Prof. Dr. Maria Katapodi

CASCADE is a Swiss, multicenter, family-based, open-ended, prospective cohort established in 2017 by contacting individuals with pathogenic variants (PV) associated with hereditary breast and ovarian cancer (HBOC) or Lynch syndrome (LS) and their biological relatives. The cohort includes individuals with PV who are either affected or unaffected by cancer, relatives without the familial PV (true negatives), and relatives who did not have genetic testing (cascade screening). Self-administered questionnaires collect information on epidemiological factors (e.g., cancer status) and risk management behaviors (e.g., risk reducing surgeries) approximately 18-24 months apart.

Since the initiation of the cohort we have examined rates of cascade screening among relatives and family communication of genetic risk (CASCADE I); and guideline-concordant cancer surveillance and risk reducing practices (CASCADE II). CASCADE III will focus on individuals from HBOC and LS families whose cancer surveillance and risk management behaviors do not correspond to the expectations of the healthcare system (discordant behaviors). We hypothesize that discordant behaviors may be related to the characteristics of the healthcare system and/or its responses to the needs of these individuals.

CASCADE III will: Aim 1: Examine the influence of individual domain clusters (e.g., cancer status), interpersonal domain clusters (e.g., partner status), and healthcare system domain clusters (e.g., provider specialty) on cancer risk management behaviors, and explore how changes in these clusters impact changes in risk management. Aim 1 will be addressed with two (additional) questionnaires approximately 24 months apart. Combined data will cover a period of close to 10 years and 6 data collection points for participants who have been in the cohort since its initiation - currently 461 carriers of pathogenic variants (index cases and relatives), and 86 untested or ‘true negative’ individuals. Newly-identified carriers and their biological relatives will also be recruited. Risk management behaviors will be analyzed longitudinally, in light of the trajectory of the person, using survival analyses.

Aim 2: Explore decision-making processes and the perceived role of providers and the healthcare system among individuals from HBOC and LS families with discordant cancer surveillance, risk management, and genetic testing behaviors. Aim 2 will be addressed with questionnaire and narrative data. Subgroups of individuals with discordant risk management behaviors (e.g., female, over 45 years old, without risk-reducing salpingo-oophorectomy) will be invited to participate either in in-depth interviews or in focus groups. Data will be analyzed with thematic analysis.

Aim 3: Design improvements in the healthcare system based on risk-stratified “survivorship care” models for families harboring HBOC or LS pathogenic variants. Aim 3 will be addressed with a Delphi survey of a panel with international and national experts and patient representatives. The panel will explore models of risk-stratified survivorship care for HBOC and LS families. Delphi methodology is based on the principle that decisions of an expert panel are more accurate than those of unstructured groups, given adequate diversity and representativeness of panel members.

Chronic lymphedema, whether primary or secondary, is a chronic and to date uncurable disease. Even though, primary lymphedema is rather rare, yet, we assume that secondary lymphedema is associated with a yearly incidence of up to 2% in industrialized countries, i.e. ~8‘000 new cases in Switzerland respectively ~80‘000 new cases in Germany.Accordingly, secondary lymphoedema of the upper extremities extremity affects a large number of patients treated for breast cancer. Depending on the cause of lymphoedemadefinition used, its incidence can vary from around ~20% (surgery-induced) up to over 50% (radio-therapy-induced) in Breast Cancer Patients.Cancer patients affected by arm lymphoedema of the arm suffer from swelling, feeling of heaviness or tightness, restricted range of motion, aching or discomfort, recurring infections and eventually hardening and thickening of the skin and subcutaneous tissue from pain, heaviness, and numbness with limited range of motion.

