Association Between Intermediate End Points, Progression-free Survival, and Overall Survival in First-line Advanced or Recurrent Endometrial Cancer.

PURPOSE: Advanced/recurrent endometrial cancer is associated with poor long-term outcomes. Clinical studies of novel regimens are ongoing, but given that data on overall survival (OS) take a long time to mature, surrogate end points are often used to support clinical-research interpretation. The aim of this study was to explore the correlation between progression-free survival (PFS)/time to progression (TTP) and OS across multiple time points in the first-line treatment of advanced/recurrent endometrial cancer. METHODS: This study comprised meta-analyses of Phase 2/3 randomized, controlled trials of first-line treatments in patients with advanced primary or first-recurrent endometrial cancer identified via systematic literature review. The strength of the surrogacy relationship was assessed by correlation analyses (estimated with Spearman and Pearson correlation coefficients) and weighted linear regression. FINDINGS: Data from 15 studies were included. PFS and TTP (TTP was reported in one study only) were highly correlated with future OS at multiple time points (Spearman values, 0.83-0.90; Pearson values, 0.86-0.93), suggesting that a change in PFS/TTP would likely be correlated with a change in OS in the same direction. On weighted linear regression, a 10% increase in PFS/TTP probability was significantly associated with a 9.3% to 13.3% increase in the probability of future OS. The strong positive association between PFS/TTP and OS was supported by findings from sensitivity analyses based on identified sources of interstudy heterogeneity. IMPLICATIONS: PFS/TTP is a good potential candidate for predicting long-term OS outcomes in trials of first-line treatment in patients with advanced/recurrent endometrial cancer. The findings from this report may help to inform health-authority and clinical decision makers that PFS/TTP improvements are likely to translate into subsequent OS improvements once data mature.

Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer.

BACKGROUND: This study shows how dynamic simulation modeling can be applied in the context of the nationwide implementation of Whole Genome Sequencing (WGS) for non-small cell lung cancer (NSCLC) to inform organizational decisions regarding the use of complex and disruptive health technologies and how these decisions affect their potential value. METHODS: Using the case of the nationwide implementation of WGS into clinical practice in lung cancer in the Dutch healthcare system, we developed a simulation model to show that including service delivery features across the diagnostic pathway can provide essential insight into the affordability and accessibility of care at the systems level. The model was implemented as a hybrid Agent-Based Model and Discrete-Event Simulation model in AnyLogic and included 78 hospital agents, 7 molecular tumor board agents, 1 WGS facility agent, and 5313 patient agents each year in simulation time. RESULTS: The model included patient and provider heterogeneity, including referral patterns, capacity constraints, and diagnostic workflows. Patient preference and adoption by healthcare professionals were also modeled. The model was used to analyze a scenario in which only academic hospitals have implemented WGS. To prevent delays in the diagnostic pathway, the capacity to sequence at least 1600 biopsies yearly should be present. There is a two-fold increase in mean diagnostic pathway duration between no patients referred or all patients referred for further diagnostics. CONCLUSIONS: The systems model can complement conventional health economic evaluations to investigate how the organization of the workflow can influence the actual use and impact of WGS. Insufficient capacity to provide WGS and referral patterns can substantially impact the duration of the diagnostic pathway and thus should be considered in the implementation of WGS.

Whole genome sequencing in oncology: using scenario drafting to explore future developments.

