human epidermal growth factor receptor 2-positive breast cancer in 2007., Results: For the population-level effect of the introduction of tamoxifen among premenopausal women diagnosed with ER-positive breast cancer in 1999, the risk of recurrence decreased by nearly one-half (OR = 0.52), consistent with evidence from clinical trials; however, the estimate was imprecise (95% confidence interval [CI] = 0.25, 1.85). We observed an imprecise association between tamoxifen use and recurrence from the time it was introduced in 1982 (OR = 1.24 95% CI = 0.46, 5.11), inconsistent with prior knowledge from clinical trials. For the introduction of trastuzumab in 2007, the estimate was also consistent with trial evidence, though imprecise (OR = 0.51; 95% CI = 0.21, 22.4)., Conclusions: We demonstrated how novel pharmacoepidemiologic analytic designs can be used to evaluate the routine clinical care and effectiveness of therapeutic advancements in a population-based setting while considering some limitations of the approach., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Little is known about current characteristics of individuals with tattoos. We quantified the prevalence of tattooing and associations of demographic, health, and risk-behavior factors with tattooing., Methods: We computed adjusted prevalence ratios (PR) of tattooing in a population-based analysis of > 18,000 Utah adults from the 2020-2021 Behavioral Risk Factor Surveillance System survey., Results: The prevalence of tattooing was 26% among women and 22% among men, with the highest prevalence among women ages 25-29 (45%). Tattoo prevalence was higher among younger individuals, individuals with a lower education level, and those without religious affiliation. Tattoo prevalence was higher among indviduals with current tobacco (women: PR = 2.89 [95% confidence interval (CI): 2.60, 3.20]; men: 3.39 [2.98, 3.86]), e-cigarette (women: 2.44 [2.21, 2.69]; men: 2.64 [2.37, 2.94]), and heavy alcohol use (women: 2.16 [1.93, 2.43]; men: 1.89 [1.63, 2.19]). Tattoo prevalence was lower among individuals receiving a flu (women: 0.84 [0.76, 0.92]; men: 0.75 [0.67, 0.84]) or COVID-19 vaccine (women: 0.65 [0.54, 0.79]; men: 0.75 [0.61, 0.92])., Conclusions: Several risk-taking behaviors were associated with tattooing. Tattoo studios/conventions may present opportunities for partnership with tobacco cessation, alcohol reduction, and vaccination public health initiatives., Competing Interests: Declarations Competing interests: The authors declare no competing interests.

Importance: Endometriosis has been associated with an increased risk of ovarian cancer; however, the associations between endometriosis subtypes and ovarian cancer histotypes have not been well-described., Objective: To evaluate the associations of endometriosis subtypes with incidence of ovarian cancer, both overall and by histotype., Design, Setting, and Participants: Population-based cohort study using data from the Utah Population Database. The cohort was assembled by matching 78 893 women with endometriosis in a 1:5 ratio to women without endometriosis., Exposures: Endometriosis cases were identified via electronic health records and categorized as superficial endometriosis, ovarian endometriomas, deep infiltrating endometriosis, or other., Main Outcomes and Measures: Estimated adjusted hazard ratios (aHRs), adjusted risk differences (aRDs) per 10 000 women, and 95% CIs for overall ovarian cancer, type I ovarian cancer, and type II ovarian cancer comparing women with each type of endometriosis with women without endometriosis. Models accounted for sociodemographic factors, reproductive history, and past gynecologic operations., Results: In this Utah-based cohort, the mean (SD) age at first endometriosis diagnosis was 36 (10) years. There were 597 women with ovarian cancer. Ovarian cancer risk was higher among women with endometriosis compared with women without endometriosis (aHR, 4.20 [95% CI, 3.59-4.91]; aRD, 9.90 [95% CI, 7.22-12.57]), and risk of type I ovarian cancer was especially high (aHR, 7.48 [95% CI, 5.80-9.65]; aRD, 7.53 [95% CI, 5.46-9.61]). Ovarian cancer risk was highest in women with deep infiltrating endometriosis and/or ovarian endometriomas for all ovarian cancers (aHR, 9.66 [95% CI, 7.77-12.00]; aRD, 26.71 [95% CI, 20.01-33.41]), type I ovarian cancer (aHR, 18.96 [95% CI, 13.78-26.08]; aRD, 19.57 [95% CI, 13.80-25.35]), and type II ovarian cancer (aHR, 3.72 [95% CI, 2.31-5.98]; aRD, 2.42 [95% CI, -0.01 to 4.85])., Conclusions and Relevance: Ovarian cancer risk was markedly increased among women with ovarian endometriomas and/or deep infiltrating endometriosis. This population may benefit from counseling regarding ovarian cancer risk and prevention and could be an important population for targeted screening and prevention studies.

Purpose: The majority of breast cancer patients are diagnosed with early-stage estrogen receptor (ER) positive disease. Despite effective treatments for these cancers, Black women have higher mortality than White women. We investigated demographic and clinical factors associated with receipt of chemotherapy among those with a discretionary indication who are at risk for overtreatment., Methods: Using Georgia Cancer Registry data, we identified females diagnosed with ER positive breast cancer who had a discretionary indication for chemotherapy (2010-2017). We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) associating patient demographic and clinical characteristics with chemotherapy initiation overall, and comparing non-Hispanic Black (NHB) with non-Hispanic White (NHW) women within strata of patient factors., Results: We identified 11,993 ER positive breast cancer patients with a discretionary indication for chemotherapy. NHB patients were more likely to initiate chemotherapy compared with NHW women (OR = 1.41, 95% CI: 1.28, 1.56). Race differences in chemotherapy initiation were pronounced among those who did not receive Oncotype DX testing (OR = 1.47, 95% CI: 1.31, 1.65) and among those residing in high socioeconomic status neighborhoods (OR = 2.48, 95% CI: 1.70, 3.61). However, we observed equitable chemotherapy receipt among patients who received Oncotype DX testing (OR = 0.90, 95% CI: 0.71, 1.14), were diagnosed with grade 1 disease (OR = 1.00, 95% CI: 0.74, 1.37), and those resided in rural areas (OR = 1.01, 95% CI: 0.76, 1.36)., Conclusion: We observed racial disparities in the initiation of chemotherapy overall and by sociodemographic and clinical factors, and more equitable outcomes when clinical guidelines were followed., (© 2024. The Author(s).)

