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Objectives: Real-world data evaluating weight changes in people living with HIV (PLWH) following switch to integrase strand transfer inhibitor (INSTI), specifically bictegravir (BIC), are limited. This retrospective cohort study analyzed weight changes upon switching to INSTI from non-nucleoside reverse transcriptase inhibitor (NNRTI) or protease inhibitor (PI) in treatment-experienced PLWH., Methods: Adult PLWH (≥18 years) treated with NNRTI or PI (non-switch cohorts) and those switching to INSTI (switch cohorts) between January 1, 2014 and August 31, 2019 were identified using IQVIA's Ambulatory Electronic Medical Records linked to a prescription drug claims database. The associations of switching to INSTI and individual INSTI agents with having ≥5% weight gain at 12 months of follow-up were evaluated, adjusting for demographics and baseline clinical characteristics., Results: At 12 months of follow-up, PLWH in the NNRTI-INSTI switch cohort ( n  = 508) were more likely to have ≥5% weight gain over 12 months compared to the NNRTI non-switch cohort ( n  = 614; odds ratio, OR [95% CI], 1.7 [1.2-2.4]). Switching from NNRTI to dolutegravir (DTG: OR [95% CI], 2.1 [1.4-3.0]) or BIC (2.0 [1.0-4.2]) resulted in significantly higher odds of ≥5% weight gain. PI-INSTI switch ( n  = 295) and non-switch ( n  = 228) cohorts had similar proportions of PLWH with ≥5% (21.1-23.4%) or ≥10% (7.8-7.9%) weight gain, and no significant association was found between switching from PI to INSTI and weight gain., Conclusion: Weight gain and related metabolic health of PLWH switching from NNRTI to DTG or BIC should be closely monitored by clinicians. Further research is needed to assess other metabolic outcomes in PLWH remaining on PI and those who switch from PI to INSTI.

Background: Treatment guidelines recommend integrase strand transfer inhibitor (INSTI)-based antiretroviral therapy (ART) regimens for treatment naïve people living with HIV (PLWH) in the United States (US). This retrospective database study compared weight changes following initiation of INSTI-, non-nucleoside reverse transcriptase inhibitor (NNRTI)-, or protease inhibitor (PI)-based ART in treatment-naïve PLWH., Methods: Adult (≥18 years) PLWH initiated on INSTI, NNRTI, or PI plus ≥2 nucleoside reverse transcriptase inhibitors (NRTI) between 1 January 2014 to 31 August 2019 were identified in IQVIA's Ambulatory Electronic Medical Records (AEMR) linked to prescription drug claims (LRx). Weight changes over up to 36 months (M) of follow-up were compared among PLWH on INSTI- vs. NNRTI- and PI-based ART separately using non-linear mixed effect models, adjusting for demographics and baseline clinical characteristics., Results: The INSTI, NNRTI, and PI cohorts included 931, 245, and 124 PLWH, respectively. For all three cohorts, the majority were male (78.2-81.2%) and overweight/obese (53.6-61.6%) at baseline; 40.8-45.2% of the groups were African American. The INSTI vs. NNRTI/PI cohorts were younger (median age: 38 years vs. 44 years/46 years), had lower weight at ART initiation (mean: 80.9 kg vs. 85.7 kg/85.0 kg), and had higher TAF usage during follow-up (55.6% vs. 24.1%/25.8%; all p  < .05). Multivariate models showed higher weight gain among PLWH in INSTI vs. NNRTI and PI cohorts during treated follow-up (estimated weight gain after 36 M: 7.1 kg vs. 3.8 kg and 3.8 kg, both p  < .05)., Conclusion: Study findings highlight the need to monitor an increase in weight and potential metabolic complications among PLWH starting ART with INSTI.

