Download or read book Optimal Policies for Personalized Breast Cancer Screening written by Turgay Ayer and published by . This book was released on 2011 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Optimal Guidelines for Screening Mammography Based on Individual Risk Factors written by Qingxia Kong and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early diagnosis is effective in reducing the death rate and treatment costs due to breast cancer. Although there is consensus that mammograms are effective for early diagnosis, not all organizations agree upon screening guidelines. Current guidelines from the American Cancer Society recommend an annual mammography starting at age 40. In contrast, the public health system in Chile guarantees two screening mammograms between the ages of 50 and 54. The objective of this paper is to study optimal individualized mammography guidelines that enable dynamic tracking of patients' risk factors, from the perspective of the public health system. We develop a stochastic dynamic programming model to minimize the total expected lifetime cost, including screening and treatment. The optimal number of screening mammograms derived from our model falls between the American Cancer Society and Chilean recommendations. However, when addressing the average breast-cancer risk, the optimal screening policy is either too aggressive for low-risk women or too conservative for high-risk women. Our results also show that it is beneficial to segment the population based on risk levels and to develop screening guidelines accordingly. Finally, sensitivity analysis indicates that optimal policies are sensitive to the costs of mammogram and treatments. This might explain why different countries have such a difference in screening polices. Thus, importing successful guidelines from other countries should not be recommended due to differences in costs of equipment and labor, and also in population genetics, lifestyles and environments.

Download or read book Personalizing the Screening Decisions for Patients with Multiple Chronic Conditions written by Ali Hjaar and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clinical practice guidelines do not sufficiently address the needs of patients with multiple chronic conditions (MCC) as these guidelines focus on single disease management and ignore unique patient-specific conditions. As a result, a nonpersonalized approach for the management of patients with MCC leads to adverse events and increases the financial burden on the health care system as over 150 million Americans experience MCC. Therefore, the focus of this dissertation is to develop methods to personalize the screening decisions for patients with MCC. Namely, we use simulation and optimization models to evaluate the impact of the national screening strategies and find the optimal screening policy for patients with MCC given their personal risk, life expectancy, and budget constraints. This dissertation is divided into 5 chapters. In Chapter 1, we review the impact of multiple chronic conditions on the health care system. In Chapter 2, we provide a literature review about completely and partially observable Markov decision processes and the use of simulation and mathematical models in improving screening guidelines. Moreover, we review the medical literature related to tailoring the clinical practice guidelines for patients with MCC. In Chapter 3, we investigate the breast cancer screening decision problem for women with Down syndrome as they 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. We use simulation modeling to estimate the potential harms and benefits of mammography screening for women with Down syndrome. We consider various mammography screening strategies that included annual, biennial, triennial, and one-time digital mammography screenings during the ages 40-74. We estimate numbers of mammograms, false-positives, benign biopsies, breast cancer deaths prevented, and life-years gained per 1000 screened women when compared with no screening. In average-risk women 50-74, biennial screening incurred 146 mammograms, 13 false-positive mammograms, and 1.9 benign biopsies per one life-year gained compared with no screening. In women with Down syndrome, the same screening strategy incurred 1,670 mammograms, 156 false-positive mammograms, and 22 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 1,230 mammograms, 112 false-positive mammograms, and 16 benign biopsies per one life-year gained compared with no screening. We find that the harm/benefit ratios for various mammography screening strategies in women with Down syndrome are not as favorable as those for average-risk women. That is, the benefit of screening mammography for women with Down syndrome is less pronounced due to lower breast cancer risk and shorter life expectancy. In Chapter 4, we focus on personalizing the screening decisions for patients with MCC. For this purpose, we develop a stochastic modeling framework and provide an exact solution algorithm. We consider the optimal management of screening decisions for an index disease (e.g., breast cancer, colorectal cancer, HIV, etc.) while accounting for the existence of a chronic condition (e.g., hypertension, diabetes, Alzheimer's disease, etc.). Our modeling framework is particularly useful for cases where the chronic condition affects the risk of the index disease. In a case study using real breast cancer epidemiology data, we demonstrate how our modeling framework can be used to personalize breast cancer screening for women with type 2 diabetes. In addition to providing a personalized breast cancer screening schedule for women with diabetes, we find some important policy insights that were not previously recognized by the medical community. More specifically, we find that compared to women with no diabetes, women with diabetes should be screened less aggressively, but screening should end at similar ages. We also find that adherence to the optimal screening policy is more crucial for women with diabetes compared to women with no diabetes. Our main insight on screening recommendations also has important resource implications as it leads to fewer screening mammograms. That is, compared to the current national breast cancer screening guidelines, the optimal breast cancer screening policy for women with diabetes could save the health care system approximately 2.6 million mammograms annually which translates to $405 million of annual cost savings. Due to the increasing cost of healthcare, financial and limited resources constraints ought to be considered. Hence, we extend our modeling framework in Chapter 5 to examine the impact of the costs related to breast cancer screening, diagnosis, and treatment on the optimal screening policy for women with no diabetes, women with pre-diabetes, and women with diabetes. We use willingness-to-pay (WTP) ratios to evaluate the costs related to screening, diagnosis, and treatment costs in terms of QALYs. Our numerical results show that the optimal screening policy is greatly affected by the WTP ratios.

