Modeling the dissemination of mammography in the United States

Assessing breast self-examination knowledge and practices among women in Iraq: A cross-sectional study

Background and Aims

The present study aims to shed light on the knowledge, attitude, and practice of breast self-examination with breast cancer (BC) among female patients in the oncology department of Baghdad Medical City.

Methods

This cross-sectional study involved 100 female participants at the Oncology Teaching Hospital in Baghdad Medical City between June 15 and October 15, 2022. Using convenient sampling, the study targeted females aged 30-75, recently or previously diagnosed with BC, admitted for treatment and follow-ups.

Results

Regarding the assessment of knowledge, among the surveyed patients, 71 are aware of breast self-examination (BSE), primarily through social media (42 patients). The study also explores the link between BSE and education levels. While Pearson's chi-square shows no significance (0.107), the likelihood ratio suggests a significant association (0.041). Regarding the analysis of attitudes, the study assessment for the reasons for compliance showed that 19 patients cite medical reasons, and 48 patients attribute noncompliance to a lack of knowledge of how to perform BSE. Regarding the examination of practice, high statistical significance is evident in both Pearson's chi-square (0.000) and likelihood ratio (0.000) tests, emphasizing the substantial relationship between the post-diagnosis initiation timing of BSE and its correct execution. Additionally, a statistically significant association exists between performing BSE correctly and discovering BC (p = 0.000).

Conclusion

Regarding the assessment of knowledge, our study found high awareness of BSE within the population, primarily through social media and health organizations. Regarding the analysis of attitudes, a notable proportion refrained from practicing BSE, primarily due to a perceived lack of knowledge about the methods. Regarding the examination of practice, the observed significant associations between performing BSE correctly, discovering BC, and the frequency of examinations underscore the pivotal role of consistent and accurate BSE in early detection.

Unlocking Early Cancer Detection: Exploring Biomarkers, Circulating DNA, and Innovative Technological Approaches

Research and development improvements in early cancer diagnosis have had a significant positive impact on health. In the treatment and prevention of cancer, early detection is essential. In this context, biomarkers are essential because they offer important information on the state of cells at any particular time. Cells go through unique changes when they shift from a healthy condition to a malignant state, changes that appropriate biomarkers may pick up. Recent advancements have been made to identify and characterize circulating cancer-specific mutations in cell-free circulating DNA derived from tumors and tumor cells. A patient's delay between the time they first detect symptoms and the time they contact a doctor has been noted for many cancer forms. The tumor's location and features significantly impact the presentation of symptoms judged appropriate for early diagnosis. Lack of knowledge of the severity of the symptoms may be one cause for this delay. Our review is largely focused on the ongoing developments of early diagnosis in the study of biomarkers, circulating DNA for diagnosis, the biology of early challenges, early symptoms, liquid biopsies, detectable by imaging, established tumor markers, plasma DNA technologies, gender differences, and artificial intelligence (AI) in diagnosis. This review aims to determine and evaluate Indicators for detecting early cancer, assessing medical conditions, and evaluating potential risks. For Individuals with a heightened likelihood of developing cancer or who have already been diagnosed, early identification is crucial for enhancing prognosis and raising the likelihood of effective treatment.

Population simulation modeling of disparities in US breast cancer mortality

BACKGROUND

Populations of African American or Black women have persistently higher breast cancer mortality than the overall US population, despite having slightly lower age-adjusted incidence.

METHODS

Three Cancer Intervention and Surveillance Modeling Network simulation teams modeled cancer mortality disparities between Black female populations and the overall US population. Model inputs used racial group-specific data from clinical trials, national registries, nationally representative surveys, and observational studies. Analyses began with cancer mortality in the overall population and sequentially replaced parameters for Black populations to quantify the percentage of modeled breast cancer morality disparities attributable to differences in demographics, incidence, access to screening and treatment, and variation in tumor biology and response to therapy.

RESULTS

Results were similar across the 3 models. In 2019, racial differences in incidence and competing mortality accounted for a net ‒1% of mortality disparities, while tumor subtype and stage distributions accounted for a mean of 20% (range across models = 13%-24%), and screening accounted for a mean of 3% (range = 3%-4%) of the modeled mortality disparities. Treatment parameters accounted for the majority of modeled mortality disparities: mean = 17% (range = 16%-19%) for treatment initiation and mean = 61% (range = 57%-63%) for real-world effectiveness.

