Participants will use a decision aid to learn about genomic sequencing and select which incidental findings they would like to receive from genomic sequencing. After using the decision aid the participants will speak with a genetic counsellor over the phone about their choice.

Participants will a genetic counsellor over the phone to learn about genomic sequencing and select which incidental findings they would like to receive from genomic sequencing.

The Genomics ADViSER is an decision aid designed to inform patients about genomic sequencing (GS) and aid them selecting which incidental findings they would like to receive from GS.

Decision Aid Plus Counselling

Participants will learn about genomic sequencing and incidental findings by speaking directly with a genetic counsellor and select which incidental findings they would like to receive with a genetic counsellor.

Genetic Counselling Only

Yvonne Bombard, PhD

Health care providers (HCP) are increasingly using genomic sequencing (GS) to target treatment for patients. However, GS may incidentally reveal inherited risks for thousands of current and future diseases. Guidelines recommend HCP inform patients of incidental GS results. No decision aid (DA) exists to guide patients' decisions about which incidental GS results they wish to learn. This study will evaluate whether the DA followed by genetic counselling (GC) reduces decisional conflict compared to GC alone in a randomized controlled trial (RCT) with 128 patients with a family history of cancer, who have had a negative genetic test and may eligible for GS. A qualitative component with a subset of participants (n=40) will explore patients' preferences for the types of incidental results they wish to receive and their decision making process.

BACKGROUND: Health care providers are increasingly using GS to diagnose, prognose and treat diseases. GS offers increased sensitivity over classic genetic tests, decreasing time-consuming and costly diagnostic cascades. However, GS may also incidentally reveal inherited risks for many other cancers and diseases. Guidelines recommend doctors inform patients of their incidental GS results. Yet there are limited tools to communicate the scope and implications of the thousands incidental results available to help guide patients' decisions about which results they wish to learn.

Gaps: Decision aids (DAs) are best suited to meet this challenge, but no DA exists to guide patients' decisions about incidental GS results.

Rationale: It is not feasible to counsel patients on the thousands of incidental findings available to make informed choices about which incidental results they wish to receive because of the limited genomics expertise and capacity among oncologists, and the long wait times for genetic counseling. Our DA fills this critical care and translational gap by improving the quality of patients' decisions and saving oncologists time counseling patients on incidental findings.

Preliminary data: 1) DA development: We created an interactive online DA. It begins with a professional whiteboard video (by Dr. Mike Evans) that conveys the key concepts, risks and benefits of learning about incidental GS results to educate patients. It then prepares patients for decision-making using a values clarification exercise (with feedback of their preferences) and a knowledge questionnaire (with correct answers provided after). It ends by asking participants to select result categories they want to learn using a menu tool. 2) Usability testing: We also evaluated the DA's usability with 15 patients in 2 rounds. Interviews demonstrated strong face validity and content comprehension. Most patients found the amount of information 'just right' (11/15), clear (12/15) and balanced (14/15). All patients felt that the information was sufficient to reach a decision, that the DA was easy to use and would recommend it.

OBJECTIVES

1. Evaluate the efficacy of the DA compared to standard genetic counseling (GC)
2. Understand the decision-making patients' use regarding GS and selecting incidental findings.

METHODS

Phase 1 - RCT to evaluate the DA:

Methods: We will evaluate the efficacy of the DA in reducing decisional conflict compared to standard genetic counseling (GC) using a superiority trial.

Population: We will recruit adult cancer patients who are eligible to have GS (i.e., tested negative for the classic gene mutation associated with their cancer - e.g., BRCA1/2, MLH, MSH, PMS, APC, MUTYH) from genetics clinics at Mount Sinai Hospital, Princess Margaret Hospital and Sunnybrook Hospital in Toronto, ON Canada. We will include adults who speak and read English and exclude patients with metastatic/recurrent disease as incidental results are less consequential to this population.

Sample size: TThe primary outcome is decisional conflict; the study requires 64 patients/arm to detect the minimal clinically important difference (MCID) of 0.3 using the Decisional Conflict Scale (DCS) (Appendix 3), assuming a standard deviation of 0.6, an alpha of 0.05 (two-sided) and power of 0.815,16. In the last 3 months, 244 patients with a family history of breast and colon cancer tested negative for their associated classic mutations (BRCA1/2, MLH, MSH, PMS, APC, MUTYH) most of who would be eligible for GS. Extrapolating this over the next 9 months we estimate that there would be 732 eligible patients. It is highly feasible to reach our target of 128 patients.

Participants will be consecutively randomized and allocated from an existing list of eligible subjects using a computer-generated randomization in a 1:1 ratio with random permuted blocks of varying sizes. Patients from each clinic will be randomized separately to ensure we have an even distribution of this population in both arms of the study.

Intervention arm: Participants will view the online DA and then complete the online self-administered measures (below) in one sitting within 14 days of recruitment. Next, they will speak with a GC over the telephone after the DA, using a standardized script. They will then complete the same online measures again after speaking to the GC.

