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BACKGROUND: Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old. OBJECTIVE: To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family history, breast density, prior biopsy) and comorbidity level to support SDM in clinical practice. DESIGN, SETTING, AND PARTICIPANTS: We adapted two established Cancer Intervention and Surveillance Modeling Network (CISNET) models to evaluate the remaining lifetime benefits and harms of screening U.S. women born in 1940, at decision ages 75, 80, and 85 years considering their individual risk factors and comorbidity levels. Results were summarized for average- and higher-risk women (defined as having breast cancer family history, heterogeneously dense breasts, and no prior biopsy, 5% of the population). MAIN OUTCOMES AND MEASURES: Remaining lifetime breast cancers detected, deaths (breast cancer/other causes), false positives, and overdiagnoses for average- and higher-risk women by age and comorbidity level for screening (one or five screens) vs. no screening per 1000 women. RESULTS: Compared to stopping, one additional screen at 75 years old resulted in six and eight more breast cancers detected (10% overdiagnoses), one and two fewer breast cancer deaths, and 52 and 59 false positives per 1000 average- and higher-risk women without comorbidities, respectively. Five additional screens over 10 years led to 23 and 31 additional breast cancer cases (29-31% overdiagnoses), four and 15 breast cancer deaths avoided, and 238 and 268 false positives per 1000 average- and higher-risk screened women without comorbidities, respectively. Screening women at older ages (80 and 85 years old) and high comorbidity levels led to fewer breast cancer deaths and a higher percentage of overdiagnoses. CONCLUSIONS: Simulation models show that continuing screening in women ≥ 75 years old results in fewer breast cancer deaths but more false positive tests and overdiagnoses. Together, clinicians and 75 + women may use model output to weigh the benefits and harms of continued screening.
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Neoplasias de la Mama , Mamografía , Femenino , Humanos , Anciano de 80 o más Años , Anciano , Mamografía/efectos adversos , Mamografía/métodos , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/epidemiología , Mama , Densidad de la Mama , Simulación por Computador , Detección Precoz del Cáncer/efectos adversos , Detección Precoz del Cáncer/métodos , Tamizaje Masivo/efectos adversos , Tamizaje Masivo/métodosRESUMEN
BACKGROUND: A recent trial showed that postmenopausal women diagnosed with hormone receptor-positive, human epidermal growth factor receptor-2 (HER2)-negative, lymph node-positive (1-3 nodes) breast cancer with a 21-gene recurrence score of ≤ 25 could safely omit chemotherapy. However, there are limited data on population-level long-term outcomes associated with omitting chemotherapy among diverse women seen in real-world practice. METHODS: We adapted an established, validated simulation model to generate the joint distributions of population-level characteristics of women diagnosed with early-stage breast cancer in the U.S. Input parameters were derived from cancer registry, meta-analyses, and clinical trial data. The effects of omitting chemotherapy on 10-year distant recurrence-free survival, life-years, and quality adjusted life-years (QALYs) were modeled for premenopausal and postmenopausal women. QALYs were discounted at 3%. Results were evaluated for subgroups stratified by race and ethnicity. Sensitivity analyses included testing results across a range of inputs. The model was validated using the published RxPONDER trial data. RESULTS: In premenopausal women, the 10-year distant recurrence-free survival rates were 85.3% with chemo-endocrine and 80.1% with endocrine therapy. The estimated life-years and QALYs gained with chemotherapy in premenopausal women were 2.1 and 0.6, respectively. There was no chemotherapy benefit in postmenopausal women. There was no variation in the absolute benefit of chemotherapy across racial or ethnic subgroups. However, there were differences in distant recurrence-free survival rates, life-years, and QALYs across groups. Sensitivity analysis showed similar results. The model closely replicated the RxPONDER trial. CONCLUSIONS: Modeled population-level outcomes show a small chemotherapy benefit in premenopausal women, but no benefit among postmenopausal women. Simulation modeling provides a useful tool to extend trial data and evaluate population-level outcomes.
