Criteria for assessing evidence for biomarker-targeted therapies in rare cancers-an extrapolation framework.

Background: Advances in targeted therapy development and tumor sequencing technology are reclassifying cancers into smaller biomarker-defined diseases. Randomized controlled trials (RCTs) are often impractical in rare diseases, leading to calls for single-arm studies to be sufficient to inform clinical practice based on a strong biological rationale. However, without RCTs, favorable outcomes are often attributed to therapy but may be due to a more indolent disease course or other biases. When the clinical benefit of targeted therapy in a common cancer is established in RCTs, this benefit may extend to rarer cancers sharing the same biomarker. However, careful consideration of the appropriateness of extending the existing trial evidence beyond specific cancer types is required. A framework for extrapolating evidence for biomarker-targeted therapies to rare cancers is needed to support transparent decision-making. Objectives: To construct a framework outlining the breadth of criteria essential for extrapolating evidence for a biomarker-targeted therapy generated from RCTs in common cancers to different rare cancers sharing the same biomarker. Design: A series of questions articulating essential criteria for extrapolation. Methods: The framework was developed from the core topics for extrapolation identified from a previous scoping review of methodological guidance. Principles for extrapolation outlined in guidance documents from the European Medicines Agency, the US Food and Drug Administration, and Australia's Medical Services Advisory Committee were incorporated. Results: We propose a framework for assessing key assumptions of similarity of the disease and treatment outcomes between the common and rare cancer for five essential components: prognosis of the biomarker-defined cancer, biomarker test analytical validity, biomarker actionability, treatment efficacy, and safety. Knowledge gaps identified can be used to prioritize future studies. Conclusion: This framework will allow systematic assessment, standardize regulatory, reimbursement and clinical decision-making, and facilitate transparent discussions between key stakeholders in drug assessment for rare biomarker-defined cancers.

Scenario analysis and multi-criteria decision analysis to explore alternative reimbursement pathways for whole genome sequencing for blood cancer patients.

BACKGROUND: Whole genome sequencing (WGS) has transformative potential for blood cancer management, but reimbursement is hindered by uncertain benefits relative to added costs. This study employed scenario planning and multi-criteria decision analysis (MCDA) to evaluate stakeholders' preferences for alternative reimbursement pathways, informing future health technology assessment (HTA) submission of WGS in blood cancer. METHODS: Key factors influencing WGS reimbursement in blood cancers were identified through a literature search. Hypothetical scenarios describing various evidential characteristics of WGS for HTA were developed using the morphological approach. An online survey, incorporating MCDA weights, was designed to gather stakeholder preferences (consumers/patients, clinicians/health professionals, industry representatives, health economists, and HTA committee members) for these scenarios. The survey assessed participants' approval of WGS reimbursement for each scenario, and scenario preferences were determined using the geometric mean method, applying an algorithm to improve reliability and precision by addressing inconsistent responses. RESULTS: Nineteen participants provided complete survey responses, primarily clinicians or health professionals (n = 6; 32 %), consumers/patients and industry representatives (both at n = 5; 26 %). "Clinical impact of WGS results on patient care" was the most critical criterion (criteria weight of 0.25), followed by "diagnostic accuracy of WGS" (0.21), "cost-effectiveness of WGS" (0.19), "availability of reimbursed treatment after WGS" (0.16), and "eligibility criteria for reimbursed treatment based on actionable WGS results" and "cost comparison of WGS" (both at 0.09). Participants preferred a scenario with substantial clinical evidence, high access to reimbursed targeted treatment, cost-effectiveness below $50,000 per quality-adjusted life year (QALY) gained, and affordability relative to standard molecular tests. Reimbursement was initially opposed until criteria such as equal cost to standard tests and better treatment accessibility were met. CONCLUSION: Payers commonly emphasize acceptable cost-effectiveness, but strong clinical evidence for many variants and comparable costs to standard tests are likely to drive positive reimbursement decisions for WGS.

Real-World Treatment and Outcomes in ALK-Rearranged NSCLC: Results From a Large U.S.-Based Database.

