Family History in a Singapore Oncology Population

The value of precision medicine within clinical care is becoming increasingly more evident. Nowhere is this clearer than in the field of oncology. With recognition of the value of genetics in clinical care, the National Cancer Centre Singapore (NCCS) established a Cancer Genetics Service in 2006. This service performs a valuable function within NCCS by overseeing the care of patients found to have hereditary cancer syndromes and providing consultation to clinical oncologists on the appropriate, targeted role of genetic testing within cancer care. While the Cancer Genetics Service is available to all clinicians within NCCS, with the continually growing and evolving understanding of how genetics plays a role in cancer and cancer treatment, there are no clear, consistent guidelines on when to request consultation. This leads to both over- and underutilization of services with some patients being referred who do not require it and others being missed whose care would benefit from the expertise of a cancer geneticist.

In an effort to address these inconsistencies in care, the study team proposes to further develop and evaluate the implementation of a Duke-developed precision medicine software program, MeTree, within NCCS breast cancer clinics. MeTree is a patient-facing family history based risk assessment tool and clinical decision aid that was developed by researchers within Duke's Center for Applied Genomics and Precision Medicine (CAGPM). The initial intent of MeTree was to assist clinicians in identifying patients at greater than population risk based on a number of clinical and family health history (FHH) factors for a range of common conditions (including cancer) and provide clinical decision support (CDS) with specific recommendations based on common U.S. guidelines for prevention and screening.MeTree has been thoroughly tested and validated and is currently being implemented across five U.S. healthcare systems by way of a large cooperative grant through NHGRI's IGNITE network.2-7 Dr. Orlando is co-PI of this study and Dr. Wu served as a site PI.

Through the efforts of Drs. Wu and Orlando, among others, a research agreement was recently signed between Duke University and the National Heart Center Singapore (NHCS) to allow testing of MeTree within a cardiovascular epidemiologic study, the Biobank study (MeTree-Biobank pilot). The Biobank study is providing data to the SPECTRA healthy population database developed by the SingHealth/Duke-NUS Institute of Precision Medicine (PRISM). SPECTRA aims to collect detailed phenotypic and genomic information on 5,000 healthy Singaporeans. MeTree will be used to collect detailed FHH on Biobank participants. This collaboration is part of a larger partnership between CAGPM and PRISM to further develop cross-institution collaborations. Enrollment in the Biobank study is currently underway and incorporation of MeTree into the data capture flow started June 2017.

This proposal leverages the larger collaborative work already started to explore clinically meaningful applications of MeTree within SingHealth. While MeTree has been shown to be clinically effective within primary care clinics in the U.S., SingHealth's oncologists are interested in leveraging MeTree's risk assessment features both to establish a more organized, standardized, and systematic process for collecting information to enhance cancer management and to maximize the advances in precision medicine for the benefit of cancer patients. Therefore, in collaboration with SingHealth oncologist Dr. Ngeow, the principal investigators propose to explore, develop, and pilot a prototype MeTree cancer module through the following two aims:

Specific Aim 1: Create a Breast Cancer Clinical Decision Support Module in MeTree Specific Aim 2: Validate and Pilot the Breast Cancer Clinical Decision Support Module in a clinical setting within SingHealth.

APPROACH Specific Aim 1: Create a Breast Cancer Clinical Decision Support Module in MeTree. The prototype will focus on breast cancer, as a demonstration case, since the prevalence is high, the value of risk assessment is established, and MeTree already assesses risk for both familial and hereditary forms. To achieve this aim the investigators will work with Dr. Joanne Ngeow, head of the Cancer Genetics Service at NCCS, to understand current risk assessment practices in the oncology clinics, identify gaps and inefficiencies in meeting Singapore's risk assessment guidelines, and adapt MeTree to facilitate uptake of guideline-based care. All aspects of risk assessment will be evaluated, from gathering the right type of data to understanding the appropriate clinical actions that follow from each risk assessment result. The goals will be to: 1) create a MeTree integration plan for both patients and providers that will optimize its value, 2) incorporate additional data elements and risk algorithms into MeTree as appropriate, 3) generate tailored clinical decision support for the patient and their oncologist to facilitate appropriate ordering and interpretation of genetic tests. Drs. Wu, Orlando, and Ngeow will work together on all three steps, with Dr. Ngeow's expertise in genetics and oncology at SingHealth being critical for ensuring the team develops a useful and facile tool that meets the needs of SingHealth oncologists.

Deliverables These efforts will provide a breast cancer clinical decision support module that is ready for implementation testing in a breast cancer clinical environment. It will be a model upon which additional cancer CDS modules could be built, tested, and implemented.

Specific Aim 2: Validate and Pilot the Breast Cancer Clinical Decision Support Module in a clinical setting within SingHealth. To assess the feasibility and potential clinical utility of the Breast Cancer Clinical Decision Support Module, the investigators will perform a mixed-methods hybrid type II implementation-effectiveness pilot in the NCCS cancer genetics clinic and one additional surgical breast cancer clinic. The results of this 12-week pilot will inform both its potential impact on clinical care and how further to optimize it for broader clinical integration.