Mapping the experiences of people with advanced cancer across multiple cancer types-a scoping review

BACKGROUND

Through the introduction of tumor agnostic therapies, people with metastatic cancer and their treating physicians are facing new treatment choices that have differing side effect and efficacy profiles from conventional chemotherapy.

OBJECTIVE

The present study undertakes a scoping review of research into the experiences of people with advanced or metastatic cancer across various solid tumor types with the goal of developing a tumor-agnostic conceptual model.

DESIGN

Automated queries on three internet search engines were performed to identify qualitative interview studies that focused on people with metastatic cancer. No limits were imposed for dates nor location of studies.

RESULTS

Of the 173 hits generated from the searches, 25 peer-reviewed papers were selected for the review with dates that ranged from 2007 to 2022. All papers originated from the USA, Europe, Australia, or Japan. Three major themes emerged that formed the basis for the tumor-agnostic conceptual model: symptoms, loss of autonomy, and adaptation/coping.

CONCLUSIONS

The explication of the interplay between the physical and emotional symptoms experienced by those with advanced and metastatic cancer using a multi-tumor approach provides the potential to make generalizations about the needs of this population. An opportunity exists to potentially address these needs through matching patient needs and preferences with the characteristics of novel therapeutics.

IMPLICATIONS FOR CANCER SURVIVORS

In the era of tumor agnostic therapies, the elicitation of patient preferences across the spectrum of anatomical origins has the potential to enhance shared decision making in the setting of metastatic disease.

Real-world diagnostic outcomes and cost-effectiveness of genome-wide sequencing for developmental and seizure disorders: Evidence from Canada

PURPOSE

To determine real-world diagnostic rates, cost trajectories, and cost-effectiveness of exome sequencing (ES) and genome sequencing (GS) for children with developmental and/or seizure disorders in British Columbia, Canada.

METHODS

Based on medical records review, we estimated real-world costs and outcomes for 491 patients who underwent standard of care (SOC) diagnostic testing at British Columbia Children's Hospital. Results informed a state-transition Markov model examining cost-effectiveness of 3 competing diagnostic strategies: (1) SOC with last-tier access to ES, (2) streamlined ES access, and (3) first-tier GS.

RESULTS

Through SOC, 49.4% (95% CI: 40.6, 58.2) of patients were diagnosed at an average cost of C$11,683 per patient (95% CI: 9200, 14,166). Compared with SOC, earlier ES or GS access yielded similar or improved diagnostic rates and shorter times to genetic diagnosis, with 94% of simulations demonstrating cost savings for streamlined ES and 60% for first-tier GS. Net benefit from the perspective of the health care system was C$2956 (95% CI: -608, 6519) for streamlined ES compared with SOC.

CONCLUSION

Using real-world data, we found earlier access to ES may yield more rapid genetic diagnosis of childhood developmental and seizure disorders and cost savings compared with current practice in a Canadian health care system.

Impact on costs and outcomes of multi-gene panel testing for advanced solid malignancies: a cost-consequence analysis using linked administrative data

Background

To date, economic analyses of tissue-based next generation sequencing genomic profiling (NGS) for advanced solid tumors have typically required models with assumptions, with little real-world evidence on overall survival (OS), clinical trial enrollment or end-of-life quality of care.

Methods

Cost consequence analysis of NGS testing (555 or 161-gene panels) for advanced solid tumors through the OCTANE clinical trial (NCT02906943). This is a longitudinal, propensity score-matched retrospective cohort study in Ontario, Canada using linked administrative data. Patients enrolled in OCTANE at Princess Margaret Cancer Centre from August 2016 until March 2019 were matched with contemporary patients without large gene panel testing from across Ontario not enrolled in OCTANE. Patients were matched according to 19 patient, disease and treatment variables. Full 2-year follow-up data was available. Sensitivity analyses considered alternative matched cohorts. Main Outcomes were mean per capita costs (2019 Canadian dollars) from a public payer's perspective, OS, clinical trial enrollment and end-of-life quality metrics.

Findings

There were 782 OCTANE patients with 782 matched controls. Variables were balanced after matching (standardized difference <0.10). There were higher mean health-care costs with OCTANE ($79,702 vs. $59,550), mainly due to outpatient and specialist visits. Publicly funded drug costs were less with OCTANE ($20,015 vs. $24,465). OCTANE enrollment was not associated with improved OS (restricted mean survival time [standard error]: 1.50 (±0.03) vs. 1.44 (±0.03) years, log-rank p = 0.153), varying by tumor type. In five tumor types with ≥35 OCTANE patients, OS was similar in three (breast, colon, uterus, all p > 0.40), and greater in two (ovary, biliary, both p < 0.05). OCTANE was associated with greater clinical trial enrollment (25.4% vs. 9.5%, p < 0.001) and better end-of-life quality due to less death in hospital (10.2% vs. 16.4%, p = 0.003). Results were robust in sensitivity analysis.

Interpretation

We found an increase in healthcare costs associated with multi-gene panel testing for advanced cancer treatment. The impact on OS was not significant, but varied across tumor types. OCTANE was associated with greater trial enrollment, lower publicly funded drug costs and fewer in-hospital deaths suggesting important considerations in determining the value of NGS panel testing for advanced cancers.

Funding

T.P H holds a research grant provided by the Ontario Institute for Cancer Research through funding provided by the Government of Ontario (#IA-035 and P.HSR.158) and through funding of the Canadian Network for Learning Healthcare Systems and Cost-Effective 'Omics Innovation (CLEO) via Genome Canada (G05CHS).

"I just wanted more": Hereditary cancer syndromes patients' perspectives on the utility of circulating tumour DNA testing for cancer screening

Hereditary cancer syndromes (HCS) predispose individuals to a higher risk of developing multiple cancers. However, current screening strategies have limited ability to screen for all cancer risks. Circulating tumour DNA (ctDNA) detects DNA fragments shed by tumour cells in the bloodstream and can potentially detect cancers early. This study aimed to explore patients' perspectives on ctDNA's utility to help inform its clinical adoption and implementation. We conducted a qualitative interpretive description study using semi-structured phone interviews. Participants were purposively sampled adult HCS patients recruited from a Canadian HCS research consortium. Thirty HCS patients were interviewed (n = 19 women, age range 20s-70s, n = 25 were white). Participants were highly concerned about developing cancers, particularly those without reliable screening options for early detection. They "just wanted more" than their current screening strategies. Participants were enthusiastic about ctDNA's potential to be comprehensive (detect multiple cancers), predictive (detect cancers early) and tailored (lead to personalized clinical management). Participants also acknowledged ctDNA's potential limitations, including false positives/negatives risks and experiencing additional anxiety. However, they saw ctDNA's potential benefits outweighing its limitations. In conclusion, participants' belief in ctDNA's potential to improve their care overshadowed its limitations, indicating patients' support for using ctDNA in HCS care.

Toward Best Practices for Economic Evaluations of Tumor-Agnostic Therapies: A Review of Current Barriers and Solutions

OBJECTIVES

Cancer therapies targeting tumor-agnostic biomarkers are challenging traditional health technology assessment (HTA) frameworks. The high prevalence of nonrandomized single-arm trials, heterogeneity, and small benefiting populations are driving outcomes uncertainty, challenging healthcare decision making. We conducted a structured literature review to identify barriers and prioritize solutions to generating economic evidence for tumor-agnostic therapies.

METHODS

We searched MEDLINE and Embase for English-language studies conducting economic evaluations of tumor-agnostic treatments or exploring related challenges and solutions. We included studies published by December 2022 and supplemented our review with Canadian Agency for Drugs and Technologies in Health and National Institute for Health and Care Excellence technical reports for approved tumor-agnostic therapies. Three reviewers abstracted and summarized key methodological and empirical study characteristics. Challenges and solutions were identified through authors' statements and categorized using directed content analysis.

RESULTS

Twenty-six studies met our inclusion criteria. Studies spanned economic evaluations (n = 5), reimbursement reviews (n = 4), qualitative research (n = 1), methods validations (n = 3), and commentaries or literature reviews (n = 13). Challenges encountered related to (1) the treatment setting and clinical trial designs, (2) a lack of data or low-quality data on clinical and cost parameters, and (3) an inability to produce evidence that meets HTA guidelines. Although attempted solutions centered on analytic approaches for managing missing data, proposed solutions highlighted the need for real-world evidence combined with life-cycle HTA to reduce future evidentiary uncertainty.

CONCLUSIONS

Therapeutic innovation outpaces HTA evidence generation and the methods that support it. Existing HTA frameworks must be adapted for tumor-agnostic treatments to support future economic evaluations enabling timely patient access.

Real-World Cost Effectiveness of a Policy of KRAS Testing to Inform Cetuximab or Panitumumab for Third-Line Therapy of Metastatic Colorectal Cancer in British Columbia, Canada

BACKGROUND

Cetuximab and panitumumab, two anti-EGFR therapies, are widely used for third-line therapy of metastatic colorectal cancer (mCRC) with wild-type KRAS, but there remains uncertainty around their cost effectiveness. The objective of this analysis was to conduct a real-world cost-effectiveness analysis of the policy change introducing KRAS testing and third-line anti-EGFR therapy mCRC in British Columbia (BC), Canada.