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Neoplasias de la Mama , Humanos , Femenino , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/genética , Neoplasias de la Mama/patología , Neoplasias de la Mama/mortalidad , Persona de Mediana Edad , Adulto , Anciano , Simulación por Computador , Premenopausia , Posmenopausia , Años de Vida Ajustados por Calidad de Vida , Metástasis Linfática , Perfilación de la Expresión Génica/métodos , Recurrencia Local de Neoplasia/genética , Receptor ErbB-2/genética , Receptor ErbB-2/metabolismo , Supervivencia sin EnfermedadRESUMEN
Introduction. Personalized web-based clinical decision tools for breast cancer prevention and screening could address knowledge gaps, enhance patient autonomy in shared decision-making, and promote equitable care. The purpose of this review was to present evidence on the availability, usability, feasibility, acceptability, quality, and uptake of breast cancer prevention and screening tools to support their integration into clinical care. Methods. We used the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews Checklist to conduct this review. We searched 6 databases to identify literature on the development, validation, usability, feasibility, acceptability testing, and uptake of the tools into practice settings. Quality assessment for each tool was conducted using the International Patient Decision Aid Standard instrument, with quality scores ranging from 0 to 63 (lowest-highest). Results. We identified 10 tools for breast cancer prevention and 9 tools for screening. The tools included individual (e.g., age), clinical (e.g., genomic risk factors), and health behavior (e.g., alcohol use) characteristics. Fourteen tools included race/ethnicity, but no tool incorporated contextual factors (e.g., insurance, access) associated with breast cancer. All tools were internally or externally validated. Six tools had undergone usability testing in samples including White (median, 71%; range, 9%-96%), insured (99%; 97%-100%) women, with college education or higher (60%; 27%-100%). All of the tools were developed and tested in academic settings. Seven (37%) tools showed potential evidence of uptake in clinical practice. The tools had an average quality assessment score of 21 (range, 9-39). Conclusions. There is limited evidence on testing and uptake of breast cancer prevention and screening tools in diverse clinical settings. The development, testing, and integration of tools in academic and nonacademic settings could potentially improve uptake and equitable access to these tools. Highlights: There were 19 personalized, interactive, Web-based decision tools for breast cancer prevention and screening.Breast cancer outcomes were personalized based on individual clinical characteristics (e.g., age, medical history), genomic risk factors (e.g., BRCA1/2), race and ethnicity, and health behaviors (e.g., smoking). The tools did not include contextual factors (e.g., insurance status, access to screening facilities) that could potentially contribute to breast cancer outcomes.Validation, usability, acceptability, and feasibility testing were conducted mostly among White and/or insured patients with some college education (or higher) in academic settings. There was limited evidence on testing and uptake of the tools in nonacademic clinical settings.
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PURPOSE: We reviewed existing personalized, web-based, interactive decision-making tools available to guide breast cancer treatment and survivorship care decisions in clinical settings. METHODS: The study was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). We searched PubMed and related databases for interactive web-based decision-making tools developed to support breast cancer treatment and survivorship care from 2013 to 2023. Information on each tool's purpose, target population, data sources, individual and contextual characteristics, outcomes, validation, and usability testing were extracted. We completed a quality assessment for each tool using the International Patient Decision Aid Standard (IPDAS) instrument. RESULTS: We found 54 tools providing personalized breast cancer outcomes (e.g., recurrence) and treatment recommendations (e.g., chemotherapy) based on individual clinical (e.g., stage), genomic (e.g., 21-gene-recurrence score), behavioral (e.g., smoking), and contextual (e.g., insurance) characteristics. Forty-five tools were validated, and nine had undergone usability testing. However, validation and usability testing included mostly White, educated, and/or insured individuals. The average quality assessment score of the tools was 16 (range: 6-46; potential maximum: 63). CONCLUSIONS: There was wide variation in the characteristics, quality, validity, and usability of the tools. Future studies should consider diverse populations for tool development and testing. IMPLICATIONS FOR CANCER SURVIVORS: There are tools available to support personalized breast cancer treatment and survivorship care decisions in clinical settings. It is important for both cancer survivors and physicians to carefully consider the quality, validity, and usability of these tools before using them to guide care decisions.
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BACKGROUND: Seasonal patterns in measured exposure biomarkers can cause measurement error in epidemiological studies. There is little research about the seasonality of metals and trace elements when assessed in toenail samples. Adjusting for such patterns in models for estimating associations between long-term exposures and health outcomes can potentially improve precision and reduce bias. OBJECTIVES: Assess and describe seasonal patterns in toenail measurements of trace elements. METHODS: The Sister Study enrolled women residing in the US, including Puerto Rico, whose sister had been diagnosed with breast cancer. At the time of enrollment, participants removed nail polish and collected their toenail clippings, which were cleaned before analysis. We considered the following elements: iron, vanadium, aluminum, chromium, manganese, cobalt, nickel, copper, zinc, arsenic, selenium, molybdenum, cadmium, tin, antimony, mercury, and lead. For two subsamples of the cohort, we fit trigonometric regression models with toenail element measures as the outcome, using sine and cosine functions of the collection day (transformed to an angle) to capture seasonal patterns. These models can estimate the amplitude and timing of the peaks in measures. We evaluated the evidence for a seasonal effect by comparing for each measured element the trigonometric model to a model that was constant across time. RESULTS: There was a seasonal trend in toenail element concentration for iron, aluminum, vanadium, chromium, manganese, cobalt, arsenic, molybdenum, cadmium, tin, and lead, all of which peaked near mid-August. Seasonal patterns were concordant across two non-overlapping samples of women, analyzed in different labs. DISCUSSION: Given the evidence supporting seasonal patterns for 11 of the 17 elements measured in toenails, correcting for seasonality of toenail levels of those trace elements in models estimating the association between those exposures and health outcomes is important. The basis for higher concentrations in toenails collected during the summer remains unknown.