BACKGROUND: In oncology, Whole Genome Sequencing (WGS) is not yet widely implemented due to uncertainties such as the required infrastructure and expertise, costs and reimbursements, and unknown pan-cancer clinical utility. Therefore, this study aimed to investigate possible future developments facilitating or impeding the use of WGS as a molecular diagnostic in oncology through scenario drafting. METHODS: A four-step process was adopted for scenario drafting. First, the literature was searched for barriers and facilitators related to the implementation of WGS. Second, they were prioritized by international experts, and third, combined into coherent scenarios. Fourth, the scenarios were implemented in an online survey and their likelihood of taking place within 5 years was elicited from another group of experts. Based on the minimum, maximum, and most likely (mode) parameters, individual Program Evaluation and Review Technique (PERT) probability density functions were determined. Subsequently, individual opinions were aggregated by performing unweighted linear pooling, from which summary statistics were extracted and reported. RESULTS: Sixty-two unique barriers and facilitators were extracted from 70 articles. Price, clinical utility, and turnaround time of WGS were ranked as the most important aspects. Nine scenarios were developed and scored on likelihood by 18 experts. The scenario about introducing WGS as a clinical diagnostic with a lower price, shorter turnaround time, and improved degree of actionability, scored the highest likelihood (median: 68.3%). Scenarios with low likelihoods and strong consensus were about better treatment responses to more actionable targets (26.1%), and the effect of centralizing WGS (24.1%). CONCLUSIONS: Based on current expert opinions, the implementation of WGS as a clinical diagnostic in oncology is heavily dependent on the price, clinical utility (both in terms of identifying actionable targets as in adding sufficient value in subsequent treatment), and turnaround time. These aspects and the optimal way of service provision are the main drivers for the implementation of WGS and should be focused on in further research. More knowledge regarding these factors is needed to inform strategic decision making regarding the implementation of WGS, which warrants support from all relevant stakeholders.

Early technology assessment of using whole genome sequencing in personalized oncology.

Introduction: Personalized medicine-based treatments in advanced cancer hold the promise to offer substantial health benefits to genetic subgroups, but require efficient biomarker-based patient stratification to match the right treatment and may be expensive. Standard molecular diagnostics are currently very heterogeneous, and tests are often performed sequentially. The alternative to whole genome sequencing (WGS) i.e. simultaneously testing for all relevant DNA-based biomarkers thereby allowing immediate selection of the most optimal therapy, is more costly than current techniques. In the current implementation stage, it is important to explore the added value and cost-effectiveness of using WGS on a patient level and to assess optimal introduction of WGS on the level of the healthcare system.Areas covered: First, an overview of current worldwide initiatives concerning the use of WGS in clinical practice for cancer diagnostics is given. Second, a comprehensive, early health technology assessment (HTA) approach of evaluating WGS in the Netherlands is described, relating to the following aspects: diagnostic value, WGS-based treatment decisions, assessment of long-term health benefits and harms, early cost-effectiveness modeling, nation-wide organization, and Ethical, Legal and Societal Implications.Expert opinion: This study provides evidence to guide further development and implementation of WGS in clinical practice and the healthcare system.

Real-World Utilization of Biomarker Testing for Patients with Advanced Non-Small Cell Lung Cancer in a Tertiary Referral Center and Referring Hospitals.

The continued introduction of biomarkers and innovative testing methods makes already complex diagnosis in patients with stage IV non-small-cell lung cancer (NSCLC) even more complex. This study primarily analyzed variations in biomarker testing in clinical practice in patients referred to a comprehensive cancer center in the Netherlands. The secondary aim was to compare the cost of biomarker testing with the cost of whole-genome sequencing. The cohort included 102 stage IV NSCLC patients who received biomarker testing in 2017 or 2018 at the comprehensive cancer center. The complete biomarker testing history of the cohort was identified using linked data from the comprehensive cancer center and the nationwide network and registry of histopathology and cytopathology in the Netherlands. Unique biomarker-test combinations, costs, turnaround times, and test utilization were examined. The results indicate substantial variation in test utilization and sequences. The mean cost per patient of biomarker testing was 2259.92 ± 1217.10 USD, or 1881.23 ± 1013.15 EUR. Targeted gene panels were most frequently conducted, followed by IHC analysis for programmed cell death protein ligand 1. Typically, the most common biomarkers were assessed within the first tests, and emerging biomarkers were tested further down the test sequence. At the cost of current biomarker testing, replacing current testing with whole-genome sequencing would have led to cost-savings in only two patients (2%).