METHODS

We conducted secondary analysis of administrative data for a cohort of mCRC patients treated in BC in 2006-2015. Patients potentially eligible for KRAS testing and third-line therapy after the policy change (July 2009) were matched 2:1 to pre-policy patients using genetic matching on propensity score and baseline covariates. Costs and survival time were calculated over an 8-year time horizon, with bootstrapping to characterize uncertainty around endpoints. Cost effectiveness was expressed using incremental cost-effectiveness ratios (ICER) and the probability of cost effectiveness at a range of thresholds.

RESULTS

The cohort included 1757 mCRC patients (n = 456 pre-policy and n = 1304 post-policy; of those, n = 420 received cetuximab or panitumumab). There was a significant increase in survival and cost following the policy change. Adoption of KRAS testing and anti-EGFR therapy had an ICER of CA$73,759 per life-year gained (LYG) (95% CI 46,133-186,446). In scenario analysis, a reduction in cetuximab and panitumumab cost of at least 50% was required to make the policy change cost effective at a threshold of CA$50,000/LYG.

CONCLUSION

A policy of third-line anti-EGFR therapy informed by KRAS testing may be considered cost effective at thresholds above CA$70,000/LYG. Reduction in drug costs, through price discounts or potential future biosimilars, would make anti-EGFR therapy considerably more cost effective. By using real-world data for a large cohort with long follow-up we can assess the value of a policy of KRAS testing and anti-EGFR therapy achieved in practice.

Evaluation of the Association Between Sociodemographic Status and Breast Screening Volumes During the COVID-19 Pandemic in a Provincial, Population-Based Organized Breast Screening Program

OBJECTIVES

We sought to evaluate the association between patient sociodemographic status and breast screening volumes (BSVs) during the COVID-19 pandemic in a large, population-based breast screening program that serves a provincial population of over 5 million.

METHODS

All patients who completed breast screening between April 1st, 2017 and March 31st, 2021 were eligible to participate. An average of 3 annual periods between April 1st, 2017 and March 31st, 2020 were defined as the pre-COVID period while the period between April 1st, 2020 and March 31st, 2021 was defined as the COVID-impacted period. The Postal CodeOM Conversion File Plus was applied to map patient residential postal codes to 2016 census standard geographical areas, which provided information on community size, income quintile and dissemination areas. Dissemination areas were subsequently linked to the Canadian Index of Multiple Deprivation (CIMD).

RESULTS

Overall BSV was reduced by 23.0% during the COVID-impacted period as compared to the pre-COVID period. Percent reductions in BSVs were greatest among younger patients aged 40 to 49 years (31.3%) and patients residing in communities with a population of less than 10,000 (27.0%). Percent reduction in BSV was greatest among patients in the lowest income quintile (28.1%). Percent reductions in BSVs were greatest for patients in the most deprived quintiles across all 4 dimensions of the CIMD.

CONCLUSION

Disproportionate reductions in BSVs were observed during the COVID-19 pandemic among younger patients, patients residing in rural communities, patients in lower income quintiles, and patients in the most deprived quintiles across all 4 dimensions of the CIMD.

Genetic matching for time-dependent treatments: a longitudinal extension and simulation study

BACKGROUND

Longitudinal matching can mitigate confounding in observational, real-world studies of time-dependent treatments. To date, these methods have required iterative, manual re-specifications to achieve covariate balance. We propose a longitudinal extension of genetic matching, a machine learning approach that automates balancing of covariate histories. We examine performance by comparing the proposed extension against baseline propensity score matching and time-dependent propensity score matching.

METHODS

To evaluate comparative performance, we developed a Monte Carlo simulation framework that reflects a static treatment assigned at multiple time points. Data generation considers a treatment assignment model, a continuous outcome model, and underlying covariates. In simulation, we generated 1,000 datasets, each consisting of 1,000 subjects, and applied: (1) nearest neighbour matching on time-invariant, baseline propensity scores; (2) sequential risk set matching on time-dependent propensity scores; and (3) longitudinal genetic matching on time-dependent covariates. To measure comparative performance, we estimated covariate balance, efficiency, bias, and root mean squared error (RMSE) of treatment effect estimates. In scenario analysis, we varied underlying assumptions for assumed covariate distributions, correlations, treatment assignment models, and outcome models.

RESULTS

In all scenarios, baseline propensity score matching resulted in biased effect estimation in the presence of time-dependent confounding, with mean bias ranging from 29.7% to 37.2%. In contrast, time-dependent propensity score matching and longitudinal genetic matching achieved stronger covariate balance and yielded less biased estimation, with mean bias ranging from 0.7% to 13.7%. Across scenarios, longitudinal genetic matching achieved similar or better performance than time-dependent propensity score matching without requiring manual re-specifications or normality of covariates.

CONCLUSIONS

While the most appropriate longitudinal method will depend on research questions and underlying data patterns, our study can help guide these decisions. Simulation results demonstrate the validity of our longitudinal genetic matching approach for supporting future real-world assessments of treatments accessible at multiple time points.

Development and early-stage evaluation of a patient portal to enhance familial communication about hereditary cancer susceptibility testing: A patient-driven approach

INTRODUCTION

Genetic testing for hereditary cancer syndromes (HCSs) can improve health outcomes through cancer risk mitigation strategies. Effective communication between tested individuals and their family members is key to reducing the hereditary cancer burden. Our objective was to develop a patient portal to improve familial communication for patients undergoing HCS genetic testing, followed by an early-phase evaluation.

METHODS

The portal was developed following the completion of 25 semistructured interviews with individuals having undergone HCS susceptibility testing at BC Cancer. Following initial development, we recruited patients and healthcare providers to provide critical feedback informing portal refinement. Quantitative feedback was summarized using descriptive statistics, and qualitative feedback was synthesized by two reviewers who engaged in iterative discussion within the research team to prioritize recommendations for integration.

RESULTS

The patient portal includes four key components consisting of (a) targeted educational information about hereditary cancer and HBOC syndrome associated risks and testing process overview, (b) a general frequently asked questions 'FAQ' page informed by the qualitative interviews, patient partner feedback, and consultation with the HCP, (c) guidance to support familial communication including a video developed with a patient partner describing their lived experience navigating the communication process and (d) a series of lay summaries of genetic test findings to support information transfer among family members. Thirteen healthcare providers and seven patients participated in user testing. Domains within which participant recommendations were provided included presentation, educational content and process clarification.

CONCLUSIONS

This investigation demonstrates the value of continual integration of patient and provider preferences through the development of tools endeavouring to assist with complex genomics-informed decision-making. Our work aims to broaden the population-wide impact of HCS testing programs by improving communication processes between probands and their potentially affected family members.

PATIENT OR PUBLIC CONTRIBUTION

This work involved a patient partner who was actively engaged in all aspects of the research investigation including protocol development, review and editing of all study documentation (including that of the previously published qualitative investigation), interpretation of results, as well as reviewing and editing the manuscript. Patient partners and healthcare professionals were recruited as research participants to provide critical feedback on the patient portal.

A perspective on life-cycle health technology assessment and real-world evidence for precision oncology in Canada

Health technology assessment (HTA) can be used to make healthcare systems more equitable and efficient. Advances in precision oncology are challenging conventional thinking about HTA. Precision oncology advances are rapid, involve small patient groups, and are frequently evaluated without a randomized comparison group. In light of these challenges, mechanisms to manage precision oncology uncertainties are critical. We propose a life-cycle HTA framework and outline supporting criteria to manage uncertainties based on real world data collected from learning healthcare systems. If appropriately designed, we argue that life-cycle HTA is the driver of real world evidence generation and furthers our understanding of comparative effectiveness and value. We conclude that life-cycle HTA deliberation processes must be embedded into healthcare systems for an agile response to the constantly changing landscape of precision oncology innovation. We encourage further research outlining the core requirements, infrastructure, and checklists needed to achieve the goal of learning healthcare supporting life-cycle HTA.

Developing Data Sharing Models for Health Research with Real-World Data: A Scoping Review of Patient and Public Preferences

For researchers to realize the benefits of real-world data in healthcare requires broader access to patient data than is currently possible given siloed data systems. To facilitate evidence generation, infrastructure must support integrated data collection and sharing enabled by patient consent. Critical to the success of data sharing is to design secured data sharing platforms around patient preferences and expectations. The objective of this review was to characterize patient and public preferences for secured data sharing platforms and incentives to share real-world data for health research. We conducted a scoping review of the data sharing and health informatics literature capturing patient and public values for data sharing platforms and incentivization. We searched Embase and Medline (OVID) databases for primary data studies. Two reviewers participated in study selection and data abstraction. Findings were summarized according to preference frequency within each major theme. The final search produced 253 articles. After screening, 12 articles were included for data extraction. Two studies discussed preferences for data sharing platforms, 7 discussed incentives preferences, and 3 addressed both. We identified considerable variation of patient and public preferences according to preferred consent mechanisms and level of control, willingness to trade off risks and benefits, and the type of incentivization appropriate to offer for participation. This preference variation informs the conditions under which individuals may be willing to engage with secured data sharing platforms to support research. Our findings indicate that platforms will need to be flexible to meet the diverse preferences of users and facilitate uptake.