CONCLUSION

Our model results suggest that changes in policies that target improvements in treatment access could increase breast cancer equity. The findings also highlight that efforts must extend beyond policies targeting equity in treatment initiation to include high-quality treatment completion. This research will facilitate future modeling to test the effects of different specific policy changes on mortality disparities.

Long-Term Outcomes and Cost-Effectiveness of Breast Cancer Screening With Digital Breast Tomosynthesis in the United States

BACKGROUND

Digital breast tomosynthesis (DBT) is increasingly being used for routine breast cancer screening. We projected the long-term impact and cost-effectiveness of DBT compared to conventional digital mammography (DM) for breast cancer screening in the United States.

METHODS

Three Cancer Intervention and Surveillance Modeling Network breast cancer models simulated US women ages 40 years and older undergoing breast cancer screening with either DBT or DM starting in 2011 and continuing for the lifetime of the cohort. Screening performance estimates were based on observational data; in an alternative scenario, we assumed 4% higher sensitivity for DBT. Analyses used federal payer perspective; costs and utilities were discounted at 3% annually. Outcomes included breast cancer deaths, quality-adjusted life-years (QALYs), false-positive examinations, costs, and incremental cost-effectiveness ratios (ICERs).

RESULTS

Compared to DM, DBT screening resulted in a slight reduction in breast cancer deaths (range across models 0-0.21 per 1000 women), small increase in QALYs (1.97-3.27 per 1000 women), and a 24-28% reduction in false-positive exams (237-268 per 1000 women) relative to DM. ICERs ranged from $195 026 to $270 135 per QALY for DBT relative to DM. When assuming 4% higher DBT sensitivity, ICERs decreased to $130 533-$156 624 per QALY. ICERs were sensitive to DBT costs, decreasing to $78 731 to $168 883 and $52 918 to $118 048 when the additional cost of DBT was reduced to $36 and $26 (from baseline of $56), respectively.

CONCLUSION

DBT reduces false-positive exams while achieving similar or slightly improved health benefits. At current reimbursement rates, the additional costs of DBT screening are likely high relative to the benefits gained; however, DBT could be cost-effective at lower screening costs.

Modeling the natural history of ductal carcinoma in situ based on population data

Background

The incidence of ductal carcinoma in situ (DCIS) has increased substantially since the introduction of mammography screening. Nevertheless, little is known about the natural history of preclinical DCIS in the absence of biopsy or complete excision.

Methods

Two well-established population models evaluated six possible DCIS natural history submodels. The submodels assumed 30%, 50%, or 80% of breast lesions progress from undetectable DCIS to preclinical screen-detectable DCIS; each model additionally allowed or prohibited DCIS regression. Preclinical screen-detectable DCIS could also progress to clinical DCIS or invasive breast cancer (IBC). Applying US population screening dissemination patterns, the models projected age-specific DCIS and IBC incidence that were compared to Surveillance, Epidemiology, and End Results data. Models estimated mean sojourn time (MST) in the preclinical screen-detectable DCIS state, overdiagnosis, and the risk of progression from preclinical screen-detectable DCIS.

Results

Without biopsy and surgical excision, the majority of DCIS (64–100%) in the preclinical screen-detectable state progressed to IBC in submodels assuming no DCIS regression (36–100% in submodels allowing for DCIS regression). DCIS overdiagnosis differed substantially between models and submodels, 3.1–65.8%. IBC overdiagnosis ranged 1.3–2.4%. Submodels assuming DCIS regression resulted in a higher DCIS overdiagnosis than submodels without DCIS regression. MST for progressive DCIS varied between 0.2 and 2.5 years.

Conclusions

Our findings suggest that the majority of screen-detectable but unbiopsied preclinical DCIS lesions progress to IBC and that the MST is relatively short. Nevertheless, due to the heterogeneity of DCIS, more research is needed to understand the progression of DCIS by grades and molecular subtypes.