Introduction: A twice-daily single inhaler triple therapy consisting of budesonide/glycopyrrolate/formoterol fumarate (BGF) was approved by the US Food and Drug Administration (FDA) in July 2020 as a maintenance treatment for patients with chronic obstructive pulmonary disease (COPD). The objective of this AURA study is to describe patient characteristics, exacerbation and treatment history, and healthcare resource utilization (HCRU) before BGF initiation to better inform treatment decisions for prescribers., Methods: This retrospective cohort study leveraged data of all payer types from IQVIA's Longitudinal Prescription Data (LRx) linked to Medical Data (Dx). Patients with COPD who had ⩾1 LRx claim for BGF between 1 October 2020 and 30 September 2021 were included. The date of first BGF claim was the index date. Patient demographic and clinical characteristics, history of COPD exacerbation or related event, treatment history, and HCRU were assessed during the 12 months before index (baseline)., Results: We identified 30,339 patients with COPD initiating BGF (mean age: 68.2 years; 57.1% female; 67.6% Medicare). Unspecified COPD (J44.9; 74.0%) was the most commonly coded COPD phenotype. The most prevalent respiratory conditions/symptoms were dyspnea (50.8%), lower respiratory tract infection (25.3%), and sleep apnea (19.0%). Uncomplicated hypertension (58.8%), dyslipidemia (43.9%), cardiovascular disease (41.4%), and heart failure (19.9%) were the most prevalent nonrespiratory conditions. During the 12-month baseline, 57.9% of patients had evidence of a COPD exacerbation or related event, and 14.9% had ⩾1 COPD-related emergency department (ED) visit; 21.0% of patients had evidence of prior triple therapy use, while 54.3% had ⩾1 oral corticosteroid (OCS) fill. Among OCS users, 29.9% had cumulative exposures >1000 mg [median [Q1-Q3] exposure: 520 (260-1183) mg]., Conclusion: This real-world data analysis indicates that BGF is being initiated in patients with COPD experiencing symptoms and exacerbations despite current therapy, and among patients who have various chronic comorbidities, most often cardiopulmonary-related.

Background: Seasonal influenza poses a substantial clinical and economic burden in the United States and vulnerable populations, including the elderly and those with comorbidities, are at elevated risk for influenza-related medical complications., Methods: We conducted a retrospective cohort study using the IQVIA PharMetrics® Plus claims database in two stages. In Stage 1, we identified patients with evidence of medically-attended influenza during influenza seasons from October 1, 2014 to May 31, 2018 (latest available data for Stage 1) and used a multivariable logistic regression model to identify patient characteristics that predicted 30-day influenza-related hospitalization. The findings from Stage 1 informed high-risk subgroups of interest for Stage 2, where we selected cohorts of influenza patients during influenza seasons from October 1, 2014 to March 1, 2019 and used 1:1 propensity score matching to patients without influenza with similar high-risk characteristics to compare influenza-attributable rates of all-cause hospital and emergency department (ED) visits during follow-up (30-day and in the index influenza season)., Results: In Stage 1, more than 1.6 million influenza cases were identified, of which 18,509 (1.2%) had a hospitalization. Elderly age was associated with 9 times the odds of hospitalization (≥65 years vs. 5-17 years; OR = 9.4, 95% CI 8.8-10.1) and select comorbidities were associated with 2-3 times the odds of hospitalization. In Stage 2, elderly influenza patients with comorbidities had 3 to 7 times higher 30-day hospitalization rates compared to matched patients without influenza, including patients with congestive heart failure (41.0% vs.7.9%), chronic obstructive pulmonary disease (34.6% vs. 6.1%), coronary artery disease (22.8% vs. 3.8%), and late-stage chronic kidney disease (44.1% vs. 13.1%; all p < 0.05)., Conclusions: The risk of influenza-related complications is elevated in the elderly, especially those with certain underlying comorbidities, leading to excess healthcare resource utilization. Continued efforts, beyond currently available vaccines, are needed to reduce influenza burden in high-risk populations., (© 2022. The Author(s).)

