•Framework on how to incorporate social equity into transport planning.•Mapping participation deserts, clusters of neighbourhoods at risk of social exclusion.•Modelling effects of accessibility on ...activity participation, stratified by SES.•Using models to map where improving accessibility will see the greatest social benefit.•Discussion on how analysis can direct transport planning and policy.
Social equity is increasingly becoming an important objective in transport planning and project evaluation. This paper provides a framework and an empirical investigation in the Greater Toronto and Hamilton Area (GTHA) examining the links between public transit accessibility and the risks of social exclusion, simply understood as the suppressed ability to conduct daily activities at normal levels. Specifically, we use a large-sample travel survey to present a new transport-geography concept termed participation deserts, neighbourhood-level clusters of lower than expected activity participation. We then use multivariate models to estimate where, and for whom, improvements in transit accessibility will effectively increase activity participation and reduce risks of transport-related social exclusion. Our results show that neighbourhoods with high concentrations of low-income and zero-car households located outside of major transit corridors are the most sensitive to having improvements in accessibility increase daily activity participation rates. We contend that transit investments providing better connections to these neighbourhoods would have the greatest benefit in terms of alleviating existing inequalities and reducing the risks of social exclusion. The ability for transport investments to liberate suppressed activity participation is not currently being predicted or valued in existing transport evaluation methodologies, but there is great potential in doing so in order to capture the social equity benefits associated with increasing transit accessibility.
Purpose The primary purposes of eligibility criteria are to protect the safety of trial participants and define the trial population. Excessive or overly restrictive eligibility criteria can slow ...trial accrual, jeopardize the generalizability of results, and limit understanding of the intervention's benefit-risk profile. Methods ASCO, Friends of Cancer Research, and the US Food and Drug Administration examined specific eligibility criteria (ie, brain metastases, minimum age, HIV infection, and organ dysfunction and prior and concurrent malignancies) to determine whether to modify definitions to extend trials to a broader population. Working groups developed consensus recommendations based on review of evidence, consideration of the patient population, and consultation with the research community. Results Patients with treated or clinically stable brain metastases should be routinely included in trials and only excluded if there is compelling rationale. In initial dose-finding trials, pediatric-specific cohorts should be included based on strong scientific rationale for benefit. Later phase trials in diseases that span adult and pediatric populations should include patients older than age 12 years. HIV-infected patients who are healthy and have low risk of AIDS-related outcomes should be included absent specific rationale for exclusion. Renal function criteria should enable liberal creatinine clearance, unless the investigational agent involves renal excretion. Patients with prior or concurrent malignancies should be included, especially when the risk of the malignancy interfering with either safety or efficacy endpoints is very low. Conclusion To maximize generalizability of results, trial enrollment criteria should strive for inclusiveness. Rationale for excluding patients should be clearly articulated and reflect expected toxicities associated with the therapy under investigation.
The FDA's Oncology Center of Excellence's (OCE) launch of Project Optimus signals increased focus on dose optimization approaches in oncology drug development, particularly toward optimization in the ...premarket setting. Although sponsors continue to adapt premarket study designs and approaches to align with FDA's expectations for dose optimization, including consideration of the optimal dosage(s), there are still instances where questions remain at the time of approval about whether the approved doses or schedules are optimal. In these cases, FDA can exercise regulatory flexibility by issuing postmarketing requirements (PMR) and avoid delaying patient access to promising therapies. This landscape analysis demonstrates that over the past decade (2012-2022), FDA frequently used PMRs to answer additional questions about dosing for novel oncology approvals. We found more than half of drugs (78/132, 59.1%) had a dosing PMR and observed a recent increase in PMRs intended to evaluate whether a lower dose could be more optimal. These results suggest there are opportunities to adapt premarket dose optimization strategies and leverage innovative development tools to ensure timely identification of the optimal dose.
Three maps are generated to visually compare the structure of transport networks, differences in travel times, and critical travel pathways for three travel modes in Calgary, Canada. The maps also ...highlight how the fractal-like structure of these urban transport networks are visually similar to natural phenomena.
The Lung Master Protocol (Lung-MAP, S1400) is a groundbreaking clinical trial designed to advance the efficient development of targeted therapies for squamous cell carcinoma (SCC) of the lung. There ...are no approved targeted therapies specific to advanced lung SCC, although The Cancer Genome Atlas project and similar studies have detected a significant number of somatic gene mutations/amplifications in lung SCC, some of which are targetable by investigational agents. However, the frequency of these changes is low (5%-20%), making recruitment and study conduct challenging in the traditional clinical trial setting. Here, we describe our approach to development of a biomarker-driven phase II/II multisubstudy "Master Protocol," using a common platform (next-generation DNA sequencing) to identify actionable molecular abnormalities, followed by randomization to the relevant targeted therapy versus standard of care.