Simulating the Impact of Risk-Based Screening and Treatment on Breast Cancer Outcomes with MISCAN-Fadia

The MISCAN-Fadia microsimulation model uses continuous tumor growth to simulate the natural history of breast cancer and has been used extensively to estimate the impact of screening and adjuvant treatment on breast cancer incidence and mortality trends. The model simulates individual life histories from birth to death, with and without breast cancer, in the presence and in the absence of screening and treatment. Life histories are simulated according to discrete events such as birth, tumor inception, the tumor's clinical diagnosis diameter in the absence of screening, and death from breast cancer or death from other causes. MISCAN-Fadia consists of 4 main components: demography, natural history of breast cancer, screening, and treatment. Screening impact on the natural history of breast cancer is assessed by simulating continuous tumor growth and the "fatal diameter" concept. This concept implies that tumors diagnosed at a size that is between the screen detection threshold and the fatal diameter are cured, while tumors diagnosed at a diameter larger than the fatal tumor diameter metastasize and lead to breast cancer death. MISCAN-Fadia has been extended by including a different natural history for molecular subtypes based on a tumor's estrogen receptor (ER) status and human epidermal growth factor receptor 2 (HER2) status. In addition, personalized screening strategies that target women based on their risk such as breast density have been incorporated into the model. This personalized approach to screening will continue to develop in light of potential polygenic risk stratification possibilities and new screening modalities.

Cost-effectiveness of breast cancer screening in the National Breast and Cervical Cancer Early Detection Program

PURPOSE

To estimate the cost-effectiveness of breast cancer screening in the National Breast and Cervical Cancer Early Detection Program (NBCCEDP).

METHODS

Using a modified CISNET breast cancer simulation model, we estimated outcomes for women aged 40-64 years associated with three scenarios: breast cancer screening within the NBCCEDP, screening in the absence of the NBCCEDP (no program), and no screening through any program. We report screening outcomes, cost, quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), and sensitivity analyses results.

RESULTS

Compared with no program and no screening, the NBCCEDP lowers breast cancer mortality and improves QALYs, but raises health care costs. Base-case ICER for the program was $51,754/QALY versus no program and $50,223/QALY versus no screening. Probabilistic sensitivity analysis ICER for the program was $56,615/QALY [95% CI $24,069, $134,230/QALY] versus no program and $51,096/QALY gained [95% CI $26,423, $97,315/QALY] versus no screening.

CONCLUSIONS

On average, breast cancer screening in the NBCCEDP was cost-effective compared with no program or no screening.

Cost-effectiveness of patient navigation for breast cancer screening in the National Breast and Cervical Cancer Early Detection Program

OBJECTIVES

Patient navigation (PN) services have been shown to improve cancer screening in disparate populations. This study estimates the cost-effectiveness of implementing PN services within the National Breast and Cervical Cancer Early Detection Program (NBCCEDP).

METHODS

We adapted a breast cancer simulation model to estimate a population cohort of women aged 40-64 years from the NBCCEDP through their lifetime. We incorporated their screening frequency and screening and diagnostic costs.

RESULTS

Within the NBCCEDP, Program with PN (vs. No PN) resulted in a greater number of mammograms per woman (4.23 vs. 4.14), lower lifetime mortality from breast cancer (3.53% vs. 3.61%), and fewer missed diagnostic resolution per woman (0.017 vs. 0.025). The estimated incremental cost-effectiveness ratios for a Program with PN was $32,531 per quality-adjusted life-years relative to Program with No PN.

CONCLUSIONS

Incorporating PN services within the NBCCEDP may be a cost-effective way of improving adherence to screening and diagnostic resolution for women who have abnormal results from screening mammography. Our study highlights the value of supportive services such as PN in improving the quality of care offered within the NBCCEDP.

Use of Mastectomy for Overdiagnosed Breast Cancer in the United States: Analysis of the SEER 9 Cancer Registries

Aim

We investigated use of mastectomy as treatment for early breast cancer in the US and applied the resulting information to estimate the minimum and maximum rates at which mastectomy could plausibly be undergone by patients with overdiagnosed breast cancer. Little is currently known about overtreatments undergone by overdiagnosed patients.