Background: The burden associated with schizophrenia is substantial. Impacts on the individual, healthcare system, and society may be particularly striking within the veteran population due to the presence of physical and mental health comorbidities. Disease burden is also influenced by a complex interplay between social determinants of health and health disparities. The objective of the current study was to compare non-healthcare societal outcomes between veterans with and without schizophrenia in the United States Veterans Health Administration (VHA)., Methods: A retrospective cohort study was conducted using the VHA database (01/2013-09/2019; study period). Veterans with schizophrenia (≥2 diagnoses of ICD-9295.xx, ICD-10 F20.x, F21, and/or F25.x during the study period) were identified; the index date was the earliest observed schizophrenia diagnosis. Veterans with schizophrenia were propensity score-matched to those without schizophrenia using baseline characteristics. A 12-month baseline and variable follow-up period were applied. The frequency of unemployment, divorce, incarceration, premature death, and homelessness were compared between the matched cohorts using standardized mean difference (SMD). Risk of unemployment and homelessness were estimated using logistic regression models., Results: A total of 102,207 veterans remained in each cohort after matching (91% male; 61% White [per AMA]; median age, 59 years). Among veterans with schizophrenia, 42% had a substance use disorder and 30% had mental health-related comorbidities, compared with 25 and 15%, respectively, of veterans without schizophrenia. Veterans with schizophrenia were more likely to experience unemployment (69% vs. 41%; SMD: 0.81), divorce (35% vs. 28%; SMD: 0.67), homelessness (28% vs. 7%; SMD: 0.57), incarceration (0.4% vs. 0.1%; SMD: 0.47), and premature death (14% vs. 12%; SMD < 0.1) than veterans without schizophrenia. After further adjustments, the risk of unemployment and of homelessness were 5.4 and 4.5 times higher among veterans with versus without schizophrenia. Other predictors of unemployment included Black [per AMA] race and history of substance use disorder; for homelessness, younger age (18-34 years) and history of mental health-related comorbidities were additional predictors., Conclusion: A greater likelihood of adverse societal outcomes was observed among veterans with versus without schizophrenia. Given their elevated risk for unemployment and homelessness, veterans with schizophrenia should be a focus of targeted, multifactorial interventions to reduce disease burden., (© 2022. The Author(s).)

Background: This study examined MDD treatment regimens received during the first observed and treated major depressive episode (MDE) among US veterans., Methods: This retrospective study, conducted using the Veterans Health Administration (VHA) database, supplemented with Medicare Part A/B/D data, included adults with ≥1 MDD diagnosis (index date) between 10/1/2015-2/28/2017 and ≥1 line of therapy (LOT) within the first observed complete MDE. Patient baseline (6-month pre-index) characteristics and up to six LOTs received during the first observed and treated MDE were assessed., Results: Of 40,240 veterans with MDD identified (mean age: 50.9 years, 83.9% male, 63.4% White, 88.6% non-Hispanic), hypertension (27.5%), hyperlipidemia (20.8%), and post-traumatic stress disorder (17.5%) were the most common baseline comorbidities. During the first observed and treated MDE, patients received a mean of 1.6 ± 1.0 LOTs, with 14.6% of patients receiving ≥3 LOTs. SSRI-monotherapy was the most commonly observed regimen in the first six LOTs, followed by SNRI-monotherapy in LOT 1 and antidepressants augmented by anticonvulsants in the remaining five LOTs. The antidepressant class of the previous LOT was commonly used in the subsequent LOT. SSRI-SSRI-SSRI was the most common LOT1-to-LOT3 sequencing pattern among patients receiving ≥3 LOTs., Limitations: The study findings are limited to data in the VHA database and may not be generalizable to the non-veteran US population., Conclusions: During the first observed and treated MDE, SSRI-monotherapy was the most common therapy in the first six LOTs. Cycling within SSRI class was the leading sequencing pattern of the first three LOTs among veterans who received ≥3 LOTs., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Objectives: To understand real-world implementation of the updated CDC HIV diagnostic testing algorithm., Study Design: Retrospective database analysis., Methods: Using data from Quest Diagnostics, we identified patients with at least 1 HIV-1/HIV-2 antibody differentiation test (BioRad Geenius HIV 1/2 Supplemental Assay [Geenius]) between January 1 and December 31, 2017. Study measures included Health Insurance Portability and Accountability Act-compliant patient demographics, test results, test frequency, and sequence relative to the CDC HIV diagnostic algorithm, including HIV-1 RNA Qualitative Assay (Aptima) or HIV-2 nucleic acid test (NAT)., Results: A total of 26,319 patients were identified (mean [SD] age, 40.7 [14.3] years; 66.4% male), with 28,954 Geenius tests, 7234 Aptima tests, and 298 HIV-2 NATs. In 26.4% of test sequences, the Geenius results were indeterminate or negative and required subsequent confirmatory NATs. A total of 8.5% of patients had more than 1 Geenius test in 2017, and 11.2% of the time, results of the first and second tests differed. A total of 74.2% of test sequences matched the CDC-recommended algorithm., Conclusions: Our study findings suggest that the CDC HIV diagnostic algorithm is complex and may pose suboptimal testing efficiency. Opportunities to improve diagnostic efficiency by reducing indeterminate results and repeat tests are warranted.

