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Objectives Estimating the maximum acceptable cost (MAC) per screened individual for low-dose computed tomography (LDCT) lung cancer (LC) screening, and determining the effect of additionally screening for chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), or both on the MAC. Methods A model-based early health technology assessment (HTA) was conducted to estimate whether a new intervention could be cost-effective by calculating the MAC at a willingness-to-pay (WTP) of €20k/quality-adjusted life-year (QALY) and €80k/QALY, for a population of current and former smokers, aged 50–75 years in The Netherlands. The MAC was estimated based on incremental QALYs gained from a stage shift assuming screened individuals are detected in earlier disease stages. Data were obtained from literature and publicly available statistics and validated with experts. Results The MAC per individual for implementing LC screening at a WTP of €20k/QALY was €113. If COPD, CVD, or both were included in screening, the MAC increased to €230, €895, or €971 respectively. Scenario analyses assessed whether screening-specific disease high-risk populations would improve cost-effectiveness, showing that high-risk CVD populations were more likely to improve economic viability compared to COPD. Conclusions The economic viability of combined screening is substantially larger than for LC screening alone, primarily due to benefits from CVD screening, and is dependent on the target screening population, which is key to optimise the screening program. The total cost of breast and cervical cancer screening is lower (€420) than the MAC of Big-3, indicating that Big-3 screening may be acceptable from a health economic perspective. Key Points • Once-off combined low-dose CT screening for lung cancer, COPD, and CVD in individuals aged 50–75 years is potentially cost-effective if screening would cost less than €971 per screened individual. • Multi-disease screening requires detailed insight into the co-occurrence of these diseases to identify the optimal target screening population. • With the same target screening population and WTP, lung cancer-only screening should cost less than €113 per screened individual to be cost-effective.

PURPOSE The combination of whole-genome and transcriptome sequencing (WGTS) is expected to transform diagnosis and treatment for patients with cancer. WGTS is a comprehensive precision diagnostic test that is starting to replace the standard of care for oncology molecular testing in health care systems around the world; however, the implementation and widescale adoption of this best-in-class testing is lacking. METHODS Here, we address the barriers in integrating WGTS for cancer diagnostics and treatment selection and answer questions regarding utility in different cancer types, cost-effectiveness and affordability, and other practical considerations for WGTS implementation. RESULTS We review the current studies implementing WGTS in health care systems and provide a synopsis of the clinical evidence and insights into practical considerations for WGTS implementation. We reflect on regulatory, costs, reimbursement, and incidental findings aspects of this test. CONCLUSION WGTS is an appropriate comprehensive clinical test for many tumor types and can replace multiple, cascade testing approaches currently performed. Decreasing sequencing cost, increasing number of clinically relevant aberrations and discovery of more complex biomarkers of treatment response, should pave the way for health care systems and laboratories in implementing WGTS into clinical practice, to transform diagnosis and treatment for patients with cancer.

Complex genomic profiling (CGP) has transformed cancer treatment decision making, yet there is a lack of robust and quantifiable evidence for how utilisation of CGP improves patient outcomes.This study evaluated cohort level clinical effectiveness of CGP to improve overall survival (OS) in real-world advanced cancer patients using a registry-based matched control population.Two cohorts of advanced and refractory cancer patients were seen in consecutive series for early phase trial enrolment consideration. The first cohort (CGP group) accessed tumour profiling via a research study; while the second cohort that followed was not profiled. Overall survival between cohorts was compared using Kaplan-Meier curves and Cox proportional hazard models. Potential confounding was analysed and adjusted for using stabilised weights based on propensity scores.Within the CGP group, 25 (17.6%) patients received treatment informed by CGP results and this subgroup had significantly improved survival compared with CGP patients in whom results did not impact their treatment (unadjusted HR = 0.44, (0.22-0.88), p = 0.02). However, when comparing the entire CGP cohort with the No CGP cohort, no significant survival benefit was evident with adjusted median OS for CGP of 13.5 months (9.2-17.0) compared with 11.0 (9.2-17.4) for No CGP (adjusted HR = 0.92, (0.65-1.30), p = 0.63).This study utilised real-world data to simulate a control arm and quantify the clinical effectiveness of genomic testing. The magnitude of survival benefit for patients who had CGP result-led treatments was insufficient to drive an overall survival gain for the entire tested population. Translation of CGP into clinics requires strategies to ensure higher rates of tested patients obtain clinical benefit to deliver on the value proposition of CGP in an advanced cancer population.