Patient-reported outcomes in a linguistically diverse cancer population: Addressing barriers to access

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Background: The census metropolitan area served by BC Cancer is Vancouver which has a population of 2.4 million. Census Canada noted the mother tongue learned in childhood and still spoken was: 54% English, 17% Indo-European, 16% Chinese, 10% Indo-Iranian, 3% English+other language, 2% other. At BC Cancer, implementation of patient reported outcomes (PROs) was launched 1 year ago with consideration of preferred language. Our goal was to examine the implementation of PROs with respect to equity of access and language preferences. Methods: BC Cancer Vancouver implemented PROs including the Edmonton Symptom Assessment Scale Revised, Canadian Problem Checklist and EQ5D in April 2021 using a web-based platform. A 1-year cohort was reviewed for patients’ mother tongue and the language used for the PROs. Qualitative interviews were undertaken for non-English mother tongue patients to ask for preferred language of PROs and reasons for the choice if mother tongue was not selected. Results: 86 patients were enrolled in the PRO program. Baseline characteristics: 66% female, age 30% < 60/ 31% 60-69/ 39% >70, primary site 54% lung/ 34% colorectal/ 18% other. Ethnic origin: 53% North American and European, 40% East and Southeast Asian, 2% Latin/Central and South American, 3% South Asian, 1% Indigenous, 1% other. Mother tongue: 52% English, 48% non-English (39% English proficient, 9% low English proficiency). Patient preferred language for PROs: 81% English, 11% Chinese, 7% other. Reasons for non-English mother tongue preference for English language included comfort with written English, use of family assistance completing questionnaires for both language and familiarity with electronic devices. Conclusions: In the Vancouver linguistically diverse cancer population, the majority of patients preferred English language PROs. Reasons for this include proficiency in the written language and the use of family members to complete the questionnaires. With 39% of patients over the age of 70 in our study, the use of electronic devices for completion may have introduced an additional barrier to access. In clinic iPad questionnaires with nursing and care aide support have been introduced to help address this gap. Clinical trial information: NCT05057234.

Tools for the Economic Evaluation of Precision Medicine: A Scoping Review of Frameworks for Valuing Heterogeneity-Informed Decisions

BACKGROUND AND OBJECTIVE

Precision medicine highlights the importance of exploring heterogeneity in the effectiveness and costs of interventions. Our objective was to identify and compare frameworks for valuing heterogeneity-informed decisions, and consider their strengths and weaknesses for application to precision medicine.

METHODS

We conducted a scoping review to identify papers that proposed an analytical framework to place a value, in terms of costs and health benefits, on using heterogeneity to inform treatment selection. The search included English-language papers indexed in MEDLINE, Embase or EconLit, and a manual review of references and citations. We compared the frameworks qualitatively considering: the purpose and setting of the analysis; the types of precision medicine interventions where the framework could be applied; and the framework's ability to address the methodological challenges of evaluating precision medicine.

RESULTS

Four analytical frameworks were identified: value of stratification, value of heterogeneity, expected value of individualised care and loss with respect to efficient diffusion. Each framework is suited to slightly different settings and research questions. All focus on maximising net benefit, and quantify the opportunity cost of ignoring heterogeneity by comparing individualised or stratified decisions to a means-based population-wide decision. Where the frameworks differ is in their approaches to uncertainty, and in the additional metrics they consider.

CONCLUSIONS

Identifying and utilising heterogeneity is at the core of precision medicine, and the ability to quantify the value of heterogeneity-informed decisions is critical. Using an analytical framework to value heterogeneity will help provide evidence to inform investment in precision medicine interventions, appropriately capturing the value of targeted health interventions.

Defining a Core Data Set for the Economic Evaluation of Precision Oncology

OBJECTIVES

Precision oncology is generating vast amounts of multiomic data to improve human health and accelerate research. Existing clinical study designs and attendant data are unable to provide comparative evidence for economic evaluations. This lack of evidence can cause inconsistent and inappropriate reimbursement. Our study defines a core data set to facilitate economic evaluations of precision oncology.

METHODS

We conducted a literature review of economic evaluations of next-generation sequencing technologies, a common application of precision oncology, published between 2005 and 2018 and indexed in PubMed (MEDLINE). Based on this review, we developed a preliminary core data set for informal expert feedback. We then used a modified-Delphi approach with individuals involved in implementation and evaluation of precision medicine, including 2 survey rounds followed by a final voting conference to refine the data set.

RESULTS

Two authors determined that variation in published data elements was reached after abstraction of 20 economic evaluations. Expert consultation refined the data set to 83 unique data elements, and a multidisciplinary sample of 46 experts participated in the modified-Delphi process. A total of 68 elements (81%) were selected as required, spanning demographics and clinical characteristics, genomic data, cancer treatment, health and quality of life outcomes, and resource use.

CONCLUSIONS

Cost-effectiveness analyses will fail to reflect the real-world impacts of precision oncology without data to accurately characterize patient care trajectories and outcomes. Data collection in accordance with the proposed core data set will promote standardization and enable the generation of decision-grade evidence to inform reimbursement.

The impact of whole genome and transcriptome analysis (WGTA) on predictive biomarker discovery and diagnostic accuracy of advanced malignancies

In this study, we evaluate the impact of whole genome and transcriptome analysis (WGTA) on predictive molecular profiling and histologic diagnosis in a cohort of advanced malignancies. WGTA was used to generate reports including molecular alterations and site/tissue of origin prediction. Two reviewers analyzed genomic reports, clinical history, and tumor pathology. We used National Comprehensive Cancer Network (NCCN) consensus guidelines, Food and Drug Administration (FDA) approvals, and provincially reimbursed treatments to define genomic biomarkers associated with approved targeted therapeutic options (TTOs). Tumor tissue/site of origin was reassessed for most cases using genomic analysis, including a machine learning algorithm (Supervised Cancer Origin Prediction Using Expression [SCOPE]) trained on The Cancer Genome Atlas data. WGTA was performed on 652 cases, including a range of primary tumor types/tumor sites and 15 malignant tumors of uncertain histogenesis (MTUH). At the time WGTA was performed, alterations associated with an approved TTO were identified in 39 (6%) cases; 3 of these were not identified through routine pathology workup. In seven (1%) cases, the pathology workup either failed, was not performed, or gave a different result from the WGTA. Approved TTOs identified by WGTA increased to 103 (16%) when applying 2021 guidelines. The histopathologic diagnosis was reviewed in 389 cases and agreed with the diagnostic consensus after WGTA in 94% of non‐MTUH cases (n = 374). The remainder included situations where the morphologic diagnosis was changed based on WGTA and clinical data (0.5%), or where the WGTA was non‐contributory (5%). The 15 MTUH were all diagnosed as specific tumor types by WGTA. Tumor board reviews including WGTA agreed with almost all initial predictive molecular profile and histopathologic diagnoses. WGTA was a powerful tool to assign site/tissue of origin in MTUH. Current efforts focus on improving therapeutic predictive power and decreasing cost to enhance use of WGTA data as a routine clinical test.

Whole genome and transcriptome analysis enhances precision cancer treatment options

BACKGROUND

Recent advances are enabling delivery of precision genomic medicine to cancer clinics. While the majority of approaches profile panels of selected genes or hotspot regions, comprehensive data provided by whole genome and transcriptome sequencing and analysis (WGTA) presents an opportunity to align a much larger proportion of patients to therapies.

PATIENTS AND METHODS

Samples from 570 patients with advanced or metastatic cancer of diverse types enrolled in the Personalized OncoGenomics (POG) program underwent WGTA. DNA-based data, including mutations, copy number, and mutation signatures, were combined with RNA-based data, including gene expression and fusions, to generate comprehensive WGTA profiles. A multidisciplinary molecular tumour board used WGTA profiles to identify and prioritize clinically actionable alterations and inform therapy. Patient responses to WGTA-informed therapies were collected.

RESULTS

Clinically actionable targets were identified for 83% of patients, 37% of whom received WGTA-informed treatments. RNA expression data were particularly informative, contributing to 67% of WGTA-informed treatments; 25% of treatments were informed by RNA expression alone. Of a total 248 WGTA-informed treatments, 46% resulted in clinical benefit. RNA expression data were comparable to DNA-based mutation and copy number data in aligning to clinically beneficial treatments. Genome signatures also guided therapeutics including platinum, PARP inhibitors, and immunotherapies. Patients accessed WGTA-informed treatments through clinical trials (19%), off-label use (35%), and as standard therapies (46%) including those which would not otherwise have been the next choice of therapy, demonstrating the utility of genomic information to direct use of chemotherapies as well as targeted therapies.