Introduction: Patients with hormone receptor positive breast cancer are recommended at least five years of adjuvant endocrine therapy, but adherence to this treatment is often suboptimal. We investigated longitudinal trends in adjuvant endocrine therapy (AET) adherence among premenopausal breast cancer patients and identified clinical characteristics, including baseline comorbidities and non-cancer chronic medication use, associated with AET adherence., Methods: We included stage I-III premenopausal breast cancer patients diagnosed during 2002-2011 and registered in the Danish Breast Cancer Group clinical database who initiated AET. We used group-based trajectory modeling to describe AET adherence patterns. We also linked patients to Danish population-based registries and fit multinomial logistic models to compute odds ratios (ORs) and 95% confidence intervals (95% CIs) associating clinical characteristics with AET adherence patterns., Results: We identified three adherence patterns among 4,353 women-high adherers (57%), slow decliners (36%), and rapid decliners (6.9%). Women with stage I disease (vs. stage II; OR: 1.9, 95% CI 1.5, 2.5), without chemotherapy (vs. chemotherapy; OR: 4.3, 95% CI 3.0, 6.1), with prevalent comorbid disease (Charlson Comorbidity Index score ≥ 1 vs. 0; OR: 1.6, 95% CI 1.1, 2.3), and with a history of chronic non-cancer medication use (vs. none; OR: 1.3, 95% CI 1.0, 1.8) were more likely to be rapid decliners compared with high adherers., Conclusions: Women with stage I cancer, no chemotherapy, higher comorbidity burden, and history of chronic non-cancer medication use were less likely to adhere to AET. Taking steps to promote adherence in these groups of women may reduce their risk of recurrence., (© 2024. The Author(s).)

Competing Interests: The authors report no conflicts of interest.

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-DII TM ), 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., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Ovarian cancer is the fifth leading cause of cancer-associated mortality among US women with survival disparities seen across race, ethnicity, and socioeconomic status, even after accounting for histology, stage, treatment, and other clinical factors. Neighborhood context can play an important role in ovarian cancer survival, and, to the extent to which minority racial and ethnic groups and populations of lower socioeconomic status are more likely to be segregated into neighborhoods with lower quality social, built, and physical environment, these contextual factors may be a critical component of ovarian cancer survival disparities. Understanding factors associated with ovarian cancer outcome disparities will allow clinicians to identify patients at risk for worse outcomes and point to measures, such as social support programs or transportation aid, that can help to ameliorate such disparities. However, research on the impact of neighborhood contextual factors in ovarian cancer survival and in disparities in ovarian cancer survival is limited. This commentary focuses on the following neighborhood contextual domains: structural and institutional context, social context, physical context represented by environmental exposures, built environment, rurality, and healthcare access. The research conducted to date is presented and clinical implications and recommendations for future interventions and studies to address disparities in ovarian cancer outcomes are proposed., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Purpose: Place-based measures of structural racism have been associated with breast cancer mortality, which may be driven, in part, by epigenetic perturbations. We examined the association between contemporary redlining, a measure of structural racism at the neighborhood level, and DNA methylation in breast tumor tissue., Methods: We identified 80 Black and White women diagnosed and treated for a first-primary breast cancer at Emory University Hospitals (2008-2017). Contemporary redlining was derived for census tracts using the Home Mortgage Disclosure Act database. Linear regression models were used to calculate the association between contemporary redlining and methylation in breast tumor tissue. We also examined epigenetic age acceleration for two different metrics, regressing β values for each cytosine-phosphate-guanine dinucleotide (CpG) site on redlining while adjusting for covariates. We employed multivariable Cox-proportional hazards models and 95% confidence intervals (CI) to estimate the association between aberrant methylation and mortality., Results: Contemporary redlining was associated with 5 CpG sites after adjustment for multiple comparisons (FDR<0.10). All genes were implicated in breast carcinogenesis, including genes related to inflammation, immune function and stress response ( ANGPT1, PRG4 and PRG4) . Further exploration of the top 25 CpG sites, identified interaction of 2 sites ( MRPS28 and cg11092048) by ER status and 1 site ( GDP1 ) was associated with all-cause mortality. Contemporary redlining was associated with epigenetic age acceleration by the Hannum metric (β=5.35; CI 95%=0.30,10.4) and showed positive but non-significant correlation with the other clock., Conclusion: We identified novel associations between neighborhood contemporary redlining and the breast tumor DNA methylome, suggesting that racist policies leading to inequitable social and environmental exposures, may impact the breast tumor epigenome. Additional research on the potential implications for prognosis is needed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Miller-Kleinhenz, Moubadder, Beyer, Zhou, Gaglioti, Collin, Gohar, Do, Conneely, Krishnamurti, Gogineni, Gabram-Mendola, D’Angelo, Henry, Torres and McCullough.)

Background: Little is known regarding the association between insurance status and treatment delays in women with breast cancer and whether this association varies by neighborhood socioeconomic deprivation status., Methods: In this cohort study, we used medical record data of women diagnosed with breast cancer between 2004 and 2022 at two Georgia-based healthcare systems. Treatment delay was defined as >90 days to surgery or >120 days to systemic treatment. Insurance coverage was categorized as private, Medicaid, Medicare, other public, or uninsured. Area deprivation index (ADI) was used as a proxy for neighborhood-level socioeconomic status. Associations between delayed treatment and insurance status were analyzed using logistic regression, with an interaction term assessing effect modification by ADI., Results: Of the 14,195 women with breast cancer, 54% were non-Hispanic Black and 52% were privately insured. Compared with privately insured patients, those who were uninsured, Medicaid enrollees, and Medicare enrollees had 79%, 75%, and 27% higher odds of delayed treatment, respectively (odds ratio [OR]: 1.79, 95% confidence interval [CI]: 1.32-2.43; OR: 1.75, 95% CI: 1.43-2.13; OR: 1.27, 95% CI: 1.06-1.51). Among patients living in low-deprivation areas, those who were uninsured, Medicaid enrollees, and Medicare enrollees had 100%, 84%, and 26% higher odds of delayed treatment than privately insured patients (OR: 2.00, 95% CI: 1.44-2.78; OR: 1.84, 95% CI: 1.48-2.30; OR: 1.26, 95% CI: 1.05-1.53). No differences in the odds of delayed treatment by insurance status were observed in patients living in high-deprivation areas., Discussion/conclusion: Insurance status was associated with treatment delays for women living in low-deprivation neighborhoods. However, for women living in neighborhoods with high deprivation, treatment delays were observed regardless of insurance status., (© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Lifestyle habits can impact breast cancer development, but its impact on breast cancer prognosis remains unclear. We investigated associations of post-diagnosis lifestyle with mortality and recurrence in 1,964 women with invasive breast cancer enrolled in the Kaiser Permanente Northern California Pathways Study shortly after diagnosis with lifestyle information at baseline (2005-2013) and the 2-year follow-up., Methods: We calculated a post-diagnosis lifestyle score (range, 0-18) based on 9 diet, physical activity, and body weight recommendations from the American Cancer Society/American Society of Clinical Oncology (ACS/ASCO) using follow-up data (body weight also included baseline data); higher scores indicate greater guideline concordance. Similarly, we calculated a pre-diagnosis lifestyle score using baseline data to investigate pre- to post-diagnosis changes. We estimated hazard ratios (HR) and 95% confidence intervals (CI) using Cox proportional hazard models, with follow-up through December 2018 (observing 290 deaths and 176 recurrences)., Results: The 2-year post-diagnosis lifestyle score was inversely associated with all-cause mortality (ACM; HR per 2-point increase = 0.90; 95% CI, 0.82-0.98), and breast cancer-related mortality (HR, 0.79; 95% CI, 0.67-0.95), but not recurrence. Relative to women who maintained low concordance with recommendations at both time points, women who maintained high concordance had a lower risk of ACM (HR, 0.61, 95% CI, 0.37-1.03). Improved concordance with some specific recommendations (particularly PA) may be associated with a lower hazard of ACM (HRPA, 0.52; 95% CI, 0.35-0.78)., Conclusions: Results suggest that women with breast cancer may benefit from a post-diagnosis lifestyle aligned with ACS/ASCO guidelines., Impact: This information may potentially guide lifestyle recommendations for breast cancer survivors to reduce mortality risk., (©2023 American Association for Cancer Research.)