Methods

In the US, screening is often recommended at ages ≥40. The study population was women age ≥40 diagnosed with breast cancer in the US SEER 9 cancer registries during 2013 (n=26,017). We evaluated first-course surgical treatments and their associations with case characteristics. Additionally, a model was developed to estimate probability of mastectomy conditional on observed case characteristics. The model was then applied to evaluate possible rates of mastectomy in overdiagnosed patients. To obtain minimum and maximum plausible rates of this overtreatment, we respectively assumed the cases that were least and most likely to be treated by mastectomy had been overdiagnosed.

Results

Of women diagnosed with breast cancer at age ≥40 in 2013, 33.8% received mastectomy. Mastectomy was common for most investigated breast cancer types, including for the early breast cancers among which overdiagnosis is thought to be most widespread: mastectomy was undergone in 26.4% of in situ and 28.0% of AJCC stage-I cases. These rates are substantively higher than in many European nations. The probability-based model indicated that between >0% and <18% of the study population could plausibly have undergone mastectomy for overdiagnosed cancer. This range reduced depending on the overdiagnosis rate, shrinking to >0% and <7% if 10% of breast cancers were overdiagnosed and >3% and <15% if 30% were overdiagnosed.

Conclusions

Screening-associated overtreatment by mastectomy is considerably less common than overdiagnosis itself but should not be assumed to be negligible. Screening can prompt or prevent mastectomy, and the balance of this harm-benefit tradeoff is currently unclear.

Can We Use Survival Data from Cancer Registries to Learn about Disease Recurrence? The Case of Breast Cancer

Background: Population-representative risks of metastatic recurrence are not generally available because cancer registries do not collect data on recurrence. This article presents a novel method that estimates the risk of recurrence using cancer registry disease-specific survival.Methods: The method is based on an illness-death process coupled with a mixture cure model for net cancer survival. The risk of recurrence is inferred from the estimated survival among the noncured fraction and published data on survival after recurrence. We apply the method to disease-specific survival curves from female breast cancer cases without a prior cancer diagnosis and with complete stage and hormone receptor (HR) status in Surveillance, Epidemiology and End Results registries (1992-2013).Results: The risk of recurrence is higher for women diagnosed with breast cancer at older age, earlier period, more advanced stage, and HR-negative tumors. For women diagnosed at ages 60-74 in 2000-2013, the projected percent recurring within 5 years is 2.5%, 9.6%, and 34.5% for stages I, II, and III HR-positive, and 6.5%, 20.2%, and 48.5% for stages I, II, and III HR-negative tumors. Although HR-positive cases have lower risk of recurrence soon after diagnosis, their risk persists longer than for HR-negative cases. Results show a high degree of robustness to model assumptions.Conclusions: The results show that it is possible to extract information about the risk of recurrence using disease-specific survival, and the methods can in principle be extended to other cancer sites.Impact: This study provides the first population-based summaries of the risk of breast cancer recurrence in U.S. women. Cancer Epidemiol Biomarkers Prev; 27(11); 1332-41. ©2018 AACR.

Common Model Inputs Used in CISNET Collaborative Breast Cancer Modeling

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.

A Bayesian Simulation Model for Breast Cancer Screening, Incidence, Treatment, and Mortality

BACKGROUND

The important but complicated research questions regarding the optimization of mammography screening for the detection of breast cancer are unable to be answered through any single trial or a simple meta-analysis of related trials. The Cancer Intervention and Surveillance Network (CISNET) breast groups provide answers using complex statistical models to simulate population dynamics. Among them, the MD Anderson Cancer Center (Model M) takes a unique approach by not making any assumptions on the natural history of breast cancer, such as the distribution of the indolent time before detection, but simulating only the observable part of a woman's disease and life.

METHODS

The simulations start with 4 million women in the age distribution found in the year 1975, and follow them over several years. Input parameters are used to describe their breast cancer incidence rates, treatment efficacy, and survival. With these parameters, each woman's history of breast cancer diagnosis, treatment, and survival are generated and recorded each year. Research questions can then be answered by comparing the outcomes of interest, such as mortality rates, quality-adjusted life years, number of false positives, differences between hypothetical scenarios, such as different combinations of screening and treatment strategies. We use our model to estimate the relative contributions of screening and treatments on the mortality reduction in the United States, for both overall and different molecular (ER, HER2) subtypes of breast cancer.

