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Viruses have brought humanity many challenges: respiratory infection, cancer, neurological impairment and immunosuppression to name a few. Virology research over the last 60+ years has responded to reduce this disease burden with vaccines and antivirals. Despite this long history, the COVID-19 pandemic has brought unprecedented attention to the field of virology. Some of this attention is focused on concern about the safe conduct of research with human pathogens. A small but vocal group of individuals has seized upon these concerns - conflating legitimate questions about safely conducting virus-related research with uncertainties over the origins of SARS-CoV-2. The result has fueled public confusion and, in many instances, ill-informed condemnation of virology. With this article, we seek to promote a return to rational discourse. We explain the use of gain-of-function approaches in science, discuss the possible origins of SARS-CoV-2 and outline current regulatory structures that provide oversight for virological research in the United States. By offering our expertise, we - a broad group of working virologists - seek to aid policy makers in navigating these controversial issues. Balanced, evidence-based discourse is essential to addressing public concern while maintaining and expanding much-needed research in virology.

Some people remain healthier throughout life than others but the underlying reasons are poorly understood. Here we hypothesize this advantage is attributable in part to optimal immune resilience (IR), defined as the capacity to preserve and/or rapidly restore immune functions that promote disease resistance (immunocompetence) and control inflammation in infectious diseases as well as other causes of inflammatory stress. We gauge IR levels with two distinct peripheral blood metrics that quantify the balance between (i) CD8+ and CD4+ T-cell levels and (ii) gene expression signatures tracking longevity-associated immunocompetence and mortality-associated inflammation. Profiles of IR metrics in ~48,500 individuals collectively indicate that some persons resist degradation of IR both during aging and when challenged with varied inflammatory stressors. With this resistance, preservation of optimal IR tracked (i) a lower risk of HIV acquisition, AIDS development, symptomatic influenza infection, and recurrent skin cancer; (ii) survival during COVID-19 and sepsis; and (iii) longevity. IR degradation is potentially reversible by decreasing inflammatory stress. Overall, we show that optimal IR is a trait observed across the age spectrum, more common in females, and aligned with a specific immunocompetence-inflammation balance linked to favorable immunity-dependent health outcomes. IR metrics and mechanisms have utility both as biomarkers for measuring immune health and for improving health outcomes.

We recently reported that the risk of sexually acquired HIV-1 infection is increased significantly by variants in the gene encoding CD101, a protein thought to modify inflammatory responses. Using blood samples from individuals with and without these variants, we demonstrate that CD101 variants modify the prevalence of circulating inflammatory cell types and show that CD101 variants are associated with increased proinflammatory cytokine production by circulating T cells. One category of CD101 variants is associated with a reduced capacity of regulatory T cells to suppress T cell cytokine production, resulting in a reduction in the baseline level of immune quiescence. These data are supported by transcriptomics data revealing alterations in the intrinsic regulation of antiviral pathways and HIV resistance genes in individuals with CD101 variants. Our data support the hypothesis that CD101 contributes to homeostatic regulation of bystander inflammation, with CD101 variants altering heterosexual HIV-1 acquisition by facilitating increased prevalence and altered function of T cell subsets.

With a solid foundation in public administration since the 1980s, few could argue that ethics is not an important aspect of a public service education. Yet, in many public human resource management (HRM) or personnel courses, ethics is relegated to one class discussion. In this study, we contend that ethics is best understood when situated within the context of other approaches to public administration. In supplying this revised theoretical and fourth approach to Rosenbloom's three approaches to public administration, we also contend that ethics, as an equally important approach, is best utilized in the public HRM course when done so consistently and frequently using decision-making cases. First, we will explain the addition of ethics as an approach for analysis and introduce a decision-making case. Next, we discuss our research findings from a survey that assessed student responses to the decision-making case from two different MPA programs.