Download or read book Saving Women s Lives written by National Research Council and published by National Academies Press. This book was released on 2004-12-18 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this report The Breast Cancer Research Foundation (BCRF) and the Institute of Medicine (IOM) present a one-day symposium that was held at the IOM to further disseminate the conclusions and recommendations of the joint IOM and National Research Council report, Saving Women's Lives: Strategies for Improving Breast Cancer Detection and Diagnosis. The committee assembled for this event was asked to share insights and consider ways in which the objectives of the report could be achieved from the standpoint of what women need to know, the best models of screening programs, manpower, risk stratification, basic research, and payment. This symposium seeks to provide continuing food for thought and ideas for actions in support of breast cancer detection and diagnosis and saving women's lives.

Download or read book Markov Decision Process Approach to Strategize National Breast Cancer Screening Policy in Data limited Settings written by Vijeta Deshpande and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Early diagnosis is a promising strategy to reduce premature mortalities and for optimal use of resources. But the absence of mathematical models specific to the data settings in LMIC's impedes the construction of economic analysis necessary for decision-makers in the development of cancer control programs. This thesis presents a new methodology for parameterizing the natural history model of breast cancer based on data availabilities in low and middle income countries, and formulation of a control optimization problem to find the optimal screening schedule for mammography screening, solved using dynamic programming. As harms and benefits are known to increase with the increase in the number of lifetime screens, the trade-off was modeled by formulating the immediate reward as a function of false positives and life-years saved. The method presented in thesis will provide optimal screening schedules for multiple scenarios of Willingness to Pay (numeric value assigned for each life-year lived), including the resulting total number of lifetime screens per person, which can help decision-makers evaluate current resource availabilities or plan future resource needs for implementation.

Download or read book Analysis of Breast Cancer Screening Policies Using Partially Observable Markov Decision Processes written by Mucahit Cevik and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we study three aspects of the breast cancer screening problem: impact of breast density and supplemental screenings, screening in resource-restricted settings and racial disparities in breast cancer outcomes. We first analyze the impacts of breast density and supplemental tests on breast cancer screening policies. We formulate the breast cancer screening problem using a discrete-time partially observable Markov decision process (POMDP) model. The state space of our model is composed of the patient's health states and the breast density states. At each decision epoch, the physician first decides whether or not the patient should undergo mammography screening, and then uses mammography result to decide whether or not to follow up with supplemental screening. Our numerical study demonstrates that incremental benefit of supplemental tests over digital mammography is rather limited; in particular, patients with high breast cancer risk should be recommended more frequent mammography screenings instead of supplemental tests. Next, we investigate the optimal allocation of limited mammography resources to screen a population. We propose a constrained POMDP model that maximizes total expected quality-adjusted life years of the patients when they are allowed only a limited number of mammography screenings. We use a variable resolution grid-based approximation scheme to convert the constrained POMDP model into a mixed-integer linear program and conduct several numerical experiments using breast cancer epidemiology data. We observe that as mammography screening capacity decreases, patients in the 40-49 age group should be given the least priority with respect to screening. We further find that efficient allocation of available resources between patients with different risk levels leads to significant quality-adjusted life year gains, especially for the patients with higher breast cancer risk. Finally, we consider race as a risk factor for breast cancer and investigate the contributing factors leading to higher breast cancer mortality among black women. We modify the University of Wisconsin Breast Cancer Simulation model to obtain race-specific models and analyze the differences in disease natural history, treatment utilization and mammography uptake. Our findings indicate that targeted prevention and detection strategies that go beyond equalizing access to mammography may be needed to eliminate racial disparities.