Control arm: The GC will conduct the GC session over the telephone within 14 days of recruitment. A topics script will be used to standardize GC discussions covering standard educational content to enable patients to select incidental GS results (participants will not view the DA nor the video). Participants will complete the online self-administered measures after speaking with the GC.

Outcome: Consistent with the Ottawa Decisional Support Framework, our primary outcome is decisional conflict. Secondary outcomes are: knowledge of GS, satisfaction with decision, preparation for decision-making and anxiety.

Measures: We will use validated scales to assess decisional conflict, knowledge, anxiety, satisfaction with the decision and preparation for decision-making. We will develop a standardized topic script for the GC in each arm, as well as a questionnaire to collect intervention fidelity (e.g., usage statistics, duration of counseling sessions), demographic and clinical characteristics (e.g., cancer status and genetic testing).

Analysis: Consistent with the Ottawa Decision Support Framework, our primary outcome is decisional conflict, assessed via the validated Decisional Conflict Scale (DCS). Knowledge is the secondary outcome, will be measured by the Cliseq genomic sequencing questionnaire and a set of internal developed knowledge questions. Satisfaction and anxiety with also be assessed. Satisfaction will be measured using the Satisfaction with Decision scale (SWD) and the Preparation for Decision Making scale (PrepDM). Anxiety will be measured using the state subscale of the State-Trait Anxiety Inventory (STAI). We will also include a demographics and cancer history questionnaire.

The analysis of outcomes will follow the intention-to-treat (ITT) approach. Mean DCS, SWD, PrepDM and STAI scores will be compared using a t-test. Knowledge scores will be assessed by summing the number of correct responses to the questions, and compared using t-tests. Linear regression will be used in a secondary analysis to account for known predictors for decisional outcomes such as education. Secondary analyses will compare the mean DCS, knowledge, SWD, PrepDM and STAI scores before and after GC in the intervention arm to explore the additional benefit of GC after the DA. Un/adjusted mean differences and 95% confidence intervals will be reported. We will use descriptive statistics to report participants' characteristics.

Phase 2 - qualitative study of decision making for incidental results:

A subset of study participants will be asked to take part in a qualitative interview about their decision-making regarding selecting incidental findings. These semi-structured interviews will take place over the phone with a total of 40 participants. For the qualitative component a purposeful sample of study participants will be used. We will target a mix of participants across ages, cancer type and stage, gender, and study group to assess the varying approaches to decision-making. At total of 40 participants will take part in the qualitative component.

Analysis: Qualitative data analysis will draw on grounded theory methodology. We will sort the data by searching for themes/patterns and variations within and across interviews using HypeRESEARCH. Coding, which is the first stage in the analysis process, will involve 'labeling' the data with descriptive codes. Two team members will independently code each transcript. Consensus on coding will be reached through comparison and discussion among these members. The second stage will involve constant comparison, where codes and their content will be compared across interviews to discern common and divergent themes and issues across them. The final stage is selective coding, which integrates all the codes under a central phenomenon to build a theory. Validation methods include triangulation and member checking.

Evaluation of a Decision Aid for Incidental Genomic Findings

Randomized Controlled Trial of a Decision Aid for Incidental Genomic Findings

The Ottawa Decision Support Framework measure of decisional conflict, a 16 item scale - developed by O'Connor et al.

Knowledge is measured using a genomics knowledge scale developed by Clinseq

A 10 item scale measuring how useful a user finds the decision aid or other intervention

A six item scale measures a patient satisfaction with a health care decision

Mesured using the 20 item State-trait scale

Canadian Institutes of Health Research (CIHR)

Unity Health Toronto

Participants in the intervention arm will use the Genetics ADviSER to learn about genomic sequencing and to select which results they would like to receive from genomics sequencing results. After using the Genetics ADviSER decision aid they will speak with genetic counselor to discuss their choices and to finalized their selection.

Participants will speak with a genetic counsellor over the phone to learn about genomic sequencing and select which incidental findings they would like to receive from genomic sequencing.

The decision aid will educate patients about the types of incidental finding they can learn from genomic sequencing and will give them opportunity select what types of results they would like to receive.

Genetics ADvISER Decision Aid Plus Standard Genetic Counselling

Standard Genetic counseling to learn about and select incidental results from genomic sequencing.

Standard Genetic Counseling

Oncologists are increasingly using genomic sequencing to diagnose and optimize care for their patients. A consequence of this technology is its capacity to detect a patient's risk for thousands of current and future conditions or diseases. Guidelines recommend doctors allow patients to choose which results they wish to receive before ordering the test. It is not feasible to counsel patients on the thousands of possible results because of the limited clinical resources and genomics expertise. Decision aids (DAs) can fill this gap, however there are no DAs to guide patients' decisions about results from genomic sequencing. A DA prototype was developed (GenomicsADvISER.com), the first DA of its kind. This study will transform the DA prototype into an interactive, adaptable and patient-centred digital decision support tool (Genetics ADvISER) via user-centred design methods. The objective of this study is to evaluate the effectiveness of Genetics ADvISER in an RCT with patients being offered results from genomic sequencing. Results of this trial will be used to establish whether the Genetics ADvISER is effective to use in practice. This could fill a critical clinical care gap, improve health outcomes and service use by reducing counselling burden as well as overuse, underuse and misuse - concerns of policy makers seeking to address the triple aims of health care.