Introduction: ALK-rearranged advanced NSCLC (aNSCLC) represents 4% of all NSCLCs, and multiple ALK-targeted therapies (ALK-inhibitors) are now available for use. Little is known about changes in treatment patterns, or how prognostic factors and sequence of therapy may impact overall survival in the real-world setting. We aim to describe initial and subsequent treatments used, survival outcomes, prognostic factors, and the impact of treatment on overall survival in the largest (N = 739) real-world cohort of patients with ALK+ aNSCLC reported in the literature. Methods: Retrospective observational cohort study with data drawn from a U.S.-based electronic health record-derived, deidentified database. Eligible patients were diagnosed with ALK+ aNSCLC between 2011-2020 and were treated in multiple different cancer clinics and across multiple geographic regions throughout the United States. Results: From a cohort of 63,667 patients with aNSCLC, 739 patients with ALK+ NSCLC were eligible for analysis, median age was 63 years, 54% patients were female, and 85% were managed in community setting. More than 168 different treatment sequences were observed, and treatment utilization changed over time. Cohort median overall survival was 37 months (95% confidence interval: 33-45). Positive prognostic factors were as follows: never-smoking history, younger age, treatment in an academic setting, and initial early stage at diagnosis. Initial treatment with a second-generation ALK-inhibitor was associated with improved survival compared with chemotherapy. Conclusions: For people with ALK+ aNSCLC, this study has identified several important clinical prognostic factors and is practice affirming; first-line treatment with a second-generation ALK-inhibitor improves survival compared with chemotherapy.

Economic Impact of Whole Genome Sequencing and Whole Transcriptome Sequencing Versus Routine Diagnostic Molecular Testing to Stratify Patients with B-Cell Acute Lymphoblastic Leukemia.

Whole genome and whole transcriptome sequencing (WGTS) can accurately distinguish B-cell acute lymphoblastic leukemia (B-ALL) genomic subtypes. However, whether this is economically viable remains unclear. This study compared the direct costs and molecular subtype classification yield using different testing strategies for WGTS in adolescent and young adult/adult patients with B-ALL. These approaches were: (1) combined BCR::ABL1 by fluorescence in situ hybridization (FISH) + WGTS for all patients; and (2) sequential BCR::ABL1 FISH + WGTS contingent on initial BCR::ABL1 FISH test outcome. The cost of routine diagnostic testing was estimated using Medicare or hospital fees, and the additional cost of WGTS was evaluated from the health care provider perspective using time-driven activity-based costing with resource identification elicited from experts. Molecular subtype classification yield data were derived from literature sources. Parameter uncertainty was assessed through deterministic sensitivity analysis; additional scenario analyses were performed. The total per patient cost of WGTS was $4319 (all costs reported in US dollars); consumables accounted for 74% of the overall cost, primarily driven by sequencing-related consumables. The incremental cost per additional patient categorized into molecular subtype was $8498 for combined BCR::ABL1 FISH + WGTS for all patients and $5656 for initial BCR::ABL1 FISH + WGTS for select patients compared with routine diagnostic testing. A reduction in the consumable costs of WGTS or an increase in the yield of molecular subtype classification is favorable.

Predicting the Population Health Economic Impact of Current and New Cancer Treatments for Colorectal Cancer: A Data-Driven Whole Disease Simulation Model for Predicting the Number of Patients with Colorectal Cancer by Stage and Treatment Line in Australia.

OBJECTIVES: Effective healthcare planning, resource allocation, and budgeting require accurate predictions of the number of patients needing treatment at specific cancer stages and treatment lines. The Predicting the Population Health Economic Impact of Current and New Cancer Treatments (PRIMCAT) for Colorectal Cancer (CRC) simulation model (PRIMCAT-CRC) was developed to meet this requirement for all CRC stages and relevant molecular profiles in Australia. METHODS: Real-world data were used to estimate treatment utilization and time-to-event distributions. This populated a discrete-event simulation, projecting the number of patients receiving treatment across all disease stages and treatment lines for CRC and forecasting the number of patients likely to utilize future treatments. Illustrative analyses were undertaken, estimating treatments across disease stages and treatment lines over a 5-year period (2022-2026). We demonstrated the model's applicability through a case study introducing pembrolizumab as a first-line treatment for mismatch-repair-deficient stage IV. RESULTS: Clinical registry data from 7163 patients informed the model. The model forecasts 15 738 incident and 2821 prevalent cases requiring treatment in 2022, rising to 15 921 and 2871, respectively, by 2026. Projections show that over 2022 to 2026, there will be a total of 116 752 treatments initiated, with 43% intended for stage IV disease. The introduction of pembrolizumab is projected for 706 patients annually, totaling 3530 individuals starting treatment with pembrolizumab over the forecasted period, without significantly altering downstream utilization of subsequent treatments. CONCLUSIONS: PRIMCAT-CRC is a versatile tool that can be used to estimate the eligible patient populations for novel cancer therapies, thereby reducing uncertainty for policymakers in decisions to publicly reimburse new treatments.