Swelling and structural changes of the extremity do not only lead to severe somatical impairments but have a significant psycho-social morbidity which can result in body dysmorphia and development of anxiety. Chronic lymphoedema is classified into 4 stages:Stage 0: Latent or preclinical stage of lymphoedema; Stage 1: Early accumulation of fluid that is relatively high in protein content and reversible with conservative treatment; Stage 2: Increase in swelling and morphological tissue changes not reversible to conservative treatment; Stage 3: Lymphostatic stage with hard, fibrotic tissues subject to infections (elephantiasis),To date, the gold-standard therapy of cronic lymphoedema is conservative complex physical decongestion therapy (CDT) that includes gentle massage, local compression, physical exercises and meticulous skin care.

Unfortunately, many patients affected with symptomatic lympoedema stages often depend on life-long conservative therapy that is only symptomatic. It is best performed on a regular base to be effective with the aim to maintain the condition of advanced lymphoedema stages rather than to improve it. Treatment of lymphoedema in these patients is often unsatisfactory with conservative therapy being ineffective and/or purely symptomatic, as well as very expensive over a life time (11). Originally, lymphedema surgery included only lymphoreductive procedures that aim at decreasing tissue excess resulting from severe lymphostatic stages, such as radical circumferential debulking of skin and subcutaneous tissue followed by defect coverage with or without skin graft or yield at linking dermal skin flaps with the underlying fascia and muscle to somehow connect the superficial lymphatic drainage system to the deep one. Unfortunately, these invasive procedures are associated with a rather high rate of pain, wound healing complication, infection and lymph fistulas and therefore nowadays are used only occasionally in countries of the first world in cases of severe elephantiasis.

More recently, suction-assisted lipectomy has been propagated to effectively remove hypertrophic fat (1997: Brorson) and fortunately is associated with far less surgery-associated morbidity, however requires life-long compression garments to be effective. With novelecent developments including improved knowledge of lymphatic anatomy and physiology, as well as availability of more powerful diagnostic devices and of (super-) microsurgical techniques,- two main therapeutic surgical options have emerged: vascularized Vascularized lymph node transfer (VLNT) and lymphaticovenous anastomosis (LVA). It has been demonstrated that VLNT is able lastingly to reduces chronic lymphoedema and improves quality of life, also in a more cost-effective way when compared to CDT alone, while LVA on the other hand results in improved objective and subjective patient outcomes, e.g.such as symptom relief in 50-100% of patients. Nowadays, LVA seems to be indicated in stage I and early stage II lymphoedema, whereas VLNT is rather performed in late stage II and stage III (associated with lympho-liposuction) lymphoedema.

Based on the current evidence available, we therefore do hypothesize that the novel (super-)microsurgical lympho-reconstructive techniques (VLNT and LVA) are superior to conservative treatment options alone. Our study goal is to demonstrate that these surgical techniques, that restore lymphatic drainage, including VLNT as well LVA, are superior (i.e. more efficient and cost-effective, resulting in higher quality of life of affected patients) compared to conservative methods in the treatment of chronic breast cancer related chronic lymphoedema.

The research network "Responsible Digital Society" is involved in a variety of ways to strengthen the promotion of interdisciplinary exchange and cooperative research in the field of digital transformation.

In the area of research, the network creates forums for regular scientific exchange and supports the coordination of interdisciplinary research proposals. In the area of promoting young researchers, the network organizes summer and winter schools for them. In the area of networking, the network promotes regular exchanges with industrial partners in the region. In the area of outreach, the network strengthens the public dialogue by organizing colloquia and panel discussions on digitization with guests from various disciplines.

Carrying a pathogenic variant associated with hereditary breast ovarian cancer (HBOC) and subsequently developing an HBOC-associated cancer triggers a variety of emotional reactions and places extraordinary demands on women's coping abilities.

Project`s goal is to better understand how these women cope with their specific situation by applying machine learning techniques via natural language processing (NLP). To study individual coping mechanisms, narrative data derived from qualitative interviews with female HBOC-mutation carriers that have been conducted within the CASCADE and DIALOGUE studies in German, French and Italian will be used, as well as additional interviews that will be conducted within this study.

