Modeling Thyroid Cancer Epidemiology in the United States Using Papillary Thyroid Carcinoma Microsimulation Model.

OBJECTIVES: Thyroid cancer incidence increased over 200% from 1992 to 2018, whereas mortality rates had not increased proportionately. The increased incidence has been attributed primarily to the detection of subclinical disease, raising important questions related to thyroid cancer control. We developed the Papillary Thyroid Carcinoma Microsimulation model (PATCAM) to answer them, including the impact of overdiagnosis on thyroid cancer incidence. METHODS: PATCAM simulates individuals from age 15 until death in birth cohorts starting from 1975 using 4 inter-related components, including natural history, detection, post-diagnosis, and other-cause mortality. PATCAM was built using high-quality data and calibrated against observed age-, sex-, and stage-specific incidence in the United States as reported by the Surveillance, Epidemiology, and End Results database. PATCAM was validated against US thyroid cancer mortality and 3 active surveillance studies, including the largest and longest running thyroid cancer active surveillance cohort in the world (from Japan) and 2 from the United States. RESULTS: PATCAM successfully replicated age- and stage-specific papillary thyroid cancers (PTC) incidence and mean tumor size at diagnosis and PTC mortality in the United States between 1975 and 2015. PATCAM accurately predicted the proportion of tumors that grew more than 3 mm and 5 mm in 5 years and 10 years, aligning with the 95% confidence intervals of the reported rates from active surveillance studies in most cases. CONCLUSIONS: PATCAM successfully reproduced observed US thyroid cancer incidence and mortality over time and was externally validated. PATCAM can be used to identify factors that influence the detection of subclinical PTCs.

Analysis of Breast Cancer Mortality in the US-1975 to 2019.

Importance: Breast cancer mortality in the US declined between 1975 and 2019. The association of changes in metastatic breast cancer treatment with improved breast cancer mortality is unclear. Objective: To simulate the relative associations of breast cancer screening, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer with improved breast cancer mortality. Design, Setting, and Participants: Using aggregated observational and clinical trial data on the dissemination and effects of screening and treatment, 4 Cancer Intervention and Surveillance Modeling Network (CISNET) models simulated US breast cancer mortality rates. Death due to breast cancer, overall and by estrogen receptor and ERBB2 (formerly HER2) status, among women aged 30 to 79 years in the US from 1975 to 2019 was simulated. Exposures: Screening mammography, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer. Main Outcomes and Measures: Model-estimated age-adjusted breast cancer mortality rate associated with screening, stage I to III treatment, and metastatic treatment relative to the absence of these exposures was assessed, as was model-estimated median survival after breast cancer metastatic recurrence. Results: The breast cancer mortality rate in the US (age adjusted) was 48/100 000 women in 1975 and 27/100 000 women in 2019. In 2019, the combination of screening, stage I to III treatment, and metastatic treatment was associated with a 58% reduction (model range, 55%-61%) in breast cancer mortality. Of this reduction, 29% (model range, 19%-33%) was associated with treatment of metastatic breast cancer, 47% (model range, 35%-60%) with treatment of stage I to III breast cancer, and 25% (model range, 21%-33%) with mammography screening. Based on simulations, the greatest change in survival after metastatic recurrence occurred between 2000 and 2019, from 1.9 years (model range, 1.0-2.7 years) to 3.2 years (model range, 2.0-4.9 years). Median survival for estrogen receptor (ER)-positive/ERBB2-positive breast cancer improved by 2.5 years (model range, 2.0-3.4 years), whereas median survival for ER-/ERBB2- breast cancer improved by 0.5 years (model range, 0.3-0.8 years). Conclusions and Relevance: According to 4 simulation models, breast cancer screening and treatment in 2019 were associated with a 58% reduction in US breast cancer mortality compared with interventions in 1975. Simulations suggested that treatment for stage I to III breast cancer was associated with approximately 47% of the mortality reduction, whereas treatment for metastatic breast cancer was associated with 29% of the reduction and screening with 25% of the reduction.

Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force.

Importance: The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective: To estimate outcomes of various mammography screening strategies. Design, Setting, and Population: Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures: Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures: Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results: Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions: This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

Reflecting on 20 years of breast cancer modeling in CISNET: Recommendations for future cancer systems modeling efforts.

Since 2000, the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET) modeling teams have developed and applied microsimulation and statistical models of breast cancer. Here, we illustrate the use of collaborative breast cancer multilevel systems modeling in CISNET to demonstrate the flexibility of systems modeling to address important clinical and policy-relevant questions. Challenges and opportunities of future systems modeling are also summarized. The 6 CISNET breast cancer models embody the key features of systems modeling by incorporating numerous data sources and reflecting tumor, person, and health system factors that change over time and interact to affect the burden of breast cancer. Multidisciplinary modeling teams have explored alternative representations of breast cancer to reveal insights into breast cancer natural history, including the role of overdiagnosis and race differences in tumor characteristics. The models have been used to compare strategies for improving the balance of benefits and harms of breast cancer screening based on personal risk factors, including age, breast density, polygenic risk, and history of Down syndrome or a history of childhood cancer. The models have also provided evidence to support the delivery of care by simulating outcomes following clinical decisions about breast cancer treatment and estimating the relative impact of screening and treatment on the United States population. The insights provided by the CISNET breast cancer multilevel modeling efforts have informed policy and clinical guidelines. The 20 years of CISNET modeling experience has highlighted opportunities and challenges to expanding the impact of systems modeling. Moving forward, CISNET research will continue to use systems modeling to address cancer control issues, including modeling structural inequities affecting racial disparities in the burden of breast cancer. Future work will also leverage the lessons from team science, expand resource sharing, and foster the careers of early stage modeling scientists to ensure the sustainability of these efforts.

Optimal breast cancer risk reduction policies tailored to personal risk level.

Depending on personal and hereditary factors, each woman has a different risk of developing breast cancer, one of the leading causes of death for women. For women with a high-risk of breast cancer, their risk can be reduced by two main therapeutic approaches: 1) preventive treatments such as hormonal therapies (i.e., tamoxifen, raloxifene, exemestane); or 2) a risk reduction surgery (i.e., mastectomy). Existing national clinical guidelines either fail to incorporate or have limited use of the personal risk of developing breast cancer in their proposed risk reduction strategies. As a result, they do not provide enough resolution on the benefit-risk trade-off of an intervention policy as personal risk changes. In addressing this problem, we develop a discrete-time, finite-horizon Markov decision process (MDP) model with the objective of maximizing the patient's total expected quality-adjusted life years. We find several useful insights some of which contradict the existing national breast cancer risk reduction recommendations. For example, we find that mastectomy is the optimal choice for the border-line high-risk women who are between ages 22 and 38. Additionally, in contrast to the National Comprehensive Cancer Network recommendations, we find that exemestane is a plausible, in fact, the best, option for high-risk postmenopausal women.

Effect of Timing of and Adherence to Social Distancing Measures on COVID-19 Burden in the United States : A Simulation Modeling Approach.

BACKGROUND: Across the United States, various social distancing measures were implemented to control the spread of coronavirus disease 2019 (COVID-19). However, the effectiveness of such measures for specific regions with varying population demographic characteristics and different levels of adherence to social distancing is uncertain. OBJECTIVE: To determine the effect of social distancing measures in unique regions. DESIGN: An agent-based simulation model. SETTING: Agent-based model applied to Dane County, Wisconsin; the Milwaukee metropolitan (metro) area; and New York City (NYC). PATIENTS: Synthetic population at different ages. INTERVENTION: Different times for implementing and easing social distancing measures at different levels of adherence. MEASUREMENTS: The model represented the social network and interactions among persons in a region, considering population demographic characteristics, limited testing availability, "imported" infections, asymptomatic disease transmission, and age-specific adherence to social distancing measures. The primary outcome was the total number of confirmed COVID-19 cases. RESULTS: The timing of and adherence to social distancing had a major effect on COVID-19 occurrence. In NYC, implementing social distancing measures 1 week earlier would have reduced the total number of confirmed cases from 203 261 to 41 366 as of 31 May 2020, whereas a 1-week delay could have increased the number of confirmed cases to 1 407 600. A delay in implementation had a differential effect on the number of cases in the Milwaukee metro area versus Dane County, indicating that the effect of social distancing measures varies even within the same state. LIMITATION: The effect of weather conditions on transmission dynamics was not considered. CONCLUSION: The timing of implementing and easing social distancing measures has major effects on the number of COVID-19 cases. PRIMARY FUNDING SOURCE: National Institute of Allergy and Infectious Diseases.