BACKGROUND: Genomic sequencing (GS) is a driver of precision oncology. Oncologists are increasingly using tumour GS for precision oncology care, which is often times accompanied by germline GS on normal control tissue. One complex feature of this technology is its capacity to generate incidental findings (IF). Guidelines recommend doctors inform patients of their incidental GS results. Yet there are limited tools to communicate the scope and implications of the thousands incidental results available to help guide patients' decisions about which results they wish to learn.

RATIONALE: There are limited decision support tools in genetics. Despite the long-standing practice of medical genetics, there are relatively few decision support tools for genetic testing and very few that have been rigorously evaluated. Even fewer decision support tools exist on possible results from genomic sequencing; existing tools target pediatric contexts, focus on genomic sequencing education-only or on the return of results; they do not cover all possible results with decision support to simulate genetic counselling, limiting their use and applicability in clinical care. Thus, there are no decision support tools to guide patients about all results available from genomic sequencing.

OBJECTIVES: Evaluate the effectiveness of the Genetics ADvISER vs standard genetic counseling (GC) with patients receiving incidental findings.

HYPOTHESIS: Use of the Genetics ADvISER will reduce patients' decisional conflict \& anxiety, improve patient knowledge, satisfaction with decisions and preparedness for decision-making when selecting IF compared to GC alone.

PHASE 1: RCT to evaluate the Decision Aid

Methods: This is a mixed method, non-blinded randomized controlled superiority trial. We will evaluate whether use of the Genetics ADvISER followed by Genetic Counsellor (GC) reduces decisional conflict compared to GC alone in a RCT. As a part of this trial, patients will receive results from exome sequencing.

Study population: Adult cancer patients who have had GS for their cancer (but did not receive incidental findings) or adult patients who have had a negative genetic panel test and may eligible for GS.

Sample: The primary outcome is decisional conflict; the study requires 64 patients/arm (128 total) to detect the minimal clinically important difference (MCID) of 0.3 using the Decisional Conflict Scale (DCS), assuming a standard deviation of 0.6, an alpha of 0.05 (two-sided) and power of 0.8. Participants will be consecutively randomized and allocated from an existing list of eligible subjects using a computer-generated randomization in a 1:1 ratio with random permuted blocks of varying sizes. Patients from each clinic will be randomized separately to ensure we have an even distribution of this population in both arms of the study.

Intervention: Participants in the intervention arm will use the Genetics ADviSER to learn about GS, select which results they would like to receive and to receive their GS results.

Control: Participants in the control arm will speak with a genetic counsellor to learn about GS, select which results they would like to receive and to receive their GS results.

Outcomes and measures: The primary outcome is decisional conflict, assessed via the validated Decisional Conflict Scale (DCS) consistent with the ODSF.

Secondary outcomes: Knowledge, measured using an established questionnaire assessing benefits and limitations of genome sequencing and a set of internally developed knowledge questions on IF; Satisfaction with decision-making, measured using the Satisfaction with Decision scale and the Preparation for Decision Making scale; Anxiety, measured using the state subscale of the State-Trait Anxiety Inventory. All sessions will be recorded to assess the length of GC sessions.

Quantitative Analysis: The analysis of outcomes will follow the intention-to-treat approach. Mean scores for decisional conflict, satisfaction with and preparation for decision-making, knowledge of IF and GC session length will be compared using a t-test. Anxiety, knowledge of sequencing benefits and sequencing limitations scores will be assessed by summing the number of correct responses to the questions, and compared adjusting for baseline score using analysis of covariance (ANCOVA). The primary time points of comparison will be (T1) for the control versus (T2) for the intervention group. Secondary exploratory analyses will examine the impact that the decision aid had alone (T1), without the addition of follow-up GC at T2 and at T3, after participants have received their IF on decision conflict, knowledge, anxiety, satisfaction and preparation with decision-making. Descriptive statistics will be used to describe participants' demographic characteristics (age, sex, education, etc.).

PHASE 2: Qualitative study

This study will explore the utility the of the Genetics ADvISER and incidental results via qualitative interviews with participants. After the study is completed, a subset set of participants (n = 40) will be selected to participate qualitative portion of the study. Participants approached to complete the qualitative portion of the study will determined by purposeful sampling, in order to get mix of participants across a range of experiences and demographic characteristics.

Qualitative Analysis: The qualitative analyses will draw on grounded theory. Open coding, constant comparison and axial coding will be used to identify common and divergent themes to characterize the entire dataset. Interviews will consider participants' socio-demographic factors that may influence their informational and decisional needs as well as how they engage with genetic information and participate in shared decision making. Two researchers will code transcripts independently; consensus on codes will be reached through discussion. Validation methods may include triangulation and member checking. In keeping with qualitative methodology, data analysis will occur in conjunction with data collection. On-going analysis will inform the development of progressive iterations of the interview guides.