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., Competing Interests: LC received research funding from the NIH. SS received research funding from NIH, Cystic Fibrosis Foundation, PCORI, Pfizer Inc., Pfizer Japan, BMS, and Daiichi Sankyo and served as a consultant for Pfizer Japan, Merck Co. Inc., BMS, and Medtronic Inc. EB received research funding from NIH and serves in an Advisory Board for Pfizer Clinical Trial Diversity Initiative. JS received research funding from NIH. SA received research funding from the New Jersey Commission on Cancer Research and is supported by a NIH grant. JK received research funding from the NIH., (Copyright © 2023 Amin, Collin, Kavecansky, Setoguchi, Satagopan and Bandera.)

Background: We investigated racial and ethnic disparities in treatment sequence [i.e., neoadjuvant chemotherapy (NACT) plus interval debulking surgery (IDS) versus primary debulking surgery (PDS) plus adjuvant chemotherapy] among patients with ovarian cancer and its contribution to disparities in mortality., Methods: Study included 37,566 women ages ≥18 years, diagnosed with stage III/IV ovarian cancer from the National Cancer Database (2004-2017). Logistic regression was used to compute ORs and 95% confidence intervals (CI) for racial and ethnic disparities in treatment sequence. Cox proportional hazards regression was used to estimate HRs and 95% CI for racial and ethnic disparities in all-cause mortality., Results: Non-Hispanic Black (NHB) and Asian women were more likely to receive NACT plus IDS relative to PDS plus adjuvant chemotherapy than non-Hispanic White (NHW) women (OR: 1.12; 95% CI: 1.02-1.22 and OR: 1.12; 95% CI: 0.99-1.28, respectively). Compared with NHW women, NHB women had increased hazard of all-cause mortality (HR: 1.14; 95% CI: 1.09-1.20), whereas Asian and Hispanic women had a lower hazard of all-cause mortality (HR: 0.81; 95% CI: 0.74-0.88 and HR: 0.83; 95% CI: 0.77-0.88, respectively), which did not change after accounting for treatment sequence., Conclusions: NHB women were more likely to receive NACT plus IDS and experience a higher all-cause mortality rates than NHW women., Impact: Differences in treatment sequence did not explain racial disparities in all-cause mortality. Further evaluation of racial and ethnic differences in treatment and survival in a cohort of patients with detailed treatment information is warranted., (©2022 American Association for Cancer Research.)

Purpose: Our research sought to describe barriers to mammography screening among a sample of predominantly Black women in metropolitan Atlanta, Georgia., Methods: The Pink Panel project convened community leaders from faith-based institutions to administer an offline survey to women via convenience sampling at fourteen churches in Atlanta in late 2019 and early 2020. With the COVID-19 pandemic, the research team switched to an online survey. The survey included seven questions about breast cancer awareness, barriers to breast cancer screening, and screening status. We used residence information to attain the 9-digit zip code to link to the Area Deprivation Index at the Census Block Group neighborhood level. We report results as descriptive statistics of the barriers to mammography screening., Results: The 643 women represented 21 counties in Georgia, predominantly from metropolitan Atlanta, and 86% identified as Black. Among women aged 40 and older, 90% have ever had a mammogram. Among all women, 79% have ever had a mammogram, and 86% indicated that they would get a mammogram if offered in their neighborhood. The top barriers to mammography screening were lack of health insurance and high cost. Barriers to mammography screening did not differ substantially by Area Deprivation Index., Conclusion: Among metropolitan Atlanta women aged 40+ , nearly all reported ever having a mammogram. However, addressing the barriers, including lack of health insurance and high cost, that women reported may further improve mammography screening rates., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: The degree to which uterine cancer metastatic to the ovary is misdiagnosed as synchronous stage I uterine and ovarian cancers is unclear. We sought to determine whether patients with synchronous cancers had mortality patterns similar to either stage IIIA uterine, stage I uterine, or stage I ovarian cancers alone., Methods: The Surveillance, Epidemiology, and End Results database was used to compare mortality of patients with synchronous stage I uterine and stage I ovarian cancers versus those with stage IIIA uterine, stage I uterine, or stage I ovarian cancers alone. We calculated age-adjusted mortality hazard ratios (HR) and 95% confidence intervals (CI) accounting for calendar year and grade, adjuvant treatment, grade 1 endometrioid cancers, grade 3 endometrioid cancers, and stage IA cancers., Results: Among the 9,321 patients, we observed lower age-adjusted mortality in patients with stage I synchronous cancers (n = 937) compared to those with stage IIIA uterine (n = 531; HR, 0.45 95% CI, 0.35-0.58), stage I uterine (n = 6,919; HR, 0.74; 95% CI, 0.60-0.91), and stage I ovarian cancers (n = 934; HR, 0.52; 95% CI, 0.41-0.67). Results were similar after taking into account diagnosis year and grade, and limiting to those receiving adjuvant therapy, grade 1 or grade 3 endometrioid cancers, or stage IA cancers., Conclusions: We observed lower mortality for synchronous stage I uterine and ovarian cancers, which was not explained by younger age, earlier stage, lower grade, histology type, or adjuvant therapy., Impact: The possible misdiagnosis associated with clinicopathologic of synchronous uterine and ovarian cancers does not appear to worsen survival on a population level., (©2022 American Association for Cancer Research.)