Objective: To evaluate frequency, severity and costs of flares in US patients with newly diagnosed SLE., Methods: Adults diagnosed with SLE between January 2005 and December 2014 were identified from US commercial claims data linked to electronic medical records. Disease and flare severity during 1 year after diagnosis were classified as mild, moderate or severe using a claims-based algorithm. Study outcomes included frequency and severity of flares stratified by disease severity during the 1-year post-diagnosis period and all-cause healthcare costs of flares by severity at 30, 60 and 90 days after flare., Results: Among 2227 patients, 26.3%, 51.0% and 22.7% had mild, moderate and severe SLE, respectively. The overall annual flare rate was 3.5 and increased with disease severity: 2.2, 3.7 and 4.2, respectively, for mild, moderate and severe SLE (p<0.0001). Patients with severe SLE had a higher annual severe flare rate (0.6) compared with moderate (0.1) or mild SLE (0; p<0.0001). Mean total all-cause costs at 30, 60 and 90 days after flare were $16 856, $22 252 and $27 468, respectively, for severe flares (mild flares: $1672, $2639 and $3312; moderate flares: $3831, $6225, $8582; (p<0.0001, all time points)). Inpatient costs were the primary driver of the increased cost of severe flares., Conclusions: Flare frequency and severity in newly diagnosed patients with SLE increase with disease severity. After a flare, healthcare costs increase over the following 90 days by disease severity. Preventing flares or reducing flare rates and duration may improve outcomes and reduce healthcare costs., Competing Interests: Competing interests: ERH, BD, XW and MJ are employees of AstraZeneca. AMN is an employee of IQVIA and was paid by AstraZeneca to conduct this research study., (© 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.)

Objective: To assess the economic burden of patients with SLE by disease severity in the USA 1 year before and after diagnosis., Methods: Patients aged ≥18 years with a first SLE diagnosis (index date) between January 2005 and December 2014 were identified from administrative commercial claims data linked to electronic medical records (EMRs). Disease severity during the year after diagnosis was classified as mild, moderate, or severe using claims-based algorithms and EMR data. Healthcare resource utilisation (HCRU) and all-cause healthcare costs (2017 US$) were reported for 1 year pre-diagnosis and post-diagnosis. Generalised linear modelling examined all-cause costs over 1 year post-index, adjusting for baseline demographics, clinical characteristics, Charlson Comorbidity Index and 1 year pre-diagnosis costs., Results: Among 2227 patients, 26.3% had mild, 51.0% moderate and 22.7% severe SLE. Mean per-patient costs were higher for patients with moderate and severe SLE compared with mild SLE during the year before diagnosis: mild US$12 373, moderate $22 559 and severe US$39 261 (p<0.0001); and 1-year post-diagnosis period: mild US$13 415, moderate US$29 512 and severe US$68 260 (p<0.0001). Leading mean cost drivers were outpatient visits (US$13 566) and hospitalisations (US$10 252). Post-diagnosis inpatient utilisation (≥1 stay) was higher for patients with severe (51.2%) and moderate (22.4%) SLE, compared with mild SLE (12.8%), with longer mean hospital stays: mild 0.47 days, moderate 1.31 days and severe 5.52 days (p<0.0001)., Conclusion: HCRU and costs increase with disease severity in the year before and after diagnosis; leading cost drivers post-diagnosis were outpatient visits and hospitalisations. Earlier diagnosis and treatment may improve health outcomes and reduce HCRU and costs., Competing Interests: Competing interests: MJ, BD, XW and ERH are employees of AstraZeneca. AMN is an employee of IQVIA and was paid by AstraZeneca to conduct this research study., (© 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.)