A risk-based framework for assessing real-time lung cancer screening eligibility that incorporates life expectancy and past screening findings.

BACKGROUND: Current lung cancer risk-based screening approaches use a single risk-threshold, disregard life-expectancy, and ignore past screening findings. We address these limitations with a comprehensive analytical framework, the individualized lung cancer screening decision (ENGAGE) tool that aims to optimize lung cancer screening for US ever-smokers under dynamic risk assessment by incorporating life expectancy and past screening findings over time. METHODS: ENGAGE employs a partially observable Markov decision process framework that integrates published risk prediction and disease progression models, to dynamically assess the trade-off between the expected health benefits and harms associated with screening. ENGAGE evaluates lung cancer risk annually and provides real-time screening eligibility that maximizes the expected quality-adjusted life-years (QALYs) of ever-smokers. We compare ENGAGE against the 2013 U.S. Preventive Services Task Force (USPSTF) lung cancer screening guideline and single-threshold risk-based screening paradigms. RESULTS: Compared with the 2013 USPSTF guidelines, ENGAGE expands screening coverage among ever-smokers (ENGAGE: 78%, USPSTF: 61%), while reducing the number of screening examinations per person (ENGAGE:10.43, USPSTF:12.07, P < .001), yields higher effectiveness in terms of increased lung cancer-specific mortality reduction (ENGAGE: 19%, USPSTF: 15%, P < .001) and improves screening efficiency (ENGAGE: 696, USPSTF: 819 screens per death avoided, P < .001). When compared against a single-threshold risk-based screening strategy, ENGAGE increases QALY requiring 30% fewer screens per death avoided (ENGAGE: 696, single-threshold: 889, P < .001), and reduces false positives by 40%. CONCLUSIONS: ENGAGE provides a comprehensive framework for dynamic risk-based assessment of lung cancer screening eligibility by incorporating life expectancy and past screening findings that can serve to guide future policies on the effectiveness and efficiency of screening. LAY SUMMARY: A novel decision-analytical screening framework was developed for lung cancer, the individualized lung cancer screening decision (ENGAGE) tool to provide personalized screening schedules for ever-smokers. ENGAGE captures the dynamic nature of lung cancer risk and incorporates life expectancy into the screening decision-making process. ENGAGE integrates past screening findings and changes in smoking behavior of individuals and provides informed screening decisions that outperform existing screening guidelines and single-threshold risk-based screening approaches. A personalized lung cancer screening program facilitated by a tool such as ENGAGE could enhance the efficiency of lung cancer screening.

Clinical Benefits, Harms, and Cost-Effectiveness of Breast Cancer Screening for Survivors of Childhood Cancer Treated With Chest Radiation : A Comparative Modeling Study.