Whole genome sequencing as a ticket to cancer treatment in the Netherlands: Are inequalities in access to molecular diagnostics unfair?

Whole genome sequencing (WGS) of a tumour may sometimes reveal additional potential targets for medical treatment. Practice variation in the use of WGS is therefore a source of unequal access to targeted therapies and, as a consequence, of disparities in health outcomes. Moreover, this may even be more significant if patients seek access to WGS by paying a relatively limited amount of money out of pocket, and sometimes effectively buy themselves a ticket to (very) expensive publicly funded treatments. Should resulting unequal access to WGS be considered unfair? Drawing from current practice in the Dutch healthcare system, known as egalitarian, we argue that differences in employment of WGS between hospitals are the consequence of the fact that medical innovation and its subsequent uptake inevitably takes time. Consequently, temporal inequalities in access can be deemed acceptable, or at least tolerated, because and insofar as, ultimately, all patients benefit. However, we argue against allowing a practice of out-of-pocket payments for WGS in publicly funded healthcare systems, for four reasons: because allowing private spending favours patients with higher socio-economic status significantly more than practice variation between hospitals does, may lead to displacement of publicly funded health care, does not help to ultimately benefit all, and may undermine the solidaristic ethos essential for egalitarian healthcare systems.

Paving the path for implementation of clinical genomic sequencing globally: Are we ready?

Despite the emerging evidence in recent years, successful implementation of clinical genomic sequencing (CGS) remains limited and is challenged by a range of barriers. These include a lack of standardized practices, limited economic assessments for specific indications, limited meaningful patient engagement in health policy decision-making, and the associated costs and resource demand for implementation. Although CGS is gradually becoming more available and accessible worldwide, large variations and disparities remain, and reflections on the lessons learned for successful implementation are sparse. In this commentary, members of the Global Economics and Evaluation of Clinical Genomics Sequencing Working Group (GEECS) describe the global landscape of CGS in the context of health economics and policy and propose evidence-based solutions to address existing and future barriers to CGS implementation. The topics discussed are reflected as two overarching themes: (1) system readiness for CGS and (2) evidence, assessments, and approval processes. These themes highlight the need for health economics, public health, and infrastructure and operational considerations; a robust patient- and family-centered evidence base on CGS outcomes; and a comprehensive, collaborative, interdisciplinary approach.

Cost Effectiveness of Molecular Diagnostic Testing Algorithms for the Treatment Selection of Frontline Ibrutinib for Patients with Chronic Lymphocytic Leukemia in Australia.

BACKGROUND: Clinical indications for ibrutinib reimbursement in Australia should consider the inclusion of patients with chronic lymphocytic leukemia (CLL) harboring prognostically unfavorable TP53/IGHV genomic aberrations. This study assessed the cost effectiveness of five first-line treatment strategies in CLL for young (aged ≤ 65 years), fit patients without significant comorbidities: (1) no testing (fludarabine, cyclophosphamide and rituximab [FCR] for all), (2) test for del(17p) only, (3) test for TP53 gene mutation status, (4) test for TP53 and IGHV gene mutation status and (5) no testing (ibrutinib for all). METHOD: A decision analytic model (decision tree and partitioned survival model) was developed from the Australian healthcare system perspective with a lifetime horizon. Comparative treatment effects were estimated from indirect treatment comparisons and survival analysis using several studies. Costs, utility and adverse events were derived from public literature sources. Deterministic and probabilistic sensitivity analyses explored the impact of modeling uncertainties on outcomes. RESULTS: Strategy 1 was associated with 5.69 quality-adjusted life-years (QALYs) and cost 458,836 Australian dollars (AUD). All other strategies had greater effectiveness but were more expensive than Strategy 1. At the willingness-to-pay (WTP) threshold of 100,000 AUD per QALY gained, Strategy 1 was most cost effective with an estimated probability of 68.8%. Strategy 4 was cost effective between thresholds 155,000-432,300 AUD per QALY gained, and Strategy 5 >432,300 AUD per QALY gained. CONCLUSION: Population targeting using mutation testing for TP53 and IGHV when performed with del(17p) testing specifically in the context of frontline ibrutinib choice does not make a cost-ineffective treatment into a cost-effective treatment.