Objectives: Gonadotropin-releasing hormone analogs are the treatment of choice for central precocious puberty (CPP). This study characterizes patients treated with histrelin implant or leuprolide injection., Methods: A US claims database was used to identify patients aged ≤20 years with ≥1 histrelin or leuprolide claim (index treatment) between April 2010 and November 2017 and continuous enrollment ≥3 months before and ≥12 months after the index treatment date., Results: Overall, 4,217 patients (histrelin, n=1,001; leuprolide, n=3,216) were identified. The percentage of patients with CPP diagnosis was greater in the histrelin (96.5%) vs. leuprolide (68.8%; p<0.0001) cohort. In patients with CPP (histrelin, n=966; leuprolide, n=2,214), mean age at treatment initiation was similar for histrelin (9.0 ± 2.0 years) and leuprolide (9.1 ± 2.3 years), with >50% of patients aged 6-9 years. Mean treatment duration was significantly longer for histrelin (26.7 ± 14.8 months) vs. leuprolide (14.1 ± 12.1 months; p<0.0001), and was longer in younger patient groups. More patients switched from leuprolide to histrelin (12.3%) than vice versa (3.6%; p<0.0001). Median annual total treatment costs were slightly lower for the histrelin cohort ($23,071 [interquartile range, $16,833-$31,050]) than the leuprolide cohort ($27,021 [interquartile range, $18,314-$34,995]; p<0.0001)., Conclusions: Patients with CPP treated with histrelin had a longer duration of treatment, lower rates of index treatment discontinuation, and lower annual treatment costs vs. those treated with leuprolide., (© 2021 Lawrence A. Silverman et al., published by De Gruyter, Berlin/Boston.)

Background: The Georgetown University-Albert Einstein College of Medicine breast cancer simulation model (Model GE) has evolved over time in structure and function to reflect advances in knowledge about breast cancer, improvements in early detection and treatment technology, and progress in computing resources. This article describes the model and provides examples of model applications., Methods: The model is a discrete events microsimulation of single-life histories of women from multiple birth cohorts. Events are simulated in the absence of screening and treatment, and interventions are then applied to assess their impact on population breast cancer trends. The model accommodates differences in natural history associated with estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) biomarkers, as well as conventional breast cancer risk factors. The approach for simulating breast cancer natural history is phenomenological, relying on dates, stage, and age of clinical and screen detection for a tumor molecular subtype without explicitly modeling tumor growth. The inputs to the model are regularly updated to reflect current practice. Numerous technical modifications, including the use of object-oriented programming (C++), and more efficient algorithms, along with hardware advances, have increased program efficiency permitting simulations of large samples., Results: The model results consistently match key temporal trends in US breast cancer incidence and mortality., Conclusion: The model has been used in collaboration with other CISNET models to assess cancer control policies and will be applied to evaluate clinical trial design, recurrence risk, and polygenic risk-based screening.

Background: Since their inception in 2000, the Cancer Intervention and Surveillance Network (CISNET) breast cancer models have collaborated to use a nationally representative core of common input parameters to represent key components of breast cancer control in each model. Employment of common inputs permits greater ability to compare model output than when each model begins with different input parameters. The use of common inputs also enhances inferences about the results, and provides a range of reasonable results based on variations in model structure, assumptions, and methods of use of the input values. The common input data are updated for each analysis to ensure that they reflect the most current practice and knowledge about breast cancer. The common core of parameters includes population rates of births and deaths; age- and cohort-specific temporal rates of breast cancer incidence in the absence of screening and treatment; effects of risk factors on incidence trends; dissemination of plain film and digital mammography; screening test performance characteristics; stage or size distribution of screen-, interval-, and clinically- detected tumors by age; the joint distribution of ER/HER2 by age and stage; survival in the absence of screening and treatment by stage and molecular subtype; age-, stage-, and molecular subtype-specific therapy; dissemination and effectiveness of therapies over time; and competing non-breast cancer mortality., Method and Results: In this paper, we summarize the methods and results for the common input values presently used in the CISNET breast cancer models, note assumptions made because of unobservable phenomena and/or unavailable data, and highlight plans for the development of future parameters., Conclusion: These data are intended to enhance the transparency of the breast CISNET models.

