Cytokine Expression in Cancer Survivors Suffering From Chronic Pain: A Systematic Review.

BACKGROUND: Chronic cancer-related pain remains underdiagnosed and undertreated, although it affects 40% of cancer survivors. Recent insights suggest that cytokine signaling between immune, neuro, and glial cells contributes to chronic pain. OBJECTIVES: This study systematically reviewed cytokine levels and their relation to chronic cancer-related pain and, additionally, investigated differences in cytokine levels between cancer survivors with and without chronic pain. STUDY DESIGN: Systematic review. METHODS: This systematic review was conducted and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (PRISMA). The study conducted a systematic literature search in the databases PubMed, Web of Science, and Embase for articles examining cytokine levels and pain experience at a time point of a minimum of 3 months post-cancer diagnosis. Pain experience was categorized into a total pain score, pain intensity, and pain interference. The risk of bias was assessed using the Newcastle Ottawa Scale. RESULTS: Eight articles were included, investigating 6 cancer types and 30 cytokines. Moderate evidence was found for pro-inflammatory cytokine IL-6 to be correlated with pain intensity, of which higher levels are observed in cancer survivors experiencing chronic pain compared to pain-free survivors. Moderate evidence was found for TNF-alpha to be not correlated with any pain experience, which is similar for anti-inflammatory cytokines IL-8 and IL-10 with pain intensity. For the remaining 26 cytokines and pain outcomes, only limited evidence was found for an association or alteration. LIMITATIONS: The number of included studies was small. Overall, studies showed a moderate risk of bias, except one indicated a high risk of bias. CONCLUSION: More standardized post-cancer treatment studies are warranted to confirm these results and explore associations and alterations of other cytokines. Nonetheless, moderate evidence suggests that elevated levels of IL-6, in contrast with TNF-alpha levels, are correlated with pain intensity in cancer survivors experiencing chronic pain compared to pain-free survivors.

Pathogenesis of Alzheimer's disease: Involvement of the choroid plexus.

The choroid plexus (ChP) produces and is bathed in the cerebrospinal fluid (CSF), which in aging and Alzheimer's disease (AD) shows extensive proteomic alterations including evidence of inflammation. Considering inflammation hampers functions of the involved tissues, the CSF abnormalities reported in these conditions are suggestive of ChP injury. Indeed, several studies document ChP damage in aging and AD, which nevertheless remains to be systematically characterized. We here report that the changes elicited in the CSF by AD are consistent with a perturbed aging process and accompanied by aberrant accumulation of inflammatory signals and metabolically active proteins in the ChP. Magnetic resonance imaging (MRI) imaging shows that these molecular aberrancies correspond to significant remodeling of ChP in AD, which correlates with aging and cognitive decline. Collectively, our preliminary post-mortem and in vivo findings reveal a repertoire of ChP pathologies indicative of its dysfunction and involvement in the pathogenesis of AD. HIGHLIGHTS: Cerebrospinal fluid changes associated with aging are perturbed in Alzheimer's disease Paradoxically, in Alzheimer's disease, the choroid plexus exhibits increased cytokine levels without evidence of inflammatory activation or infiltrates In Alzheimer's disease, increased choroid plexus volumes correlate with age and cognitive performance.

Pain prevalence and characteristics in survivors of solid cancers: a systematic review and meta-analysis.

PURPOSE: The latest systematic review on the prevalence of pain in cancer survivors was published 5 years ago. The current review aims to provide an extended overview on the prevalence of pain, pain mechanisms, pain characteristics, and assessment methods in cancer survivors. METHODS: A systematic research was conducted on 17th of April 2020 using MEDLINE, Embase, Scopus, Web of Science, and Cochrane looking at studies from 2014 to 2020. Studies had to report pain prevalence rates in cancer survivors with a solid tumor who finished curative treatment at least 3 months ago. Methodological quality was assessed by two independent reviewers using the Joanna Briggs Institute quality appraisal tool. Characteristics of the included studies, participants and reported pain prevalence rates were extracted. The reported prevalence rates of the individual studies were pooled within a meta-analysis. Meta-regressions were performed to identify possible determinants of the pooled pain prevalence. RESULTS: After deduplication, 7300 articles were screened, after which 38 were included in the meta-analysis. Risk of bias was rated low in 26 articles and moderate in 12 articles. The pooled pain prevalence was 47% (95%CI 39-55), with a heterogeneity of 98.99%. CONCLUSION: This meta-analysis suggests that nearly half of cancer survivors report pain after completing curative treatment at least 3 months ago. However, substantial unexplained heterogeneity warrants cautious interpretation of these results. Meta-regression using cancer type, treatment location, pain measurement, and follow-up time as a covariate could not explain influencing factors explaining the high heterogeneity.