Importance: Increasing evidence suggests that low socioeconomic status and geographic residence in disadvantaged neighborhoods contribute to disparities in breast cancer outcomes. However, little epidemiological research has sought to better understand these disparities within the context of location., Objective: To examine the association between neighborhood deprivation and racial disparities in mortality among Black and White patients with breast cancer in the state of Georgia., Design, Setting, and Participants: This population-based cohort study collected demographic and geographic data from patients diagnosed with breast cancer between January 1, 2004, and February 11, 2020, in 3 large health care systems in Georgia. A total of 19 580 patients with breast cancer were included: 12 976 from Piedmont Healthcare, 2285 from Grady Health System, and 4319 from Emory Healthcare. Data were analyzed from October 2, 2020, to August 11, 2022., Exposures: Area deprivation index (ADI) scores were assigned to each patient based on their residential census block group. The ADI was categorized into quartile groups, and associations between ADI and race and ADI × race interaction were examined., Main Outcomes and Measures: Cox proportional hazards regression models were used to compute hazard ratios (HRs) and 95% CIs associating ADI with overall mortality by race. Kaplan-Meier curves were used to visualize mortality stratified across racial and ADI groups., Results: Of the 19 580 patients included in the analysis (mean [SD] age at diagnosis, 58.8 [13.2] years), 3777 (19.3%) died during the course of the study. Area deprivation index contributed differently to breast cancer outcomes for Black and White women. In multivariable-adjusted models, living in a neighborhood with a greater ADI (more deprivation) was associated with increased mortality for White patients with breast cancer; compared with the ADI quartile of less than 25 (least deprived), increased mortality HRs were found in quartiles of 25 to 49 (1.22 [95% CI, 1.07-1.39]), 50 to 74 (1.32 [95% CI, 1.13-1.53]), and 75 or greater (1.33 [95% CI, 1.07-1.65]). However, an increase in the ADI quartile group was not associated with changes in mortality for Black patients with breast cancer (quartile 25 to 49: HR, 0.81 [95% CI, 0.61-1.07]; quartile 50 to 74: HR, 0.91 [95% CI, 0.70-1.18]; and quartile ≥75: HR, 1.05 [95% CI, 0.70-1.36]). In neighborhoods with an ADI of 75 or greater, no racial disparity was observed in mortality (HR, 1.11 [95% CI, 0.92-1.36])., Conclusions and Relevance: Black women with breast cancer had higher mortality than White women in Georgia, but this disparity was not explained by ADI: among Black patients, low ADI was not associated with lower mortality. This lack of association warrants further investigation to inform community-level approaches that may mitigate the existing disparities in breast cancer outcomes in Georgia.

Background: The authors identified tumor, treatment, and patient characteristics that may contribute to differences in breast cancer (BC) mortality by race, rurality, and area-level socioeconomic status (SES) among women diagnosed with stage IIIB-IV BC in Georgia., Methods: Using the Georgia Cancer Registry, 3084 patients with stage IIIB-IV primary BC (2013-2017) were identified. Cox proportional hazards regression was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) comparing mortality among non-Hispanic Black (NHB) versus non-Hispanic White (NHW), residents of rural versus urban neighborhoods, and residents of low- versus high-SES neighborhoods by tumor, treatment, and patient characteristics. The mediating effects of specific characteristics on the association between race and BC mortality were estimated., Results: Among the study population, 41% were NHB, 21% resided in rural counties, and 72% resided in low SES neighborhoods. The authors observed mortality disparities by race (HR, 1.27; 95% CI, 1.13, 1.41) and rurality (HR, 1.14; 95% CI, 1.00, 1.30), but not by SES (HR, 1.04; 95% CI, 0.91, 1.19). In the stratified analyses, racial disparities were the most pronounced among women with HER2 overexpressing tumors (HR, 2.30; 95% CI, 1.53, 3.45). Residing in a rural county was associated with increased mortality among uninsured women (HR, 2.25; 95% CI, 1.31, 3.86), and the most pronounced SES disparities were among younger women (<40 years: HR, 1.46; 95% CI, 0.88, 2.42)., Conclusions: There is considerable variation in racial, regional, and socioeconomic disparities in late-stage BC mortality by tumor, treatment, and patient characteristics., (© 2022 American Cancer Society.)

Background: Black women are more likely to die of breast cancer than White women. This study evaluated the contribution of time to primary surgical management and surgical facility characteristics to racial disparities in breast cancer mortality among both Black and White women., Methods: The study identified 2224 Black and 3787 White women with a diagnosis with stages I to III breast cancer (2010-2014). Outcomes included time to surgical treatment (> 30 days from diagnosis) and breast cancer mortality. Odds ratios (ORs) and 95% confidence intervals (CIs) associating surgical facility characteristics with surgical delay were computed, and Cox proportional hazards regression was used to compute hazard ratios (HRs) and 95% CIs associating delay and facility characteristics with breast cancer mortality., Results: Black women were two times more likely to have a surgical delay (OR, 2.15; 95% CI, 1.92-2.41) than White women. Racial disparity in surgical delay was least pronounced among women treated at a non-profit facility (OR, 1.95; 95% CI, 1.70-2.25). The estimated mortality rate for Black women was two times that for White women (HR, 2.00; 95% CI, 1.83-2.46). Racial disparities in breast cancer mortality were least pronounced among women who experienced no surgical delay (HR, 1.81; 95% CI, 1.28-2.56), received surgery at a government facility (HR, 1.31; 95% CI, 0.76-2.27), or underwent treatment at a Commission on Cancer-accredited facility (HR, 1.82; 95% CI, 1.38-2.40)., Conclusions: Black women were more likely to experience a surgical delay and breast cancer death. Persistent racial disparities in breast cancer mortality were observed across facility characteristics except for government facilities., (© 2022. Society of Surgical Oncology.)