Download or read book Economic Evaluation in Health Care written by Michael Drummond and published by . This book was released on 2001 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: To accompany the hugely sccessful 'Methods for Economic Evaluation of Health Care Programmes 2e', this book is a thorough and rigourous discussion of the methodological principles and recent advances in the rapidly advancing field of theory and practice of economic evaluation in health care. Written by an internationally acclaimed group of authors, the book provides an in-depth discussion of the latest theoretical advances and gives comprehensive reviews of the available literature. The book covers the main areas of economic evaluation, including the methods for measuring costs and outcomes, the collection of data alongside clinical studies, ways of handling uncertainty, discounting and issues relating to the transferability of economic data. It is an ideal book for those studying economic evaluation on postgraduate or professional courses in health economics or public health.

Download or read book Assessing Multi Modality Breast Cancer Screening Strategies for BRCA 1 2 Gene Mutation Carriers and Other High Risk Populations written by Çağlar Çağlayan and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Women with certain risk factors such as BRCA 1/2 gene mutations and family history of breast or ovarian cancer are at higher risk for breast cancer. For high-risk women, the existing guidelines suggest intensified screening and the use of ultrasound (US) and magnetic resonance imaging (MRI) to address some of the limitations of mammography, the standard screening modality for average-risk women. Yet, the cost and false positive rates of MRI and operator dependency of US raise concerns about these modalities and their optimal use. Despite being capable of detecting more cancers than mammography, MRI is significantly more expensive and yields higher number of false-positives. US is cheaper but generally less sensitive than MRI, and is an operator dependent technology, causing substantial variability in the number of resulting false- positive readings and the associated costs. Currently there is no consensus on the optimal use of US and MRI in conjunction with, or instead of, mammography in high-risk women. Given the lack of definitive results from comprehensive randomized controlled trials, our objective in this paper is to study the multi-modality breast cancer screening problem in the high-risk population and identify optimal and cost-effective population screening strategies. For this purpose, we first develop a Markov model to capture the disease progression in high-risk women and parameterize it using the best available evidence. Then, we formulate a mixed integer linear program to identify the optimal structured strategies that are practical for implementation. We further study the structure of the optimal strategies, and establish the conditions under which a strategy with more frequent but less sensitive screens yields higher health benefits than a strategy with more sensitive but less frequent screens. Our main findings are as follows: (1) for young women (women aged 25-44 years-old), annual screening with ultrasound alone, despite its high operator dependency, is affordable with moderate budgets, optimal over a wide range of budget levels and is cost-effective, (2) for middle-aged women (women 45-74 years-old), annual mammography screening is robustly optimal and cost-effective and (3) the use of MRI alone or combined with mammogram, a recommended strategy by the current guidelines, leads to outcomes that are not cost-effective. Our findings can be helpful in designing future trials, developing evidence-based guidelines and informing insurance coverage decisions.

Download or read book Personalized Decision Modeling for Intervention and Prevention of Cancers written by Fan Wang and published by . This book was released on 2017 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Personalized medicine has been utilized in all stages of cancer care in recent years, including the prevention, diagnosis, treatment and follow-up. Since prevention and early intervention are particularly crucial in reducing cancer mortalities, personalizing the corresponding strategies and decisions so as to provide the most appropriate or optimal medical services for different patients can greatly improve the current cancer control practices. This dissertation research performs an in-depth exploration of personalized decision modeling of cancer intervention and prevention problems. We investigate the patient-specific screening and vaccination strategies for breast cancer and the cancers related to human papillomavirus (HPV), representatively. Three popular healthcare analytics techniques, Markov models, regression-based predictive models, and discrete-event simulation, are developed in the context of personalized cancer medicine. We discuss multiple possibilities of incorporating patient-specific risk into personalized cancer prevention strategies and showcase three practical examples. The first study builds a Markov decision process model to optimize biopsy referral decisions for women who receives abnormal breast cancer screening results. The second study directly optimizes the annual breast cancer screening using a regression-based adaptive decision model. The study also proposes a novel model selection method for logistic regression with a large number of candidate variables. The third study addresses the personalized HPV vaccination strategies and develops a hybrid model combining discrete-event simulation with regression-based risk estimation. Our findings suggest that personalized screening and vaccination benefit patients by maximizing life expectancies and minimizing the possibilities of dying from cancer. Preventive screening and vaccination programs for other cancers or diseases, which have clearly identified risk factors and measurable risk, may all benefit from patient-specific policies.