RESULTS

We estimate and compare the benefits (life-years gained) and harm (false-positives, over-diagnoses) of mammography screening strategies with different frequencies (annual, biennial, triennial, mixed) and different starting (40 and 50 years) and end ages (70 and 80 years).

CONCLUSIONS

We will extend our model in future studies to account for local, regional, and distant disease recurrences.

Structure, Function, and Applications of the Georgetown-Einstein (GE) Breast Cancer Simulation Model

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.

Association of Screening and Treatment With Breast Cancer Mortality by Molecular Subtype in US Women, 2000-2012

IMPORTANCE

Given recent advances in screening mammography and adjuvant therapy (treatment), quantifying their separate and combined effects on US breast cancer mortality reductions by molecular subtype could guide future decisions to reduce disease burden.

OBJECTIVE

To evaluate the contributions associated with screening and treatment to breast cancer mortality reductions by molecular subtype based on estrogen-receptor (ER) and human epidermal growth factor receptor 2 (ERBB2, formerly HER2 or HER2/neu).

DESIGN, SETTING, AND PARTICIPANTS

Six Cancer Intervention and Surveillance Network (CISNET) models simulated US breast cancer mortality from 2000 to 2012 using national data on plain-film and digital mammography patterns and performance, dissemination and efficacy of ER/ERBB2-specific treatment, and competing mortality. Multiple US birth cohorts were simulated.

EXPOSURES

Screening mammography and treatment.

MAIN OUTCOMES AND MEASURES

The models compared age-adjusted, overall, and ER/ERBB2-specific breast cancer mortality rates from 2000 to 2012 for women aged 30 to 79 years relative to the estimated mortality rate in the absence of screening and treatment (baseline rate); mortality reductions were apportioned to screening and treatment.

RESULTS

In 2000, the estimated reduction in overall breast cancer mortality rate was 37% (model range, 27%-42%) relative to the estimated baseline rate in 2000 of 64 deaths (model range, 56-73) per 100 000 women: 44% (model range, 35%-60%) of this reduction was associated with screening and 56% (model range, 40%-65%) with treatment. In 2012, the estimated reduction in overall breast cancer mortality rate was 49% (model range, 39%-58%) relative to the estimated baseline rate in 2012 of 63 deaths (model range, 54-73) per 100 000 women: 37% (model range, 26%-51%) of this reduction was associated with screening and 63% (model range, 49%-74%) with treatment. Of the 63% associated with treatment, 31% (model range, 22%-37%) was associated with chemotherapy, 27% (model range, 18%-36%) with hormone therapy, and 4% (model range, 1%-6%) with trastuzumab. The estimated relative contributions associated with screening vs treatment varied by molecular subtype: for ER+/ERBB2-, 36% (model range, 24%-50%) vs 64% (model range, 50%-76%); for ER+/ERBB2+, 31% (model range, 23%-41%) vs 69% (model range, 59%-77%); for ER-/ERBB2+, 40% (model range, 34%-47%) vs 60% (model range, 53%-66%); and for ER-/ERBB2-, 48% (model range, 38%-57%) vs 52% (model range, 44%-62%).

CONCLUSIONS AND RELEVANCE

In this simulation modeling study that projected trends in breast cancer mortality rates among US women, decreases in overall breast cancer mortality from 2000 to 2012 were associated with advances in screening and in adjuvant therapy, although the associations varied by breast cancer molecular subtype.

Comparative effectiveness of incorporating a hypothetical DCIS prognostic marker into breast cancer screening

PURPOSE

Due to limitations in the ability to identify non-progressive disease, ductal carcinoma in situ (DCIS) is usually managed similarly to localized invasive breast cancer. We used simulation modeling to evaluate the potential impact of a hypothetical test that identifies non-progressive DCIS.

METHODS

A discrete-event model simulated a cohort of U.S. women undergoing digital screening mammography. All women diagnosed with DCIS underwent the hypothetical DCIS prognostic test. Women with test results indicating progressive DCIS received standard breast cancer treatment and a decrement to quality of life corresponding to the treatment. If the DCIS test indicated non-progressive DCIS, no treatment was received and women continued routine annual surveillance mammography. A range of test performance characteristics and prevalence of non-progressive disease were simulated. Analysis compared discounted quality-adjusted life years (QALYs) and costs for test scenarios to base-case scenarios without the test.