Genetics Adviser: Evaluating a Digital Decision Support Tool for Genetic Results

Data will be made available to research who are interested in / conducting similar research in this field. This data will be available upon request, keeping with research ethics procedures.

The Ottawa Decision Support Framework measure of decisional conflict, a 16 item scale - developed by O'Connor et al. Each item is scored 1-5 and a total score on the DCS is calculated by summing all items on the DCS and then dividing by 16, giving a final score between 1 and 5. A lower score on the DCS indicates lower level of decisional conflict.

Knowledge is measured using a genomics knowledge scale developed by Clinseq, an established 11-item questionnaire consisting of two subscales assessing benefits and limitations of genome sequencing. Responses are on a five-point Likert scale ranging from strongly agree to strongly disagree, with responses being assigned a value of 1-5. Higher knowledge score s indicates a higher level of knowledge.

A six item scale measures a patient satisfaction with a health care decision. Items are scored 1-4. A higher score signifies a higher level of satisfaction or preparation with a decision. Items can be summed and scored (sum the 6 items and divide by 6).

A 10 item scale assesses a patient's perception of how useful a decision aid or other decision support intervention is in preparing the respondent to communicate with their practitioner at a consultation visit and making a health decision. Items are scored 1-4. Items can be summed and scored (sum the 10 items and divide by 10). A higher score indicates a higher level of preparation.

Measured using the 20 item State-trait scale. Anxiety was measured using the state subscale of the State-Trait Anxiety Inventory. Items can be summed and scored (sum the 20 items and divide by 20). Higher scores on the State-Trait Anxiety Inventory indicate higher level of anxiety.

Assessed using the 14 item Hospital Anxiety and Depression Scale (HADS). HADS has an Anxiety subscale and a Depression subscale, each with 7 questions. Add the scores of each of the 7 questions of the Anxiety subscale for a total score on the Anxiety subscale. Add the scores of each of the 7 questions of the Depression subscale for a total score on the Depression subscale. Scores range, 0-21 on each subscale; score \> 10 indicates clinical anxiety or depression; scores 8-10 indicate "borderline" anxiety or depression.

Assessed using a modified version of the an acceptability questionnaire developed by the Ottawa decision aid framework. Acceptability refers to ratings regarding the comprehensibility of components of a decision aid, its length, amount of information, balance in presentation of information about options, and overall suitability for decision making. Response options to individual items are poor, fair, good excellent, with good and excellent indicating a higher level of acceptability. This is not a scales responses can are reported descriptively for each item separately in terms of proportions responding positively or negatively on each criteria.

Measure of total time with Genetic counselor.

Neoplasms

Symptoms and General Pathology

All Conditions

Neoplasm Metastasis

Patients enrolled in POG who initiated WGTA between July 2014 and December 2017

Matched controls who received usual care and were diagnosed with metastatic cancer prior to December 2017

POG-related WGTA generally involves collecting biopsy samples, applying whole-genome and transcriptome sequencing, and using bioinformatics analysis to interpret sequence data and inform clinical decision-making.

Initiation of POG-related WGTA

Usual care, not involving the initiation of POG-related WGTA

Usual care

This study aims to determine the clinical effectiveness of whole-genome and transcriptome analysis (WGTA) to guide advanced cancer care. The study setting is the British Columbia (BC) Personalized OncoGenomics (POG) program, a single group research study of WGTA guiding treatment planning for patients with advanced, incurable cancers (NCT02155621). To characterize clinical effectiveness, the survival impacts of POG's approach compared to usual care in matched controls will be estimated.

WGTA provides an opportunity to improve health outcomes for patients by tailoring treatments to each individual's genomic profile. The BC POG Program is a single arm research study integrating WGTA information into clinical decision-making for patients with advanced stage, incurable cancers.The clinical effectiveness of POG's approach is unknown. This retrospective quasi-experimental observational study will estimate the real-world effectiveness of WGTA for guiding advanced cancer care. To identify a counterfactual for POG's single-arm approach, matching methods combined with administrative healthcare data will be used. The survival impacts of POG's approach compared to usual care in matched controls will then be estimated.

Specific Aims and Hypotheses

This study aims to estimate the overall survival effects of POG's approach versus usual care for patients with advanced cancers.

Hypothesis (null): there is no difference in survival across POG and usual care patients

Hypothesis (alternative): POG patients who initiated WGTA live longer, on average, than usual care patients

Study Design

This study will apply a retrospective cohort design. Cohorts will include patients who consented to POG and underwent a biopsy for WGTA between July 2014 and December 2017 and matched usual care controls. POG patients who enrolled prior to July 2014 will be excluded from our study because during this feasibility period, referring clinicians employed a high level of case-by-case recruitment selection. Usual care patients will be matched to POG patients using supervised learning techniques. The study period will range from patient's time of metastatic cancer diagnosis to December 31 2018.