Data collected from a validation substudy permit calculation of a bias-adjusted estimate of effect that is expected to equal the estimate that would have been observed had the gold standard measurement been available for the entire study population. In this paper, we develop and apply a framework for adaptive validation to determine when sufficient validation data have been collected to yield a bias-adjusted effect estimate with a prespecified level of precision. Prespecified levels of precision are decided a priori by the investigator, based on the precision of the conventional estimate and allowing for wider confidence intervals that would still be substantively meaningful. We further present an applied example of the use of this method to address exposure misclassification in a study of transmasculine/transfeminine youth and self-harm. Our method provides a novel approach to effective and efficient estimation of classification parameters as validation data accrue, with emphasis on the precision of the bias-adjusted estimate. This method can be applied within the context of any parent epidemiologic study design in which validation data will be collected and modified to meet alternative criteria given specific study or validation study objectives., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

In 1995, journalist Gary Taubes published an article in Science titled "Epidemiology faces its limits," which questioned the utility of nonrandomized epidemiologic research and has since been cited more than 1000 times. He highlighted numerous examples of research topics he viewed as having questionable merit. Studies have since accumulated for these associations. We systematically evaluated current evidence of 53 example associations discussed in the article. Approximately one-quarter of those presented as doubtful are now widely viewed as causal based on current evaluations of the public health consensus. They include associations between alcohol consumption and breast cancer, residential radon exposure and lung cancer, and the use of tanning devices and melanoma. This history should inform current debates about the reproducibility of epidemiologic research results.

Background: Gastrointestinal (GI) cancers represent a diverse group of diseases. We assessed differences in geographic and racial disparities in cancer-specific mortality across subtypes, overall and by patient characteristics, in a geographically and racially diverse US population., Methods: Clinical, sociodemographic, and treatment characteristics for patients diagnosed during 2009-2014 with colorectal cancer (CRC), pancreatic cancer, hepatocellular carcinoma (HCC), or gastric cancer in Georgia were obtained from the Surveillance, Epidemiology, and End Results Program database. Patients were classified by geography (rural or urban county) and race and followed for cancer-specific death. Multivariable Cox proportional hazards models were used to calculate stratified hazard ratios (HR) and 95% confidence intervals (CIs) for associations between geography or race and cancer-specific mortality., Results: Overall, 77% of the study population resided in urban counties and 33% were non-Hispanic Black (NHB). For all subtypes, NHB patients were more likely to reside in urban counties than non-Hispanic White patients. Residing in a rural county was associated with an overall increased hazard of cancer-specific mortality for HCC (HR = 1.15, 95% CI = 1.02-1.31), pancreatic (HR = 1.11, 95% CI = 1.03-1.19), and gastric cancer (HR = 1.17, 95% CI = 1.03-1.32) but near-null for CRC. Overall racial disparities were observed for CRC (HR = 1.18, 95% CI = 1.11-1.25) and HCC (HR = 1.12, 95% CI = 1.01-1.24). Geographic disparities were most pronounced among HCC patients receiving surgery. Racial disparities were pronounced among CRC patients receiving any treatment., Conclusion: Geographic disparities were observed for the rarer GI cancer subtypes, and racial disparities were pronounced for CRC. Treatment factors appear to largely drive both disparities., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background: This study evaluated the association between preexisting stress-related diagnoses and mortality in a Danish population-based cancer cohort., Methods: This study included Danish patients with cancer diagnosed in 1995-2011 who had a stress-related diagnosis before their cancer diagnosis. Cancer patients without a prior stress-related diagnosis were matched 5:1 to the stress disorder cohort by cancer site, age group, calendar period, and sex. The 5-year cumulative incidence of cancer-specific and all-cause mortality was computed by stress-related diagnosis category. Hazard ratios and 95% confidence intervals (CIs) associating stress-related diagnoses with mortality were computed by follow-up time, stress-related diagnosis category, stage, comorbidity status, and cancer type., Results: This study identified 4437 cancer patients with a preexisting stress-related diagnosis and 22,060 matched cancer cohort members. The 5-year cumulative risk of cancer-specific mortality was 33% (95% CI, 32%-35%) for those with a preexisting stress-related diagnosis and 29% (95% CI, 28%-29%) for those without a prior stress-related diagnosis. Cancer patients with a preexisting stress-related diagnosis had a 1.3 times higher cancer-specific mortality rate than the comparison cohort members (95% CI, 1.2-1.5). This increase persisted across categories of stress-related diagnosis. The association varied by stage and cancer type, with more pronounced associations found among those with a late stage at diagnosis and hematological malignancies., Conclusions: Cancer patients with preexisting stress-related diagnoses had increased rates of cancer-specific and all-cause mortality. The results suggest that psychiatric comorbidities may be an important consideration for cancer prognosis, and cancer treatment informed by a patient's history may improve outcomes., (© 2021 American Cancer Society.)

Background: Validation studies estimating the positive predictive value (PPV) of neonatal abstinence syndrome (NAS) have consistently suggested overreporting in hospital discharge records. However, few studies estimate the negative predictive value (NPV). Even slightly imperfect NPVs have the potential to bias estimated prevalences of rare outcomes like NAS. Given the challenges in estimating NPV, our objective was to evaluate whether the PPV was sufficient to understand the influence of NAS misclassification bias on conclusions of the NAS prevalence in surveillance research., Methods: We used hospital discharge data from the 2016 New Jersey State Inpatient Databases, Healthcare Cost and Utilization Project. We adjusted surveillance data for misclassification using quantitative bias analysis models to estimate the expected NAS prevalence under a range of PPV and NPV bias scenarios., Results: The 2016 observed NAS prevalence was 0.61%. The misclassification-adjusted prevalence estimates ranged from 0.31% to 0.91%. When PPV was assumed to be ≥90%, the misclassification-adjusted prevalence was typically greater than the observed prevalence but the reverse was true for PPV ≤70%. Under PPV 80%, the misclassification-adjusted prevalence was less than the observed prevalence for NPV >99.9% but flipped for NPV <99.9%., Conclusions: When we varied the NPV below 100%, our results suggested that the direction of bias (over or underestimation) was dependent on the PPV, and sometimes dependent on the NPV. However, NPV was important for understanding the magnitude of bias. This study serves as an example of how quantitative bias analysis methods can be applied in NAS surveillance to supplement existing validation data when NPV estimates are unavailable., Competing Interests: The authors report no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Increased transparency in study design and analysis is one proposed solution to the perceived reproducibility crisis facing science. Systematic review and meta-analysis-through which individual studies on a specific association are ascertained, assessed for quality and quantitatively combined-is a critical process for building consensus in medical research. However, the conventional publication model creates static evidence summaries that force the quality assessment criteria and analytical choices of a small number of authors onto all stakeholders, some of whom will have different views on the quality assessment and key features of the analysis. This leads to discordant inferences from meta-analysis results and delayed arrival at consensus. We propose a shift to interactive meta-analysis, through which stakeholders can take control of the evidence synthesis using their own quality criteria and preferred analytic approach-including the option to incorporate prior information on the association in question-to reveal how their summary estimate differs from that reported by the original analysts. We demonstrate this concept using a web-based meta-analysis of the association between genetic variation in a key tamoxifen-metabolising enzyme and breast cancer recurrence in tamoxifen-treated women. We argue that interactive meta-analyses would speed consensus-building to the degree that they reveal invariance of inferences to different study selection and analysis criteria. On the other hand, when inferences are found to differ substantially as a function of these choices, the disparities highlight where future research resources should be invested to resolve lingering sources of disagreement., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Hypoxia-inducible factor-1α (HIF-1α) is a transcription factor that facilitates the adaptation of cancer cells to hypoxic conditions and may be prognostic of breast cancer recurrence. We evaluated the association of HIF-1α expression with breast cancer recurrence, and its association with timing of breast cancer recurrence., Methods: In this population-based case-control study, we included women diagnosed with stage I-III breast cancer between 1985 and 2001, aged 35-69 years, registered in the Danish Breast Cancer Group. We identified 541 cases of breast cancer recurrence among women with estrogen receptor (ER)-positive disease who were treated with tamoxifen for at least 1 year (ER+ TAM+). We also enrolled 300 breast cancer recurrence cases among women with ER-negative disease, not treated with tamoxifen, who survived at least 1 year (ER-/TAM-). Controls were recurrence-free breast cancer patients at the time of case diagnosis, matched to recurrence cases on ER/TAM status, date of surgery, menopausal status, cancer stage, and county of residence. Expression of HIF-1α was measured by immunohistochemistry on tissue microarrays. We fitted logistic regression models to compute odds ratios (ORs) and 95% confidence intervals (CIs) associating HIF-1α expression with recurrence, and with timing of recurrence., Results: HIF-1α expression was observed in 23% of cases and 20% of controls in the ER+/TAM+ stratum, and in 47% of cases and 48% of controls in the ER-/TAM- stratum. We observed a near-null association between HIF-1α expression in both ER/TAM groups (ER+/TAM+ OR = 1.21, 95%CI 0.88, 1.67 and ER-/TAM- OR = 0.97, 95%CI 0.68, 1.39). HIF-1α expression was not associated with time to recurrence among women in the ER+/TAM+ stratum, but was associated with early recurrence among women in the ER-/TAM- stratum., Conclusion: In this study, HIF-1α expression was not associated with breast cancer recurrence overall but may be associated with early recurrence among women diagnosed with ER- breast cancer., (© 2021. The Author(s).)