BACKGROUND: Surveillance with annual mammography and breast magnetic resonance imaging (MRI) is recommended for female survivors of childhood cancer treated with chest radiation, yet benefits, harms, and costs are uncertain. OBJECTIVE: To compare the benefits, harms, and cost-effectiveness of breast cancer screening strategies in childhood cancer survivors. DESIGN: Collaborative simulation modeling using 2 Cancer Intervention and Surveillance Modeling Network breast cancer models. DATA SOURCES: Childhood Cancer Survivor Study and published data. TARGET POPULATION: Women aged 20 years with a history of chest radiotherapy. TIME HORIZON: Lifetime. PERSPECTIVE: Payer. INTERVENTION: Annual MRI with or without mammography, starting at age 25, 30, or 35 years. OUTCOME MEASURES: Breast cancer deaths averted, false-positive screening results, benign biopsy results, and incremental cost-effectiveness ratios (ICERs). RESULTS OF BASE-CASE ANALYSIS: Lifetime breast cancer mortality risk without screening was 10% to 11% across models. Compared with no screening, starting at age 25 years, annual mammography with MRI averted the most deaths (56% to 71%) and annual MRI (without mammography) averted 56% to 62%. Both strategies had the most screening tests, false-positive screening results, and benign biopsy results. For an ICER threshold of less than $100 000 per quality-adjusted life-year gained, screening beginning at age 30 years was preferred. RESULTS OF SENSITIVITY ANALYSIS: Assuming lower screening performance, the benefit of adding mammography to MRI increased in both models, although the conclusions about preferred starting age remained unchanged. LIMITATION: Elevated breast cancer risk was based on survivors diagnosed with childhood cancer between 1970 and 1986. CONCLUSION: Early initiation (at ages 25 to 30 years) of annual breast cancer screening with MRI, with or without mammography, might reduce breast cancer mortality by half or more in survivors of childhood cancer. PRIMARY FUNDING SOURCE: American Cancer Society and National Institutes of Health.

Neighborhood disadvantage and 30-day readmission risk following Clostridioides difficile infection hospitalization.

BACKGROUND: Clostridioides difficile infection (CDI) is commonly associated with outcomes like recurrence and readmission. The effect of social determinants of health, such as 'neighborhood' socioeconomic disadvantage, on a CDI patient's health outcomes is unclear. Living in a disadvantaged neighborhood could interfere with a CDI patient's ability to follow post-discharge care recommendations and the success probability of these recommendations, thereby increasing risk of readmission. We hypothesized that neighborhood disadvantage was associated with 30-day readmission risk in Medicare patients with CDI. METHODS: In this retrospective cohort study, odds of 30-day readmission for CDI patients are evaluated controlling for patient sociodemographics, comorbidities, and hospital and stay-level variables. The cohort was created from a random 20% national sample of Medicare patients during the first 11 months of 2014. RESULTS: From the cohort of 19,490 patients (39% male; 80% white; 83% 65 years or older), 22% were readmitted within 30 days of an index stay. Unadjusted analyses showed that patients from the most disadvantaged neighborhoods were readmitted at a higher rate than those from less disadvantaged neighborhoods (26% vs. 21% rate: unadjusted OR = 1.32 [1.20, 1.45]). This relationship held in adjusted analyses, in which residence in the most disadvantaged neighborhoods was associated with 16% increased odds of readmission (adjusted OR = 1.16 [1.04, 1.28]). CONCLUSIONS: Residence in disadvantaged neighborhoods poses a significantly increased risk of readmission in CDI patients. Further research should focus on in-depth assessments of this population to better understand the mechanisms underlying these risks and if these findings apply to other infectious diseases.

Benefits and Harms of Mammography Screening for Women With Down Syndrome: a Collaborative Modeling Study.