Data Sources

De-identified linked population-based administrative datasets will be obtained from BC Cancer for all adult patients (\>18 years) diagnosed with cancers in BC prior to December 2017. POG patients will be identified from the BC Cancer Outcomes and Surveillance Integration System (OaSIS) POG Module Database. Eligible control patients will be identified from the BC Cancer Registry, a population-based provincial cancer registry. These data will be linked with data from the BC Cancer Pharmacy Database, Radiotherapy Database, and Cancer Agency Information System (CAIS) using agency-specific identifiers.

Statistical Approach

The investigators will match POG patients and usual care patients based on their date of metastatic disease diagnosis. They will apply 1:1 genetic algorithm-based matching (1:2 in sensitivity analysis) and match patients on propensity scores and baseline covariates, including patient demographics, clinical characteristics, treatment histories, and healthcare utilization prior to metastatic disease diagnosis. When necessary, matching analyses will be stratified to account for variation across cancer types.

To estimate overall survival in POG patients and matched controls, non-parametric and parametric survival analyses will be used. These analyses will be adjusted for censoring. The investigators will explore heterogeneity in clinical effectiveness across cancer subtypes through subgroup analysis and use scenario analysis to determine the impact of future changes in the application of WGTA on clinical effectiveness.

Real-world Clinical Effectiveness of Whole Genome and Transcriptome Analysis to Guide Advanced Cancer Care

Retrospective Observational Study Determining the Clinical Effectiveness of Whole Genome and Transcriptome Analysis to Guide Advanced Cancer Care

The patient-level administrative data used in this retrospective study are confidential and will not be made available in a public repository, in accordance with institutional policies.

BC Cancer Foundation

Genome British Columbia

British Columbia Cancer Agency

Infections

Musculoskeletal Diseases

Rare Diseases

Communicable Diseases

Bone Neoplasms

Disease Attributes

Bone Diseases

Prosthetic Joint Infection

Genomic sequencing

Histological examination

Translational research aimed at improving diagnostic accuracy of musculoskeletal infection and musculoskeletal tumours using machine learning applied to clinical data, histopathological sections and genomic sequencing.

Histological slides and limited sequencing data

Artificial Intelligence in the Diagnosis of Orthopaedic Conditions, Particularly Bone Tumours and Infection

Data may be made available as part of publication

Identification of infection and tumours using sequencing data

Keele University

Robert Jones and Agnes Hunt Orthopaedic and District NHS Trust

Patients in Intervention will receive GS results related to primary indication (cancer) and will be offered the option learning their incidental results, categorized into five "bins" based on a framework by Berg et al.

Patients in the control will receive the intervention GS results for Primary Indications only.

Patient will receive GS results related to their primary indication (cancer), as well as the option to learn incidental GS results. Incidental results will be categorized into five "bins" based on Berg et al.'s framework (medically actionable and pharmacogenetic, common disease SNPs, Mendelian conditions, early-onset brain diseases, and carrier status). In pre-test counseling, patients will have the option to select which bins of incidental results they would like to learn, if any.

Incidental Genomic Sequencing Results

Patients will receive GS results related to the primary indication (cancer) only.

GS Results for Primary Indications only

Health care providers (HCP) are increasingly using genomic sequencing (GS) to diagnose diseases and target treatment for patients. However, GS may incidentally reveal inherited risks for thousands of current and future diseases. Guidelines recommend HCP inform patients of incidental GS results. GS is a relatively new technology, raising many questions about its adoption in clinical care, including: What are the psychological harms, health outcomes, clinical utility and economic costs of receiving primary and incidental GS results? We will use a randomized controlled trial (RCT) to evaluate whether patients receiving incidental GS results will report higher levels of distress and more risk reducing behaviors compared to patients receiving GS for their primary indication alone. We will explore the personal utility of GS via in-depth interviews with a subset of patients. Clinical utility for cancer and incidental results will be evaluated through diagnostic yield, clinical actions triggered by GS results and in-depth interviews with a subset of patients and providers. The economic impact will be evaluated in two ways: (a) health service use will be assessed retrospectively using billing records from the Institute of Clinical Evaluative Sciences (ICES); and, (b) participants' personal costs incurred as a result of GS will be assessed via surveys. Participants will be adult cancer patients who have received negative single gene or panel test results and who have been determined by their health care provider to be a candidate for GS.

Background

Genomic sequencing (GS) is considered the 'next step' towards personalized medicine, providing an opportunity to improve the prevention, diagnosis and treatment of disease. Across Canada, clinicians are increasingly using GS to identify treatments and management approaches likely to benefit patients based on molecular makeup, especially in oncology. GS offers increased sensitivity over classic genetic tests. For example, multi-gene sequencing has been shown to increase the sensitivity of identifying clinically actionable mutations in breast cancer patients by 50% to 60% when compared to testing for BRCA1/2 alone. Often breast cancer patients who test negative for BRCA1/2 will be offered GS to identify causative mutations. In addition, GS can also be used to analyze the molecular profile of a patient's tumour (somatic GS) to identify therapeutic targets.

