Monitoring of tumor radio frequency ablation using derivative spectroscopy

Despite the widespread use of radio frequency (RF) ablation, an effective way to assess thermal tissue damage during and after the procedure is still lacking. We present a method for monitoring RF ablation efficacy based on thermally induced methemoglobin as a marker for full tissue ablation. Diffuse reflectance (DR) spectra were measured from human blood samples during gradual heating of the samples from 37 to 60, 70, and 85°C. Additionally, reflectance spectra were recorded real-time during RF ablation of human liver tissue ex vivo and in vivo. Specific spectral characteristics of methemoglobin were extracted from the spectral slopes using a custom optical ablation ratio. Thermal coagulation of blood caused significant changes in the spectral slopes, which is thought to be caused by the formation of methemoglobin. The time course of these changes was clearly dependent on the heating temperature. RF ablation of liver tissue essentially led to similar spectral alterations. In vivo DR measurements confirmed that the method could be used to assess the degree of thermal damage during RF ablation and long after the tissue cooled

Heterogeneous response and progression patterns reveal phenotypic heterogeneity of tyrosine kinase inhibitor response in metastatic renal cell carcinoma

SC was funded by fellowships from NIHR and Cancer Research UK. IK was funded by the UCLH Experimental Cancer Centre and UCLH NIHR Biomedical Research Centre. TP was funded by grants from Cancer Research UK (the Experimental Cancer Medicine Centre). MG was funded by grants from Cancer Research UK, Prostate Cancer UK, the Prostate Cancer Foundation, the Schottlander Research Charitable Trust, the Royal Marsden NIHR Biomedical Research Centre for Cancer and the Wellcome Trust (grant number: 105104/Z/14/Z

Effects of switching between anti-TNF therapies on HAQ response in patients who do not respond to their first anti-TNF drug

Objectives. Small studies have shown an improvement in disease activity in patients with RA who have switched between anti-TNF therapies for reasons of inefficacy. However, it is not clear whether switching improves longer term outcomes, such as disability. This analysis compares changes in HAQ scores 1 yr following lack of response to a first anti-TNF based on subsequent treatment during that year

Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis

Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10-8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10-11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry. © 2013 Cui et al

Secular changes in the progression of clinical markers and patient-reported outcomes in early rheumatoid arthritis

© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Rheumatology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.OBJECTIVES: To examine secular trends in the progression of clinical and patient-reported outcomes in early RA. METHODS: A total of 2701 patients recruited to the Early Rheumatoid Arthritis Study or Early Rheumatoid Arthritis Network with year of diagnosis from 1986 to 2011. The 5-year progression rates for patients diagnosed at different points in time were modelled using mixed-effects regression; 1990, 2002 and 2010, were compared. Clinical markers of disease included the 28-joint count DAS and the ESR. Patient-reported markers included the HAQ, visual analogue scale of pain and global health, and the Short-Form 36. RESULTS: Statistically significant improvements in both 28-joint count DAS and ESR were seen over the 5 years in patients diagnosed with RA compared with those diagnosed earlier. By 5 years, 59% of patients with diagnosis in 2010 were estimated to reach low disease activity compared with 48% with diagnosis in 2002 and 32% with diagnosis in 1990. Whilst HAQ demonstrated statistically significant improvements, these improvements were small, with similar proportions of patients achieving HAQ scores of ≤1.0 by 5 years with a diagnosis in 1990 compared with 2010. Levels of the visual analogue scale and the Mental Component Scores of the Short-Form 36 indicated similar, statistically non-significant levels over the 5 years, irrespective of year diagnosed. CONCLUSION: This study demonstrates improvements in inflammatory markers over time in early RA, in line with improved treatment strategies. These have not translated into similar improvements in patient-reported outcomes relating to either physical or mental health.Peer reviewedFinal Published versio

Initial results of secukinumab drug survival in patients with psoriasis: A multicentre daily practice cohort study

Interleukin 17-antagonist secukinumab demonstrated high efficacy for treatment of psoriasis in randomized controlled trials. However, performance in daily practice may differ from trials. Drug survival is a comprehensive outcome covering effectiveness and safety, suitable for analyses of daily practice. The aim of this study was to evaluate drug survival of secukinumab in a daily practice psoriasis cohort. Data were collected from 13 hospitals. Drug survival was analysed using Kaplan–Meier survival curves, split for reason of discontinuation. In total, 196 patients were included (83% biologic experienced). Overall, 12 and 18 months drug survival of secukinumab was 76% and 67%, respectively, and was mostly determined by ineffectiveness. There was a trend towards shorter drug survival in women and in biologic experienced patients. Thirteen percent of patients experienced at least one episode of fungal infection. This is one of the first studies of drug survival of secukinumab in patients with psoriasis treated in daily practice

Killer immunoglobulin-like receptor and human leukocyte antigen-C genotypes in rheumatoid arthritis primary responders and non-responders to anti-TNF-α therapy

The identification of patients who will respond to anti-tumor necrosis factor alpha (anti-TNF-α) therapy will improve the efficacy, safety, and economic impact of these agents. We investigated whether killer cell immunoglobulin-like receptor (KIR) genes are related to response to anti-TNF-α therapy in patients with rheumatoid arthritis (RA). Sixty-four RA patients and 100 healthy controls were genotyped for 16 KIR genes and human leukocyte antigen-C (HLA-C) group 1/2 using polymerase chain reaction sequence-specific oligonucleotide probes (PCR-SSOP). Each patient received anti-TNF-α therapy (adalimumab, etanercept, or infliximab), and clinical responses were evaluated after 3 months using the disease activity score in 28 joints (DAS28). We investigated the correlations between the carriership of KIR genes, HLA-C group 1/2 genes, and clinical data with response to therapy. Patients responding to therapy showed a significantly higher frequency of KIR2DS2/KIR2DL2 (67.7% R vs. 33.3% NR; P = 0.012). A positive clinical outcome was associated with an activating KIR–HLA genotype; KIR2DS2(+)HLA-C group 1/2 homozygous. Inversely, non-response was associated with the relatively inhibitory KIR2DS2(–)HLA-C group 1/2 heterozygous genotype. The KIR and HLA-C genotype of an RA patient may provide predictive information for response to anti-TNF-α therapy

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data

Contains fulltext : 89126.pdf (publisher's version ) (Open Access)BACKGROUND: Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. RESULTS: The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the Fc gamma RIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. CONCLUSIONS: Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. Availability: http://sourceforge.net/projects/sdrproject/