Introduction: While randomized controlled trials remain the reference standard for evaluating treatment efficacy, there is an increased interest in the use of external control arms (ECA), namely in oncology, using real-world data (RWD). Challenges related to measurement of real-world oncology endpoints, like progression-free survival (PFS), are one factor limiting the use and acceptance of ECAs as comparators to trial populations. Differences in how and when disease assessments occur in the real-world may introduce measurement error and limit the comparability of real-world PFS (rwPFS) to trial progression-free survival. While measurement error is a known challenge when conducting an externally-controlled trial with real-world data, there is limited literature describing key contributing factors, particularly in the context of multiple myeloma (MM). Methods: We distinguish between biases attributed to how endpoints are derived or ascertained (misclassification bias) and when outcomes are observed or assessed (surveillance bias). We further describe how misclassification of progression events (i.e., false positives, false negatives) and irregular assessment frequencies in multiple myeloma RWD can contribute to these biases, respectively. We conduct a simulation study to illustrate how these biases may behave, both individually and together. Results: We observe in simulation that certain types of measurement error may have more substantial impacts on comparability between mismeasured median PFS (mPFS) and true mPFS than others. For instance, when the observed progression events are misclassified as either false positives or false negatives, mismeasured mPFS may be biased towards earlier (mPFS bias = −6.4 months) or later times (mPFS bias = 13 months), respectively. However, when events are correctly classified but assessment frequencies are irregular, mismeasured mPFS is more similar to the true mPFS (mPFS bias = 0.67 months). Discussion: When misclassified progression events and irregular assessment times occur simultaneously, they may generate bias that is greater than the sum of their parts. Improved understanding of endpoint measurement error and how resulting biases manifest in RWD is important to the robust construction of ECAs in oncology and beyond. Simulations that quantify the impact of measurement error can help when planning for ECA studies and can contextualize results in the presence of endpoint measurement differences. [ABSTRACT FROM AUTHOR]

Background: Regulators and oncology healthcare providers are increasingly interested in using observational studies of real‐world data (RWD) to complement clinical evidence from randomized controlled trials for informed decision‐making. To generate valid evidence, RWD studies must be carefully designed to avoid systematic biases. The clone‐censor‐weight (CCW) method has been proposed to address immortal time and other time‐related biases. Methods: The objective of this manuscript is to de‐mystify the CCW method for cancer researchers by describing and presenting its core components in an accessible and digestible format, using visualizations and examples from cancer‐relevant studies. The CCW method has been applied in diverse settings, including investigations of the effects of surgery within a certain time after cancer diagnosis, the continuation of annual screening mammography, and chemotherapy duration on survival. Results: The method handles complex data wherein the treatment group to which an individual belongs is unknown at the start of follow‐up. The three steps of the CCW method involve cloning or duplicating the patient population and assigning one clone to each treatment strategy, artificially censoring the clones when their observed data are inconsistent with the assigned strategy and weighting the cloned and censored population to address selection bias created by the artificial censoring. Conclusions: The CCW method is a powerful tool for designing RWD studies in cancer that are free from time‐related biases and successfully, to the extent possible, emulate features of a randomized clinical trial. [ABSTRACT FROM AUTHOR]

Randomized trials estimate the average treatment effect within individuals who are eligible, invited, and agree to enroll. However, decision-makers often require evidence that extends beyond the trial's enrolled population to inform policy or actions for their specific target population. Each decision-maker has distinct target populations, the composition of which may not often align with that of the trial population. As researchers, we should identify a decision-maker for whom we aim to generate evidence early in the research process. We can then specify a target population of their interest and determine if a policy or action can be informed using results from a trial alone, or if additional complementary real-world data and analysis are required. In this commentary, we outline 5 key groupings of decision-makers: policymakers, payers, purchasers, providers, and patients. We then specify relevant target populations for decision-makers interested in the effectiveness of beta-blockers after a myocardial infarction with preserved ejection fraction. Finally, we summarize the scenarios in which results from a randomized trial may or may not apply to these target populations and suggest relevant analytic approaches that can generate evidence to better align with a decision-maker's needs. This article is part of a Special Collection on Pharmacoepidemiology. [ABSTRACT FROM AUTHOR]