However, the process of decoding the genome an individual or their tumour may incidentally reveal information about inherited predispositions to other cancers and diseases, including genetic variants/changes associated with current (undiagnosed) disease, drug response, risk for future diseases and variants of unknown clinical significance. Increasing policy guidance suggests that 'medically actionable' results should be offered to patients undergoing clinical sequencing, with calls to offer additional incidental results based on patient preferences. There is limited evidence on the psychological harms and clinical benefits of returning incidental GS results to patients.

Psychological distress: Single-gene and multiplex testing for hereditary cancers, neurological and cardiac disease appears to have minimal psychological impacts. A recent study found that few participants report distress from GS results. However, these findings are based on individuals who agreed to be tested for particular genes, and were prepared through counseling or otherwise to receive these results. This may not translate to incidentally-discovered genetic risk, which individuals did not anticipate or choose to learn a priori. Distress related to receiving incidental GS results remains unknown.

Personal utility: Studies suggest that individuals want to learn their GS results because they expect them to offer 'personal utility'. Personal utility is considered an increasingly important precursor of clinical utility, which is believed to offer richer self-knowledge and motivate risk reducing behaviors. Most studies focus on the hypothetical return of incidental GS results, little is known about individuals' actual perceived value of receiving GS results.

Health benefits: Single-gene and multiplex testing for low risk single nucleotide polymorphisms (SNPs) and high penetrance susceptibility alleles appears to influence the uptake of diet and medication changes, risk-reducing surgeries and surveillance. However, these findings are based on individuals who requested testing for selected genes, and may not represent individuals who learn incidental results.

Clinical Utility: Due to the challenges of applying traditional measures of clinical utility (quality adjusted life years, life years gained) in the context of genomic medicine, an 'intermediate outcome' of utility has emerged based on the 'usefulness and added value to patient management decision making,' of results captured by clinical actions or altered medical recommendations. Preliminary evidence shows GS holds great promise to enable personalized treatments and efficient diagnoses, has demonstrated to facilitate diagnosis in cases of rare diseases with unclear etiology, and strong potential to inform personalized drug therapies compatible with patients' genotypes. The utility of germline GS has largely been examined in limited clinical contexts, such as paediatrics and rare diseases. GS results have been shown to alter clinical management, such as by informing specialist referrals. In a study among a small sample of physicians, providers expressed that while they viewed the current utility of GS as low, they expect it to become more commonplace and more useful in the future. The actual and perceived utility of GS will ultimately determine its clinical implementation, and more evidence in broader clinical settings is needed to inform GS' optimal translation into clinical practice.

Economic Analysis: A lack of evidence remains around the costs and cost-effectiveness of GS. Some believe GS has potential to reduce overall healthcare spending by streamlining the diagnostic process enabling tailored treatments, and informing specific prevention efforts. Others, however, believe that GS will increase healthcare expenditures with limited clinical benefits, as sequencing and variant interpretation costs remain high and results may trigger cascades of additional testing and screening procedures. Out-of-pocket costs may be incurred by patients including medications, counseling, and peripheral costs such as lost wages and transportation. Cost-effectiveness studies have predominately been conducted in the context of tumour sequencing for pharmacological applications; the cost-effectiveness of germ-line GS for primary indication has been examined in few clinical contexts. Regarding incidental findings, cost-effectiveness studies have been conducted for fewer than one third of conditions whose disclosure is recommended by the American College of Medical Genetics and Genomics (ACMG). Modelling predicts incidental finding disclosure may be cost-effective for diagnostics but not currently for general population screening. Further investigation into the utility, costs, and cost-effectiveness of GS is necessary to inform health service delivery and funding decisions.

Rationale

It is unknown whether incidental GS results will be perceived as useful, and whether they motivate the intent or uptake of risk-reducing behaviours. The clinical utility of GS results has not been fully explored, and there is a lack of evidence around cost-effectiveness and costs associated with GS to patients and the healthcare system, which poses a barrier to its clinical implementation.

Research Question

Do patients receiving incidental GS results experience higher levels of distress and engage in more risk reducing behaviours? What is the diagnostic yield of GS, and how do GS results influence clinical decision making? What are the short-term and long-term costs associated with receiving GS results to patients and the healthcare system?

Objectives

1. Evaluate the psychological distress of receiving incidental GS results
2. Evaluate the personal utility and impact of receiving incidental GS results on subsequent risk reduction behaviours.
3. Evaluate the clinical utility of GS:

   a. Assess the diagnostic yield of GS results: i. Related to primary cancer indication. ii. Medically actionable incidental findings. iii. Incidental findings with implications for reproductive decisions, lifestyle and relatives.

   b. Explore the nature and extent of clinical activity triggered by primary and incidental GS results (referrals to specialists, laboratory testing, scans and screens, etc.).

   c. Explore patient and provider perspectives of the perceived and actual clinical utility of primary and incidental GS results.
4. Examine the short-term (1 year) and long-term (5 year) costs associated with genomic sequencing:

   1. Costs to the healthcare system.
   2. Personal costs.

Study procedures

Patients will be recruited from familial cancer clinics in the Greater Toronto Area (GTA), consented by a genetic counselor, and randomized. Following randomization, participants in the intervention arm will have the option to select which categories of incidental results they would be willing to receive, with a genetic counselor. Participants' genomes will be sequenced and interpreted. Results will be returned by a genetic counselor. Referrals will be made based on sequencing results. Outcomes will be measured at multiple time points before and after the return of results.