Furthermore, this study will have access to narrative data from 150 interviews that have been conducted at Boston College, US, and focus on HBOC-affected women, genetic testing, and coping. The transcripts will be analyzed with both natural language processing techniques (NLP, sentiment analysis) and traditional qualitative methods (grounded theory method after Strauss and Corbin, constant comparative method after Glaser) with the aim to identify individual stressors and coping mechanisms of female HBOC-mutation carriers.

It will be explored if NLP methods can generate codes that support or augment qualitative codes, and if NLP is able to simplify and partially replace traditional qualitative analyses. By clarifying HBOC-carrying women's individual needs and coping strategies, healthcare professionals and therapists will be able to better support them during vulnerable and demanding times related to treatment decision-making, family communication regarding the pathogenic variant, and maintaining an equilibrium between social, family, and potentially professional roles.

Several hundred cancer patients in Switzerland carry pathogenic germline variants associated with hereditary breast/ovarian cancer (HBOC) and Lynch syndrome (LS). HBOC and LS cases are at significantly higher risk of primary and secondary cancers and need lifelong cancer surveillance and access to different risk management options. Their close blood relatives have 12.5%-50% probability of inheriting the respective cancer predisposition and need access to genetic evaluation. European-based studies suggest that most cancer patients with hereditary cancer syndromes are not identified and do not receive adequate cancer surveillance. Most evidence comes from cross-sectional studies; there is little available information about changes in adherence to surveillance over time. Little is known about how genetic test results affect subsequent surveillance for HBOC and LS cases and blood relatives, and the overall response of the Swiss healthcare system to mutation carriers' and relatives' needs for long-term surveillance and cancer prevention.

CASCADE II will collect prospective three-year data from confirmed mutation carriers and blood relatives to examine how cancer surveillance practices, uptake of risk management options, and access to genetic services (for untested relatives) change over time. Specific Aim 1: Monitor changes over time in cancer status, surveillance practices, uptake of risk management options, and uptake of genetic testing (for previously untested relatives), and explore whether there are differences in occurrence of these events (or cumulative incidence of events) during the follow-up period among the different participant groups.

Specific Aim 2: Examine the predictive value of individual domain clusters (e.g., cancer status), interpersonal domain clusters (e.g., family environment), and healthcare system domain clusters (e.g., provider specialty) on cancer surveillance practices, uptake of risk management options, and uptake of genetic testing (for previously untested relatives). Specific Aim 3: Explore participants' preferences for the role and involvement of healthcare providers in organization of cancer surveillance and follow-up care.

Longitudinal data from the CASCADE cohort, a prospective, family-based cohort targeting HBOC and LS confirmed cases and blood relatives will address these aims. CASCADE uses surveys to assess cancer status, surveillance, management of hereditary cancer risk, and coordination of care, covering multi-level factors affecting cancer prevention and survivorship. Data from the CASCADE I and CASCADE II studies span a period of over 6 years and 4 data collection points, each approximately 18 months apart, for participants entering the cohort since its initiation. Recruitment takes place in oncology and/or genetic testing centres in three linguistic regions of Switzerland.

Longitudinal survey data will address Aims 1 and 2. We will use Kaplan-Meier analyses and multivariate and/or multi-level Cox Proportional Hazards models to regress "cancer surveillance" event and "use of genetic services" event on predictors. Exploratory factor analyses and hierarchical cluster analyses will generate domain clusters for participants.

Narrative data (focus groups and interviews) from selected participants to present diverse perspectives, triangulated with survey data, will address Aim 3. Data from the CASCADE cohort have considerable potential to enhance the development of high-quality comprehensive support systems to improve cancer surveillance and access to genetic specialists and coordination of cancer care services in Switzerland.