CONCLUSIONS

Integrating RNA expression and genome data illuminated treatment options that resulted in 46% of treated patients experiencing positive clinical benefit, supporting the use of comprehensive WGTA profiling in clinical cancer care.

CLINICAL TRIAL NUMBER

NCT02155621.

Life-cycle health technology assessment for precision oncology

e18704

Background: Rapid advances in precision oncology challenge timely and sustainable reimbursement decisions. Life-cycle health technology assessment (LC-HTA) can enable conditional patient access to promising precision oncology innovations alongside evidence development. Our objective was to create a life-cycle evaluative framework, called PRecision oncology Evidence Development in Cancer Treatment (PREDiCT). Methods: Through an iterative, health system and stakeholder-informed approach, we designed our LC-HTA framework. Elements supporting data and evidence generation were subsequently implemented within British Columbia, Canada’s provincial cancer control system. Our development, refinement, and pilot implementation process included a structured literature review, multi-disciplinary international expert consultation, a formal gap assessment, and a series of pan-Canadian inter-disciplinary stakeholder workshops to refine framework elements. Results: We engaged n = 15 pan-Canadian and international stakeholders to co-develop the LC-HTA framework. Defining framework components include: (a) managed access that defines the time horizon and pricing conditions of real-world healthcare system trialing; (b) collection of core data elements required to enable economic evaluation of precision oncology using real world data; (c) externally leveraged real world data and evidence generation to determine comparative effectiveness, cost-effectiveness, and the value of conducting additional research; and (d) data interpretation updating decisions, including investment, continued evaluation, or disinvestment from managed access. Key to the success of early framework implementation is the expansion of infrastructure to enable routine collection and linkage of genomic sequencing and cancer treatment data, patient quality of life and clinical outcomes, as well as health resource use spanning the diagnostic, treatment, and follow up trajectory. Conclusions: Sustainable integration of precision oncology requires the design and implementation of learning healthcare systems (LHS) that integrate genomic data with other health information. LC-HTA moves beyond static estimates of clinical and cost-effectiveness to continuously generate evidence that reduces evidentiary uncertainty and supports life-cycle decisions. We are embarking on a PREDiCT pilot to implement the framework in real-time to demonstrate the ability of real-world data to support life cycle evaluation.

Utility maximization versus regret minimization in health choice behavior: Evidence from four datasets

Choice models in health are almost exclusively based on the neoclassical economic paradigm of utility maximization. Recently developed choice models have captured and shown empirical support for regret minimization as an alternative decision rule. In health economics, recent applications of RRM models indicate that individuals making health-based choices may exhibit regret minimization-type behavior. In this paper, we build on this research using a more flexible model that allows for heterogeneous decision rules, separately from preference heterogeneity, and comparing it to models that assume single decision rules. We use four datasets from diverse settings in which individuals make health choices: tobacco markets, genomic testing, and HIV prevention. We found that, if a one-size-fits-all rule is applied, then utility maximization was preferable to regret minimization for these datasets. However, we also find that individuals apply varying decision rules in similar proportions in these health settings, suggesting that models for heterogeneous decision rules were needed to capture these behaviors in these settings.

FDA Accelerated Approval for Malignant Hematology and Oncology Indications in the Canadian Environment

Accelerated approval (AA) by the FDA enables earlier access to promising new therapies. Health Canada has a similar process. Canada implemented a national health technology assessment (HTA) for reimbursement decisions in 2011. This study evaluated regulatory and funding timelines and decisions for FDA AA cancer therapies in Canada. The FDA’s AA of malignant hematology and oncology from January 2000–December 2019 was reviewed. Dates from Health Canada, HTA decisions and provincial listings were collected. There were 94 FDA AAs, two of which were subsequently withdrawn. Of the 92 AAs, 70 received full (46)/conditional (24) Health Canada approval, and 22 were not filed. Since the introduction of HTA, 31 out of 45 of Health Canada’s approved indications underwent HTA review: 18 received a positive recommendation conditional on cost-effectiveness, 8 were not recommended and 5 were withdrawn/suspended. The median time from the AA to any Health Canada approval is 9.4 months, from any Health Canada approval to HTA decision is 5.8 months and from HTA decision to the first formulary listing is 12.0 months. The access and timeline for the first formulary listing differences were observed between the USA and Canada due to the decision of pharmaceutical companies to submit (or not) to regulatory/HTA bodies, national procedural delays with different healthcare delivery models and submission timelines. This study demonstrates that there is delayed access to promising new therapies in Canada.

OUP accepted manuscript

Background

We explored health professionals’ views on the utility of circulating tumor DNA (ctDNA) testing in hereditary cancer syndrome (HCS) management.

Materials and Methods

A qualitative interpretive description study was conducted, using semi-structured interviews with professionals across Canada. Thematic analysis employing constant comparison was used for analysis. 2 investigators coded each transcript. Differences were reconciled through discussion and the codebook was modified as new codes and themes emerged from the data.

Results

Thirty-five professionals participated and included genetic counselors (n = 12), geneticists (n = 9), oncologists (n = 4), family doctors (n = 3), lab directors and scientists (n = 3), a health-system decision maker, a surgeon, a pathologist, and a nurse. Professionals described ctDNA as “transformative” and a “game-changer”. However, they were divided on its use in HCS management, with some being optimistic (optimists) while others were hesitant (pessimists). Differences were driven by views on 3 factors: (1) clinical utility, (2) ctDNA’s role in cancer screening, and (3) ctDNA’s invasiveness. Optimists anticipated ctDNA testing would have clinical utility for HCS patients, its role would be akin to a diagnostic test and would be less invasive than standard screening (eg imaging). Pessimistic participants felt ctDNA testing would add limited utility; it would effectively be another screening test in the pathway, likely triggering additional investigations downstream, thereby increasing invasiveness.

Conclusions

Providers anticipated ctDNA testing will transform early cancer detection for HCS families. However, the contrasting positions on ctDNA’s role in the care pathway raise potential practice variations, highlighting a need to develop evidence to support clinical implementation and guidelines to standardize adoption.

Stakeholder Perspectives on Navigating Evidentiary and Decision Uncertainty in Precision Oncology

(1) Background: Precision oncology has the potential to improve patient health and wellbeing through targeted prevention and treatment. Owing to uncertain clinical and economic outcomes, reimbursement has been limited. The objective of this pan-Canadian qualitative study was to investigate barriers to precision oncology implementation from the perspectives of health system stakeholders. (2) Methods: We conducted 32 semi-structured interviews with health technology decision makers (n = 14) and clinicians (n = 18) experienced with precision oncology. Participants were recruited using a purposive sampling technique. Interviews were analyzed using thematic analysis. Recruitment continued until two qualitative analysts reached agreement that thematic saturation was reached. (3) Results: While cautiously optimistic about the potential for enhanced therapeutic alignment, participants identified multiple decisional challenges under conditions of evidentiary uncertainty. Decision makers voiced concern over resource requirements alongside small benefitting patient populations and limited evidence supporting patient and health system impacts. Clinicians were comparatively tolerant of evidentiary uncertainty guiding clinical decision-making practices. Clinicians applied a broader definition of patient benefit, focusing on the ability to assist patients making informed clinical decisions. (4) Conclusions: Sustainable precision oncology must balance demand with evidence demonstrating benefit. We show that clinicians and decision makers vary in their tolerance for evolving knowledge, suggesting a need to establish evidentiary standards supporting precision oncology reimbursement decisions.

Early-stage economic analysis of research-based comprehensive genomic sequencing for advanced cancer care

Genomic research is driving discovery for future population benefit. Limited evidence exists on immediate patient and health system impacts of research participation. This study uses real-world data and quasi-experimental matching to examine early-stage cost and health impacts of research-based genomic sequencing. British Columbia’s Personalized OncoGenomics (POG) single-arm program applies whole genome and transcriptome analysis (WGTA) to characterize genomic landscapes in advanced cancers. Our cohort includes POG patients enrolled between 2014 and 2015 and 1:1 genetic algorithm–matched usual care controls. We undertake a cost consequence analysis and estimate 1-year effects of WGTA on patient management, patient survival, and health system costs reported in 2015 Canadian dollars. WGTA costs are imputed and forecast using system of equations modeling. We use Kaplan-Meier survival analysis to explore survival differences and inverse probability of censoring weighted linear regression to estimate mean 1-year survival times and costs. Non-parametric bootstrapping simulates sampling distributions and enables scenario analysis, revealing drivers of incremental costs, survival, and net monetary benefit for assumed willingness to pay thresholds. We identified 230 POG patients and 230 matched controls for cohort inclusion. The mean period cost of research-funded WGTA was $26,211 (SD: $14,191). Sequencing costs declined rapidly, with WGTA forecasts hitting $13,741 in 2021. The incremental healthcare system effect (non-research expenditures) was $5203 (95% CI: 75, 10,424) compared to usual care. No overall survival differences were observed, but outcome heterogeneity was present. POG patients receiving WGTA-informed treatment experienced incremental survival gains of 2.49 months (95% CI: 1.32, 3.64). Future cost consequences became favorable as WGTA cost drivers declined and WGTA-informed treatment rates improved to 60%. Our study demonstrates the ability of real-world data to support evaluations of only-in-research health technologies. We identify situations where precision oncology research initiatives may produce survival benefit at a cost that is within healthcare systems’ willingness to pay. This economic evidence informs the early-stage healthcare impacts of precision oncology research.