Incidental Genomics

The Health Outcomes, Utility, and Costs of Returning Incidental Genomic Findings

Perceived utility of genomic sequencing results will be measured using a scale from Lupo et al. Scale values range from 0-24, with higher scores indicating higher perceived utility of genomic sequencing results. (PMID: 27019659).

Patient charts will be reviewed. The number and type of medical recommendations following GS will be quantified.

Participants will be asked about whether their genomic sequencing results have impacted their reproductive decisions or reproductive planning through questions adapted from Bombard et al. (PMID: 27256091).

This standardized, validated measure will assess decisional conflict. Possible scores range from 0 to 100, with higher scores indicating higher decisional conflict (worse outcome). There are three subscales: Uncertainty, Informed, and Values Clarity. Scores on each subscale range from 0-100, with higher scores indicating worse outcome. (PMID: 7898294)

Immediately after sequence analysis is complete, will record the number and frequencies of deleterious germline mutations related to the patients' phenotype over, and by subgroup: phenotype, extent of family history, transmission type, pathogenic/likely pathogenic, deleterious germline mutations known to be recurrently mutated by cancer type.

An adapted version of the HINTS questionnaire will assess how participants use and access health information. (https://hints.cancer.gov/)

Billing records held at the Institute for Clinical Evaluative Sciences (ICES) will be accessed to obtain information related to resource use following return of results, including physician visits, hospital visits, additional testing, and diagnostic tests.

Participants will be asked to report personal costs associated with GS results, including out-of-pocket medications as well as peripheral costs such as transportation and lost wages.

Communication of genomic sequencing results to relatives will be assessed through questions adapted from Bombard et al. that indicate which relatives they have communicated their results to (PMID: 27256091).

Participants will be asked about which relatives, to their knowledge, have received genetic testing as a result of learning the participant's genome sequencing results.

Participants will be asked about which relatives, to their knowledge, have changed their health behaviors as a result of the participant's genome sequencing results.

This standardized, validated measure assesses perceptions of uncertainty. Scores range from 1 to 5, with higher scores indicating higher perceptions of uncertainty. (PMID: 27925165)

This scale measures participants' tolerance of ambiguity. Scores range from 7 to 49, with higher scores indicating higher tolerance for ambiguity. (PMID: 8231339)

Our primary outcome is distress, measured by the Hospital Anxiety \& Depression Scale (HADS) using a validated cut-off of \>11 on either the anxiety or depression subscale. The Hospital Anxiety and Depression Scale measures clinically significant anxiety and depression. There are two subscales, anxiety (7 items) and depression (7 items). Scores on each subscale range from 0-21, with higher scores indicating worse outcome (higher anxiety or depression). Subscale scores are not combined for a total score. (PMID: 6880820, 25005549)

The Impact of Event Scale-Revised (IES-R) is a standardized, validated scale that measures symptoms of traumatic stress. The IES-R comprises of three subscales: Intrusion (8 items), Avoidance (8 items), and Hyperarousal (6 items). The IES-R yields a total score that ranges from 0-88, with higher scores indicating worse outcomes. Scores on the Intrusion subscale range from 0-32, with higher scores indicating worse outcomes. Score on the Avoidance subscale range from 0-32, with higher scores indicating worse outcomes. Scores on the Hyperarousal subscale range from 0-24, with higher scores indicating worse outcomes. (PMID: 23243796)

The Multi-Dimensional Impact of Cancer Risk Assessment (MICRA) is a 25-item standardized, validated scale that measures the impact of result disclosure from genetic tests. There are three subscales: Distress (6 items), Uncertainty (9 items) and Positive Experiences (4 items). Total scores range from 0-125, with higher scores indicating worse outcome. Scores on the Distress subscale range from 0-30, with higher scores indicating worse outcome. Scores on the Uncertainty subscale range from 0-45, with higher scores indicating worse outcome. Scores on the Positive Experiences Subscale range from 0-20, with higher scores indicating worse outcomes. (PMID: 12433008)

We will assess the intended use and actual adoption of risk-reducing behaviours and preventative services across all RCT participants using CDC's Behavioural Risk Factor Surveillance System (BRFSS) questionnaire. We have adapted the BFRSS to examine whether the receipt of GS results influences participants' intent to adopt, and actual self-reported adoption of: screening, prophylactic surgery, dietary changes, reduced alcohol intake, increased exercise, adherence/changes to medication, and smoking cessation (beyond those taken due to their cancer diagnosis). Self-reported actual or intended use of these behaviours will be ascertained over the telephone. Higher scores indicate higher uptake of health behaviours.

The SF-12 scale measures quality of life. The SF-12 has 12 items that address physical and mental functioning. Physical and mental health composite scores range from 0 to 100, with 0 indicating the lowest possible level of health, and 100 indicating the highest possible level of health.

