On the Edge: Facing a Challenging and Uncertain Future

Introduces the Boston Elder Economic Security Standard as a tool to assess the real economic circumstances, needs, and resources of the low- and middle-income elderly in Boston, depending on their health, housing, marital status and other factors

The Elder Economic Security Initiative™ Program: The Elder Economic Security Standard™ Index for Pennsylvania

This report will address the question of income adequacy for Pennsylvania’s older adults using the WOW-GI National Elder Economic Security Standard Index (the Index) methodology. The Index will benchmark basic costs of living for elder households. It will illustrate how costs of living vary geographically and are based on the characteristics of elder households: household size, homeownership or renter, mode of transportation, and health status. The costs are for basic needs of elder households; they are based on market costs and do not assume any subsidies

The Elder Economic Security Initiative™ Program: The Elder Economic Security Standard™ Index for Illinois

This report will address the question of income adequacy for Illinois’ older adults using the national WOW-GI National Elder Economic Security Standard Index (the Index) methodology. The Index will benchmark basic costs of living for elder households. It will illustrate how costs of living vary geographically and are based on the characteristics of elder households: household size, homeownership or renter, mode of transportation, and health status. The costs are for basic needs of elder households; they are based on market costs and do not assume any subsidies

Elder Economic Security Initiative: The Elder Economic Security Standard for Massachusetts

What is an adequate income for older adults in Massachusetts to age in place? How does it vary according to where they live, and their life circumstances: whether they are living alone or with a spouse, rent or own their home, drive a car or use other transportation? How do elders’ living costs change as their health status and life circumstances change? What happens if they need long-term care to keep living at home? This report will address these questions through the development of a measure of income adequacy for older adults using the WOW-GI National Elder Economic Security Standard (Elder Standard) methodology. The Elder Standard will benchmark basic costs of living for elder households. It will illustrate how costs of living vary geographically and are based on the characteristics of elder households: household size, homeownership or renter, mode of transportation, and health status. The costs are for basic needs of elder households; they are based on market costs and do not assume any subsidies

On the Edge: Facing a Challenging and Uncertain Future. Elder Economic Security Standard™ for the Boston Area

What is an adequate income for older adults in the Boston area to age in place? How does it vary according to their life circumstances: whether they are living alone or with a spouse, rent or own their home, drive a car or use other transportation? How do Boston area elders’ living costs change as their health status and life circumstances change? What happens if they need long-term care to keep living at home? This report will address these questions through the development of a measure of income adequacy for older adults, the Elder Economic Security Standard (Elder Standard). The Elder Standard will benchmark basic costs of living for elder households. It will illustrate how costs of living vary geographically and are based on the characteristics of elder households: household size, homeownership or renter, mode of transportation, and health status. The costs are for basic needs of elder households; they are based on market costs and do not assume any subsidies

The Elder Economic Security Initiative™ Program: The Elder Economic Security Standard™ Index for Wisconsin

This report addresses income adequacy for Wisconsin’s older adults using the WOW-GI Elder Economic Security Standard Index (the Index) methodology. The Index benchmarks basic costs of living for elder households and illustrates how costs of living vary geographically and are based on the characteristics of elder households, including household size, home ownership or renter status, and health status. The costs are based on market costs for basic needs of elder households and do not assume any public or private supports

Application of prioritization approaches to optimize environmental monitoring and testing of pharmaceuticals

Pharmaceuticals are ubiquitous in the natural environment with concentrations expected to rise as human population increases. Environmental risk assessments are available for a small portion of pharmaceuticals in use, raising concerns over the potential risks posed by other drugs that have little or no data. With >1900 active pharmaceutical ingredients in use, it would be a major task to test all of the compounds with little or no data. Desk-based prioritization studies provide a potential solution by identifying those substances that are likely to pose the greatest risk to the environment and which, therefore, need to be considered a priority for further study. The aim of this review was to (1) provide an overview of different prioritization exercises performed for pharmaceuticals in the environment and the results obtained; and (2) propose a new holistic risk-based prioritization framework for drugs in the environment. The suggested models to underpin this framework are discussed in terms of validity and applicability. The availability of data required to run the models was assessed and data gaps identified. The implementation of this framework may harmonize pharmaceutical prioritization efforts and ensure that, in the future, experimental resources are focused on molecules, endpoints, and environmental compartments that are biologically relevant

Autologous humanized PDX modeling for immuno-oncology recapitulates features of the human tumor microenvironment.