Toward the diagnosis of rare childhood genetic diseases: what do parents value most?

Genomic testing is becoming routine for diagnosing rare childhood genetic disease. Evidence underlying sustainable implementation is limited, focusing on short-term endpoints such as diagnostic yield, unable to fully characterize patient and family valued outcomes. Although genomic testing is becoming widely available, evidentiary and outcomes uncertainty persist as key challenges for implementation. We examine whether the current evidence base reflects public tolerance for uncertainty for genomics to diagnose rare childhood genetic disease. We conducted focus groups with general population parents in Vancouver, Canada, and Oxford, United Kingdom, to discuss expectations and concerns related to genomic testing to diagnose rare childhood genetic disease. Applying a purposive sampling technique, recruitment continued until thematic saturation was reached. Transcripts were analysed using thematic analysis. Thirty-three parents participated across four focus groups. Participants valued causal diagnoses alongside management strategies to improve patient health and wellbeing. Further, participants valued expanding the evidence base to reduce evidentiary uncertainty while ensuring security of information. Willingness to pay out of pocket for testing reflected perceived familial health benefit. Diagnostic yield fails to fully capture valued outcomes, and efforts to resolve uncertainty better reflect public priorities. Evaluations of genomic testing that fully integrate valued endpoints are necessary to ensure consistency with best practices and public willingness to accept the uncertain familial benefit.

Patient and public preferences for being recontacted with updated genomic results: a mixed methods study

Variants of uncertain significance (VUS) are frequently reclassified but recontacting patients with updated results poses significant resource challenges. We aimed to characterize public and patient preferences for being recontacted with updated results. A discrete choice experiment (DCE) was administered to representative samples of the Canadian public and cancer patients. DCE attributes were uncertainty, cost, recontact modality, choice of results, and actionability. DCE data were analyzed using a mixed logit model and by calculating willingness to pay (WTP) for types of recontact. Qualitative interviews exploring recontact preferences were analyzed thematically. DCE response rate was 60% (n = 1003, 50% cancer patient participants). 31 participants were interviewed (11 cancer patients). Interviews revealed that participants expected to be recontacted. Quantitatively, preferences for how to be recontacted varied based on certainty of results. For certain results, WTP was highest for being recontacted by a doctor with updates ($1075, 95% CI: $845, $1305) and for contacting a doctor to request updates ($1038, 95% CI: $820, $1256). For VUS results, WTP was highest for an online database ($1735, 95% CI: $1224, $2247) and for contacting a doctor ($1705, 95% CI: $1102, $2307). Qualitative data revealed that preferences for provider-mediated recontact were influenced by trust in healthcare providers. Preferences for a database were influenced by lack of trust in providers and desire for control. Patients and public participants support an online database (e.g. patient portal) to recontact for VUS, improving feasibility, and provider-mediated recontact for certain results, consistent with usual care.

Canadian Regulatory and Health Technology Assessment for Malignant Hematology and Oncology Indications Compared With the US Food and Drug Administration Accelerated Approval Program

This quality improvement study compares US Food and Drug Administration accelerated approvals with Canadian health and technology assessment approvals and timelines for malignant hematology and oncology treatments.

Clinical and cost outcomes following genomics-informed treatment for advanced cancers

BACKGROUND

Single-arm trials are common in precision oncology. Owing to the lack of randomized counterfactual, resultant data are not amenable to comparative outcomes analyses. Difference-in-difference (DID) methods present an opportunity to generate causal estimates of time-varying treatment outcomes. Using DID, our study estimates within-cohort effects of genomics-informed treatment versus standard care on clinical and cost outcomes.

METHODS

We focus on adults with advanced cancers enrolled in the single-arm BC Cancer Personalized OncoGenomics program between 2012 and 2017. All individuals had a minimum of 1-year follow up. Logistic regression explored baseline differences across patients who received a genomics-informed treatment versus a standard care treatment after genomic sequencing. DID estimated the incremental effects of genomics-informed treatment on time to treatment discontinuation (TTD), time to next treatment (TTNT), and costs. TTD and TTNT correlate with improved response and survival.

RESULTS

Our study cohort included 346 patients, of whom 140 (40%) received genomics-informed treatment after sequencing and 206 (60%) received standard care treatment. No significant differences in baseline characteristics were detected across treatment groups. DID estimated that the incremental effect of genomics-informed versus standard care treatment was 102 days (95% CI: 35, 167) on TTD, 91 days (95% CI: -9, 175) on TTNT, and CAD$91,098 (95% CI: $46,848, $176,598) on costs. Effects were most pronounced in gastrointestinal cancer patients.

CONCLUSIONS

Genomics-informed treatment had a statistically significant effect on TTD compared to standard care treatment, but at increased treatment costs. Within-cohort evidence generated through this single-arm study informs the early-stage comparative effectiveness of precision oncology.

Cost-Effectiveness Analysis of Stereotactic Ablative Body Radiotherapy for the Treatment of Oligometastatic Tumors versus Standard of Care

BACKGROUND

Recent clinical trial results reported that stereotactic radiotherapy (SABR) may improve survival for patients with oligometastatic (OM) cancer. Given that these results come from a phase II trial, there remains considerable uncertainty about this finding, and about the cost-effectiveness of SABR for patients with OM cancer. In this analysis, we estimate the cost-effectiveness of SABR for oligometastatic cancer patients.

METHODS

A probabilistic time-dependent Markov model was constructed to simulate treatment of oligometastatic cancer patients over five- and ten-year time horizons. The primary data source was the phase II, Stereotactic Ablative Radiotherapy for the Comprehensive Treatment of Oligometastases (SABR-COMET )trial and supplemented with data from the literature. We estimated the effect of SABR and the standard of care (SoC) using quality-adjusted life-years (QALYs). Costs were measured from a provincial payer perspective (2018 Canadian dollars).

RESULTS

In the reference case analysis (five-year time horizon), SABR was associated with additional incremental costs of CAD 38,487 and an incremental QALY gain of 0.84. This resulted in an incremental cost-effectiveness ratio (ICER) of CAD 45,726 per QALY gained. Over a ten-year time horizon, the increased uncertainty in the long-term effectiveness of SABR resulted in an ICER of CAD 291,544 per QALY gained. Estimates from the probabilistic analysis indicated that at a willingness-to-pay (WTP) threshold of CAD 50,000 and CAD 100,000 per QALY gained, there is 54% and 78% probability (respectively) that SABR would be cost-effective using the five-year time horizon.

CONCLUSIONS

The adoption of SABR therapy requires a considerable upfront capital investment. Our results suggest that the cost-effectiveness of SABR is contingent on the uncertainty in the evidence base. Further clinical trials to confirm the effectiveness of SABR and research into the real-world costs associated with this treatment could reduce the uncertainty around implementation of the technology.

Describing practices of priority setting and resource allocation in publicly funded health care systems of high-income countries

BACKGROUND

Healthcare spending has grown over the last decades in all developed countries. Making hard choices for investments in a rational, evidence-informed, systematic, transparent and legitimate manner constitutes an important objective. Yet, most scientific work in this area has focused on developing/improving prescriptive approaches for decision making and presenting case studies. The present work aimed to describe existing practices of priority setting and resource allocation (PSRA) within the context of publicly funded health care systems of high-income countries and inform areas for further improvement and research.

METHODS

An online qualitative survey, developed from a theoretical framework, was administered with decision-makers and academics from 18 countries. 450 individuals were invited and 58 participated (13% of response rate).

RESULTS

We found evidence that resource allocation is still largely carried out based on historical patterns and through ad hoc decisions, despite the widely held understanding that decisions should be based on multiple explicit criteria. Health technology assessment (HTA) was the tool most commonly indicated by respondents as a formal priority setting strategy. Several approaches were reported to have been used, with special emphasis on Program Budgeting and Marginal Analysis (PBMA), but limited evidence exists on their evaluation and routine use. Disinvestment frameworks are still very rare. There is increasing convergence on the use of multiple types of evidence to judge the value of investment options.

CONCLUSIONS

Efforts to establish formal and explicit processes and rationales for decision-making in priority setting and resource allocation have been still rare outside the HTA realm. Our work indicates the need of development/improvement of decision-making frameworks in PSRA that: 1) have well-defined steps; 2) are based on multiple criteria; 3) are capable of assessing the opportunity costs involved; 4) focus on achieving higher value and not just on adoption; 5) engage involved stakeholders and the general public; 6) make good use and appraisal of all evidence available; and 6) emphasize transparency, legitimacy, and fairness.