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.

Immune checkpoint inhibitors have been approved in the USA for tumours exhibiting mismatch repair deficiency (dMMR), microsatellite instability (MSI), or high tumour mutational burden (TMB), with regulatory and reimbursement applications in multiple other countries underway. As the estimated budget impacts of future reimbursements depend on the size of the potential target population, we performed a scoping review and meta-analysis of the prevalence of these pan-tumour biomarkers in different cancers. We systematically searched Medline/Embase and included studies reporting the prevalence of dMMR/MSI/high TMB in solid tumours published 01/01/2018–31/01/2021. Meta-analyses were performed separately for the pan-cancer prevalence of each biomarker, and by cancer type and stage where possible. The searches identified 3890 papers, with 433 prevalence estimates for 32 different cancer types from 201 studies included in meta-analyses. The pooled overall prevalence of dMMR, MSI and high TMB (≥ 10 mutations/Mb) in pan-cancer studies was 2.9%, 2.7% and 14.0%, respectively. The prevalence profiles of dMMR/MSI and high TMB differed across cancer types. For example, endometrial, colorectal, small bowel and gastric cancers showed high prevalence of both dMMR and MSI (range: 8.7–26.8% and 8.5–21.9%, respectively) and high TMB (range: 8.5–43.0%), while cervical, esophageal, bladder/urothelial, lung and skin cancers showed low prevalence of dMMR and MSI (

Refereed/Peer-reviewed Australia spends more than $20 billion annually on medicines, delivering significant health benefits for the population. However, inappropriate prescribing and medicine use also result in harm to individuals and populations, and waste of precious health resources. Medication data linked with other routine collections enable evidence generation in pharmacoepidemiology; the science of quantifying the use, effectiveness and safety of medicines in real-world clinical practice. This review details the history of medicines policy and data access in Australia, the strengths of existing data sources, and the infrastructure and governance enabling and impeding evidence generation in the field. Currently, substantial gaps persist with respect to cohesive, contemporary linked data sources supporting quality use of medicines, effectiveness and safety research; exemplified by Australia's limited capacity to contribute to the global effort in real-world studies of vaccine and disease-modifying treatments for COVID-19. We propose a roadmap to bolster the discipline, and population health more broadly, underpinned by a distinct capability governing and streamlining access to linked data assets for accredited researchers. Robust real-world evidence generation requires current data roadblocks to be remedied as a matter of urgency to deliver efficient and equitable health care and improve the health and well-being of all Australians.

Background Prostate cancer is the most common internal malignancy in Australian men, and although most patients have good survival outcomes, treatment toxicities can impair function, leading to diminished quality of life for prostate cancer survivors. Socioeconomic disadvantage and geographical remoteness have been shown to be related to worse oncologic outcomes, and it is expected that they would similarly influence functional outcomes in prostate cancer. Methods Using data from the Victorian Prostate Cancer Outcomes Registry (n = 10,924), we investigated functional outcomes as measured by the Expanded Prostate Cancer Index Composite-26 (EPIC-26) following prostate cancer treatment, focusing on associations with socioeconomic status and geographical remoteness and controlling for clinicopathologic characteristics. A single composite score was developed from the five separate EPIC-26 domains for use in geo-mapping. Results A total of 7690 patients had complete EPIC-26 data, allowing mapping hotspots of poor function using our composite score. These hotspots were observed to relate to areas of socioeconomic disadvantage. Significant heterogeneity in outcomes was seen in urban areas, with hotspots of good and poor function. Both socioeconomic disadvantage and geographical remoteness were found to predict for worse functional outcomes, although only the former is significant on multivariate analysis. Conclusions Geo-mapping of functional outcomes in prostate cancer has the potential to guide health care service provision and planning. A nuanced policy approach is required so as not to miss disadvantaged patients who live in urban areas. We have demonstrated the potential of geo-mapping to visualise population-level outcomes, potentially allowing targeted interventions to address inequities in quality of care.