Background: Molecular characterization of breast cancer allows subtype-directed interventions. Estrogen receptor (ER) is the longest-established molecular marker., Methods: We used six established population models with ER-specific input parameters on age-specific incidence, disease natural history, mammography characteristics, and treatment effects to quantify the impact of screening and adjuvant therapy on age-adjusted US breast cancer mortality by ER status from 1975 to 2000. Outcomes included stage-shifts and absolute and relative reductions in mortality; sensitivity analyses evaluated the impact of varying screening frequency or accuracy., Results: In the year 2000, actual screening and adjuvant treatment reduced breast cancer mortality by a median of 17 per 100000 women (model range = 13-21) and 5 per 100000 women (model range = 3-6) for ER-positive and ER-negative cases, respectively, relative to no screening and no adjuvant treatment. For ER-positive cases, adjuvant treatment made a higher relative contribution to breast cancer mortality reduction than screening, whereas for ER-negative cases the relative contributions were similar for screening and adjuvant treatment. ER-negative cases were less likely to be screen-detected than ER-positive cases (35.1% vs 51.2%), but when screen-detected yielded a greater survival gain (five-year breast cancer survival = 35.6% vs 30.7%). Screening biennially would have captured a lower proportion of mortality reduction than annual screening for ER-negative vs ER-positive cases (model range = 80.2%-87.8% vs 85.7%-96.5%)., Conclusion: As advances in risk assessment facilitate identification of women with increased risk of ER-negative breast cancer, additional mortality reductions could be realized through more frequent targeted screening, provided these benefits are balanced against screening harms., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Obesity affects multiple points along the breast cancer control continuum from prevention to screening and treatment, often in opposing directions. Obesity is also more prevalent in Blacks than Whites at most ages so it might contribute to observed racial disparities in mortality. We use two established simulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) to evaluate the impact of obesity on race-specific breast cancer outcomes. The models use common national data to inform parameters for the multiple US birth cohorts of Black and White women, including age- and race-specific incidence, competing mortality, mammography characteristics, and treatment effectiveness. Parameters are modified by obesity (BMI of ≥ 30 kg/m(2)) in conjunction with its age-, race-, cohort- and time-period-specific prevalence. We measure age-standardized breast cancer incidence and mortality and cases and deaths attributable to obesity. Obesity is more prevalent among Blacks than Whites until age 74; after age 74 it is more prevalent in Whites. The models estimate that the fraction of the US breast cancer cases attributable to obesity is 3.9-4.5 % (range across models) for Whites and 2.5-3.6 % for Blacks. Given the protective effects of obesity on risk among women <50 years, elimination of obesity in this age group could increase cases for both the races, but decrease cases for women ≥ 50 years. Overall, obesity accounts for 4.4-9.2 % and 3.1-8.4 % of the total number of breast cancer deaths in Whites and Blacks, respectively, across models. However, variations in obesity prevalence have no net effect on race disparities in breast cancer mortality because of the opposing effects of age on risk and patterns of age- and race-specific prevalence. Despite its modest impact on breast cancer control and race disparities, obesity remains one of the few known modifiable risks for cancer and other diseases, underlining its relevance as a public health target.

