The Use of Advanced Ultrasound Techniques for the Evaluation of Uterine Fibroids pre and post Uterine Artery Embolization

Introduction: Uterine fibroids are the most common benign tumor in females of reproductive age. Uterine artery embolization (UAE) is a less-invasive alternative to hysterectomy. Our objective is to assess the ability of superb microvascular imaging (SMI) to characterize fibroid microvascularity before and after UAE compared to conventional Doppler modes using contrast-enhanced ultrasound (CEUS) and clinical outcomes as reference standards. Methods: Participants will be 40 adult females who are scheduled for UAE. Participants receive three transabdominal ultrasounds at day 0, day 14 and day 90 post-UAE using an Aplio i800 scanner. Subjects undergo examination with four non-contrast ultrasound modalities— color doppler (CDI), power doppler (PDI), color SMI (cSMI) and monochrome SMI (mSMI)— followed by CEUS. Qualitative analysis is performed by two radiologists who score the fibroids as having internal, peripheral or no vascularity. ImageJ is used to quantify fractional vascularity (FV) and signal intensity (SI). Results: Results from 31 fibroids in 22 subjects are currently available. In agreement with CEUS findings, analysis of the FV showed significant differences across modes and examination times (p\u3c0.001). Though analysis of signal intensity across imaging modes showed no significant differences (p=0.9), differences were observed across examination times (p\u3c0.001). Compared to the CEUS findings, one reader showed no difference for all modes (p=0.2), while the other reader showed no difference for CDI, PDI and cSMI (p\u3e0.1), but did show a difference for mSMI (p=0.047). Discussion: Preliminary results indicate that Doppler and SMI modes agree with CEUS findings when evaluating fibroid vascularity, and may provide clinical benefit

An Active Learning Approach for Rapid Characterization of Endothelial Cells in Human Tumors

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers

Efficacy of first-line treatments for multiple myeloma patients not eligible for stem cell transplantation

Decision making for not transplant eligible patients with multiple myeloma is complicated by lacking head-to-head comparisons of standards of care, increasing treatment modalities and rapidly evolving promising results of studies with novel regimens. To support evidence-based decision making, we performed a network meta-analysis for not transplant-eligible multiple myeloma patients that synthesizes direct and indirect evidence and enable a comparison of all treatments. Relevant randomized clinical trials were identified by a systematic literature review in EMBASE®, MEDLINE®, MEDLINE®-in-Process and the Cochrane Central Register of Controlled Trials for January-1999 to March-2016. Efficacy outcomes (i.e. the hazard ratio and 95% confidence interval for progression-free survival) were extracted and synthesized in a random effects network-meta analysis. In total 24 studies were identified including 21 treatments. According to the network-meta analysis, the hazard ratio for progression-free survival was favorable for all not transplant-eligible myeloma treatments compared to dexamethasone (hazard ratios between 0.19-0.90). Daratumumabbortezomib-melphalan-prednisone and bortezomib-melphalan-prednisone-thalidomide with bortezomib-thalidomide maintenance were identified as the most effective treatments (hazard ratio: 0.19 (95% confidence interval 0.08-0.45) and 0.22 (95% confidence interval 0.10-0.51), respectively). The hazard ratios and 95% confidence interval for currently recommended treatments, bortezomiblenalidomide-dexamethasone, bortezomib-melphalan-prednisone, and lenalidomide-dexamethasone compared to dexamethasone, were 0.31 (0.16-0.59), 0.39 (0.20-0.75) and 0.44 (0.29-0.65), respectively. In addition to identifying the most effective treatment options, we illustrate the additional value and evidence of network meta-analysis in clinical practice. In the current treatment landscape, the results of network meta-analysis may support evidence based decisions and ultimately help to optimize treatment and outcomes of not transplant eligible multiple myeloma patients

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe

Does young age really put the heart at risk?

Despite significant advances in the management and treatment of heart disease in children, there continue to be patients who have worse outcomes than might be expected. A number of risk factors that could be responsible have been identified. Evidence based findings will be reviewed including whether young age and/or reduced body weight exacerbate these responses. For example, newborn children undergoing congenital cardiac surgery are known to have worse outcomes than older children. Evidence exists that newborn hearts do not tolerate ischemia as well as adults; developing irreversible injury sooner and exhibiting at risk metabolic profiles. As well, in response to the administration of heparin, elevations in free fatty acids occur during congenital heart surgery in children which can have detrimental effects on the heart. Furthermore, myocardial energetic state has also been suggested to impact outcomes. Unfavorable energetic profiles were correlated to lower body weights in the same age healthy newborn piglet model. Newborn children suffering from congenital heart disease, with lower body weights, also had lower myocardial energetic state and this correlated with longer post operative ventilatory support as well as a trend to longer Intensive Care Unit stay. These findings imply that unfavorable myocardial metabolic profiles could contribute to post operative complications.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Multinomial network meta-analysis using response rates: relapsed/refractory multiple myeloma treatment rankings differ depending on the choice of outcome

Background : Due to the fast growing relapsed/refractory multiple myeloma (RRMM) treatment landscape, a comparison of all the available treatments was warranted. For clinical practice it is important to consider both immediate effects such as response quality and prolonged benefits such as progression-free survival (PFS) in a meta-analysis. The objective of this study was to assess the impact of the choice of outcome on the treatment rankings in RRMM. Methods : A multinomial logistic network meta-analysis was conducted to estimate the ranking of sixteen treatments based on both complete and objective response rates (CRR and ORR). Seventeen phase III randomized controlled trials from a previously performed systematic literature review were included. Treatment ranking was based on the surface under the cumulative ranking curve (SUCRA). Sensitivity analysis was conducted. Results : The ranking of treatments differed when comparing PFS hazard ratios rankings with rankings based on CRR. Pomalidomide, bortezomib and dexamethasone ranked highest, while a substantial lower ranking was observed for the triplet elotuzumab, lenalidomide, dexamethasone. The ranking of treatments did not differ when comparing PFS hazard ratios and ORR. The scenario analyses showed that the results were robust. In all scenarios the top three was dominated by the same triplets. The treatment with the highest probability of having the best PFS and ORR was the triplet daratumumab, lenalidomide plus dexamethasone in the base case. Conclusion : This analysis shows that depending on the chosen outcome treatment rankings in RRMM may differ. When conducting NMAs, the response rate, a clinically recognized outcome, should therefore be more frequently considered