RESULTS

Compared to the base case, a perfect prognostic test resulted in a 40% decrease in treatment costs, from $13,321 to $8005 USD per DCIS case. A perfect test produced 0.04 additional QALYs (16 days) for women diagnosed with DCIS, added to the base case of 5.88 QALYs per DCIS case. The results were sensitive to the performance characteristics of the prognostic test, the proportion of DCIS cases that were non-progressive in the model, and the frequency of mammography screening in the population.

CONCLUSION

A prognostic test that identifies non-progressive DCIS would substantially reduce treatment costs but result in only modest improvements in quality of life when averaged over all DCIS cases.

Validation of SDM-Q-Doc Questionnaire to measure shared decision-making physician's perspective in oncology practice

OBJECTIVE

The aim of this study was to analyze the psychometric properties of the Shared Decision-Making Questionnaire-Physician version (SDM-Q-Doc) in a sample of medical oncologists who provide adjuvant treatment to patients with non-metastatic resected cancer and the correlations between the total SDM-Q-Doc score and physician satisfaction with the information provided.

METHODS

Prospective, observational and multicenter study in which 32 medical oncologists and 520 patients were recruited. The psychometric properties, dimensionality, and factor structure of the SDM-Q-Doc were assessed.

RESULTS

Exploratory factor analyses suggested that the most likely solution was two-dimensional, with two correlated factors: one factor regarding information and another one about treatment. Confirmatory factor analysis based on cross-validation showed that the fitted two-dimensional solution provided the best fit to the data. Reliability analyses revealed good accuracy for the derived scores, both total and sub-scale, with estimates ranging from 0.81 to 0.89. The results revealed significant correlations between the total SDM-Q-Doc score and physician satisfaction with the information provided (p < 0.01); between information sub-scale scores (factor 1) and satisfaction (p < 0.01), and between treatment sub-scale scores (factor 2) and satisfaction (p < 0.01). Medical oncologists of older age and those with more years of experience showed more interest in the patient preferences (p = 0.026 and p = 0.020, respectively). Patient age negatively correlated with SDM information (p < 0.01) and physicians appear to provide more information to young patients.

CONCLUSION

SDM-Q-Doc showed good psychometric properties and could be a helpful tool that examines physician's perspective of SDM and as an indicator of quality and satisfaction in patients with cancer.

Tailoring Breast Cancer Screening Intervals by Breast Density and Risk for Women Aged 50 Years or Older: Collaborative Modeling of Screening Outcomes

BACKGROUND

Biennial screening is generally recommended for average-risk women aged 50 to 74 years, but tailored screening may provide greater benefits.

OBJECTIVE

To estimate outcomes for various screening intervals after age 50 years based on breast density and risk for breast cancer.

DESIGN

Collaborative simulation modeling using national incidence, breast density, and screening performance data.

SETTING

United States.

PATIENTS

Women aged 50 years or older with various combinations of breast density and relative risk (RR) of 1.0, 1.3, 2.0, or 4.0.

INTERVENTION

Annual, biennial, or triennial digital mammography screening from ages 50 to 74 years (vs. no screening) and ages 65 to 74 years (vs. biennial digital mammography from ages 50 to 64 years).

MEASUREMENTS

Lifetime breast cancer deaths, life expectancy and quality-adjusted life-years (QALYs), false-positive mammograms, benign biopsy results, overdiagnosis, cost-effectiveness, and ratio of false-positive results to breast cancer deaths averted.

RESULTS

Screening benefits and overdiagnosis increase with breast density and RR. False-positive mammograms and benign results on biopsy decrease with increasing risk. Among women with fatty breasts or scattered fibroglandular density and an RR of 1.0 or 1.3, breast cancer deaths averted were similar for triennial versus biennial screening for both age groups (50 to 74 years, median of 3.4 to 5.1 vs. 4.1 to 6.5 deaths averted; 65 to 74 years, median of 1.5 to 2.1 vs. 1.8 to 2.6 deaths averted). Breast cancer deaths averted increased with annual versus biennial screening for women aged 50 to 74 years at all levels of breast density and an RR of 4.0, and those aged 65 to 74 years with heterogeneously or extremely dense breasts and an RR of 4.0. However, harms were almost 2-fold higher. Triennial screening for the average-risk subgroup and annual screening for the highest-risk subgroup cost less than $100 000 per QALY gained.