Early detection of breast cancer through screening and the advent of new treatments has contributed greatly to disease survival. This, in turn, elevates the importance of disease prognosis i.e., survival and cancer recurrence. A prognostic model with increased ability to classify patients into different risk groups and estimate overall survival time can influence choice of treatment and can spare patients from unnecessary treatments. Clinicians can offer patients individualized treatment and disease management strategies if a reliable and accurate prognostic model is available and has been incorporated in clinical practice. Most patients also desire information about their prognosis and overall survival. Researchers can design more efficient and ethical clinical trials by using accurate prognostic models to stratify patients. Finally, prognostic models have a great impact on health policy and allocation of social resources among cancer survivors. In the past two decades, several models have been developed for breast cancer prognosis.

Most models have been developed to test the prognostic value of a specific biomarker or to compare methods for model development, rather than to support clinical decision-making. Few models went through the complete translational pathway from preclinical development, validation, to the evaluation of clinical usefulness, such as the improvement of clinical decision-making. Only one model, which can classify patients into two risk groups (Dying vs. Surviving) was tested for "clinical usefulness".

Classifying patients into two groups cannot reflect its usefulness in clinical settings, since there are numerous treatments, treatment decisions are based on various factors and often change over time. A clinically useful prognostic model should be able to classify patients into multiple risk groups so that it can have mutual corroboration with treatment options and guidelines. The model eventually needs to be accessed in a randomized control trial, testing whether using the model to classify patients into different risk groups and informing treatment decisions improves survival or other patient reported outcomes.

Finally, the performance of current models varies across different populations. No model was developed with patients from Switzerland, validated for the Swiss population, or has been evaluated for clinical usefulness in Swiss clinical settings. Machine learning offers an alternative approach to classical model-based prediction e.g. Cox proportional hazard (PH) regression. It can address limitations of classical modeling and improve accuracy from 70% of Cox PH models to about 85%. A machine learning-based prognostic model learns from real world data where more than 20% breast cancer treatment decisions disagree with clinical guidelines and change over time. It can classify breast cancer patients into multiple risk groups, and also generate risk predictions based on different treatments.

The treatment-specific stratification can inform treatment decision-making. However, no machine learning-based breast cancer prognostic model has been validated in independent populations for generalizability, and no machine learning-based model was tested for clinical usefulness, such as supporting clinical decision-making. We aim to create a machine learning-based breast cancer prognostic model, the Swiss-BCpro, to support personalized management of breast cancer with data collected from Swiss cancer registries.

The specific aims are 1. to develop the Swiss-BCpro by using machine learning to analyze data available in the Geneva cancer registry; 2. to compare the calibration and predictive accuracy of Swiss-BCpro with other state-of-the-art models for breast cancer prognosis i.e., PREDICT, NPI, CancerMath; 3. to externally validate Swiss-BCpro with independent data from the cancer registries of Zurich and St. Gallen; 4. to explore its clinical usefulness, namely comparing the clinical utility of Swiss-BCpro stratification with both guideline-based clinical decision-making and actual treatments patients received.

The study will contribute to the personalized management of breast cancer patients in Switzerland by translating machine leaning-based breast cancer prognostic modeling into clinical practice.

Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminatory accuracy (0.53-0.64). Machine learning (ML) offers an alternative approach to standard prediction modeling that may address current limitations and improve accuracy of those tools. The purpose of this study was to compare the discriminatory accuracy of ML-based estimates against a pair of established methods-the Breast Cancer Risk Assessment Tool (BCRAT) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) models.

The performance of eight different ML methods to the performance of BCRAT and BOADICEA using eight simulated datasets and two retrospective samples: a random population-based sample of U.S. breast cancer patients and their cancer-free female relatives (N = 1143), and a clinical sample of Swiss breast cancer patients and cancer-free women seeking genetic evaluation and/or testing (N = 2481) was quantified and compared.

Predictive accuracy (AU-ROC curve) reached 88.28% using ML-Adaptive Boosting and 88.89% using ML-random forest versus 62.40% with BCRAT for the U.S. population-based sample. Predictive accuracy reached 90.17% using ML-adaptive boosting and 89.32% using ML-Markov chain Monte Carlo generalized linear mixed model versus 59.31% with BOADICEA for the Swiss clinic-based sample.