BACKGROUND: Interactions between immune and tumor cells are critical to determining cancer progression and response. In addition, preclinical prediction of immune-related drug efficacy is limited by interspecies differences between human and mouse, as well as inter-person germline and somatic variation. To address these gaps, we developed an autologous system that models the tumor microenvironment (TME) from individual patients with solid tumors. METHOD: With patient-derived bone marrow hematopoietic stem and progenitor cells (HSPCs), we engrafted a patient\u27s hematopoietic system in MISTRG6 mice, followed by transfer of patient-derived xenograft (PDX) tissue, providing a fully genetically matched model to recapitulate the individual\u27s TME. We used this system to prospectively study tumor-immune interactions in patients with solid tumor. RESULTS: Autologous PDX mice generated innate and adaptive immune populations; these cells populated the TME; and tumors from autologously engrafted mice grew larger than tumors from non-engrafted littermate controls. Single-cell transcriptomics revealed a prominent vascular endothelial growth factor A (VEGFA) signature in TME myeloid cells, and inhibition of human VEGF-A abrogated enhanced growth. CONCLUSIONS: Humanization of the interleukin 6 locus in MISTRG6 mice enhances HSPC engraftment, making it feasible to model tumor-immune interactions in an autologous manner from a bedside bone marrow aspirate. The TME from these autologous tumors display hallmarks of the human TME including innate and adaptive immune activation and provide a platform for preclinical drug testing

SARS-CoV-2 omicron (B.1.1.529)-related COVID-19 sequelae in vaccinated and unvaccinated patients with cancer: results from the OnCovid registry

Background COVID-19 sequelae can affect about 15% of patients with cancer who survive the acute phase of SARS-CoV-2 infection and can substantially impair their survival and continuity of oncological care. We aimed to investigate whether previous immunisation affects long-term sequelae in the context of evolving variants of concern of SARS-CoV-2. Methods OnCovid is an active registry that includes patients aged 18 years or older from 37 institutions across Belgium, France, Germany, Italy, Spain, and the UK with a laboratory-confirmed diagnosis of COVID-19 and a history of solid or haematological malignancy, either active or in remission, followed up from COVID-19 diagnosis until death. We evaluated the prevalence of COVID-19 sequelae in patients who survived COVID-19 and underwent a formal clinical reassessment, categorising infection according to the date of diagnosis as the omicron (B.1.1.529) phase from Dec 15, 2021, to Jan 31, 2022; the alpha (B.1.1.7)-delta (B.1.617.2) phase from Dec 1, 2020, to Dec 14, 2021; and the pre-vaccination phase from Feb 27 to Nov 30, 2020. The prevalence of overall COVID-19 sequelae was compared according to SARS-CoV-2 immunisation status and in relation to post-COVID-19 survival and resumption of systemic anticancer therapy. This study is registered with ClinicalTrials.gov, NCT04393974. Findings At the follow-up update on June 20, 2022, 1909 eligible patients, evaluated after a median of 39 days (IQR 24-68) from COVID-19 diagnosis, were included (964 [ 50 center dot 7%] of 1902 patients with sex data were female and 938 [49 center dot 3%] were male). Overall, 317 (16 center dot 6%; 95% CI 14 center dot 8-18 center dot 5) of 1909 patients had at least one sequela from COVID-19 at the first oncological reassessment. The prevalence of COVID-19 sequelae was highest in the prevaccination phase (191 [19 center dot 1%; 95% CI 16 center dot 4-22 center dot 0] of 1000 patients). The prevalence was similar in the alpha-delta phase (110 [16 center dot 8%; 13 center dot 8- 20 center dot 3] of 653 patients, p=0 center dot 24), but significantly lower in the omicron phase (16 [6 center dot 2%; 3 center dot 5-10 center dot 2] of 256 patients, p<0 center dot 0001). In the alpha- delta phase, 84 (18 center dot 3%; 95% CI 14 center dot 6-22 center dot 7) of 458 unvaccinated patients and three (9 center dot 4%; 1 center dot 9- 27 center dot 3) of 32 unvaccinated patients in the omicron phase had sequelae. Patients who received a booster and those who received two vaccine doses had a significantly lower prevalence of overall COVID-19 sequelae than unvaccinated or partially vaccinated patients (ten [7 center dot 4%; 95% CI 3 center dot 5-13 center dot 5] of 136 boosted patients, 18 [9 center dot 8%; 5 center dot 8-15 center dot 5] of 183 patients who had two vaccine doses vs 277 [ 18 center dot 5%; 16 center dot 5-20 center dot 9] of 1489 unvaccinated patients, p=0 center dot 0001), respiratory sequelae (six [4 center dot 4%; 1 center dot 6-9 center dot 6], 11 [6 center dot 0%; 3 center dot 0-10 center dot 7] vs 148 [9 center dot 9%; 8 center dot 4- 11 center dot 6], p= 0 center dot 030), and prolonged fatigue (three [2 center dot 2%; 0 center dot 1-6 center dot 4], ten [5 center dot 4%; 2 center dot 6-10 center dot 0] vs 115 [7 center dot 7%; 6 center dot 3-9 center dot 3], p=0 center dot 037)