Substantial adjuvant chemotherapy (AC) overtreatment for stage II colorectal cancer results in a health and financial burden. Circulating tumour DNA (ctDNA) can improve patient selection for AC by detecting micro-metastatic disease. We estimated the health economic potential of ctDNA-guided AC for stage II colorectal cancer.A cost-utility analysis was performed to compare ctDNA-guided AC to standard of care, where 22.6% of standard of care patients and all ctDNA-positive patients (8.7% of tested patients) received AC and all ctDNA-negative patients (91.3%) did not. A third preference-sensitive ctDNA strategy was included where 6.8% of ctDNA-negative patients would receive AC. A state-transition model was populated using data from a prospective cohort study and clinical registries. Health and economic outcomes were discounted at 5% over a lifetime horizon from a 2019 Australian payer perspective. Extensive scenario and probabilistic analyses quantified model uncertainty.Compared to standard of care, the ctDNA and preference-sensitive ctDNA strategies increased quality-adjusted life-years by 0.20 (95% confidence interval - 0.40 to 0.81) and 0.19 (- 0.40 to 0.78), and resulted in incremental costs of AUD - 4055 (- 16,853 to 8472) and AUD - 2284 (- 14,685 to 10,116), respectively. Circulating tumour DNA remained cost effective at a willingness to pay of AUD 20,000 per quality-adjusted life-year gained throughout most scenario analyses in which the proportion of ctDNA-positive patients cured by AC and compliance to a ctDNA-negative test results were decreased.Circulating tumour-guided AC is a potentially cost-effective strategy towards reducing overtreatment in stage II colorectal cancer. Results from ongoing randomised clinical studies will be important to reduce uncertainty in the estimates.

Background: KRAS mutations are found in 20–30 % of non-small cell lung cancers (NSCLC) and were traditionally considered undruggable. KRASG12C mutation confers sensitivity to KRASG12C covalent inhibitors, however its prognostic impact remains unclear. This study assesses the frequency, clinical features, prevalence of brain metastases and outcomes in KRASG12C NSCLC in a real-world setting. Methods: Patients enrolled in the prospective Thoracic Malignancies Cohort (TMC) between July 2012 to October 2019 with recurrent/metastatic non-squamous NSCLC, available KRAS results, and without EGFR/ALK/ROS1 gene aberrations, were selected. Data was extracted from TMC and patient records. Clinicopathologic features, treatment and overall survival (OS) was compared for KRAS wildtype (KRASWT) and KRAS mutated (KRASmut); and KRASG12C and other (KRASother) mutations. Results: Of 1386 NSCLC patients, 1040 were excluded: non-metastatic/recurrent (526); unknown KRAS status (356); ALK/EGFR/ROS1 positive (154); duplicate (4). Of 346 patients analysed, 144 (42 %) were KRASmut, of whom 65 (45 %) were KRASG12C. All patients with KRASG12C were active or ex-smokers, compared to 92 % of KRASother and 83 % of KRASWT. The prevalence of brain metastases during follow-up was similar between KRASmut and KRASWT (33 % vs 40 %, p = 0.17), and KRASG12C and KRASother (40 % vs 41 %, p = 0.74). The proportion of patients receiving one or multiple lines of systemic therapy was comparable. OS was similar between KRASmut and KRASWT (p = 0.54), and KRASG12C and KRASother (p = 0.39). Conclusion: Patients with KRASmut and KRASWT, and KRASG12C and KRASother NSCLC have comparable clinical features, treatment and survival. While not prognostic, KRASG12C may be an important predictive biomarker as promising KRASG12C covalent inhibitors continue to be developed.