Morphometric evaluation of traumatic axonal injury and the correlation with post-traumatic cerebral atrophy and functional outcome.

INTRODUCTION: Imaging plays a crucial role in the diagnosis, prognosis and follow-up of traumatic brain injury. Whereas computed tomography plays a pivotal role in the acute setting, magnetic resonance imaging is best suited to detect the true extent of traumatic brain injury, and more specifically diffuse axonal injury. Post-traumatic brain atrophy is a well-known complication of traumatic brain injury. PURPOSE: This study investigated the correlation between diffuse axonal injury detected with fluid-attenuated inversion recovery and susceptibility-weighted imaging magnetic resonance imaging, post-traumatic brain atrophy and functional outcome (Glasgow outcome scale - extended). MATERIALS AND METHODS: Twenty patients with a closed head injury and diffuse axonal injury detected with fluid-attenuated inversion recovery and susceptibility-weighted imaging were included. The total volumes of the diffuse axonal injury fluid-attenuated inversion recovery lesions were determined for each subject's initial (<14 days) and follow-up magnetic resonance scan (average: day 303 ± 83 standard deviation). The different brain volumes were automatically quantified using a validated and both US Food and Drug Administration-cleared and CE-marked machine learning algorithm (icobrain). The number of susceptibility-weighted imaging lesions and functional outcome scores (Glasgow outcome scale - extended) were retrieved from the Collaborative European NeuroTrauma Effectiveness Research Traumatic Brain Injury dataset. RESULTS: The volumetric fluid-attenuated inversion recovery diffuse axonal injury lesion load showed a significant inverse correlation with functional outcome (Glasgow outcome scale - extended) (r = -0.57; P = 0.0094) and white matter volume change (r = -0.50; P = 0.027). In addition, white matter volume change correlated significantly with the Glasgow outcome scale - extended score (P = 0.0072; r = 0.58). Moreover, there was a strong inverse correlation between longitudinal fluid-attenuated inversion recovery lesion volume change and whole brain volume change (r = -0.63; P = 0.0028). No significant correlation existed between the number of diffuse axonal injury susceptibility-weighted imaging lesions, brain atrophy and functional outcome. CONCLUSIONS: Volumetric analysis of diffuse axonal injury on fluid-attenuated inversion recovery imaging and automated brain atrophy calculation are potentially useful tools in the clinical management and follow-up of traumatic brain injury patients with diffuse axonal injury.

Relationship of admission blood proteomic biomarkers levels to lesion type and lesion burden in traumatic brain injury: A CENTER-TBI study.

BACKGROUND: We aimed to understand the relationship between serum biomarker concentration and lesion type and volume found on computed tomography (CT) following all severities of TBI. METHODS: Concentrations of six serum biomarkers (GFAP, NFL, NSE, S100B, t-tau and UCH-L1) were measured in samples obtained <24 hours post-injury from 2869 patients with all severities of TBI, enrolled in the CENTER-TBI prospective cohort study (NCT02210221). Imaging phenotypes were defined as intraparenchymal haemorrhage (IPH), oedema, subdural haematoma (SDH), extradural haematoma (EDH), traumatic subarachnoid haemorrhage (tSAH), diffuse axonal injury (DAI), and intraventricular haemorrhage (IVH). Multivariable polynomial regression was performed to examine the association between biomarker levels and both distinct lesion types and lesion volumes. Hierarchical clustering was used to explore imaging phenotypes; and principal component analysis and k-means clustering of acute biomarker concentrations to explore patterns of biomarker clustering. FINDINGS: 2869 patient were included, 68% (n=1946) male with a median age of 49 years (range 2-96). All severities of TBI (mild, moderate and severe) were included for analysis with majority (n=1946, 68%) having a mild injury (GCS 13-15). Patients with severe diffuse injury (Marshall III/IV) showed significantly higher levels of all measured biomarkers, with the exception of NFL, than patients with focal mass lesions (Marshall grades V/VI). Patients with either DAI+IVH or SDH+IPH+tSAH, had significantly higher biomarker concentrations than patients with EDH. Higher biomarker concentrations were associated with greater volume of IPH (GFAP, S100B, t-tau;adj r2 range:0·48-0·49; p<0·05), oedema (GFAP, NFL, NSE, t-tau, UCH-L1;adj r2 range:0·44-0·44; p<0·01), IVH (S100B;adj r2 range:0.48-0.49; p<0.05), Unsupervised k-means biomarker clustering revealed two clusters explaining 83·9% of variance, with phenotyping characteristics related to clinical injury severity. INTERPRETATION: Interpretation: Biomarker concentration within 24 hours of TBI is primarily related to severity of injury and intracranial disease burden, rather than pathoanatomical type of injury. FUNDING: CENTER-TBI is funded by the European Union 7th Framework programme (EC grant 602150).