Purpose: Early diagnosis is fundamental to reducing breast cancer (BC) mortality, and understanding potential barriers from initial screening to confirmed diagnosis is essential. The aim of this study was to evaluate patient characteristics that contribute to delay in diagnosis of screen-detected cancers and the contribution of delay to tumor characteristics and BC mortality., Methods: Three hundred sixty-two White and 368 Black women were identified who were screened and received subsequent BC diagnoses within Emory Healthcare, a part of Emory University health care system (2010-2014). Multivariable-adjusted logistic regression was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) associating patient characteristics with delay to diagnostic evaluation (≥30 versus <30 days), delay to biopsy (≥15 versus <15 days), and total delay (≥45 versus <45 days). Additionally, the ORs and 95% CIs associating delay with tumor characteristics and BC mortality were computed., Results: Black women and women diagnosed at later stages, with larger tumor sizes, and with triple-negative tumors were more likely to experience ≥45 days to diagnosis. In multivariable-adjusted models, Black women had at least a two-fold increase in the odds of delay to diagnostic evaluation (OR, 1.98; 95% CI, 1.45-2.71), biopsy delays (OR, 2.41; 95% CI, 1.67-3.41), and total delays ≥45 days (OR, 2.22; 95% CI, 1.63-3.02) compared with White women. A 1.6-fold increased odds of BC mortality was observed among women who experienced total delays ≥45 days compared with women without delays in diagnosis (OR, 1.57, 95% CI, 0.96-2.58)., Conclusions: The study demonstrated racial disparities in delays in the diagnostic process for screen-detected malignancies. Total delay in diagnosis was associated with an increase in BC mortality., (Copyright © 2021 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Background: Racial disparities in breast cancer mortality in the United States are well documented. Non-Hispanic Black (NHB) women are more likely to die of their disease than their non-Hispanic White (NHW) counterparts. The disparity is most pronounced among women diagnosed with prognostically favorable tumors, which may result in part from variations in their receipt of guideline care. In this study, we sought to estimate the effect of guideline-concordant care (GCC) on prognosis, and to evaluate whether receipt of GCC modified racial disparities in breast cancer mortality., Patients and Methods: Using the Georgia Cancer Registry, we identified 2,784 NHB and 4,262 NHW women diagnosed with a stage I-III first primary breast cancer in the metropolitan Atlanta area, Georgia, between 2010 and 2014. Women were included if they received surgery and information on their breast tumor characteristics was available; all others were excluded. Receipt of recommended therapies (chemotherapy, radiotherapy, endocrine therapy, and anti-HER2 therapy) as indicated was considered GCC. We used Cox proportional hazards models to estimate the impact of receiving GCC on breast cancer mortality overall and by race, with multivariable adjusted hazard ratios (HRs)., Results: We found that NHB and NHW women were almost equally likely to receive GCC (65% vs 63%, respectively). Failure to receive GCC was associated with an increase in the hazard of breast cancer mortality (HR, 1.74; 95% CI, 1.37-2.20). However, racial disparities in breast cancer mortality persisted despite whether GCC was received (HRGCC: 2.17 [95% CI, 1.61-2.92]; HRnon-GCC: 1.81 [95% CI, 1.28-2.91] )., Conclusions: Although receipt of GCC is important for breast cancer outcomes, racial disparities in breast cancer mortality did not diminish with receipt of GCC; differences in mortality between Black and White patients persisted across the strata of GCC.

