Approaches to decision-making among late-stage melanoma patients: a multifactorial investigation.

PurposeThe treatment decisions of melanoma patients are poorly understood. Most research on cancer patient decision-making focuses on limited components of specific treatment decisions. This study aimed to holistically characterize late-stage melanoma patients' approaches to treatment decision-making in order to advance understanding of patient influences and supports.Methods(1) Exploratory analysis of longitudinal qualitative data to identify themes that characterize patient decision-making. (2) Pattern analysis of decision-making themes using an innovative method for visualizing qualitative data: a hierarchically-clustered heatmap. Participants were 13 advanced melanoma patients at a large academic medical center.ResultsExploratory analysis revealed eight themes. Heatmap analysis indicated two broad types of patient decision-makers. "Reliant outsiders" relied on providers for medical information, demonstrated low involvement in decision-making, showed a low or later-in-care interest in clinical trials, and expressed altruistic motives. "Active insiders" accessed substantial medical information and expertise in their networks, consulted with other doctors, showed early and substantial interest in trials, demonstrated high involvement in decision-making, and employed multiple decision-making strategies.ConclusionWe identified and characterized two distinct approaches to decision-making among patients with late-stage melanoma. These differences spanned a wide range of factors (e.g., behaviors, resources, motivations). Enhanced understanding of patients as decision-makers and the factors that shape their decision-making may help providers to better support patient understanding, improve patient-provider communication, and support shared decision-making

Beyond Exploratory: A Tailored Framework for Assessing Rigor in Qualitative Health Services Research

Objective: To propose a framework for assessing the rigor of qualitative research that identifies and distinguishes between the diverse objectives of qualitative studies currently used in patient-centered outcomes and health services research (PCOR and HSR). Study Design: Narrative review of published literature discussing qualitative guidelines and standards in peer-reviewed journals and national funding organizations that support PCOR and HSR. Principal Findings: We identify and distinguish three objectives of current qualitative studies in PCOR and HSR: exploratory, descriptive, and comparative. For each objective, we propose methodological standards that can be used to assess and improve rigor across all study phases—from design to reporting. Similar to quantitative studies, we argue that standards for qualitative rigor differ, appropriately, for studies with different objectives and should be evaluated as such. Conclusions: Distinguishing between different objectives of qualitative HSR improves the ability to appreciate variation in qualitative studies as well as appropriately evaluate the rigor and success of studies in meeting their own objectives. Researchers, funders, and journal editors should consider how adopting the criteria for assessing qualitative rigor outlined here may advance the rigor and potential impact of qualitative research in patient-centered outcomes and health services research

Demonstrating Diversity in Star Formation Histories with the CSI Survey

We present coarse but robust star formation histories (SFHs) derived from spectro-photometric data of the Carnegie-Spitzer-IMACS Survey, for 22,494 galaxies at 0.3<z<0.9 with stellar masses of 10^9 Msun to 10^12 Msun. Our study moves beyond "average" SFHs and distribution functions of specific star formation rates (sSFRs) to individually measured SFHs for tens of thousands of galaxies. By comparing star formation rates (SFRs) with timescales of 10^10, 10^9, and 10^8 years, we find a wide diversity of SFHs: 'old galaxies' that formed most or all of their stars early; galaxies that formed stars with declining or constant SFRs over a Hubble time, and genuinely 'young galaxies' that formed most of their stars since z=1. This sequence is one of decreasing stellar mass, but, remarkably, each type is found over a mass range of a factor of 10. Conversely, galaxies at any given mass follow a wide range of SFHs, leading us to conclude that: (1) halo mass does not uniquely determine SFHs; (2) there is no 'typical' evolutionary track; and (3) "abundance matching" has limitations as a tool for inferring physics. Our observations imply that SFHs are set at an early epoch, and that--for most galaxies--the decline and cessation of star formation occurs over a Hubble-time, without distinct "quenching" events. SFH diversity is inconsistent with models where galaxy mass, at any given epoch, grows simply along relations between SFR and stellar mass, but is consistent with a 2-parameter lognormal form, lending credence to this model from a new and independent perspective.Comment: 17 pages, 10 figures; accepted by ApJ; version 2 - no substantive changes; clarifications and correction

Human Herpes Virus 8 in HIV-1 infected individuals receiving cancer chemotherapy and stem cell transplantation