Comparing modeling strategies combining changes in multiple serum tumor biomarkers for early prediction of immunotherapy non-response in non-small cell lung cancer.

BACKGROUND: Patients treated with immune checkpoint inhibitors (ICI) are at risk of adverse events (AEs) even though not all patients will benefit. Serum tumor markers (STMs) are known to reflect tumor activity and might therefore be useful to predict response, guide treatment decisions and thereby prevent AEs. OBJECTIVE: This study aims to compare a range of prediction methods to predict non-response using multiple sequentially measured STMs. METHODS: Nine prediction models were compared to predict treatment non-response at 6-months (n = 412) using bi-weekly CYFRA, CEA, CA-125, NSE, and SCC measurements determined in the first 6-weeks of therapy. All methods were applied to six different biomarker combinations including two to five STMs. Model performance was assessed based on sensitivity, while model training aimed at 95% specificity to ensure a low false-positive rate. RESULTS: In the validation cohort, boosting provided the highest sensitivity at a fixed specificity across most STM combinations (12.9% -59.4%). Boosting applied to CYFRA and CEA achieved the highest sensitivity on the validation data while maintaining a specificity >95%. CONCLUSIONS: Non-response in NSCLC patients treated with ICIs can be predicted with a specificity >95% by combining multiple sequentially measured STMs in a prediction model. Clinical use is subject to further external validation.

System dynamics simulation for evaluating implementation strategies of genomic sequencing: tutorial and conceptual model.

INTRODUCTION: Precision Medicine (PM), especially in oncology, involve diagnostic and complex treatment pathways that are based on genomic features. To conduct evaluation and decision analysis for PM, advanced modeling techniques are needed due to its complexity. Although System Dynamics (SD) has strong modeling power, it has not been widely used in PM and individualized treatment. AREAS COVERED: We explained SD tools using examples in cancer context and the rationale behind using SD for genomic testing and personalized oncology. We compared SD with other Dynamic Simulation Modelling (DSM) methods and listed SD's advantages. We developed a conceptual model using Causal Loop Diagram (CLD) for strategic decision-making in Whole Genome Sequencing (WGS) implementation. EXPERT OPINION: The paper demonstrates that SD is well-suited for health policy evaluation challenges and has useful tools for modeling precision oncology and genomic testing. SD's system-oriented modeling captures dynamic and complex interactions within systems using feedback loops. SD models are simple to implement, utilize less data and computational resources, and conduct both exploratory and explanatory analyses over time. If the targeted system has complex interactions and many components, deals with lack of data, and requires interpretability and clinicians' input, SD offers attractive advantages for modeling and evaluating scenarios.

Willingness to participate in combination screening for lung cancer, chronic obstructive pulmonary disease and cardiovascular disease in four European countries.

OBJECTIVES: Lung cancer screening (LCS), using low-dose computed tomography (LDCT), can be more efficient by simultaneously screening for chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD), the Big-3 diseases. This study aimed to determine the willingness to participate in (combinations of) Big-3 screening in four European countries and the relative importance of amendable participation barriers. METHODS: An online cross-sectional survey aimed at (former) smokers aged 50-75 years elicited the willingness of individuals to participate in Big-3 screening and used analytical hierarchy processing (AHP) to determine the importance of participation barriers. RESULTS: Respondents were from France (n = 391), Germany (n = 338), Italy (n = 399), and the Netherlands (n = 342), and consisted of 51.2% men. The willingness to participate in screening was marginally influenced by the diseases screened for (maximum difference of 3.1%, for Big-3 screening (73.4%) vs. lung cancer and COPD screening (70.3%)) and by country (maximum difference of 3.7%, between France (68.5%) and the Netherlands (72.3%)). The largest effect on willingness to participate was personal perceived risk of lung cancer. The most important barriers were the missed cases during screening (weight 0.19) and frequency of screening (weight 0.14), while diseases screened for (weight 0.11) ranked low. CONCLUSIONS: The difference in willingness to participate in LCS showed marginal increase with inclusion of more diseases and limited variation between countries. A marginal increase in participation might result in a marginal additional benefit of Big-3 screening. The amendable participation barriers are similar to previous studies, and the new criterion, diseases screened for, is relatively unimportant. CLINICAL RELEVANCE STATEMENT: Adding diseases to combination screening modestly improves participation, driven by personal perceived risk. These findings guide program design and campaigns for lung cancer and Big-3 screening. Benefits of Big-3 screening lie in long-term health and economic impact, not participation increase. KEY POINTS: • It is unknown whether or how combination screening might affect participation. • The addition of chronic obstructive pulmonary disease and cardiovascular disease to lung cancer screening resulted in a marginal increase in willingness to participate. • The primary determinant influencing individuals' engagement in such programs is their personal perceived risk of the disease.

Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value.

BACKGROUND: Demonstrating safety and efficacy of new medical treatments requires clinical trials but clinical trials are costly and may not provide value proportionate to their costs. As most health systems have limited resources, it is therefore important to identify the trials with the highest value. Tools exist to assess elements of a clinical trial such as statistical validity but are not wholistic in their valuation of a clinical trial. This study aims to develop a measure of clinical trials value and provide an online tool for clinical trial prioritisation. METHODS: A search of the academic and grey literature and stakeholder consultation was undertaken to identify a set of criteria to aid clinical trial valuation using multi-criteria decision analysis. Swing weighting and ranking exercises were used to calculate appropriate weights of each of the included criteria and to estimate the partial-value function for each underlying metric. The set of criteria and their respective weights were applied to the results of six different clinical trials to calculate their value. RESULTS: Seven criteria were identified: 'unmet need', 'size of target population', 'eligible participants can access the trial', 'patient outcomes', 'total trial cost', 'academic impact' and 'use of trial results'. The survey had 80 complete sets of responses (51% response rate). A trial designed to address an 'Unmet Need' was most commonly ranked as the most important with a weight of 24.4%, followed by trials demonstrating improved 'Patient Outcomes' with a weight of 21.2%. The value calculated for each trial allowed for their clear delineation and thus a final value ranking for each of the six trials. CONCLUSION: We confirmed that the use of the decision tool for valuing clinical trials is feasible and that the results are face valid based on the evaluation of six trials. A proof-of-concept applying this tool to a larger set of trials with an external validation is currently underway.

Implementing competing risks in discrete event simulation: the event-specific probabilities and distributions approach.

Background: Although several strategies for modelling competing events in discrete event simulation (DES) exist, a methodological gap for the event-specific probabilities and distributions (ESPD) approach when dealing with censored data remains. This study defines and illustrates the ESPD strategy for censored data. Methods: The ESPD approach assumes that events are generated through a two-step process. First, the type of event is selected according to some (unknown) mixture proportions. Next, the times of occurrence of the events are sampled from a corresponding survival distribution. Both of these steps can be modelled based on covariates. Performance was evaluated through a simulation study, considering sample size and levels of censoring. Additionally, an oncology-related case study was conducted to assess the ability to produce realistic results, and to demonstrate its implementation using both frequentist and Bayesian frameworks in R. Results: The simulation study showed good performance of the ESPD approach, with accuracy decreasing as sample sizes decreased and censoring levels increased. The average relative absolute error of the event probability (95%-confidence interval) ranged from 0.04 (0.00; 0.10) to 0.23 (0.01; 0.66) for 60% censoring and sample size 50, showing that increased censoring and decreased sample size resulted in lower accuracy. The approach yielded realistic results in the case study. Discussion: The ESPD approach can be used to model competing events in DES based on censored data. Further research is warranted to compare the approach to other modelling approaches for DES, and to evaluate its usefulness in estimating cumulative event incidences in a broader context.

A tailored approach to horizon scanning for cancer medicines.