Readiness of Healthcare Systems to Generate Real-World Evidence: Reliability of CT Radiographic End Points for Evaluation of First-Line Systemic Treatment

PURPOSE

Regulatory agencies such as the US Food and Drug Administration and health technology assessment bodies are increasingly using real-world evidence (RWE). The ability of healthcare systems to reliably generate response rate and progression-free survival from real-world data is unknown. We examined the capacity of a single-payer system to provide RWE by evaluating the frequency of computed tomography (CT) imaging during standard first-line metastatic systemic treatment of breast, colorectal, and lung cancer.

METHODS

A 1-year cohort of patients with metastatic-at-diagnosis breast, colorectal, and lung cancer treated with first-line systemic therapy (excluding hormone therapy) referred to BC Cancer in 2016 was retrospectively reviewed for first-line treatment and CT imaging. Duration of first-line treatment was calculated from the first to the last dose of therapy. CT imaging was counted from the start of therapy to 8 weeks after the last therapy dose.

RESULTS

A cohort of 664 patients was identified from the BC Cancer Registry. Distribution of metastatic disease at diagnosis was breast (n = 82), colorectal (n = 214), and lung (n = 368) cancer. For breast, colorectal, and lung cancer, there was a baseline CT within 4 weeks of treatment initiation in 59%, 51%, and 48% of patients, with median duration of first-line treatment of 14.6, 25.3, and 11.9 weeks and median CT imaging interval of 9.1, 9.0, and 6.1 weeks.

CONCLUSION

In our publicly funded healthcare system, availability of baseline CT imaging was 48% to 59% and the frequency of assessment ranged from 6.1 to 9.1 weeks, subject to patterns of practice and resource availability. Our system was not capable of providing RWE for image-based end points. Alternative end points should be considered to capitalize on the wealth of real-world data.

Matching methods in precision oncology: An introduction and illustrative example

BACKGROUND

Randomized controlled trials (RCTs) are uncommon in precision oncology. We provide an introduction and illustrative example of matching methods for evaluating precision oncology in the absence of RCTs. We focus on British Columbia's Personalized OncoGenomics (POG) program, which applies whole-genome and transcriptome analysis (WGTA) to inform advanced cancer care.

METHODS

Our cohort comprises 230 POG patients enrolled between 2014 and 2015 and matched POG-naive controls. We generated our matched cohort using 1:1 propensity score matching (PSM) and genetic matching prior to exploring survival differences.

RESULTS

We find that genetic matching outperformed PSM when balancing covariates. In all cohorts, overall survival did not significantly differ across POG and POG-naive patients (p > 0.05). Stratification by WGTA-informed treatment indicated unmatched survival differences. Patients whose WGTA information led to treatment change were at a reduced hazard of death compared to POG-naive controls in all cohorts, with estimated hazard ratios ranging from 0.33 (95% CI: 0.13, 0.81) to 0.41 (95% CI: 0.17, 0.98).

CONCLUSION

These results signal that clinical effectiveness of precision oncology approaches will depend on rates of genomics-informed treatment change. Our study will guide future evaluations of precision oncology and support reliable effect estimation when RCT data are unavailable.

Cost-effectiveness of brentuximab vedotin in advanced stage Hodgkin's lymphoma: a probabilistic analysis

BACKGROUND

Treatment with ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) is a well-established therapy for advanced Hodgkin's lymphoma (HL). However, the recently completed ECHELON-1 trial showed potential net clinical benefit for brentuximab vedotin (BREN+AVD) compared to ABVD as frontline therapy in patients with advanced Hodgkin's lymphoma. The objective of this analysis is to determine whether, on current evidence, BREN+AVD is cost-effective relative to ABVD as frontline therapy in patients with advanced HL.

METHODS

We constructed a probabilistic Markov model with two arms and six mutually exclusive health states, using six-month cycle lengths, and a 15-year time horizon. Time-dependent transition probabilities were calculated from 'real-world' data collected by the BC Cancer's Centre for Lymphoid Cancer database or from the literature for ABVD. Time-dependent transition probabilities for BREN+AVD were taken from the ECHELON-1 trial. We estimated the incremental cost and effects per patient of each therapy and calculated the incremental cost-effectiveness ratio (ICER). Costs were measured in 2018 Canadian dollars and effects measured in quality-adjusted life years (QALYs). A probabilistic analysis was used to generate a cost-effectiveness acceptability curve (CEAC).

RESULTS

The incremental cost between standard therapy with ABVD and therapy with BREN+AVD was estimated to be $192,336. The regimen of BREN+AVD resulted in a small benefit in terms of QALYs (0.46 QALYs). The estimated ICER was $418,122 per QALY gained. The probabilistic analysis suggests very few (8%) simulations fall below $100,000 per QALY. Even at a threshold of $200,000 per QALY gained, there was only a 24% chance that BREN+AVD would be considered cost-effective. Sensitivity analyses evaluating price reductions for brentuximab showed that these reductions needed to be in excess of 70% for this regimen to be cost-effective at a threshold of $100,000 per QALY.

CONCLUSIONS

There may be a clinical benefit associated with BREN+AVD, but on current evidence the benefit is not adequately substantive compared to ABVD therapy given the cost of brentuximab vedotin. Agencies responsible for making decisions about BREN+AVD as frontline therapy for patients with advanced HL should consider whether they are willing to implement this treatment given the current uncertainty and cost-benefit profile, or negotiate substantial price-reductions from the manufacturer should they choose to reimburse.

Genomic Testing for Relapsed and Refractory Lymphoid Cancers: Understanding Patient Values

BACKGROUND

New clinical genomic assays for lymphoid cancers allow for improved disease stratification and prognostication. At present, clinical implementation has been appropriately limited, owing to a paucity of evidence to support clinical and cost effectiveness. Understanding patients' values for precision oncology under conditions of uncertainty can be used to inform priority-setting decisions.

OBJECTIVES

Our objective was to ascertain patients' qualitative preferences and attitudes for prognostic-based genomic testing.

METHODS

Individuals who were diagnosed with lymphoid cancer between 2000 and 2018 in British Columbia, Canada, were recruited to participate in one of three focus groups. A maximum variation sampling technique was used to capture a diversity of perspectives. A patient partner was involved in the development of the focus group topic guide and presentation materials. All sessions were audio recorded and analyzed using NVivo qualitative analysis software, version 12.

RESULTS

In total, 26 participants took part in focus groups held between November 2018 and February 2019. Results illustrate qualitative preference heterogeneity for situations under which individuals would be willing to undergo genomic testing for relapsed lymphoid cancers. Preferences were highly contextualized within personal experiences with disease and treatment protocols. Hypothetical willingness to pay for testing was contingent on invasiveness, the potential for treatment de-escalation, and personal health benefit.

CONCLUSIONS

Patients are supportive and accepting of evidentiary uncertainty up until the point at which they are required to trade-off the potential for improved quality and length of life. Demand for precision medicine is contingent on expectations for benefit alongside an acknowledgment of the opportunity cost required for implementation. The clinical implementation of precision medicine will be required to address evidentiary uncertainty surrounding personal benefit while ensuring equitable access to emerging innovations.

Provider preferences for resolving uncertainty and avoiding harms in precision medicine: a discrete choice experiment

Background: Substantial uncertainty exists about how providers assess the value of genomic testing. Materials & methods: We developed and administered a discrete choice experiment to a national sample of providers. We analyzed responses using an error components mixed logit model. Results: We received responses from 356 providers. The attributes important to providers were patient health and function, life expectancy, cost, expert agreement, and biomarker prevalence. Providers significantly valued reducing uncertainty only when it eliminated the possibility of decreased life expectancy. Providers valued improving certainty about life expectancy gains from 12 ± 18 to 12 ± 6 months at US$400 (US$200-600) versus US$200 (-US$60-500) for 4 ± 4 to 4 ± 2 years. Conclusion: Providers value resolving uncertainty most when it eliminates the possibility of substantial harm.

Heterogeneous Patient Preferences for Modern Antiretroviral Therapy: Results of a Discrete Choice Experiment

OBJECTIVE

Limited data describe patient preferences for the growing number of antiretroviral therapies (ARTs). We quantified preferences for key characteristics of modern ART deemed relevant to shared decision making.

METHODS

A discrete choice experiment survey elicited preferences for ART characteristics, including dosing (frequency and number of pills), administration characteristics (pill size and meal requirement), most bothersome side effect (from diarrhea, sleep disturbance, headaches, dizziness/difficulty thinking, depression, or jaundice), and most bothersome long-term effect (from increased risk of heart attacks, bone fractures, renal dysfunction, hypercholesterolemia, or hyperglycemia). Between March and August 2017, the discrete choice experiment was fielded to 403 treatment-experienced persons living with human immunodeficiency virus (HIV), enrolled from 2 infectious diseases clinics in the southern United States and a national online panel. Participants completed 16 choice tasks, each comparing 3 treatment options. Preferences were analyzed using mixed and latent class logit models.