Background: Timing of initiation of screening for breast cancer is controversial in the United States., Objective: To determine the threshold relative risk (RR) at which the harm-benefit ratio of screening women aged 40 to 49 years equals that of biennial screening for women aged 50 to 74 years., Design: Comparative modeling study., Data Sources: Surveillance, Epidemiology, and End Results program, Breast Cancer Surveillance Consortium, and medical literature., Target Population: A contemporary cohort of women eligible for routine screening., Time Horizon: Lifetime., Perspective: Societal., Intervention: Mammography screening starting at age 40 versus 50 years with different screening methods (film, digital) and screening intervals (annual, biennial)., Benefits: life-years gained, breast cancer deaths averted; harms: false-positive mammography findings; harm-benefit ratios: false-positive findings/life-years gained, false-positive findings/deaths averted., Results of Base-Case Analysis: Screening average-risk women aged 50 to 74 years biennially yields the same false-positive findings/life-years gained as biennial screening with digital mammography starting at age 40 years for women with a 2-fold increased risk above average (median threshold RR, 1.9 [range across models, 1.5 to 4.4]). The threshold RRs are higher for annual screening with digital mammography (median, 4.3 [range, 3.3 to 10]) and when false-positive findings/deaths averted is used as an outcome measure instead of false-positive findings/life-years gained. The harm-benefit ratio for film mammography is more favorable than for digital mammography because film has a lower false-positive rate., Results of Sensitivity Analysis: The threshold RRs changed slightly when a more comprehensive measure of harm was used and were relatively insensitive to lower adherence assumptions., Limitation: Risk was assumed to influence onset of disease without influencing screening performance., Conclusion: Women aged 40 to 49 years with a 2-fold increased risk have similar harm-benefit ratios for biennial screening mammography as average-risk women aged 50 to 74 years. Threshold RRs required for favorable harm-benefit ratios vary by screening method, interval, and outcome measure., Primary Funding Source: National Cancer Institute.

Objective: To investigate the association between self-reported endometriosis and the putative functional promoter +331C/T single nucleotide polymorphism and the PROGINS allele., Design: Control subjects from ovarian cancer case-control studies participating in the international Ovarian Cancer Association Consortium. The majority of controls are drawn from population-based studies., Setting: An international ovarian cancer consortium including studies from Australia, Europe, and the United States., Patient(s): Five thousand eight hundred twelve white female controls, of whom 348 had endometriosis, from eight ovarian cancer case-control studies., Intervention(s): None., Main Outcome Measure(s): Genotypes for the +331C/T single nucleotide polymorphism and PROGINS allele and a history of endometriosis., Result(s): The occurrence of endometriosis was reduced in women carrying one or more copies of the +331 T allele (odds ratio=0.65; 95% confidence interval: 0.43-0.98), whereas there was no association between the PROGINS allele and endometriosis (odds ratio=0.94, 95% confidence interval 0.76-1.16)., Conclusion(s): Additional studies of the +331C/T variant are warranted given the current finding and the equivocal results of previous studies. The +331 T allele has been shown to result in a reduced progesterone (P) receptor A to P receptor B ratio, and if the observed association with endometriosis is confirmed it would suggest that this ratio is important for this disease., (Copyright © 2011. Published by Elsevier Inc.)

Background: U.S. Black women have higher breast cancer mortality rates than White women despite lower incidence. The aim of this study is to investigate how much of the mortality disparity can be attributed to racial differences in natural history, uptake of mammography screening, and use of adjuvant therapy., Methods: Two simulation models use common national race, and age-specific data for incidence, screening and treatment dissemination, stage distributions, survival, and competing mortality from 1975 to 2010. Treatment effectiveness and mammography sensitivity are assumed to be the same for both races. We sequentially substituted Black parameters into the White model to identify parameters that drive the higher mortality for Black women in the current time period., Results: Both models accurately reproduced observed breast cancer incidence, stage and tumor size distributions, and breast cancer mortality for White women. The higher mortality for Black women could be attributed to differences in natural history parameters (26-44%), use of adjuvant therapy (11-19%), and uptake of mammography screening (7-8%), leaving 38% to 46% unexplained., Conclusion: Black women appear to have benefited less from cancer control advances than White women, with a greater race-related gap in the use of adjuvant therapy than screening. However, a greater portion of the disparity in mortality appears to be due to differences in natural history and undetermined factors., Impact: Breast cancer mortality may be reduced substantially by ensuring that Black women receive equal adjuvant treatment and screening as White women. More research on racial variation in breast cancer biology and treatment utilization is needed., (©2011 AACR.)