BACKGROUND: Horizon scanning (HS) is the systematic identification of emerging therapies to inform policy and decision-makers. We developed an agile and tailored HS methodology that combined multi-criteria decision analysis weighting and Delphi rounds. As secondary objectives, we aimed to identify new medicines in melanoma, non-small cell lung cancer and colorectal cancer most likely to impact the Australian government's pharmaceutical budget by 2025 and to compare clinician and consumer priorities in cancer medicine reimbursement. METHOD: Three cancer-specific clinician panels (total n = 27) and a consumer panel (n = 7) were formed. Six prioritisation criteria were developed with consumer input. Criteria weightings were elicited using the Analytic Hierarchy Process (AHP). Candidate medicines were identified and filtered from a primary database and validated against secondary and tertiary sources. Clinician panels participated in a three-round Delphi survey to identify and score the top five medicines in each cancer type. RESULTS: The AHP and Delphi process was completed in eight weeks. Prioritisation criteria focused on toxicity, quality of life (QoL), cost savings, strength of evidence, survival, and unmet need. In both curative and non-curative settings, consumers prioritised toxicity and QoL over survival gains, whereas clinicians prioritised survival. HS results project the ongoing prevalence of high-cost medicines. Since completion in October 2021, the HS has identified 70 % of relevant medicines submitted for Pharmaceutical Benefit Advisory Committee assessment and 60% of the medicines that received a positive recommendation. CONCLUSION: Tested in the Australian context, our method appears to be an efficient and flexible approach to HS that can be tailored to address specific disease types by using elicited weights to prioritise according to incremental value from both a consumer and clinical perspective. POLICY SUMMARY: Since HS is of global interest, our example provides a reproducible blueprint for adaptation to other healthcare settings that integrates consumer input and priorities.

Assessing neuro-oncology clinical trial impact and value: Testing a novel multi-criteria decision analysis app.

BACKGROUND: Many clinical trials are conducted globally, creating challenges in deciding which trial outcomes deserve a clinician's focus and where to direct limited resources. Determining the 'value' of a clinical trial relative to others could be useful in this context. The aim of this study was to test a novel web-based application using multi-criteria decision analysis (MCDA) to rank clinical trial value. METHODS: The MCDA tool combines seven metrics: unmet need; target population size; access; outcomes; cost; academic impact and use of results. Clinical trials were ranked according to their calculated 'value' - meaning the importance or worth of a trial. We determined face validity of the app using a set of ten published Phase 3 neuro-oncology clinical trials. A survey of neuro-oncology clinicians asked them to rank the same ten clinical trials, and to rank the seven metrics in terms of importance. RESULTS: The two highest app-ranked trials were in concordance with that of the survey respondents, and consistent with the two studies that have had the most impact on routine clinical practice in neuro-oncology. Of the seven metrics, surveyed clinicians considered patient outcomes and unmet need to be the most important when determining clinical trial value. CONCLUSIONS: The metrics app was able to rank and produce a numerical 'value' for existing phase 3 neuro-oncology clinical trials. In the future, a related app to prospectively rank future trials at the startup stage could be developed to help centers determine which should be prioritized to be conducted at their site.

Patient and healthcare professional acceptability of pharmacogenetic screening for DPYD and UGT1A1: A cross sectional survey.

This study explored the acceptability of a novel pharmacist-led pharmacogenetics (PGx) screening program among patients with cancer and healthcare professionals (HCPs) taking part in a multicenter clinical trial of PGx testing (PACIFIC-PGx ANZCTR:12621000251820). Medical oncologists, oncology pharmacists, and patients with cancer from across four sites (metropolitan/regional), took part in an observational, cross-sectional survey. Participants were recruited from the multicenter trial. Two study-specific surveys were developed to inform implementation strategies for scaled and sustainable translation into routine clinical care: one consisting of 21 questions targeting HCPs and one consisting of 17 questions targeting patients. Responses were collected from 24 HCPs and 288 patients. The 5-to-7-day PGx results turnaround time was acceptable to HCP (100%) and patients (69%). Most HCPs (92%) indicated that it was appropriate for the PGx clinical pharmacist to provide results to patients. Patients reported equal preference for receiving PGx results from a doctor/pharmacist. Patients and HCPs highly rated the pharmacist-led PGx service. HCPs were overall accepting of the program, with the majority (96%) willing to offer PGx testing to their patients beyond the trial. HCPs identified that lack of financial reimbursements (62%) and lack of infrastructure (38%) were the main reasons likely to prevent/slow the implementation of PGx screening program into routine clinical care. Survey data have shown overall acceptability from patients and HCPs participating in the PGx Program. Barriers to implementation of PGx testing in routine care have been identified, providing opportunity to develop targeted implementation strategies for scaled translation into routine practice.

The effect of time before diagnosis and treatment on colorectal cancer outcomes: systematic review and dose-response meta-analysis.