RESULTS

Most participants were male (68%) and older (interquartile range: 42-58 years), and had substantial treatment experience (interquartile range: 7-21 years). In mixed logit analyses, all attributes were associated with preferences. Side and long-term effects were most important, with evidence of substantial preference heterogeneity. Latent class analysis identified 5 preference classes. For classes 1 (40%), 2 (24%), and 3 (21%), side effects were most important, followed by long-term effects. For class 4 (10%), dosing was most important. Class 5 (4%) was largely indifferent to ART characteristics.

CONCLUSION

Overall, treatment-experienced persons living with HIV valued minimizing side effects and long-term toxicities over dosing and administration characteristics. Preferences varied widely, highlighting the need to elicit individual patient preferences in models of shared antiretroviral decision making.

Validation of a Cyclic Algorithm to Proxy Number of Lines of Systemic Cancer Therapy Using Administrative Data

PURPOSE

Researchers are automating the process for identifying the number of lines of systemic cancer therapy received by patients. To date, algorithm development has involved manual modifications to predefined classification rules. In this study, we propose a supervised learning algorithm for determining the best-performing proxy for number of lines of therapy and validate this approach in four patient groups.

MATERIALS AND METHODS

We retrospectively analyzed BC Cancer pharmacy records from patients' cancer diagnosis until end of follow-up (cohort-specific, 2014/2015). We created and validated a cyclic algorithm in patients with advanced cancers of varying histologies, diffuse large B-cell lymphoma, follicular lymphoma, and chronic lymphocytic leukemia. To assess internal and external validity, we used a split-sample approach for all analyses and considered lines of therapy identified through manual review as our criterion standard. We measured agreement using correlation coefficients, mean squared error, nonparametric hypothesis testing, and quantile-quantile plots.

RESULTS

Cohorts comprised 91 patients with advanced cancers, 121 with chronic lymphocytic leukemia, 440 with follicular lymphoma, and 679 with diffuse large B-cell lymphoma. Number of lines of therapy received and patients' treatment period length varied substantially across cohorts. Despite these differences, our algorithm successfully identified a best-performing proxy for number of lines of therapy for each cohort, which was moderate to highly correlated with (within-sample: 0.73 ≤ Pearson correlation ≤ 0.84; out-of-sample: 0.52 ≤ Pearson correlation ≤ 0.76) and whose distribution did not significantly differ from the criterion standard within or out of sample (P > .10).

CONCLUSION

Supervised learning is an ideal tool for generating a best-performing proxy that recognizes prescription drug patterns and approximates number of lines of therapy. Our cyclic approach can be used in jurisdictions with access to administrative pharmacy data.

Addressing Challenges of Economic Evaluation in Precision Medicine Using Dynamic Simulation Modeling

OBJECTIVES

The objective of this article is to describe the unique challenges and present potential solutions and approaches for economic evaluations of precision medicine (PM) interventions using simulation modeling methods.

METHODS

Given the large and growing number of PM interventions and applications, methods are needed for economic evaluation of PM that can handle the complexity of cascading decisions and patient-specific heterogeneity reflected in the myriad testing and treatment pathways. Traditional approaches (eg, Markov models) have limitations, and other modeling techniques may be required to overcome these challenges. Dynamic simulation models, such as discrete event simulation and agent-based models, are used to design and develop mathematical representations of complex systems and intervention scenarios to evaluate the consequence of interventions over time from a systems perspective.

RESULTS

Some of the methodological challenges of modeling PM can be addressed using dynamic simulation models. For example, issues regarding companion diagnostics, combining and sequencing of tests, and diagnostic performance of tests can be addressed by capturing patient-specific pathways in the context of care delivery. Issues regarding patient heterogeneity can be addressed by using patient-level simulation models.

CONCLUSION

The economic evaluation of PM interventions poses unique methodological challenges that might require new solutions. Simulation models are well suited for economic evaluation in PM because they enable patient-level analyses and can capture the dynamics of interventions in complex systems specific to the context of healthcare service delivery.

Genetic testing for hereditary cancer syndromes: patient recommendations for improved risk communication

Background

Multi‐gene panel testing is replacing single‐gene testing for patients with suspected hereditary cancer syndromes. The detection of a hereditary cancer syndrome allows tested individuals to initiate enhanced primary and secondary prevention efforts—where available—with a view to reduce disease burden. Current policy prevents testing programmes from communicating genetic test results with potentially affected family members, yet it is well documented that tested individuals face multiple challenges in initiating such discussions with relatives.

Objective

In response to this challenge, we sought patient recommendations about how to improve genetic risk communication to enhance interfamilial discussions about primary and secondary disease prevention.

Design

We conducted 25 semi‐structured interviews with individuals who received genetic testing through British Columbia’s Hereditary Cancer Program between 2017 and 2018. Interviews were professionally transcribed and analysed using a constant comparative approach.

Results

Participants described difficulty engaging in conversations with relatives who were resistant to receiving genetic risk information, when communicating with younger relatives and where participants reported strained familial relationships. Participants recommended that testing facilities provide a summary of results and implications and that resources be made available to prepare patients for challenging discussions with family members.

Discussion

Our study demonstrates that individuals undergoing genetic testing for suspected hereditary cancer syndromes would benefit from additional supportive resources alongside genetic counselling. Providing this on‐going support will enhance the accurate and transparent communication of risk to facilitate the uptake of cascade testing and enhanced prevention strategies.

Payer Preferences and Willingness to Pay for Genomic Precision Medicine: A Discrete Choice Experiment

BACKGROUND

Although precision medicine using genetic information offers significant promise, its uptake and eventual clinical and economic impacts are uncertain. Health care payers will play an important role in evaluating evidence and costs to develop coverage and reimbursement policies.

OBJECTIVE

To elicit U.S. health care payer preference for genomic precision medicine to better understand trade-offs among clinical benefits, uncertainty, and cost.

METHODS

Using key informant interviewer discussions (N = 6 payers), we identified 6 key attributes of genetic tests important to payers: type of information the test provides (screening vs. treatment prediction), probability that the member has an informative genetic marker, expert agreement on changing medical care based on the marker, quality-of-life gains, life expectancy gains (with statistical uncertainty), and cost to the plan. We designed a stated preference discrete choice experiment using these attributes and administered a web survey to a sample of U.S. health care payers. We used effects coding and analyzed the data using an error component mixed logit modeling approach.

RESULTS

The survey response rate was 58% (150 participants completed the survey). Approximately 53% of respondents had previous experience evaluating genetic tests for reimbursement, and 85% had more than 5 years of health care decision-making experience. Payers valued improvements in quality of life the most (marginal willingness to pay [mWTP] of $1,513-$6,076), followed by medical expert agreement on the treatment change (mWTP of $2,881-$3,489). Payers placed a relatively lower value for genetic tests with lower marker probability (mWTP of $2,776 for highest marker probability to $423 for lowest marker probability). Payers mWTP was lowest for resolving uncertainty in quality of life (mWTP of $1,513-$2,031) and life expectancy gains ($536-$1,537).

CONCLUSIONS

Payers exhibited a strong preference for genetic tests that improved quality of life, had high expert agreement on changing medical care, and increased life expectancy. These findings suggest that payers will need evidence of clinical utility to support coverage and reimbursement of genomic precision medicine.

DISCLOSURES

This study was supported by a grant from the NIH Common Fund and NIA (1U01AG047109-01) via the Personalized Medicine Economics Research (PriMER) project. Unrelated to this study, Veenstra reports consulting fees from Bayer and Halozyme; Basu reports consulting fees from Salutis Consulting; and Reiger reports consulting fees from Roche. Carlson reports grants from Institute for Clinical and Economic Review, during the conduct of this study, and consulting fees from Bayer, Adaptive Biotechnologies, Allergan, Galderma, and Vifor Pharma, unrelated to this study.

Demand for Precision Medicine: A Discrete-Choice Experiment and External Validation Study

BACKGROUND

A limited evidence base and lack of clear clinical guidelines challenge healthcare systems' adoption of precision medicine. The effect of these conditions on demand is not understood.

OBJECTIVE

This research estimated the public's preferences and demand for precision medicine outcomes.

METHODS

A discrete-choice experiment survey was conducted with an online sample of the US public who had recent healthcare experience. Statistical analysis was undertaken using an error components mixed logit model. The responsiveness of demand in the context of a changing evidence base was estimated through the price elasticity of demand. External validation was examined using real-world demand for the 21-gene recurrence score assay for breast cancer.

RESULTS

In total, 1124 (of 1849) individuals completed the web-based survey. The most important outcomes were survival gains with statistical uncertainty, cost of testing, and medical expert agreement on changing care based on test results. The value ($US, year 2017 values) for a test where most (vs. few) experts agreed to changing treatment based on test results was $US1100 (95% confidence interval [CI] 916-1286). Respondents were willing to pay $US265 (95% CI 46-486) for a test that could result in greater certainty around life-expectancy gains. The predicted demand of the assay was 9% in 2005 and 66% in 2014, compared with real-world uptake of 7% and 71% (root-mean-square prediction error 0.11). Demand was sensitive to price (1% increase in price resulted in > 1% change in demand) when first introduced and insensitive to price (1% increase in price resulted in < 0.1% change in demand) as the evidence base became established.