There was a striking improvement in the accuracy of classification of women with and without breast cancer achieved with ML algorithms compared to the state-of-the-art model-based approaches. High-accuracy prediction techniques are important in personalized medicine because they facilitate stratification of prevention strategies and individualized clinical management.   

Quality of life of caregivers of cancer patients is lower compared with the quality of life of caregivers of chronic disease patients. Moreover, no research assessing quality of life of caregivers have been conducted in Central Asia and in Kazakhstan, where lack of trained personnel; limited hospice and palliative beds availability; and underdevelopment of in-home and outpatient day-care services exist.

Aims: To assess the state of palliative care in the Republic of Kazakhstan within the past 5 years. To assess the effectiveness of palliative care on cancer patients' and their caregivers' quality of life, patients' length of stay, and caregivers' mental health and bereavement. To assess the cost-effectiveness of inpatient hospice-based palliative care services for cancer patients in the Republic of Kazakhstan.

Methods Sample: Data collection will be conducted in all five hospices across Kazakhstan. A total of 100 hospice patients with clinically terminal cancer will be given consent and asked to fill out the survey with or without help from their family caregivers. In addition, 50 healthcare professionals and 50 family caregivers will be surveyed and interviewed privately in their offices/rooms.

Design: The proposed study will use retrospective and prospective data involving quantitative and qualitative mixed-methods research, where integration of individual semi-structured in-depth interviews, a cross-sectional survey and analyses of existing data will be conducted. The financial impact of palliative care will be estimated using the incremental cost-effectiveness ratio. Finally, to check variations in outcomes under a given set of assumptions, a sensitivity analysis will be conducted.

Data collection and analyses: The short form surveys will be administered to assess quality of life of patients and caregivers. The quality-adjusted life years (QALYs) indicator will be calculated using the analyzed results of the survey and the average life expectancy of each participant as obtained from the WHO life-tables. R software, version 3.6.0. (r-project.org) will be used for conducting data checking, cleaning and computing total scores. The NVivo program will be utilized for qualitative analyses. Thus, after coding, a construction of emergent themes will be performed.

In Hereditary Breast and Ovarian Cancer (HBOC) syndrome, communication of genetic test results with relatives is essential to cascade genetic screening. Cascade genetic screening is a sequential process of identifying and testing blood relatives of a known mutation carrier to determine if they also carry the pathogenic variant, in order to propose preventive and other clinical management options that reduce morbidity and mortality. However, according to Swiss and Korean privacy laws, individuals identified with the pathogenic variant have the sole responsibility to share information about test results and health implication to relatives. Empirical evidence suggests that up to 50% of biological relatives are unaware of relevant genetic information, suggesting that potential benefits of genetic testing are not communicated effectively. Thus, interventions designed to help probands effectively communicate with relatives are critical for better management of hereditary cancer risk.

Technology could play a significant role in facilitating communication and genetic education within HBOC families. Given the lack of well-developed digital health tools to assist individuals with genetic predisposition to cancer effectively communicate genetic information to their relatives, the study aims to develop a modern, scalable, mobile friendly digital health solution for Swiss and Korean HBOC families. The digital health solution will be based on the Family Gene Toolkit (FGT), a web-based intervention designed to enhance communication of genetic test results within HBOC families that has been successfully tested for acceptability, usability, and participant satisfaction.

The study will also expand an existing research infrastructure developed in Switzerland, to enable future collaborative projects between Switzerland and Korea in this field. The Specific Aims of the project are: 1) Develop a digital health solution to support the communication of cancer predisposition among HBOC families, based on linguistic and cultural adaptation methods of the Family Gene Toolkit for the Swiss and Korean population 2) Develop the K-CASCADE research infrastructure in Korea by expanding an existing research infrastructure developed by the CASCADE Consortium in Switzerland 3) Evaluate the efficacy of the aforementioned digital solution on psychological distress and communication of genetic test results, as well as knowledge of cancer genetics, coping, decision making and quality of life 4) Explore the reach, effectiveness, adoption, implementation, and maintenance of the aforementioned digital solution.