Purpose: The oncology quality, characterization, and assessment of real‐world data (Oncology QCARD) Initiative was formed to develop a set of minimum study design and data elements needed to evaluate the fitness of the real‐world data (RWD) source(s) proposed in an initial study concept as part of early interaction with scientific reviewers. Methods: A multidisciplinary executive committee (EC) was established to guide the Oncology QCARD Initiative. The EC conducted a landscape review of published literature, guidances, and guidelines to evaluate relevant dimensions of data quality measurement. Guided by the review and informed by expert feedback, the Oncology QCARD Initial Protocol Characterization (IPC) provides a summary of minimum elements needed to adequately describe an initial clinical study concept that involves RWD and is intended to support decision‐making. Results: Fit‐for‐use data and fit‐for‐purpose design emerged as themes from the landscape analysis. Data that are fit‐for‐use are both relevant (sufficiently capturing exposure, outcomes, and covariates) and reliable (understanding data accrual and quality control and whether the data represent the underlying concepts they are intended to represent) to answer a specific research question. A fit‐for‐purpose design takes appropriate steps to ensure internal and external validity and allows for transparency in reporting. The QCARD‐IPC focuses on high‐level characteristics of RWD sources and study design domains including data temporality, population, medical product exposure, comparators, and covariates, endpoints, statistical analysis, and data quality assurance plans. Conclusions: Evaluation of studies including RWD requires understanding the data source, study design, and potential biases to preliminarily evaluate whether selected RWD are fit‐for‐use for the research question. The Oncology QCARD‐IPC provides a structured, transparent approach to facilitate early review and enhanced communication between study sponsors and scientific reviewers of initial study proposals including RWD. [ABSTRACT FROM AUTHOR]

Clinicians, researchers, regulators, and other decision-makers increasingly rely on evidence from real-world data (RWD), including data routinely accumulating in health and administrative databases. RWD studies often rely on algorithms to operationalize variable definitions. An algorithm is a combination of codes or concepts used to identify persons with a specific health condition or characteristic. Establishing the validity of algorithms is a prerequisite for generating valid study findings that can ultimately inform evidence-based health care. In this paper, we aim to systematize terminology, methods, and practical considerations relevant to the conduct of validation studies of RWD-based algorithms. We discuss measures of algorithm accuracy, gold/reference standards, study size, prioritization of accuracy measures, algorithm portability, and implications for interpretation. Information bias is common in epidemiologic studies, underscoring the importance of transparency in decisions regarding choice and prioritizing measures of algorithm validity. The validity of an algorithm should be judged in the context of a data source, and one size does not fit all. Prioritizing validity measures within a given data source depends on the role of a given variable in the analysis (eligibility criterion, exposure, outcome, or covariate). Validation work should be part of routine maintenance of RWD sources. This article is part of a Special Collection on Pharmacoepidemiology. [ABSTRACT FROM AUTHOR]

Background To describe reasons for deviations from planned chemotherapy treatments in women with nonmetastatic breast cancer that contribute to less-than-planned receipt of chemotherapy. Methods Electronic medical records for patients receiving chemotherapy were reviewed for adverse events and treatment modifications. Log-binomial regression models were used to estimate relative risks (RRs) with 95% CIs to examine associations between chemotherapy modifications, patient characteristics, and treatment modalities. Results Delays in chemotherapy initiation (7%) were for surgical complications (58%), personal reasons (16%), and other (26%; port malfunction, infections, and obtaining extra imaging). Delays during chemotherapy (38%) were for infections (20%), neutropenia (13%), and personal reasons (13%). Dose reductions (38%) were for neuropathy (36%), unknown causes (9%), anemia (9%), and neutropenia (8%). Early treatment discontinuations (23%) were for neuropathy (29%). Patients receiving paclitaxel/nab-paclitaxel (RR 2.05; 95% CI, 1.47-2.87) and an anthracycline (RR 1.89; 95% CI, 1.39-2.57) reported more dose delays during chemotherapy. Black race (RR 1.46; 95% CI, 1.07-2.00), stage 3 (RR 1.79; 95% CI, 1.09-2.93), and paclitaxel/nab-paclitaxel receipt (RR 1.39; 95% CI, 1.02-1.90) increased the likelihood of dose reduction. Both Black race (RR 2.06; 95% CI, 1.35-3.15) and receipt of paclitaxel/nab-paclitaxel (RR 1.93; 95% CI, 1.19-3.13) increased the likelihood of early discontinuation. Patients receiving anthracyclines had higher rates of hospitalizations during chemotherapy (RR: 1.79; 95% CI, 1.11-2.89). Conclusion Toxicities are the most common reason for treatment modifications and need close monitoring in high-risk groups for timely intervention. Dose reductions and early treatment discontinuations occurred more for Black patients and need further study. [ABSTRACT FROM AUTHOR]