LIMITATION

Models did not consider women younger than 50 years, those with an RR less than 1, or other imaging methods.

CONCLUSION

Average-risk women with low breast density undergoing triennial screening and higher-risk women with high breast density receiving annual screening will maintain a similar or better balance of benefits and harms than average-risk women receiving biennial screening.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Disparities in the use of screening magnetic resonance imaging of the breast in community practice by race, ethnicity, and socioeconomic status

BACKGROUND

Uptake of breast magnetic resonance imaging (MRI) coupled with breast cancer risk assessment offers the opportunity to tailor the benefits and harms of screening strategies for women with differing cancer risks. Despite the potential benefits, there is also concern for worsening population-based health disparities.

METHODS

Among 316,172 women aged 35 to 69 years from 5 Breast Cancer Surveillance Consortium registries (2007-2012), the authors examined 617,723 negative screening mammograms and 1047 screening MRIs. They examined the relative risks (RRs) of MRI use by women with a <20% lifetime breast cancer risk and RR in the absence of MRI use by women with a ≥20% lifetime risk.

RESULTS

Among women with a <20% lifetime risk of breast cancer, non-Hispanic white women were found to be 62% more likely than nonwhite women to undergo an MRI (95% confidence interval, 1.32-1.98). Of these women, those with an educational level of some college or technical school were 43% more likely and those who had at least a college degree were 132% more likely to receive an MRI compared with those with a high school education or less. Among women with a ≥20% lifetime risk, there was no statistically significant difference noted with regard to the use of screening MRI by race or ethnicity, but high-risk women with a high school education or less were less likely to undergo screening MRI than women who had graduated from college (RR, 0.40; 95% confidence interval, 0.25-0.63).

CONCLUSIONS

Uptake of screening MRI of the breast into clinical practice has the potential to worsen population-based health disparities. Policies beyond health insurance coverage should ensure that the use of this screening modality reflects evidence-based guidelines.

Projected Clinical, Resource Use, and Fiscal Impacts of Implementing Low-Dose Computed Tomography Lung Cancer Screening in Medicare

PURPOSE

The Centers for Medicare and Medicaid Services (CMS) recently issued a national coverage determination that provides reimbursement for low-dose computed tomography (CT) lung cancer screening for enrollees age 55 to 77 years with ≥ 30-pack-year smoking history who currently smoke or quit in the last 15 years. The clinical, resource use, and fiscal impacts of this change in screening coverage policy remain uncertain.

METHODS

We developed a simulation model to forecast the 5-year health outcome impacts of the CMS low-dose CT screening policy in Medicare compared with no screening. The model used data from the National Lung Screening Trial, CMS enrollment statistics and reimbursement schedules, and peer-reviewed literature. Outcomes included counts of screening examinations, patient cases of lung cancer detected, stage distribution, and total and per-enrollee per-month fiscal impact.

RESULTS

Over 5 years, we project that low-dose CT screening will result in 10.7 million more low-dose CT scans, 52,000 more lung cancers detected, and increased overall expenditure of $6.8 billion ($2.22 per Medicare enrollee per month). The most fiscally impactful factors were the average cost-per-screening episode, proportion of enrollees eligible for screening, and cost of treating stage I lung cancer.

CONCLUSION

Low-dose CT screening is expected to increase lung cancer diagnoses, shift stage at diagnosis toward earlier stages, and substantially increase Medicare expenditures over a 5-year time horizon. These projections can inform planning efforts by Medicare administrators, contracted health care providers, and other stakeholders.

Comparative effectiveness of combined digital mammography and tomosynthesis screening for women with dense breasts

PURPOSE

To evaluate the effectiveness of combined biennial digital mammography and tomosynthesis screening, compared with biennial digital mammography screening alone, among women with dense breasts.