Background: Human Herpes Virus 8 (HHV8) can cause Kaposi’s Sarcoma (KS) in immunosuppressed individuals. However, little is known about the association between chemotherapy or hematopoietic stem cell transplantation (HSCT), circulating HHV8 DNA levels, and clinical KS in HIV-1-infected individuals with various malignancies. Therefore, we examined the associations between various malignancies, systemic cancer chemotherapy, T cell phenotypes, and circulating HHV8 DNA in 29 HIV-1-infected participants with concomitant KS or other cancer diagnoses. Methods: We quantified HHV8 plasma viral loads and cell-associated HHV8 DNA and determined the relationship between circulating HHV8 DNA and lymphocyte counts, and markers of early and late lymphocyte activation, proliferation and exhaustion. Results: There were no significant differences in plasma HHV8 DNA levels between baseline and post-chemotherapy time points or with the presence or absence of clinical KS. However, in two participants circulating HHV8 DNA increased following treatment for KS or HSCT for lymphoma,. We observed an approximately 2-log10 reduction in plasma HHV8 DNA in an individual with KS and multicentric Castleman disease following rituximab monotherapy. Although individuals with clinical KS had lower mean CD4+ T cell counts and percentages as expected, there were no significant associations with these factors and plasma HHV8 levels. We identified increased proportions of CD8+ and CD4+ T cells expressing CD69 (P = 0.01 & P = 0.04 respectively), and increased CD57 expression on CD4+ T cells (P = 0.003) in participants with detectable HHV8. Conclusion: These results suggest there is a complex relationship between circulating HHV8 DNA and tissue-based disease in HIV-1 and HHV8 co-infected individuals with various malignancies

Assay precision and risk of misclassification at rule-out cut-offs for high-sensitivity cardiac troponin

Clinical trials and guidelines support the use of very low high-sensitivity cardiac troponin (hs-cTn) results to rule-out a myocardial infarction (MI) ( 1) ). The International Federation of Clinical Chemistry and Laboratory Medicine Committee on Clinical Applications of Cardiac Biomarkers committee, through a modeling approach, suggests assays need to have a lower limit near 3 ng/L and an analytical variation of 10% below 7 ng/L if these low values are to perform consistently in practice ( 2) ). Our objectives for the present study were to assess: i) if any type of instrument or individual instrument could achieve a coefficient of variation (CV) of ≤10% at very low hs-cTn cut-offs (i.e., targets) recommended in clinical pathways; ii) the frequency of results at the hs-cTn target, above the target and below the target, with the latter group representing potential misclassification to the low risk group where the target level would in the intermediate risk range.<br/

Severe Community-acquired Pneumonia Due to Staphylococcus aureus, 2003–04 Influenza Season

S. aureus community-acquired pneumonia has been reported from 9 states

Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of “modifiable risk factors”, measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details

Cardiovascular inflammation in healthy women: multilevel associations with state-level prosperity, productivity and income inequality

<p>Abstract</p> <p>Background</p> <p>Cardiovascular inflammation is a key contributor to the development of atherosclerosis and the prediction of cardiovascular events among healthy women. An emerging literature suggests biomarkers of inflammation vary by geography of residence at the state-level, and are associated with individual-level socioeconomic status. Associations between cardiovascular inflammation and state-level socioeconomic conditions have not been evaluated. The study objective is to estimate whether there are independent associations between state-level socioeconomic conditions and individual-level biomarkers of inflammation, in excess of individual-level income and clinical covariates among healthy women.</p> <p>Methods</p> <p>The authors examined cross-sectional multilevel associations among state-level socioeconomic conditions, individual-level income, and biomarkers of inflammation among women (n = 26,029) in the Women's Health Study, a nation-wide cohort of healthy women free of cardiovascular diseases at enrollment. High sensitivity C-reactive protein (hsCRP), soluble intercellular adhesion molecule-1 (sICAM-1) and fibrinogen were measured between 1993 and 1996. Biomarker levels were examined among women within quartiles of state-level socioeconomic conditions and within categories of individual-level income.</p> <p>Results</p> <p>The authors found that favorable state-level socioeconomic conditions were correlated with lower hsCRP, in excess of individual-level income (e.g. state-level real per capital gross domestic product fixed effect standardized Βeta coefficient [Std B] -0.03, 95% CI -0.05, -0.004). Individual-level income was more closely associated with sICAM-1 (Std B -0.04, 95% CI -0.06, -0.03) and fibrinogen (Std B -0.05, 95% CI -0.06, -0.03) than state-level conditions.</p> <p>Conclusions</p> <p>We found associations between state-level socioeconomic conditions and hsCRP among healthy women. Personal household income was more closely associated with sICAM-1 and fibrinogen than state-level socioeconomic conditions. Additional research should examine these associations in other cohorts, and investigate what more-advantaged states do differently than less-advantaged states that may influence levels of cardiovascular inflammation among healthy women.</p