Background Frailty is a dynamic syndrome characterized by reduced physiological reserve to maintain homeostasis. Prospective studies have reported frailty worsening in women with breast cancer during chemotherapy, with improvements following treatment. We evaluated whether the Faurot frailty index, a validated claims-based frailty measure, could identify changes in frailty during chemotherapy treatment and identified predictors of trajectory patterns. Methods We included women (65+ years) with stage I-III breast cancer undergoing adjuvant chemotherapy in the SEER-Medicare database (2003-2019). We estimated the Faurot frailty index (range: 0-1; higher scores indicate greater frailty) at chemotherapy initiation, 4 months postinitiation, and 10 months postinitiation. Changes in frailty were compared to a matched noncancer comparator cohort. We identified patterns of frailty trajectories during the year following chemotherapy initiation using K-means clustering. Results Twenty-one thousand five hundred and ninety-nine women initiated adjuvant chemotherapy. Mean claims-based frailty increased from 0.037 at initiation to 0.055 4 months postchemotherapy initiation and fell to 0.049 10 months postinitiation. Noncancer comparators experienced a small increase in claims-based frailty over time (0.055-0.062). We identified 6 trajectory patterns: a robust group (78%), 2 resilient groups (16%), and 3 nonresilient groups (6%). Black women and women with claims for home hospital beds, wheelchairs, and Parkinson's disease were more likely to experience nonresilient trajectories. Conclusions We observed changes in a claims-based frailty index during chemotherapy that are consistent with prior studies using clinical measures of frailty and identified predictors of nonresilient frailty trajectories. Our study demonstrates the feasibility of using claims-based frailty indices to assess changes in frailty during cancer treatment. [ABSTRACT FROM AUTHOR]

Background The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center has developed a novel data resource, the Cancer Information and Population Health Resource (CIPHR), for conducting catchment area evaluation and cancer population health research that links the North Carolina Central Cancer Registry (NCCCR) to medical and pharmacy claims data from Medicare, Medicaid, and private plans operating within North Carolina. This study's aim was to describe the CIPHR data and provide examples of potential cohorts available in those data. Methods We present the underlying populations included in the NCCCR and claims data before linkage and demonstrate estimated sample sizes when these data are linked and commonly used insurance enrollment criteria are applied. Results Data for the years 2003-2020 are present in CIPHR and include 947 977 cancer cases from the NCCCR and 21.6 million enrollees in public and private health insurance (cancer and noncancer cases). When limited to first or only cancers (n = 672 377), 86% could be linked to insurance enrollment for at least 1 month during 2003-2020 (n = 582 638), with 62% of individuals linking to enrollment during the month of cancer diagnosis. Among all registry cancer cases, 47% (n = 317 898) had continuous insurance enrollment for at least 12 months before and after cancer diagnosis. Conclusion CIPHR illustrates the utility of establishing and maintaining a statewide, comprehensive cancer population health database. This resource serves to characterize the cancer center catchment area and aids in tracking cancer outcomes and trends in care delivery as well as identifying disparities that require intervention and policy focus. [ABSTRACT FROM AUTHOR]

Mucosal infections pose a significant global health burden. Antigen-specific tissue-resident T cells are critical to maintaining barrier immunity. Previous studies in the context of systemic infection suggest that memory [CD8.sup.+] T cells may also provide innate-like protection against antigenically unrelated pathogens independent of T cell receptor engagement. Whether bystander T cell activation is also an important defense mechanism in the mucosa is poorly understood. Here, we investigated whether innate-like memory [CD8.sup.+] T cells could protect against a model mucosal virus infection, herpes simplex virus 2 (HSV-2). We found that immunization with an irrelevant antigen delayed disease progression from lethal HSV-2 challenge, suggesting that memory [CD8.sup.+] T cells may mediate protection despite the lack of antigen specificity. Upon HSV-2 infection, we observed an early infiltration, rather than substantial local proliferation, of antigen- nonspecific [CD8.sup.+] T cells, which became bystander-activated only within the infected mucosal tissue. Critically, we show that Bystander-activated [CD8.sup.+] T cells are sufficient to reduce early viral burden after HSV-2 infection. Finally, local cytokine cues within the tissue microenvironment after infection were sufficient for bystander activation of mucosal tissue memory [CD8.sup.+] T cells from mice and humans. Altogether, our findings suggest that local bystander activation of [CD8.sup.+] memory T cells contributes a fast and effective innate-like response to infection in mucosal tissue., Introduction Maintaining a balance of protection from pathogens while minimizing pathology is a perpetual process in mucosal barrier tissues, and tissue-resident memory [CD8.sup.+] T cells ([CD8.sup.+] TRMs) have been shown [...]