The content for the digital health solution will be based on the FGT with linguistic adaptation to Korean, German, French and Italian, and will be made available for web and mobile access. Aim 1 will be achieved through focus groups in each country to better identify cultural context with 20 -24 HBOC mutation carriers and relatives and 6-10 healthcare providers involved in genetic services (counseling and testing).

For Aim 2 , K-CASCADE, a Korean database of HBOC families (mutation carriers and relatives) will be created based on the Swiss CASCADE Consortium database, creating a lasting research infrastructure that will facilitate future collaboration, including the possibility to apply machine learning algorithms for prediction of breast and ovarian cancer risk.

For Aim 3, feasibility and efficacy of the digital health solution against the comparison intervention will be assessed in a randomized trial, with a sample of 104 HBOC mutation carriers (52 in each study arm).

Aim 4 will be achieved with survey and interview data collected from participating HBOC families and healthcare providers during all phases of the study. Dissemination strategies will also be generated to ensure sustainable use of the digital health solution. Adapting existing interventions, rather than developing new ones, takes advantage of previous valid experiences without duplicating efforts.

Adaptation and implementation of culturally sensitive, digital health interventions that can facilitate communication processes within the family and enhance understanding of genetic cancer risk are extremely timely and relevant, given the expansion of genetic testing technology, the falling costs of genetic testing, and the increased pressure for integration of genetic knowledge in routine clinical care. The study would be one of the first resource-effective international research platforms to develop digital health solutions that can be scaled to large patient numbers and can be used in routine practice.

Early detection of breast cancer and advances in treatment have considerably increased the probability of survival for patients. However, patients who receive advanced treatments also experience short and long term side effects. Approximately 75% of breast cancer patients experience cancer related cognitive impairment (CRCI) prior to, during, or after treatment. CRCI remains a significant long-term problem for about 35% of breast cancer survivors.

CRCI may interfere with patients' self-care activities, such as ability to adhere to treatment, manage side effects, and re-integrate into the workforce, which can have a negative impact on their quality of life. Current studies provide conflicting evidence about subgroups of breast cancer patient who might be at higher risk for experiencing CRCI. Little is known about the contribution of genetic variations in the catecholaminergic and serotonergic pathways in the development and severity of CRCI. Finally, although acupuncture is being recommended for the management of hot-flashes and pain in cancer patients, there is little evidence that acupuncture can contribute to the management of CRCI.

The specific aims of this study are to: Identify subgroups of breast cancer patients who are at higher risk for CRCI (accounting for demographic characteristics and clinical predictors) during the first 6 months after surgery Explore associations between catecholaminergic and serotonergic genes with CRCI subgroup membership Evaluate the efficacy of acupuncture to reduce CRCI

The aims of the study will be addressed with quantitative, prospective, longitudinal, observational data collected in the U.S. regarding symptom burden among breast cancer patients prior to surgery and up to 60 months post systemic treatment (Aims 1 and 2); Aim 3 will be addressed with data collected in Germany for a prospective, single blind, randomized, controlled, multi-group comparison trial, which examined the efficacy of acupuncture for alleviating multiple symptoms in breast cancer patients receiving radiotherapy. Studies from all over the world report CRCI in breast cancer patients, since treatment protocols are implemented almost identically in western countries.

This project will bring the long-term management of CRCI among breast cancer patients to the forefront of personalized care, and provide a better understanding of possible contributions of genetic variations of common neurotransmitters (i.e., catecholamines and serotonin) increased CRCI burden. A non-pharmacological intervention (i.e., acupuncture) may prove efficacious and effective for alleviating CRCI. The study will contribute to precision medicine research in Switzerland.