CONCLUSIONS

Evidence of external validity was found. Demand was weak and responsive to price in the near term because of uncertainty and an immature evidence base. Clear communication of precision medicine outcomes and uncertainty is crucial in allowing healthcare to align with individual preferences.

Evidence, values, and funding decisions in Canadian cancer systems

Expenditure on cancer therapies is rising rapidly in many countries, particularly for cancer drugs. In recent years, this has stimulated a global debate among the public, patients, clinicians, decision-makers, and the pharmaceutical industry on value, affordability, and sustainability propositions relating to cancer therapies. In this article, we discuss some recent developments in evidence-based approaches to priority setting and resource allocation in Canadian cancer systems. These developments include new methods for deliberative public engagement, generating and using real-world evidence, multi-criteria decision analysis, and handling uncertainty with evidence for gene therapies.

Health-related quality of life in oncology drug reimbursement submissions in Canada: A review of submissions to the pan-Canadian Oncology Drug Review

BACKGROUND

In Canada, the Canadian Agency for Drugs and Technologies in Health (CADTH) evaluates and makes recommendations for the reimbursement of cancer drugs. One component of its recommendation is based on an economic evaluation, which typically takes the form of a cost-utility analysis. A cost-utility analysis measures the effects of competing therapies with quality-adjusted life-years (QALYs). The data for this calculation typically come from generic, preference-based measures of health-related quality of life (HRQOL). The objective of this review is to determine the frequency at which HRQOL data are collected alongside cancer drug trials and used in the cost-utility analysis submitted to the CADTH pan-Canadian Oncology Drug Review (pCODR).

METHODS

Submissions between 2015 and 2018 to pCODR, the group charged with evaluating cancer drug submissions at CADTH, were reviewed. All pCODR submissions, either in progress or completed, were publicly available online. The search was restricted to completed evaluations.

RESULTS

Forty-three submissions met the inclusion criteria. The incremental gain in QALYs in most submissions from the new technology was small (median incremental gain, 0.86; interquartile range, 0.6-1.39). More than half of the submissions (56%) did not include original data on HRQOL, with most relying on previous studies of variable relevance and quality. Re-analyses by pCODR based on concerns over HRQOL data used in the submitted model were common (52%).

CONCLUSIONS

Drug manufacturers do not consistently collect data on HRQOL alongside clinical trials and instead rely on evidence generated in previous studies to inform cost-utility analyses. These findings should induce manufacturers to collect original HRQOL data that are simultaneously relevant to patients and decision makers.

Clinical exome sequencing vs. usual care for hereditary colorectal cancer diagnosis: A pilot comparative effectiveness study

BACKGROUND

Clinical exome sequencing (CES) provides the advantage of assessing genetic variation across the human exome compared to a traditional stepwise diagnostic approach or multi-gene panels. Comparative effectiveness research methods offer an approach to better understand the patient-centered and economic outcomes of CES.

PURPOSE

To evaluate CES compared to usual care (UC) in the diagnostic work-up of inherited colorectal cancer/polyposis (CRCP) in a randomized controlled trial (RCT).

METHODS

The primary outcome was clinical sensitivity for the diagnosis of inherited CRCP; secondary outcomes included psychosocial outcomes, family communication, and healthcare resource utilization. Participants were surveyed 2 and 4 weeks after results return and at 3-month intervals up to 1 year.

RESULTS

Evolving outcome measures and standard of care presented critical challenges. The majority of participants in the UC arm received multi-gene panels [94.73%]. Rates of genetic findings supporting the diagnosis of hereditary CRCP were 7.5% [7/93] vs. 5.4% [5/93] in the CES and UC arms, respectively (P = 0.28). Differences in privacy concerns after receiving CRCP results were identified (0.88 in UC vs 0.38 in CES, P = 0.05); however, healthcare resource utilization, family communication and psychosocial outcomes were similar between the two arms. More participants with positive results (17.7%) intended to change their life insurance 1  month after the first return visit compared to participants returned a variant of uncertain significance (9.1%) or negative result (4.8%) (P = 0.09).

CONCLUSION

Our results suggest that CES provides similar clinical benefits to multi-gene panels in the diagnosis of hereditary CRCP.

Real-world costing analysis for diffuse large B-cell lymphoma in British Columbia

Introduction

Diffuse large B-cell lymphoma (dlbcl) accounts for 30%-40% of all non-Hodgkin lymphomas. Approximately 60% of patients are cured with standard treatment. Targeted treatments are being investigated and might improve disease outcomes; however, their effect on cancer drug budgets will be significant. For the present study, we conducted an analysis of real-world costs for dlbcl patients treated in British Columbia, useful for health care system planning.

Methods

Patient records from a retrospective cohort of patients diagnosed with dlbcl in British Columbia during 2004-2013 were anonymously linked across multiple administrative data sources: systemic therapy, radiotherapy, hospitalizations, oncologist services, outpatient medications, and fee-for-service physician services. Using generalized linear modelling regression, time-dependent costs (in 2015 Canadian dollars) were estimated in 6-month intervals over a 5-year period. The inverse probability weighting method was applied to account for censored observations. Nonparametric bootstrapping was used to estimate standard errors for the mean cost at each time interval.

Results

The cohort consisted of 678 patients (5-year overall survival: 67%). Mean age at diagnosis was 64 ± 14 years; median follow-up was 3.2 years. Mean total cost of care was highest in the first 6 months after diagnosis ($29,120; 95% confidence interval: $28,986 to $29,170) and after disease progression ($18,480; 95% confidence interval: $15,187 to $24,772). Systemic therapy and hospitalization costs were the largest cost drivers. At each time interval, costs were observed to be positively skewed.

Conclusions

Our results depict real-world costs for the treatment of dlbcl patients with standard chop-r therapy. Cost-model parameters are also provided for economic modelling of dlbcl interventions.

The EORTC QLU-C10D: The Canadian Valuation Study and Algorithm to Derive Cancer-Specific Utilities From the EORTC QLQ-C30

Objective. The EORTC QLQ-C30 is widely used for assessing quality of life in cancer. However, QLQ-C30 responses cannot be incorporated in cost-utility analysis because they are not based on general population's preferences, or utilities. To overcome this limitation, the QLU-C10D, a cancer-specific utility algorithm, was derived from the QLQ-C30. The aim of this study was to obtain Canadian population utility weights for the QLU-C10D. Methods. Respondents from a Canadian research panel expressed their preferences for 16 choice sets in an online discrete choice experiment. Each choice set consisted of two health states described by the 10 QLU-C10D domains plus an attribute representing duration of survival. Using a conditional logit model, responses were converted into utility decrements by evaluating the marginal rate of substitution between each QLU-C10D domain level with respect to duration. Results. A total of 3,363 individuals were recruited. A total of 2,345 completed at least one choice set and 2,271 completed all choice sets. The largest utility decrements were associated with the worse levels of Physical Functioning (-0.24), Pain (-0.18), Role Functioning (-0.15), Emotional Functioning (-0.12), and Nausea (-0.12). The remaining domains and levels had decrements of -0.05 to -0.09. The utility of the worst possible health state was -0.15. Conclusion. Respondents from the general population were most concerned with generic health domains, but Nausea and Bowel Problems also had an impact on the individual's utility. It is unclear as to whether cancer-specific domains will affect cost-utility analysis when evaluating cancer treatments; this will be tested in the next phase of the study.

Economic Evaluations of Next-Generation Precision Oncology: A Critical Review

Purpose

Precision oncology has the potential to improve patient health and reduce treatment costs. Yet the up-front cost of genomic testing with next-generation sequencing (NGS) technologies can be prohibitive. Our study is a structured review of economic evaluations of precision oncology informed by NGS. The aim is to characterize the availability and scope of economic evidence.

Materials and Methods

We searched Medline (PubMed), Embase (Ovid), and Web of Science databases for English-language full-text peer-reviewed articles published between 2000 and 2016. We focused our search on articles that estimated the benefit of precision oncology in relation to its costs. We excluded studies that did not undertake full economic evaluations or did not focus on NGS technologies. We reviewed all included studies and summarized key methodological and empirical study characteristics.

Results

Fifty-five economic evaluations met our inclusion criteria. The number of published studies increased steadily, from three studies between 2005 and 2007 to 26 between 2014 and 2016. Most studies evaluated multiplex panels (86%). We found testing was frequently used to predict prognosis (67%), to diagnose patients (24%), or to identify targeted therapeutic options (7%). Methods and cost effectiveness differed according to NGS technology, test strategy, and cancer type. Deterministic and probabilistic analyses were typically used to characterize parameter and decision uncertainty (91% and 75%).

Conclusion

Although the availability of economic evidence examining precision oncology increased over time, methods used often did not align with current guidelines. Future evaluations should undertake extensive sensitivity analysis to address all sources of uncertainty associated with rapidly changing NGS technologies. Furthermore, additional research is needed evaluating the cost effectiveness of more comprehensive next-generation technologies before implementing these on a wider scale.