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Seasonal patterns in measured exposure biomarkers can cause measurement error in epidemiological studies. There is little known about the seasonality of trace elements when measured in toenails. Adjusting for such patterns when estimating associations between long-term exposures and health outcomes could be needed to improve precision and reduce bias. Our goal was to assess seasonal patterns in toenail measurements of trace elements. At enrollment, Sister Study participants, who were US residents, removed polish and collected toenail clippings, which were cleaned before analysis. We measured: iron, vanadium, aluminum, chromium, manganese, cobalt, nickel, copper, zinc, arsenic, selenium, molybdenum, cadmium, tin, antimony, mercury, and lead. For a sample of the cohort we fit trigonometric regression models with toenail element measures as the outcome, using sine and cosine functions of the collection day of the year (transformed to an angle) to assess seasonality. Results were replicated in a second sample of women, with measurements done in a separate lab. There was a seasonal association between day of collection and toenail measures for iron, aluminum, vanadium, chromium, manganese, cobalt, arsenic, molybdenum, cadmium, tin, and lead, all of which peaked near mid-August. Seasonal patterns were concordant across the two samples of women. Given the evidence supporting seasonal patterns for 11 of the 17 elements measured in toenails, correcting for seasonality of toenail levels of those trace elements in models estimating the association between those exposures and health outcomes is important. The basis for higher concentrations in toenails collected during the summer remains unknown.
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PURPOSE: Structural racism could contribute to racial and ethnic disparities in cancer mortality via its broad effects on housing, economic opportunities, and health care. However, there has been limited focus on incorporating structural racism into simulation models designed to identify practice and policy strategies to support health equity. We reviewed studies evaluating structural racism and cancer mortality disparities to highlight opportunities, challenges, and future directions to capture this broad concept in simulation modeling research. METHODS: We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review Extension guidelines. Articles published between 2018 and 2023 were searched including terms related to race, ethnicity, cancer-specific and all-cause mortality, and structural racism. We included studies evaluating the effects of structural racism on racial and ethnic disparities in cancer mortality in the United States. RESULTS: A total of 8345 articles were identified, and 183 articles were included. Studies used different measures, data sources, and methods. For example, in 20 studies, racial residential segregation, one component of structural racism, was measured by indices of dissimilarity, concentration at the extremes, redlining, or isolation. Data sources included cancer registries, claims, or institutional data linked to area-level metrics from the US census or historical mortgage data. Segregation was associated with worse survival. Nine studies were location specific, and the segregation measures were developed for Black, Hispanic, and White residents. CONCLUSIONS: A range of measures and data sources are available to capture the effects of structural racism. We provide a set of recommendations for best practices for modelers to consider when incorporating the effects of structural racism into simulation models.
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Neoplasias , Racismo Sistemático , Humanos , Negro o Afroamericano , Disparidades en el Estado de Salud , Neoplasias/mortalidad , Neoplasias/terapia , Estados Unidos/epidemiología , Hispánicos o Latinos , BlancoRESUMEN
BACKGROUND: While inhaled corticosteroids (ICS) are considered the essential foundation of most asthma therapy, ICS inhaler nonadherence is a notoriously common problem and a significant cause of asthma-related morbidity. Partially acknowledging the problem of nonadherence, international organizations recently made paradigm-shifting recommendations that all patients with mild-to-moderate persistent asthma be considered for symptom-driven ICS-containing inhalers rather than relying on adherence to traditional maintenance ICS inhalers and symptom-driven short-acting beta-agonists (SABA). With this new approach, asthma patients are at least exposed to the important anti-inflammatory effects of ICS-containing inhalers when their symptom reliever inhaler is deployed due to acute symptoms. METHODS: This study will (Part 1) complete a pragmatic randomized controlled trial to evaluate if an inhaler strategy that utilizes symptom-driven ICS inhalers is particularly beneficial in maintenance ICS inhaler non-adherent asthma patients, and (Part 2) use a dissemination and implementation (D&I) science conceptual framework to better understand patients' and providers' views of inhaler nonadherence. This study, which will have an option of taking place entirely remotely, will use a Food and Drug Administration (FDA)-approved electronic sensor (Hailie® sensor) to monitor inhaler adherence and includes semi-structured interviews guided by the Consolidated Framework for Implementation Research (CFIR). DISCUSSION: This study is assessing the problem of nonadherence using a D&I implementation science research lens while testing a new inhaler approach to potentially ameliorate the detrimental consequences of maintenance inhaler nonadherence. We hypothesize that the use of a symptom-driven ICS/LABA management strategy, as compared to traditional maintenance ICS treatment and symptom-driven SABA, will lead to improved adherence to an asthma treatment strategy, decreased asthma-related morbidity, less cumulative ICS exposure, and greater patient satisfaction with an inhaler approach. TRIAL REGISTRATION: ClinicalTrials.gov NCT05111262. Registered on November 8, 2021.