BACKGROUND: This systematic review and meta-analysis aimed to evaluate existing evidence on the relationship between diagnostic and treatment intervals and outcomes for colorectal cancer. METHODS: Four databases were searched for English language articles assessing the role of time before initial treatment in colorectal cancer on any outcome, including stage and survival. Two reviewers independently screened articles for inclusion and data were synthesised narratively. A dose-response meta-analysis was performed to examine the association between treatment interval and survival. RESULTS: One hundred and thirty papers were included in the systematic review, eight were included in the meta-analysis. Forty-five different intervals were considered in the time from first symptom to treatment. The most common finding was of no association between the length of intervals on any outcome. The dose-response meta-analysis showed a U-shaped association between the treatment interval and overall survival with the nadir at 45 days. CONCLUSION: The review found inconsistent, but mostly a lack of, association between interval length and colorectal cancer outcomes, but study design and quality were heterogeneous. Meta-analysis suggests survival becomes increasingly poorer for those commencing treatment more than 45 days after diagnosis. REGISTRATION: This review was registered, and the protocol is available, in PROSPERO, the international database of systematic reviews, with the registration ID CRD42021255864.

Withdrawing biologics in non-systemic JIA: what matters to pediatric rheumatologists?

OBJECTIVE: Approximately one third of children with JIA receive biologic therapy, but evidence on biologic therapy withdrawal is lacking. This study aims to increase our understanding of whether and when pediatric rheumatologists postpone a decision to withdraw biologic therapy in children with clinically inactive non-systemic JIA. METHODS: A survey containing questions about background characteristics, treatment patterns, minimum treatment time with biologic therapy, and 16 different patient vignettes, was distributed among 83 pediatric rheumatologists in Canada and the Netherlands. For each vignette, respondents were asked whether they would withdraw biologic therapy at their minimum treatment time, and if not, how long they would continue biologic therapy. Statistical analysis included descriptive statistics, logistic and interval regression analysis. RESULTS: Thirty-three pediatric rheumatologists completed the survey (40% response rate). Pediatric rheumatologists are most likely to postpone the decision to withdraw biologic therapy when the child and/or parents express a preference for continuation (OR 6.3; p < 0.001), in case of a flare in the current treatment period (OR 3.9; p = 0.001), and in case of uveitis in the current treatment period (OR 3.9; p < 0.001). On average, biologic therapy withdrawal is initiated 6.7 months later when the child or parent prefer to continue treatment. CONCLUSION: Patient's and parents' preferences were the strongest driver of a decision to postpone biologic therapy withdrawal in children with clinically inactive non-systemic JIA and prolongs treatment duration. These findings highlight the potential benefit of a tool to support pediatric rheumatologists, patients and parents in decision making, and can help inform its design.

An evidence-base for the implementation of hospital-based palliative care programs in routine cancer practice: A systematic review.

BACKGROUND: Despite global support, there remain gaps in the integration of early palliative care into cancer care. The methods of implementation whereby evidence of benefits of palliative care is translated into practice deserve attention. AIM: To identify implementation frameworks utilised in integrated palliative care in hospital-based oncology services and to describe the associated enablers and barriers to service integration. DESIGN: Systematic review with a narrative synthesis including qualitative, mixed methods, pre-post and quasi experimental designs following the guidance by the Centre for Reviews and Dissemination (PROSPERO registration CRD42021252092). DATA SOURCES: Six databases searched in 2021: EMBASE, EMCARE, APA PsycINFO, CINAHL, Cochrane Library and Ovid MEDLINE searched in 2023. Included were qualitative or quantitative studies, in English language, involving adults >18 years, and implementing hospital-based palliative care into cancer care. Critical appraisal tools were used to assess the quality and rigour. RESULTS: Seven of the 16 studies explicitly cited the use of frameworks including those based on RE-AIM, Medical Research Council evaluation of complex interventions and WHO constructs of health service evaluation. Enablers included an existing supportive culture, clear introduction to the programme across services, adequate funding, human resources and identification of advocates. Barriers included a lack of communication with the patients, caregivers, physicians and palliative care team about programme goals, stigma around the term 'palliative', a lack of robust training, or awareness of guidelines and undefined staff roles. CONCLUSIONS: Implementation science frameworks provide a method to underpin programme development and evaluation as palliative care is integrated within the oncology setting.