Quantitative bias analysis comprises the tools used to estimate the direction, magnitude, and uncertainty from systematic errors affecting epidemiologic research. Despite the availability of methods and tools, and guidance for good practices, few reports of epidemiologic research incorporate quantitative estimates of bias impacts. The lack of familiarity with bias analysis allows for the possibility of misuse, which is likely most often unintentional but could occasionally include intentional efforts to mislead. We identified 3 examples of suboptimal bias analysis, one for each common bias. For each, we describe the original research and its bias analysis, compare the bias analysis with good practices, and describe how the bias analysis and research findings might have been improved. We assert no motive to the suboptimal bias analysis by the original authors. Common shortcomings in the examples were lack of a clear bias model, computed example, and computing code; poor selection of the values assigned to the bias model's parameters; and little effort to understand the range of uncertainty associated with the bias. Until bias analysis becomes more common, community expectations for the presentation, explanation, and interpretation of bias analyses will remain unstable. Attention to good practices should improve quality, avoid errors, and discourage manipulation., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Black, Hispanic, and Indigenous persons in the United States have an increased risk of SARS-CoV-2 infection and death from COVID-19, due to persistent social inequities. However, the magnitude of the disparity is unclear because race/ethnicity information is often missing in surveillance data., Methods: We quantified the burden of SARS-CoV-2 notification, hospitalization, and case fatality rates in an urban county by racial/ethnic group using combined race/ethnicity imputation and quantitative bias analysis for misclassification., Results: The ratio of the absolute racial/ethnic disparity in notification rates after bias adjustment, compared with the complete case analysis, increased 1.3-fold for persons classified Black and 1.6-fold for those classified Hispanic, in reference to classified White persons., Conclusions: These results highlight that complete case analyses may underestimate absolute disparities in notification rates. Complete reporting of race/ethnicity information is necessary for health equity. When data are missing, quantitative bias analysis methods may improve estimates of racial/ethnic disparities in the COVID-19 burden., Competing Interests: The authors report no conflicts of interest., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: Premenopausal women diagnosed with estrogen receptor (ER)-positive breast cancer are prescribed 5-10 years of endocrine therapy to prevent or delay recurrence. In this study, we evaluated the association between early discontinuation of endocrine therapy and breast cancer recurrence in a cohort of premenopausal women., Experimental Design: We identified 4,503 patients with premenopausal ER-positive breast cancer who initiated adjuvant endocrine therapy and were registered in the Danish Breast Cancer Group clinical database (2002-2011). Women were excluded if they had a recurrence or were lost to follow-up less than 1.5 years after breast cancer surgery. Endocrine therapy was considered complete if the patient received at least 4.5 years of treatment or discontinued medication less than 6 months before recurrence. Exposure status was updated annually and modeled as a time-dependent variable. We accounted for baseline and time-varying confounders via time-varying weights, which we calculated from multivariable logistic regression models, and included in regression models to estimate HRs and 95% confidence intervals (CIs) associating early discontinuation with recurrence., Results: Over the study follow-up, 1,001 (22%) women discontinued endocrine therapy. We observed 202 (20%) recurrences among those who discontinued endocrine therapy, and 388 (11%) among those who completed the recommended treatment. The multivariable-adjusted estimated rate of recurrence was higher in women who discontinued endocrine therapy relative to those who completed their treatment (hazard ratio, 1.67; 95% CI, 1.25-2.14)., Conclusions: These results highlight the importance of clinical follow-up and behavioral interventions that support persistence of adjuvant endocrine therapy to prevent breast cancer recurrence., (©2020 American Association for Cancer Research.)

Background: Structural inequities have important implications for the health of marginalized groups. Neighborhood-level redlining and lending bias represent state-sponsored systems of segregation, potential drivers of adverse health outcomes. We sought to estimate the effect of redlining and lending bias on breast cancer mortality and explore differences by race., Methods: Using Georgia Cancer Registry data, we included 4,943 non-Hispanic White (NHW) and 3,580 non-Hispanic Black (NHB) women with a first primary invasive breast cancer diagnosis in metro-Atlanta (2010-2014). Redlining and lending bias were derived for census tracts using the Home Mortgage Disclosure Act database. We calculated hazard ratios and 95% confidence intervals (CI) for the associations of redlining, lending bias on breast cancer mortality and estimated race-stratified associations., Results: Overall, 20% of NHW and 80% of NHB women lived in redlined census tracts, and 60% of NHW and 26% of NHB women lived in census tracts with pronounced lending bias. Living in redlined census tracts was associated with a nearly 1.60-fold increase in breast cancer mortality (hazard ratio = 1.58; 95% CI, 1.37-1.82) while residing in areas with substantial lending bias reduced the hazard of breast cancer mortality (hazard ratio = 0.86; 95% CI, 0.75-0.99). Among NHB women living in redlined census tracts, we observed a slight increase in breast cancer mortality (hazard ratio = 1.13; 95% CI, 0.90-1.42); among NHW women the association was more pronounced (hazard ratio = 1.39; 95% CI, 1.09-1.78)., Conclusions: These findings underscore the role of ecologic measures of structural racism on cancer outcomes., Impact: Place-based measures are important contributors to health outcomes, an important unexplored area that offers potential interventions to address disparities., (©2020 American Association for Cancer Research.)

Modern epidemiologic studies permit investigation of the complex pathways that mediate effects of social, behavioral, and molecular factors on health outcomes. Conventional analytical approaches struggle with high-dimensional data, leading to high likelihoods of both false-positive and false-negative inferences. Herein, we describe a novel Bayesian pathway analysis approach, the algorithm for learning pathway structure (ALPS), which addresses key limitations in existing approaches to complex data analysis. ALPS uses prior information about pathways in concert with empirical data to identify and quantify complex interactions within networks of factors that mediate an association between an exposure and an outcome. We illustrate ALPS through application to a complex gene-drug interaction analysis in the Predictors of Breast Cancer Recurrence (ProBe CaRe) Study, a Danish cohort study of premenopausal breast cancer patients (2002-2011), for which conventional analyses severely limit the quality of inference., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

An internal validation substudy compares an imperfect measurement of a variable with a gold-standard measurement in a subset of the study population. Validation data permit calculation of a bias-adjusted estimate, which has the same expected value as the association that would have been observed had the gold-standard measurement been available for the entire study population. Existing guidance on optimal sampling for validation substudies assumes complete enrollment and follow-up of the target cohort. No guidance exists for validation substudy design while cohort data are actively being collected. In this article, we use the framework of Bayesian monitoring methods to develop an adaptive approach to validation study design. This method monitors whether sufficient validation data have been collected to meet predefined criteria for estimation of the positive and negative predictive values. We demonstrate the utility of this method using the Study of Transition, Outcomes and Gender-a cohort study of transgender and gender nonconforming people. We demonstrate the method's ability to determine efficacy (when sufficient validation data have accumulated to obtain estimates of the predictive values that fall above a threshold value) and futility (when sufficient validation data have accumulated to conclude the mismeasured variable is an untenable substitute for the gold-standard measurement). This proposed method can be applied within the context of any parent epidemiologic study design and modified to meet alternative criteria given specific study or validation study objectives. Our method provides a novel approach to effective and efficient estimation of classification parameters as validation data accrue.