Download or read book Individualized Strategies for Breast Cancer Surveillance Based on Aggregated Familial Information written by and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work is concerned with methodological aspects of a new approach to optimization of breast cancer screening designed to utilize aggregated family history information. The problem of optimal cancer surveillance is set up as a search for optimal scheduling of screening examinations subject to certain constraints on the number and timing of medical tests. In Year 1, we developed a mathematical model yielding an algorithm for designing optimal schedules of breast cancer screening. An explicit expression of the efficiency functional is based on a plausible assumption that the intensity of detection (the hazard function for the age at detection) is proportional to the current tumor size. The main advantage of the proposed approach is that it accommodates cohort data of a fairly general structure, not only the data resulting from screening trials. We have also developed several numerical algorithms and software for estimating the hazard function for breast cancer incidence from the data amassed in the Utah Population Data Base; these procedures will be used (in Year 2) for testing covariate effects associated with different indicators of family history.

Download or read book Fulfilling the Potential of Cancer Prevention and Early Detection written by National Research Council and published by National Academies Press. This book was released on 2003-05-07 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer ranks second only to heart disease as a leading cause of death in the United States, making it a tremendous burden in years of life lost, patient suffering, and economic costs. Fulfilling the Potential for Cancer Prevention and Early Detection reviews the proof that we can dramatically reduce cancer rates. The National Cancer Policy Board, part of the Institute of Medicine, outlines a national strategy to realize the promise of cancer prevention and early detection, including specific and wide-ranging recommendations. Offering a wealth of information and directly addressing major controversies, the book includes: A detailed look at how significantly cancer could be reduced through lifestyle changes, evaluating approaches used to alter eating, smoking, and exercise habits. An analysis of the intuitive notion that screening for cancer leads to improved health outcomes, including a discussion of screening methods, potential risks, and current recommendations. An examination of cancer prevention and control opportunities in primary health care delivery settings, including a review of interventions aimed at improving provider performance. Reviews of professional education and training programs, research trends and opportunities, and federal programs that support cancer prevention and early detection. This in-depth volume will be of interest to policy analysts, cancer and public health specialists, health care administrators and providers, researchers, insurers, medical journalists, and patient advocates.

Download or read book Optimal Breast Cancer Decision Making to Reduce Overdiagnosis and to Maximize the Benefit of Supplementary Screening Tests written by Sait Tunc and published by . This book was released on 2017 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the first part of this dissertation, we develop a large-scale, finite-horizon Markov decision process model, namely, the large-scale diagnostic decision model (LSDDM), with around 4.6 million states to optimize the post-mammography diagnostic decisions. To reduce the computational burden, we develop and prove the optimality of a novel algorithm that relies on upper bounds on the optimal decision thresholds. We project the high-dimensional MDP onto two lower-dimensional MDPs to obtain feasible and tight upper bounds for the optimal decision thresholds. We use real data from mammography databases to conduct numerical experiments and solve our MDP optimally. Our numerical experiments show that optimal diagnosis of breast cancer can significantly decrease overdiagnosis when compared to current practice. To demonstrate the population impact of the optimal diagnostic policies obtained by the LSDDM over the current practice, we incorporate our findings into the University of Wisconsin Breast Cancer Simulation (UWBCS) model to examine the comparative effectiveness of the optimal breast cancer diagnostic policies. Next, we develop logistic regression models to discover which mammographic features best discriminate indolent diseases from more aggressive diseases in order to see if prospective identification of more aggressive disease might be possible. We also develop a Markov model to estimate the progression characteristic of indolent breast cancer subtypes into invasive cancer by using the natural history studies from the literature. In the last part of this dissertation, we propose a measure on the new information obtained by supplementary ultrasound screening, while the patient already has a screening mammogram. We aim to find the mammographic features and demographic factors that are most informative, and consequently to determine the patient subgroup for which a supplementary ultrasound screening gives the most additional information. We then develop a finite-horizon feature-based MDP model, namely, the cost-effective supplementary screening decision model (CESSDM), to optimize the supplementary screening decisions and determine the patient subgroup for which the supplemental ultrasonography screening is cost-effective. We also propose a model to study the long term information effect of supplemental screening decisions by proving the separability of the mutual information function and inductively calculate the long term reduction in the risk.