BACKGROUND: Women with Down syndrome have a lower breast cancer risk and significantly lower life expectancies than women without Down syndrome. Therefore, it is not clear whether mammography screening strategies used for women without Down syndrome would benefit women with Down syndrome in the same way. OBJECTIVE: To determine the benefits and harms of various mammography screening strategies for women with Down syndrome using collaborative simulation modeling. DESIGN: Two established Cancer Intervention and Surveillance Modeling Network (CISNET) simulation models estimated the benefits and harms of various screening strategies for women with Down syndrome over a lifetime horizon. PARTICIPANTS: We modeled a hypothetical cohort of US women with Down syndrome who were born in 1970. INTERVENTIONS: Annual, biennial, triennial, and one-time digital mammography screenings during the ages 40-74. MAIN MEASURES: The models estimated numbers of mammograms, false-positives, benign biopsies, breast cancer deaths prevented, and life-years gained per 1000 screened women when compared with no screening. KEY RESULTS: In average-risk women 50-74, biennial screening incurred 122 mammograms, 10 false-positive mammograms, and 1.4 benign biopsies per one life-year gained compared with no screening. In women with Down syndrome, the same screening strategy incurred 2752 mammograms, 242 false-positive mammograms, and 34 benign biopsies per one life-year gained compared with no screening. The harm/benefit ratio varied for other screening strategies, and was most favorable for one-time screening at age 50, which incurred 1629 mammograms, 144 false-positive mammograms, and 20 benign biopsies per one life-year gained compared with no screening. CONCLUSIONS: The harm/benefit ratios for various mammography screening strategies in women with Down syndrome are not as favorable as those for average-risk women. The benefit of screening mammography for women with Down syndrome is less pronounced due to lower breast cancer risk and shorter life expectancy.

Biomass co-pyrolysis: Effects of blending three different biomasses on oil yield and quality.

In the present study, pyrolysis and co-pyrolysis of sugarcane bagasse, poppy capsule pulp, and rice husk were conducted in a fixed bed reactor at 550°C in nitrogen atmosphere. The moisture (5%-8%), ash (4%-17%), volatile matter (60%-76%), and fixed carbon analyses (11%-24%) of the utilized biomass were conducted. The decomposition behavior of biomasses due to the heat effect was investigated by thermogravimetric analysis/differential thermal analysis . In the pyrolysis of biomasses separately, the highest bio-oil yield was obtained with sugarcane bagasse (27.4%). In the co-pyrolysis of the binary blends of biomass, the highest bio-oil yield was obtained with the rice husk and sugarcane bagasse blends. While the mean bio-oil yield obtained with the separate pyrolysis of these two biomasses was 23.9%, it was observed that the bio-oil yield obtained with the co-pyrolysis of biomass blends was 28.4%. This suggested a synergistic interaction between the two biomasses during pyrolysis. It was observed that as the total ash content in the biomasses used in the pyrolysis increased, the bio-oil yield decreased, and the solid product content increased. Characterization studies of bio-oils were conducted by Fourier-transform infrared spectroscopy, gas chromatography-mass spectrometry (GC-MS), and hydrogen-1 nuclear magnetic resonance analyses. Results of these studies revealed that, all bio-oils were mainly composed of aliphatic and oxygenated compounds. The calorific values of bio-oils were determined by calorimeter bomb. Based on the GC-MS, the bio-oils with high fatty acid and its ester content also had high calorific values. The highest calorific value was 29.68 MJ kg-1, and this was obtained by pyrolysis of poppy capsule and sugarcane bagasse blend.

Interventions to Reduce the Incidence of Hospital-Onset Clostridium difficile Infection: An Agent-Based Modeling Approach to Evaluate Clinical Effectiveness in Adult Acute Care Hospitals.

Background: Despite intensified efforts to reduce hospital-onset Clostridium difficile infection (HO-CDI), its clinical and economic impacts continue to worsen. Many institutions have adopted bundled interventions that vary considerably in composition, strength of evidence, and effectiveness. Considerable gaps remain in our knowledge of intervention effectiveness and disease transmission, which hinders HO-CDI prevention. Methods: We developed an agent-based model of C. difficile transmission in a 200-bed adult hospital using studies from the literature, supplemented with primary data collection. The model includes an environmental component and 4 distinct agent types: patients, visitors, nurses, and physicians. We used the model to evaluate the comparative clinical effectiveness of 9 single interventions and 8 multiple-intervention bundles at reducing HO-CDI and asymptomatic C. difficile colonization. Results: Daily cleaning with sporicidal disinfectant and C. difficile screening at admission were the most effective single-intervention strategies, reducing HO-CDI by 68.9% and 35.7%, respectively (both P < .001). Combining these interventions into a 2-intervention bundle reduced HO-CDI by 82.3% and asymptomatic hospital-onset colonization by 90.6% (both, P < .001). Adding patient hand hygiene to healthcare worker hand hygiene reduced HO-CDI rates an additional 7.9%. Visitor hand hygiene and contact precaution interventions did not reduce HO-CDI, compared with baseline. Excluding those strategies, healthcare worker contact precautions were the least effective intervention at reducing hospital-onset colonization and infection. Conclusions: Identifying and managing the vast hospital reservoir of asymptomatic C. difficile by screening and daily cleaning with sporicidal disinfectant are high-yield strategies. These findings provide much-needed data regarding which interventions to prioritize for optimal C. difficile control.