SARS-CoV-2 omicron (B.1.1.529)-related COVID-19 sequelae in vaccinated and unvaccinated patients with cancer: results from the OnCovid registry

Background COVID-19 sequelae can affect about 15% of patients with cancer who survive the acute phase of SARS-CoV-2 infection and can substantially impair their survival and continuity of oncological care. We aimed to investigate whether previous immunisation affects long-term sequelae in the context of evolving variants of concern of SARS-CoV-2. Methods OnCovid is an active registry that includes patients aged 18 years or older from 37 institutions across Belgium, France, Germany, Italy, Spain, and the UK with a laboratory-confirmed diagnosis of COVID-19 and a history of solid or haematological malignancy, either active or in remission, followed up from COVID-19 diagnosis until death. We evaluated the prevalence of COVID-19 sequelae in patients who survived COVID-19 and underwent a formal clinical reassessment, categorising infection according to the date of diagnosis as the omicron (B.1.1.529) phase from Dec 15, 2021, to Jan 31, 2022; the alpha (B.1.1.7)-delta (B.1.617.2) phase from Dec 1, 2020, to Dec 14, 2021; and the pre-vaccination phase from Feb 27 to Nov 30, 2020. The prevalence of overall COVID-19 sequelae was compared according to SARS-CoV-2 immunisation status and in relation to post-COVID-19 survival and resumption of systemic anticancer therapy. This study is registered with ClinicalTrials.gov, NCT04393974. Findings At the follow-up update on June 20, 2022, 1909 eligible patients, evaluated after a median of 39 days (IQR 24-68) from COVID-19 diagnosis, were included (964 [ 50 center dot 7%] of 1902 patients with sex data were female and 938 [49 center dot 3%] were male). Overall, 317 (16 center dot 6%; 95% CI 14 center dot 8-18 center dot 5) of 1909 patients had at least one sequela from COVID-19 at the first oncological reassessment. The prevalence of COVID-19 sequelae was highest in the prevaccination phase (191 [19 center dot 1%; 95% CI 16 center dot 4-22 center dot 0] of 1000 patients). The prevalence was similar in the alpha-delta phase (110 [16 center dot 8%; 13 center dot 8- 20 center dot 3] of 653 patients, p=0 center dot 24), but significantly lower in the omicron phase (16 [6 center dot 2%; 3 center dot 5-10 center dot 2] of 256 patients, p<0 center dot 0001). In the alpha- delta phase, 84 (18 center dot 3%; 95% CI 14 center dot 6-22 center dot 7) of 458 unvaccinated patients and three (9 center dot 4%; 1 center dot 9- 27 center dot 3) of 32 unvaccinated patients in the omicron phase had sequelae. Patients who received a booster and those who received two vaccine doses had a significantly lower prevalence of overall COVID-19 sequelae than unvaccinated or partially vaccinated patients (ten [7 center dot 4%; 95% CI 3 center dot 5-13 center dot 5] of 136 boosted patients, 18 [9 center dot 8%; 5 center dot 8-15 center dot 5] of 183 patients who had two vaccine doses vs 277 [ 18 center dot 5%; 16 center dot 5-20 center dot 9] of 1489 unvaccinated patients, p=0 center dot 0001), respiratory sequelae (six [4 center dot 4%; 1 center dot 6-9 center dot 6], 11 [6 center dot 0%; 3 center dot 0-10 center dot 7] vs 148 [9 center dot 9%; 8 center dot 4- 11 center dot 6], p= 0 center dot 030), and prolonged fatigue (three [2 center dot 2%; 0 center dot 1-6 center dot 4], ten [5 center dot 4%; 2 center dot 6-10 center dot 0] vs 115 [7 center dot 7%; 6 center dot 3-9 center dot 3], p=0 center dot 037)