Download or read book Breast MRI Interpretation written by Gillian M. Newstead and published by Thieme. This book was released on 2021-01-06 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art resource details effective breast MRI techniques for improved screening and diagnosis Magnetic resonance imaging (MRI) of the breast has evolved into an important breast cancer screening tool and major advance in women's health. Breast MRI is currently the most sensitive detection technique for both non-invasive and invasive cancers and follow-up in women with a new breast cancer diagnosis. It is increasingly becoming the go-to imaging method for screening women at high and intermediate risk of breast cancer and those with dense breast tissue on mammography. Yet despite its reliability and growing use, many radiologists lack the expertise to accurately perform breast MR image interpretation. Breast MRI Interpretation: Text and Case Analysis for Screening and Diagnosis by Gillian M. Newstead reflects insights and expertise from one of the leading authorities on breast imaging. The book is a highly practical reference on evaluation and interpretation of breast MR imaging, with discussion of the modality as a screening and diagnostic tool. Topics include image acquisition and interpretation, clinical implementation, managing findings, and overcoming problems. Key Highlights About 3,000 illustrations from the University of Chicago including single selected images, side-by-side images at different time points and acquisition parameters, and 3-D images enhance understanding of breast imaging Discussion of advanced acquisition techniques and future potential applications including non-contrast imaging, quantitative dynamic imaging, and artificial intelligence using advanced computer analytic methods This remarkable resource streamlines the breast MRI process, enabling radiologists to incorporate this imaging modality into practice, conduct screening and diagnostic exams more efficaciously, and interpret findings accurately.

Download or read book Handbook of Healthcare Analytics written by Tinglong Dai and published by John Wiley & Sons. This book was released on 2018-08-10 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century? Editors Tinglong Dai and Sridhar Tayur, aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers a wide range of macro-, meso- and micro-level thrusts—such as market design, competing interests, global health, personalized medicine, residential care and concierge medicine, among others—and structures what has been a highly fragmented research area into a coherent scientific discipline. The handbook also provides an easy-to-comprehend introduction to five essential research tools—Markov decision process, game theory and information economics, queueing games, econometric methods, and data science—by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts. The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook: Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective—a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable—can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately. Facilitates collaboration between healthcare experts and analytics scholar to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose. The handbook is designed to be accessible to the independent reader, and it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course.

Download or read book Economic Dimensions of Personalized and Precision Medicine written by Ernst R. Berndt and published by University of Chicago Press. This book was released on 2019-04-22 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Personalized and precision medicine (PPM)—the targeting of therapies according to an individual’s genetic, environmental, or lifestyle characteristics—is becoming an increasingly important approach in health care treatment and prevention. The advancement of PPM is a challenge in traditional clinical, reimbursement, and regulatory landscapes because it is costly to develop and introduces a wide range of scientific, clinical, ethical, and socioeconomic issues. PPM raises a multitude of economic issues, including how information on accurate diagnosis and treatment success will be disseminated and who will bear the cost; changes to physician training to incorporate genetics, probability and statistics, and economic considerations; questions about whether the benefits of PPM will be confined to developed countries or will diffuse to emerging economies with less developed health care systems; the effects of patient heterogeneity on cost-effectiveness analysis; and opportunities for PPM’s growth beyond treatment of acute illness, such as prevention and reversal of chronic conditions. This volume explores the intersection of the scientific, clinical, and economic factors affecting the development of PPM, including its effects on the drug pipeline, on reimbursement of PPM diagnostics and treatments, and on funding of the requisite underlying research; and it examines recent empirical applications of PPM.

Download or read book Handbook of Healthcare Analytics written by Tinglong Dai and published by John Wiley & Sons. This book was released on 2018-07-30 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century? Editors Tinglong Dai and Sridhar Tayur, aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers a wide range of macro-, meso- and micro-level thrusts—such as market design, competing interests, global health, personalized medicine, residential care and concierge medicine, among others—and structures what has been a highly fragmented research area into a coherent scientific discipline. The handbook also provides an easy-to-comprehend introduction to five essential research tools—Markov decision process, game theory and information economics, queueing games, econometric methods, and data science—by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts. The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook: Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective—a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable—can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately. Facilitates collaboration between healthcare experts and analytics scholar to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose. The handbook is designed to be accessible to the independent reader, and it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course.

Download or read book European Guidelines for Quality Assurance in Breast Cancer Screening and Diagnosis written by European Commission. Directorate-General for Health and Consumer Protection and published by . This book was released on 2006 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast cancer is the most frequent cause of cancer-related deaths in women in Europe, and demographic trends indicate a continuing increase in this substantial public health problem. Systematic early detection through screening, effective diagnostic pathways and optimal treatment have the ability to substantially lower current breast cancer mortality rates and reduce the burden of this disease in the population. This is the fourth edition of these guidelines which contains information on recommended standards and procedures for breast cancer screening and diagnostic services, including chapters on multi-disciplinary aspects of quality assurance, data collection and monitoring, effective communication of information, requirements of a specialist unit, and a certification protocol.