Fatigue in patients with chronic disease:results from the population-based Lifelines Cohort Study

(1) To evaluate the prevalence of severe and chronic fatigue in subjects with and without chronic disease; (2) to assess to which extent multi-morbidity contributes to severe and chronic fatigue; and (3) to identify predisposing and associated factors for severe and chronic fatigue and whether these are disease-specific, trans-diagnostic, or generic. The Dutch Lifelines cohort was used, including 78,363 subjects with (n = 31,039, 53 ± 12 years, 33% male) and without (n = 47,324, 48 ± 12 years, 46% male) ≥ 1 of 23 chronic diseases. Fatigue was assessed with the Checklist Individual Strength-Fatigue. Compared to participants without a chronic disease, a higher proportion of participants with ≥ 1 chronic disease were severely (23% versus 15%, p < 0.001) and chronically (17% versus 10%, p < 0.001) fatigued. The odds of having severe fatigue (OR [95% CI]) increased from 1.6 [1.5–1.7] with one chronic disease to 5.5 [4.5–6.7] with four chronic diseases; for chronic fatigue from 1.5 [1.5–1.6] to 4.9 [3.9–6.1]. Multiple trans-diagnostic predisposing and associated factors of fatigue were found, explaining 26% of variance in fatigue in chronic disease. Severe and chronic fatigue are highly prevalent in chronic diseases. Multi-morbidity increases the odds of having severe and chronic fatigue. Several trans-diagnostic factors were associated with fatigue, providing a rationale for a trans-diagnostic approach

The Patient Health Questionnaire-9 for detection of major depressive disorder in primary care: consequences of current thresholds in a crosssectional study

<p>Abstract</p> <p>Background</p> <p>There is a need for brief instruments to ascertain the diagnosis of major depressive disorder. In this study, we present the reliability, construct validity and accuracy of the PHQ-9 and PHQ-2 to detect major depressive disorder in primary care.</p> <p>Methods</p> <p>Cross-sectional analyses within a large prospective cohort study (PREDICT-NL). Data was collected in seven large general practices in the centre of the Netherlands. 1338 subjects were recruited in the general practice waiting room, irrespective of their presenting complaint. The diagnostic accuracy (the area under the ROC curve and sensitivities and specificities for various thresholds) was calculated against a diagnosis of major depressive disorder determined with the Composite International Diagnostic Interview (CIDI).</p> <p>Results</p> <p>The PHQ-9 showed a high degree of internal consistency (ICC = 0.88) and test-retest reliability (correlation = 0.94). With respect to construct validity, it showed a clear association with functional status measurements, sick days and number of consultations. The discriminative ability was good for the PHQ-9 (area under the ROC curve = 0.87, 95% CI: 0.84-0.90) and the PHQ-2 (ROC area = 0.83, 95% CI 0.80-0.87). Sensitivities at the recommended thresholds were 0.49 for the PHQ-9 at a score of 10 and 0.28 for a categorical algorithm. Adjustment of the threshold and the algorithm improved sensitivities to 0.82 and 0.84 respectively but the specificity decreased from 0.95 to 0.82 (threshold) and from 0.98 to 0.81 (algorithm). Similar results were found for the PHQ-2: the recommended threshold of 3 had a sensitivity of 0.42 and lowering the threshold resulted in an improved sensitivity of 0.81.</p> <p>Conclusion</p> <p>The PHQ-9 and the PHQ-2 are useful instruments to detect major depressive disorder in primary care, provided a high score is followed by an additional diagnostic work-up. However, often recommended thresholds for the PHQ-9 and the PHQ-2 resulted in many undetected major depressive disorders.</p

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Identification and selective expansion of functionally superior T cells expressing chimeric antigen receptors

Background: T cells expressing chimeric antigen receptors (CARs) have shown exciting promise in cancer therapy, particularly in the treatment of B-cell malignancies. However, optimization of CAR-T cell production remains a trial-and-error exercise due to a lack of phenotypic benchmarks that are clearly predictive of anti-tumor functionality. A close examination of the dynamic changes experienced by CAR-T cells upon stimulation can improve understanding of CAR–T-cell biology and identify potential points for optimization in the production of highly functional T cells. Methods: Primary human T cells expressing a second-generation, anti-CD19 CAR were systematically examined for changes in phenotypic and functional responses to antigen exposure over time. Multi-color flow cytometry was performed to quantify dynamic changes in CAR-T cell viability, proliferation, as well as expression of various activation and exhaustion markers in response to varied antigen stimulation conditions. Results: Stimulated CAR-T cells consistently bifurcate into two distinct subpopulations, only one of which (CARhi/CD25+) exhibit anti-tumor functions. The use of central memory T cells as the starting population and the resilience—but not antigen density—of antigen-presenting cells used to expand CAR-T cells were identified as critical parameters that augment the production of functionally superior T cells. We further demonstrate that the CARhi/CD25+ subpopulation upregulates PD-1 but is resistant to PD-L1-induced dysfunction. Conclusions: CAR-T cells expanded ex vivo for adoptive T-cell therapy undergo dynamic phenotypic changes during the expansion process and result in two distinct populations with dramatically different functional capacities. Significant and sustained CD25 and CAR expression upregulation is predictive of robust anti-tumor functionality in antigen-stimulated T cells, despite their correlation with persistent PD-1 upregulation. The functionally superior subpopulation can be selectively augmented by careful calibration of antigen stimulation and the enrichment of central memory T-cell type. Electronic supplementary material The online version of this article (doi:10.1186/s12967-015-0519-8) contains supplementary material, which is available to authorized users

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]