MATERIALS AND METHODS

An established, discrete-event breast cancer simulation model was used to estimate the comparative clinical effectiveness and cost-effectiveness of biennial screening with both digital mammography and tomosynthesis versus digital mammography alone among U.S. women aged 50-74 years with dense breasts from a federal payer perspective and a lifetime horizon. Input values were estimated for test performance, costs, and health state utilities from the National Cancer Institute Breast Cancer Surveillance Consortium, Medicare reimbursement rates, and medical literature. Sensitivity analyses were performed to determine the implications of varying key model parameters, including combined screening sensitivity and specificity, transient utility decrement of diagnostic work-up, and additional cost of tomosynthesis.

RESULTS

For the base-case analysis, the incremental cost per quality-adjusted life year gained by adding tomosynthesis to digital mammography screening was $53 893. An additional 0.5 deaths were averted and 405 false-positive findings avoided per 1000 women after 12 rounds of screening. Combined screening remained cost-effective (less than $100 000 per quality-adjusted life year gained) over a wide range of incremental improvements in test performance. Overall, cost-effectiveness was most sensitive to the additional cost of tomosynthesis.

CONCLUSION

Biennial combined digital mammography and tomosynthesis screening for U.S. women aged 50-74 years with dense breasts is likely to be cost-effective if priced appropriately (up to $226 for combined examinations vs $139 for digital mammography alone) and if reported interpretive performance metrics of improved specificity with tomosynthesis are met in routine practice.

Identifying Sociocultural Barriers to Mammography Adherence Among Appalachian Kentucky Women

Despite lower breast cancer incidence rates, Appalachian women evidence lower frequency of screening mammography and higher mortality risk for breast cancer compared to non-Appalachian women in Kentucky, and in the United States, overall. Utilizing data from 27 in-depth interviews from women in seven Appalachian Kentucky counties, this study examines how Appalachian women explain sociocultural barriers and facilitators to timely screening mammography, and explores their common narratives about their mammography experiences. The women describe how pain and embarrassment, less personal and less professional mammography experiences, cancer fears, and poor provider communication pose barriers to timely and appropriate mammography schedule adherence and follow-up care. The study also identifies how improving communication strategies in the mammography encounter may improve mammography experiences and adherence to screening guidelines.

The diffusion of docetaxel in patients with metastatic prostate cancer

BACKGROUND

Diffusion of new cancer treatments can be both inefficient and incomplete. The uptake of new treatments over time (diffusion) has not been well studied. We analyzed the diffusion of docetaxel in metastatic prostate cancer.

METHODS

We identified metastatic prostate cancer patients diagnosed from 1995 to 2007 using the Surveillance, Epidemiology, and End Results Program (SEER)-Medicare database. Medicare claims through 2008 were analyzed. We assessed cumulative incidence of docetaxel by socioeconomic, demographic, and comorbidity variables, and compared diffusion patterns to landmark events including release of phase III results and FDA approval dates. We compared docetaxel diffusion patterns in prostate cancer to those in metastatic breast, lung, ovarian, and gastric cancers. To model docetaxel use over time, we used the classic "mixed influence" deterministic diffusion model. All statistical tests were two-sided.

RESULTS

We identified 6561 metastatic prostate cancer patients; 1350 subsequently received chemotherapy. Among patients who received chemotherapy, docetaxel use was 95% by 2008. Docetaxel uptake was statistically significantly slower (P < .01) for patients older than 65 years, blacks, patients in lower income areas, and those who experienced poverty. Eighty percent of docetaxel diffusion occurred prior to the May, 2004 release of phase III results showing superiority of docetaxel over standard-of-care. The maximum increase in the rate of use of docetaxel occurred nearly simultaneously for prostate cancer as for all other cancers combined (in 2000).

CONCLUSION

Efforts to increase the diffusion of treatments with proven survival benefits among disadvantaged populations could lead to cancer population survival gains. Docetaxel diffusion mostly preceded phase III evidence for its efficacy in castration-resistant prostate cancer, and appeared to be a cancer-wide-rather than a disease-specific-phenomenon. Diffusion prior to definitive evidence indicates the prevalence of off-label chemotherapy use.

Effects of screening and systemic adjuvant therapy on ER-specific US breast cancer mortality

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.