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.

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.

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.

Collaborative Modeling of the Benefits and Harms Associated With Different U.S. Breast Cancer Screening Strategies.

BACKGROUND: Controversy persists about optimal mammography screening strategies. OBJECTIVE: To evaluate screening outcomes, taking into account advances in mammography and treatment of breast cancer. DESIGN: Collaboration of 6 simulation models using national data on incidence, digital mammography performance, treatment effects, and other-cause mortality. SETTING: United States. PATIENTS: Average-risk U.S. female population and subgroups with varying risk, breast density, or comorbidity. INTERVENTION: Eight strategies differing by age at which screening starts (40, 45, or 50 years) and screening interval (annual, biennial, and hybrid [annual for women in their 40s and biennial thereafter]). All strategies assumed 100% adherence and stopped at age 74 years. MEASUREMENTS: Benefits (breast cancer-specific mortality reduction, breast cancer deaths averted, life-years, and quality-adjusted life-years); number of mammograms used; harms (false-positive results, benign biopsies, and overdiagnosis); and ratios of harms (or use) and benefits (efficiency) per 1000 screens. RESULTS: Biennial strategies were consistently the most efficient for average-risk women. Biennial screening from age 50 to 74 years avoided a median of 7 breast cancer deaths versus no screening; annual screening from age 40 to 74 years avoided an additional 3 deaths, but yielded 1988 more false-positive results and 11 more overdiagnoses per 1000 women screened. Annual screening from age 50 to 74 years was inefficient (similar benefits, but more harms than other strategies). For groups with a 2- to 4-fold increased risk, annual screening from age 40 years had similar harms and benefits as screening average-risk women biennially from 50 to 74 years. For groups with moderate or severe comorbidity, screening could stop at age 66 to 68 years. LIMITATION: Other imaging technologies, polygenic risk, and nonadherence were not considered. CONCLUSION: Biennial screening for breast cancer is efficient for average-risk populations. Decisions about starting ages and intervals will depend on population characteristics and the decision makers' weight given to the harms and benefits of screening. PRIMARY FUNDING SOURCE: National Institutes of Health.

Cost-effectiveness of alternative colonoscopy surveillance strategies to mitigate metachronous colorectal cancer incidence.

BACKGROUND: The incidence of metachronous colorectal cancer (MCRC) among colorectal cancer (CRC) survivors varies significantly, and the optimal colonoscopy surveillance practice for mitigating MCRC incidence is unknown. METHODS: A cost-effectiveness analysis was used to compare the performances of the US Multi-Society Task Force guideline and all clinically reasonable colonoscopy surveillance strategies for 50- to 79-year-old posttreatment CRC patients with a computer simulation model. RESULTS: The US guideline [(1,3,5)] recommends the first colonoscopy 1 year after treatment, whereas the second and third colonoscopies are to be repeated at 3- and 5-year intervals. Some promising alternative cost-effective strategies were identified. In comparison with the US guideline, under various scenarios for a 20-year period, 1) reducing the surveillance interval of the guideline after the first colonoscopy by 1 year [(1,2,5)] would save up to 78 discounted life-years (LYs) and prevent 23 MCRCs per 1000 patients (incremental cost-effectiveness ratio [ICER] ≤ $23,270/LY), 2) reducing the intervals after the first and second negative colonoscopies by 1 year [(1,2,4)] would save/prevent up to 109 discounted LYs and 36 MCRCs (ICER ≤ $52,155/LY), and 3) reducing the surveillance intervals after the first and second negative colonoscopy by 1 and 2 years [(1,2,3)] would save/prevent up to 141 discounted LYs and 50 MCRCs (ICER ≤ $63,822/LY). These strategies would require up to 1100 additional colonoscopies per 1000 patients. Although the US guideline might not be cost-effective in comparison with a less intensive oncology guideline [(3,3,5); the ICER could be as high as $140,000/LY], the promising strategies would be cost-effective in comparison with such less intensive guidelines unless the cumulative MCRC incidence were very low. CONCLUSIONS: The US guideline might be improved by a slight increase in the surveillance intensity at the expense of moderately increased cost. More research is warranted to explore the benefits/harms of such practices. Cancer 2016;122:2560-70. © 2016 American Cancer Society.

Benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts.

BACKGROUND: Many states have laws requiring mammography facilities to tell women with dense breasts and negative results on screening mammography to discuss supplemental screening tests with their providers. The most readily available supplemental screening method is ultrasonography, but little is known about its effectiveness. OBJECTIVE: To evaluate the benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts. DESIGN: Comparative modeling with 3 validated simulation models. DATA SOURCES: Surveillance, Epidemiology, and End Results Program; Breast Cancer Surveillance Consortium; and medical literature. TARGET POPULATION: Contemporary cohort of women eligible for routine screening. TIME HORIZON: Lifetime. PERSPECTIVE: Payer. INTERVENTION: Supplemental ultrasonography screening for women with dense breasts after a negative screening mammography result. OUTCOME MEASURES: Breast cancer deaths averted, quality-adjusted life-years (QALYs) gained, biopsies recommended after a false-positive ultrasonography result, and costs. RESULTS OF BASE-CASE ANALYSIS: Supplemental ultrasonography screening after a negative mammography result for women aged 50 to 74 years with heterogeneously or extremely dense breasts averted 0.36 additional breast cancer deaths (range across models, 0.14 to 0.75), gained 1.7 QALYs (range, 0.9 to 4.7), and resulted in 354 biopsy recommendations after a false-positive ultrasonography result (range, 345 to 421) per 1000 women with dense breasts compared with biennial screening by mammography alone. The cost-effectiveness ratio was $325,000 per QALY gained (range, $112,000 to $766,000). Supplemental ultrasonography screening for only women with extremely dense breasts cost $246,000 per QALY gained (range, $74,000 to $535,000). RESULTS OF SENSITIVITY ANALYSIS: The conclusions were not sensitive to ultrasonography performance characteristics, screening frequency, or starting age. LIMITATION: Provider costs for coordinating supplemental ultrasonography were not considered. CONCLUSION: Supplemental ultrasonography screening for women with dense breasts would substantially increase costs while producing relatively small benefits. PRIMARY FUNDING SOURCE: National Cancer Institute.

Pyrolysis of poppy capsule pulp for bio-oil production.

The feasibility of biofuel production via the pyrolysis of poppy capsule pulp, the main waste product of Afyon Alkoloid Factory, was investigated. The poppy capsule pulp was shown to have a high volatile matter content (ca. 76%). Pyrolysis experiments were carried out in the temperature range 400-550°C (heating rate 18°C min-1 and holding time 20 min) under a nitrogen atmosphere. The chemical components of the bio-oil were characterized by Fourier transform infrared spectrometry and gas chromatography-mass spectrometry. The effects of pyrolysis temperature on the production efficiency and the calorific value of the bio-oil were investigated. The maximum bio-oil yield and its calorific value at 500°C were 23.6% and 31.6 MJ kg-1, respectively. The latter value is close to that of many petroleum fractions. This high-energy bio-oil is therefore a clean fuel precursor and can be upgraded into higher quality fuels.

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.