The HYDRUS unsaturated flow and transport model was modified to simulate the effects of non-linear air-water interfacial (AWI) adsorption, solution surface tension-induced flow, and variable solution ...viscosity on the unsaturated transport of per- and polyfluoroalkyl substances (PFAS) within the vadose zone. These modifications were made and completed between March 2019 and May 2019, and were implemented into both the one-dimensional (1D) and two-dimensional (2D) versions of HYDRUS. Herein, the model modifications are described and validated against the available literature-derived PFAS transport data (i.e., 1D experimental column transport data). The results of both 1D and 2D example simulations are presented to highlight the function and utility of the model to capture the dynamic and transient nature of the temporally and spatially variable interfacial area of the AWI (Aaw) as it changes with soil moisture content (Θw) and how it affects PFAS unsaturated transport. Specifically, the simulated examples show that while AWI adsorption of PFAS can be a significant source of retention within the vadose zone, it is not always the dominant source of retention. The contribution of solid-phase sorption can be considerable in many PFAS-contaminated vadose zones. How the selection of an appropriate Aaw(Θw) function can impact PFAS transport and how both mechanisms contribute to PFAS mass flux to an underlying groundwater source is also demonstrated. Finally, the effects of soil textural heterogeneities on PFAS unsaturated transport are demonstrated in the results of both 1D and 2D example simulations.
BackgroundTumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, demonstrates predictive biomarker potential for the identification ...of patients with cancer most likely to respond to immune checkpoint inhibitors. TMB is optimally calculated by whole exome sequencing (WES), but next-generation sequencing targeted panels provide TMB estimates in a time-effective and cost-effective manner. However, differences in panel size and gene coverage, in addition to the underlying bioinformatics pipelines, are known drivers of variability in TMB estimates across laboratories. By directly comparing panel-based TMB estimates from participating laboratories, this study aims to characterize the theoretical variability of panel-based TMB estimates, and provides guidelines on TMB reporting, analytic validation requirements and reference standard alignment in order to maintain consistency of TMB estimation across platforms.MethodsEleven laboratories used WES data from The Cancer Genome Atlas Multi-Center Mutation calling in Multiple Cancers (MC3) samples and calculated TMB from the subset of the exome restricted to the genes covered by their targeted panel using their own bioinformatics pipeline (panel TMB). A reference TMB value was calculated from the entire exome using a uniform bioinformatics pipeline all members agreed on (WES TMB). Linear regression analyses were performed to investigate the relationship between WES and panel TMB for all 32 cancer types combined and separately. Variability in panel TMB values at various WES TMB values was also quantified using 95% prediction limits.ResultsStudy results demonstrated that variability within and between panel TMB values increases as the WES TMB values increase. For each panel, prediction limits based on linear regression analyses that modeled panel TMB as a function of WES TMB were calculated and found to approximately capture the intended 95% of observed panel TMB values. Certain cancer types, such as uterine, bladder and colon cancers exhibited greater variability in panel TMB values, compared with lung and head and neck cancers.ConclusionsIncreasing uptake of TMB as a predictive biomarker in the clinic creates an urgent need to bring stakeholders together to agree on the harmonization of key aspects of panel-based TMB estimation, such as the standardization of TMB reporting, standardization of analytical validation studies and the alignment of panel-based TMB values with a reference standard. These harmonization efforts should improve consistency and reliability of panel TMB estimates and aid in clinical decision-making.
The purpose of this study is to define the geographic boundaries of commercial areas by creating a consistent definition, combining various commercial area types, including downtowns, retail centres, ...financial districts, and other employment subcentres. Our research involved the collection of office, retail and job density data from 69 metropolitan regions across USA and Canada. Using this data, we conducted an unsupervised image segmentation model and clustering methods to identify distinctive commercial geographic boundaries. As a result, we identified 23,751 commercial areas, providing a detailed perspective on the commercial landscape of metropolitan areas in the USA and Canada. In addition, the generated boundaries were successfully validated through comparison with previously established commerce-related boundaries. The output of this study has implications for urban and regional planning and economic development, delivering valuable insights into the overall commercial geography in the region. The commercial boundary and used codes are freely available on the School of Cities Github, and users can reuse, reproduce and modify the boundaries.
Tumor mutational burden (TMB) is a quantitative assessment of the number of somatic mutations within a tumor genome. Immunotherapy benefit has been associated with TMB assessed by whole-exome ...sequencing (wesTMB) and gene panel sequencing (psTMB). The initiatives of Quality in Pathology (QuIP) and Friends of Cancer Research have jointly addressed the need for harmonization among TMB testing options in tissues. This QuIP study identifies critical sources of variation in psTMB assessment.
A total of 20 samples from three tumor types (lung adenocarcinoma, head and neck squamous cell carcinoma, and colon adenocarcinoma) with available WES data were analyzed for psTMB using six panels across 15 testing centers. Interlaboratory and interplatform variation, including agreement on variant calling and TMB classification, were investigated. Bridging factors to transform psTMB to wesTMB values were empirically derived. The impact of germline filtering was evaluated.
Sixteen samples had low interlaboratory and interpanel psTMB variation, with 87.7% of pairwise comparisons revealing a Spearman’s ρ greater than 0.6. A wesTMB cut point of 199 missense mutations projected to psTMB cut points between 7.8 and 12.6 mutations per megabase pair; the corresponding psTMB and wesTMB classifications agreed in 74.9% of cases. For three-tier classification with cut points of 100 and 300 mutations, agreement was observed in 76.7%, weak misclassification in 21.8%, and strong misclassification in 1.5% of cases. Confounders of psTMB estimation included fixation artifacts, DNA input, sequencing depth, genome coverage, and variant allele frequency cut points.
This study provides real-world evidence that all evaluated panels can be used to estimate TMB in a routine diagnostic setting and identifies important parameters for reliable tissue TMB assessment that require careful control. As complex or composite biomarkers beyond TMB are likely playing an increasing role in therapy prediction, the efforts by QuIP and Friends of Cancer Research also delineate a general framework and blueprint for the evaluation of such assays.
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