Consistent with the Extended Parallel Process Model (EPPM) which suggests that that higher risk results could motivate individuals to adopt risk-reducing behaviors if they perceive an increased risk of disease, as long as self-efficacy is also high, we will assess genetic self-efficacy using a standardized, validated measure (PMID: 20884465).

Consistent with the Extended Parallel Process Model (EPPM) which suggests that that higher risk results could motivate individuals to adopt risk-reducing behaviors if they perceive an increased risk of disease, as long as self-efficacy is also high, we will assess risk perception. Participants will be asked to report their perceived likelihood of developing diseases related to their incidental results. For each disease risk, scores range from 1 to 5, and higher scores indicate higher perceived risk. (PMID: 16969872, 24131974)

We will use in-depth interviews with patients to provide further insights into the ways in which incidental results impact the quality of life and health outcomes of cancer patients receiving incidental results. Patient interviews will explore: reasons for learning incidental GS results, to whom, how and why results have been communicated, perceived utility and impact of incidental results for personal, familial or life planning.

Provider interviews will explore: improvements to patient management and treatment decisions on the basis of their patients' incidental results and their perceptions of the clinical, familial and personal benefits or harms of these results for patients. Interviews will also explore providers' views on any physical or physiological impacts that receipt of incidental results have had on patients.

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Prostatic Neoplasms

Genital Neoplasms, Male

Urogenital Neoplasms

Genital Diseases

Genital Diseases, Male

Urogenital Diseases

Prostatic Diseases

Male Urogenital Diseases

Jinge Zhao, Dr.

Hao Zeng, Dr.

The investigators plan to perform multi-omics technologies, including genomic, transcriptomic, epigenomic and proteomic methods, in patients with metastatic prostate cancer, aiming at uncovering the mechanism of the tumor progression, identifying distinct tumor subtypes and finding new treatment targets.

Prostate cancer is the commonest malignancy and the second leading cause of tumor-related death among males worldwide. Though patients with early stage prostate cancer can obtain satisfactory therapeutic efficacy from radical prostatectomy or radiotherapy, the prognosis of men with metastatic prostate cancer (mPCa), especially metastatic castration-resistant prostate cancer (mCRPC), is still poor. Recent years have witnessed the rapid development of the high-throughput technologies, including genomic, transcriptomic, epigenomic and proteomic methods. These techniques are promising in uncovering the mechanism of the tumor progression, identifying distinct tumor subtypes and finding new treatment targets.

In the current prospective study, the investigators plan to perform multi-omics technologies in patients with mPCa, aiming at uncovering the mechanism of the tumor progression, identifying distinct tumor subtypes and finding new treatment targets.

A Multi-omics Study of Metastatic Prostate Cancer (MOSMPCA)

Mutation identified via whole-genome sequencing will be recored.

Determining the transcriptomic information of metastatic prostate cancer by performing whole transcriptome sequencing

Determining the epigenomic status of specific genes by performing DNA-methylation sequencing

Determing the expression status of centain proteins by performing immunohistochemistry in prostate biopsy specimen

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Evaluation of a Decision Aid for Incidental Genomic Findings	NCT03244202	Cancer	Decision Aid Pl... Genetic Counsel...	18 Years -	Unity Health Toronto
Genetics Adviser: Evaluating a Digital Decision Support Tool for Genetic Results	NCT04725565	Cancer	Genetics ADvISE... Standard Geneti...	18 Years -	Unity Health Toronto
Real-world Clinical Effectiveness of Whole Genome and Transcriptome Analysis to Guide Advanced Cancer Care	NCT04141397	Metastatic Canc... Advanced Cancer Cancers That Ca...	Initiation of P... Usual care	19 Years - 85 Years	British Columbia Cancer Agency
Artificial Intelligence in the Diagnosis of Orthopaedic Conditions, Particularly Bone Tumours and Infection	NCT04746001	Bone Tumours Bone Infection Prosthetic Join... Prosthetic Infe...	Genomic sequenc... Histological ex...	18 Years -	Robert Jones and Agnes Hunt Orthopaedic and District NHS Trust
Incidental Genomics	NCT03597165	Cancer	Incidental Geno... GS Results for ...	18 Years -	Unity Health Toronto
Real-world Clinical Effectiveness of Whole Genome and Transcriptome Analysis to Guide Advanced Cancer Care	NCT04141397	Metastatic Canc... Advanced Cancer Cancers That Ca...	Initiation of P... Usual care	19 Years - 85 Years	British Columbia Cancer Agency
A Multi-omics Study of Metastatic Prostate Cancer (MOSMPCA)	NCT04660617	Prostate Cancer...		40 Years -	West China Hospital
Artificial Intelligence in the Diagnosis of Orthopaedic Conditions, Particularly Bone Tumours and Infection	NCT04746001	Bone Tumours Bone Infection Prosthetic Join... Prosthetic Infe...	Genomic sequenc... Histological ex...	18 Years -	Robert Jones and Agnes Hunt Orthopaedic and District NHS Trust

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