Blood biomarkers on admission in acute traumatic brain injury: Relations to severity, CT findings and care path in the CENTER-TBI study.

BACKGROUND: Serum biomarkers may inform and improve care in traumatic brain injury (TBI). We aimed to correlate serum biomarkers with clinical severity, care path and imaging abnormalities in TBI, and explore their incremental value over clinical characteristics in predicting computed tomographic (CT) abnormalities. METHODS: We analyzed six serum biomarkers (S100B, NSE, GFAP, UCH-L1, NFL and t-tau) obtained <24 h post-injury from 2867 patients with any severity of TBI in the Collaborative European NeuroTrauma Effectiveness Research (CENTER-TBI) Core Study, a prospective, multicenter, cohort study. Univariable and multivariable logistic regression analyses were performed. Discrimination was assessed by the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals. FINDINGS: All biomarkers scaled with clinical severity and care path (ER only, ward admission, or ICU), and with presence of CT abnormalities. GFAP achieved the highest discrimination for predicting CT abnormalities (AUC 0•89 [95%CI: 0•87-0•90]), with a 99% likelihood of better discriminating CT-positive patients than clinical characteristics used in contemporary decision rules. In patients with mild TBI, GFAP also showed incremental diagnostic value: discrimination increased from 0•84 [95%CI: 0•83-0•86] to 0•89 [95%CI: 0•87-0•90] when GFAP was included. Results were consistent across strata, and injury severity. Combinations of biomarkers did not improve discrimination compared to GFAP alone. INTERPRETATION: Currently available biomarkers reflect injury severity, and serum GFAP, measured within 24 h after injury, outperforms clinical characteristics in predicting CT abnormalities. Our results support the further development of serum GFAP assays towards implementation in clinical practice, for which robust clinical assay platforms are required. FUNDING: CENTER-TBI study was supported by the European Union 7th Framework program (EC grant 602150).

Automatic Quantification of Computed Tomography Features in Acute Traumatic Brain Injury.

Traumatic brain injury is a complex and diverse medical condition with a high frequency of intracranial abnormalities. These can typically be visualized on a computed tomography (CT) scan, which provides important information for further patient management, such as the need for operative intervention. In order to quantify the extent of acute intracranial lesions and associated secondary injuries, such as midline shift and cisternal compression, visual assessment of CT images has limitations, including observer variability and lack of quantitative interpretation. Automated image analysis can quantify the extent of intracranial abnormalities and provide added value in routine clinical practice. In this article, we present icobrain, a fully automated method that reliably computes acute intracranial lesions volume based on deep learning, cistern volume, and midline shift on the noncontrast CT image of a patient. The accuracy of our method is evaluated on a subset of the multi-center data set from the CENTER-TBI (Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury) study for which expert annotations were used as a reference. Median volume differences between expert assessments and icobrain are 0.07 mL for acute intracranial lesions and -0.01 mL for cistern segmentation. Correlation between expert assessments and icobrain is 0.91 for volume of acute intracranial lesions and 0.94 for volume of the cisterns. For midline shift computations, median error is -0.22 mm, with a correlation of 0.93 with expert assessments.