Personality, psychological stress, and self-reported influenza symptomatology

<p>Abstract</p> <p>Background</p> <p>Psychological stress and negative mood have been related to increased vulnerability to influenza-like illness (ILI). This prospective study re-evaluated the predictive value of perceived stress for self-reported ILI. We additionally explored the role of the negative affectivity and social inhibition traits.</p> <p>Methods</p> <p>In this study, 5,404 respondents from the general population were assessed in terms of perceived stress, personality, and control variables (vaccination, vitamin use, exercise, etc.). ILI were registered weekly using self-report measures during a follow-up period of four weeks.</p> <p>Results</p> <p>Multivariable logistic regression analysis on ILI was performed to test the predictive power of stress and personality. In this model, negative affectivity (OR = 1.05, p = 0.009), social inhibition (OR = 0.97, p = 0.011), and perceived stress (OR = 1.03, p = 0.048) predicted ILI reporting. Having a history of asthma (OR = 2.33, p = < 0.0001) was also associated with ILI reporting. Older age was associated with less self-reported ILI (OR = 0.98, P = 0.017).</p> <p>Conclusion</p> <p>Elderly and socially inhibited persons tend to report less ILI as compared to their younger and less socially inhibited counterparts. In contrast, asthma, trait negative affectivity, and perceived stress were associated with higher self-report of ILI. Our results demonstrate the importance of including trait markers in future studies examining the relation between stress and self-report symptom measures.</p

Feasibility and efficacy of addition of individualized-dose lenalidomide to chlorambucil and rituximab as first-line treatment in elderly and FCR-unfit patients with advanced chronic lymphocytic leukemia

Lenalidomide has been proven to be effective but with a distinct and difficult to manage toxicity profile in the context of chronic lymphocytic leukemia, potentially hampering combination treatment with this drug. We conducted a phase 1-2 study to evaluate the efficacy and safety of six cycles of chlorambucil (7 mg/m2 daily), rituximab (375 mg/m2 cycle 1 and 500 mg/m2 cycles 2-6) and individually-dosed lenalidomide (escalated from 2.5 mg to 10 mg) (induction-I) in first-line treatment of patients with chronic lymphocytic leukemia unfit for treatment with fludarabine, cyclophosphamide and rituximab. This was followed by 6 months of 10 mg lenalidomide monotherapy (induction-II). Of 53 evaluable patients in phase 2 of the study, 47 (89%) completed induction-I and 36 (68%) completed induction-II. In an intention-to-treat analysis, the overall response rate was 83%. The median progression-free survival was 49 months, after a median follow-up time of 27 months. The 2- and 3-year progression-free survival rates were 58% and 54%, respectively. The corresponding rates for overall survival were 98% and 95%. No tumor lysis syndrome was observed, while tumor flair reaction occurred in five patients (9%, 1 grade 3). The most common hematologic toxicity was grade 3-4 neutropenia, which occurred in 73% of the patients. In conclusion, addition of lenalidomide to a chemotherapy backbone followed by a fixed duration of lenalidomide monotherapy resulted in high remission rates and progression-free survival rates, which seem comparable to those observed with novel drug combinations including novel CD20 monoclonal antibodies or kinase inhibitors. Although lenalidomide-specific toxicity remains a concern, an individualized dose-escalation schedule is feasible and results in an acceptable toxicity profile. EuraCT number: 2010-022294-34

How to Define and Test an Indirect Moderation Model: The Missing Link in Regression-Based Path Models

Two of the most important extensions of the basic regression model are moderated effects (due to interactions) and mediated effects (i.e. indirect effects). Combinations of these effects may also be present. In this work, an important, yet missing combination is presented that can determine whether a moderating effect itself is mediated by another variable. This ‘indirect moderation’ model can be assessed by a four-step decision tree which guides the user through the necessary regression analyses to infer or refute indirect moderation. A simulation experiment shows how the method works under some basic scenarios

Supplementary materials [code] to: How to define and test an indirect moderation model: The missing link in regression-based path models

Supplementary materials [code] to: van Kollenburg, G. H., & Croon, M. A. (2022). How to define and test an indirect moderation model: The missing link in regression-based path models. Methodology, 18(3). https://doi.org/10.5964/meth.9473In the supplementary material provided is the R code used in the research

How to define and test an Indirect Moderation model: The missing link in regression-based path models

Two of the most important extensions of the basic regression model are moderated effects (due to interactions) and mediated effects (i.e., indirect effects). Combinations of these effects may also be present. In this work, an important, yet missing combination is presented that can determine whether a moderating effect itself is mediated by another variable. This ‘indirect moderation’ model can be assessed by a four-step decision tree which guides the user through the necessary regression analyses to infer or refute indirect moderation. A simulation experiment shows how the method works under some basic scenarios.reviewedacceptedVersio