The electability of the candidates for the 2020 Democratic U.S. presidential nomination was frequently debated. Arguments regarding a candidate's electability often claimed that they would affect the general election by changing the behavior of a certain subset of eligible voters. For example, is it more important electorally that a candidate drive turnout or swing voting? As lay consumers of political opinion, we were having difficulty weighing these questions from a strategic standpoint. Although candidate electability is a nebulous term that might be interpreted in various ways, one interpretation of the term is a population-based causal question: What would the effect of the Democratic nominee be on the presidential election result? Population-based causal questions are commonly studied in epidemiology. To aid interpretation of electability arguments, we frame the question through a counterfactual model used in epidemiology. Specifically, we define the causal effect by characterizing the population of eligible voters into nine counterfactual response types. The definition clarifies our ability to interpret arguments regarding the electability of the candidates. For example, the causal effect can be subdivided into three parts: the effect of the nominee on (1) Democratic turnout, (2) Republican turnout, and (3) swing voting. We show using notation that the third part has twice the weight as the other two. The definition follows intuition. However, we hope its formalization using counterfactual response types may foster interdisciplinary communication., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: The cardiotoxic effects of breast cancer therapies are well documented in clinical trials. However, clinical trials often underrepresent those at highest risk for cardiovascular disease (CVD)related outcomes and have limited generalizability to the larger breast cancer population. In addition, racial differences in treatment-associated CVD mortality have yet to be explored. In this study, we sought to quantify the relationship between breast cancer therapies and CVD mortality, and explore whether this effect differed between non-Hispanic black (NHB) and white (NHW) women., Methods: Using data from the Georgia Cancer Registry, we identified women diagnosed with a first primary invasive breast cancer [2010-2014], residing in the metropolitan Atlanta area (n=3,580 NHB; n=4,923 NHW), and followed them for mortality through December 31, 2018. Exposures of interest included therapies with potential cardiotoxic effects including chemotherapy and hormone therapy, which are routinely collected by the GCR. Individual agents are not captured within the GCR, therefore trastuzumab was identified using natural language processing of textual descriptions. We used propensity score weighted Cox proportional hazards regression to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between each treatment modality and CVD mortality among the overall cohort and by race., Results: In the overall cohort, similar hazards of CVD mortality were found among women treated with chemotherapy (HR =1.10, 95% CI: 0.62, 1.96) and hormone therapy (HR =0.94, 95% CI: 0.59, 1.50), compared to women who did not receive the respective treatments. In contrast, women treated with trastuzumab had a higher hazard of CVD mortality compared to women not treated with trastuzumab (HR =2.05, 95% CI: 0.76, 5.52). In race-specific models, hormone therapy was associated with a higher hazard of CVD mortality among NHB women (HR =2.18, 95% CI: 0.78, 6.12), but not NHW women (HR =0.66, 95% CI: 0.39, 1.13). Similar, albeit attenuated, associations were found for chemotherapy. We were unable to investigate race-specific effects of trastuzumab due to low prevalence and insufficient number of events., Conclusions: In our study, we observed more pronounced associations of chemotherapy and hormone therapy with CVD mortality among NHB women, for whom we know have greater CVD-related comorbidities at breast cancer diagnosis. Patients may benefit from treatment plans that find a balance between curative breast cancer treatment and prevention of CVD-related events and mortality. CVD-related outcomes may be most relevant for women with hormone receptor positive disease due to shared risk factors (e.g., obesity, tobacco use, physical activity) and longer survival., Competing Interests: Conflicts of Interest: K Gogineni reports serving on the advisory board with Pfizer and Lilly corporations, and receives research funding to her institution from Pfizer, Calithera and Merck. The other authors have conflicts of interest to declare.

Background: Tamoxifen and its metabolites compete with estrogen to occupy the estrogen receptor. The conventional dose of adjuvant tamoxifen overwhelms estrogen in this competition, reducing breast cancer recurrence risk by nearly half. Phase I metabolism generates active tamoxifen metabolites, and phase II metabolism deactivates them. No earlier pharmacogenetic study has comprehensively evaluated the metabolism and transport pathways, and no earlier study has included a large population of premenopausal women., Methods: We completed a cohort study of 5,959 Danish nonmetastatic premenopausal breast cancer patients, in whom 938 recurrences occurred, and a case-control study of 541 recurrent cases in a cohort of Danish predominantly postmenopausal breast cancer patients, all followed for 10 years. We collected formalin-fixed paraffin-embedded tumor blocks and genotyped 32 variants in 15 genes involved in tamoxifen metabolism or transport. We estimated conventional associations for each variant and used prior information about the tamoxifen metabolic path to evaluate the importance of metabolic and transporter pathways., Results: No individual variant was notably associated with risk of recurrence in either study population. Both studies showed weak evidence of the importance of phase I metabolism in the clinical response to adjuvant tamoxifen therapy., Conclusions: Consistent with prior knowledge, our results support the role of phase I metabolic capacity in clinical response to tamoxifen. Nonetheless, no individual variant substantially explained the modest phase I effect on tamoxifen response., Impact: These results are consistent with guidelines recommending against genotype-guided prescribing of tamoxifen, and for the first time provide evidence supporting these guidelines in premenopausal women., (©2020 American Association for Cancer Research.)

Background: Breast cancer (BC) survivors are at increased risk of cardiovascular disease (CVD) due to shared risk factors with BC and cardiotoxic treatment effects. We aim to investigate racial differences in mortality due to CVD and BC among women diagnosed with invasive BC., Methods: Data from 407 587 non-Hispanic Black (NHB) and White (NHW) women diagnosed with malignant BC (1990-2014) were obtained from the Surveillance, Epidemiology, and End Results database. Cumulative incidence of mortality due to CVD and BC was calculated by race and age (years). Cox models were used to obtain hazard ratios (HR) and 95% confidence intervals (95%CI) for the association of race/ethnicity with cause-specific mortality., Results: The 20-year cumulative incidence of CVD-related mortality was higher among younger NHBs than NHWs (e.g. age 55-69: 13.3% vs 8.9%, respectively). NHBs had higher incidence of BC-specific mortality than NHWs, regardless of age. There was a monotonic reduction in CVD-related mortality disparities with increasing age (age <55: HR = 3.71, 95%CI: 3.29, 4.19; age 55-68: HR = 2.31, 95%CI: 2.15, 2.49; age 69+: HR = 1.24, 95%CI: 1.19, 1.30). The hazard of BC-specific mortality among NHBs was approximately twice that of NHWs (e.g. age <55: HR = 1.98, 95%CI: 1.92, 2.04)., Conclusions: There are substantial differences in mortality due to CVD and BC between NHB and NHW women diagnosed with invasive BC. Racial differences were greatest among younger women for CVD-related mortality and similar across age groups for BC-specific mortality. Future studies should identify pathways through which race/ethnicity affects cause-specific mortality, to inform efforts towards reducing disparities., (© The Author(s) 2019; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)