Flexible evaluation of surrogacy in platform studies.

Trial-level surrogates are useful tools for improving the speed and cost effectiveness of trials but surrogates that have not been properly evaluated can cause misleading results. The evaluation procedure is often contextual and depends on the type of trial setting. There have been many proposed methods for trial-level surrogate evaluation, but none, to our knowledge, for the specific setting of platform studies. As platform studies are becoming more popular, methods for surrogate evaluation using them are needed. These studies also offer a rich data resource for surrogate evaluation that would not normally be possible. However, they also offer a set of statistical issues including heterogeneity of the study population, treatments, implementation, and even potentially the quality of the surrogate. We propose the use of a hierarchical Bayesian semiparametric model for the evaluation of potential surrogates using nonparametric priors for the distribution of true effects based on Dirichlet process mixtures. The motivation for this approach is to flexibly model relationships between the treatment effect on the surrogate and the treatment effect on the outcome and also to identify potential clusters with differential surrogate value in a data-driven manner so that treatment effects on the surrogate can be used to reliably predict treatment effects on the clinical outcome. In simulations, we find that our proposed method is superior to a simple, but fairly standard, hierarchical Bayesian method. We demonstrate how our method can be used in a simulated illustrative example (based on the ProBio trial), in which we are able to identify clusters where the surrogate is, and is not useful. We plan to apply our method to the ProBio trial, once it is completed.

Exploring mean platelet volume and neutrophil-to-albumin ratio as surrogate markers for monitoring tuberculosis treatment: a prospective longitudinal study.

BACKGROUND: Tuberculosis (TB) remains a global health challenge, with India bearing a significant burden. Despite advancements in TB diagnosis and treatment, monitoring TB treatment is challenging, particularly in resource-limited settings. This study aimed to explore the mean platelet volume (MPV) as a potential surrogate marker for monitoring TB treatment and assessing if the neutrophil-to-albumin ratio (NAR) enhances treatment monitoring. METHODS: Patients diagnosed with TB following NTEP guidelines were recruited. Participants underwent routine blood tests during the six-month Anti-Tubercular therapy course at the start, end of the intensive phase, and end of the continuous phase. Statistical analyses included Spearman correlation, Friedman test, linear mixed effects (LME) models, and multiple linear regression. RESULTS: 150 individuals were included for analysis. Deviations from normality were noted. Significant associations were found between CRP and sputum grade. MPV mediated between CRP and sputum grade. Significant differences were observed across the three-time points. LME models showed changes in MPV and CRP levels over time. Including NAR enhanced predictive capability. CONCLUSIONS: MPV may serve as a promising surrogate marker for monitoring ATT. Personalized approaches are crucial in TB treatment monitoring. LME models revealed MPV and CRP level trends. Future research should explore MPV's treatment response mechanisms and cost-effectiveness.

Research progress on detection methods for hepatitis B virus covalently closed circular DNA.

Hepatitis B virus (HBV) infection remains a serious global public health problem, and HBV covalently closed circular DNA (cccDNA) in the nucleus of infected cells cannot be eliminated by current treatments and is a major factor in the persistence and recurrence of hepatitis B. Efficient and scientific detection methods are important for clinical monitoring of cccDNA and targeted drug development. Western blotting is the gold standard for the quantitative detection of cccDNA, but it is time-consuming and complex. In recent years, new detection technologies have been continuously updated. There are new developments and breakthroughs in both next-generation polymerase chain reaction (PCR) and non-PCR methods such as in situ hybridization. Some HBV-related markers (such as hepatitis B core-related antigen) have also been shown to be closely related to cccDNA, and they can be used as surrogate markers to indirectly reflect cccDNA content. In this paper, the main detection methods of cccDNA and their improvements are reviewed, the advantages and limitations of these methods are analysed and summarized, and future development directions are proposed.

Robust approach to combining multiple markers to improve surrogacy.

Identifying effective and valid surrogate markers to make inference about a treatment effect on long-term outcomes is an important step in improving the efficiency of clinical trials. Replacing a long-term outcome with short-term and/or cheaper surrogate markers can potentially shorten study duration and reduce trial costs. There is sizable statistical literature on methods to quantify the effectiveness of a single surrogate marker. Both parametric and nonparametric approaches have been well developed for different outcome types. However, when there are multiple markers available, methods for combining markers to construct a composite marker with improved surrogacy remain limited. In this paper, building on top of the optimal transformation framework of Wang et al. (2020), we propose a novel calibrated model fusion approach to optimally combine multiple markers to improve surrogacy. Specifically, we obtain two initial estimates of optimal composite scores of the markers based on two sets of models with one set approximating the underlying data distribution and the other directly approximating the optimal transformation function. We then estimate an optimal calibrated combination of the two estimated scores which ensures both validity of the final combined score and optimality with respect to the proportion of treatment effect explained by the final combined score. This approach is unique in that it identifies an optimal combination of the multiple surrogates without strictly relying on parametric assumptions while borrowing modeling strategies to avoid fully nonparametric estimation which is subject to the curse of dimensionality. Our identified optimal transformation can also be used to directly quantify the surrogacy of this identified combined score. Theoretical properties of the proposed estimators are derived, and the finite sample performance of the proposed method is evaluated through simulation studies. We further illustrate the proposed method using data from the Diabetes Prevention Program study.

[Alveolar rhabdomyosarcoma: novel surrogate markers associated with oncogenic translocation]. / Al'veolyarnaya rabdomiosarkoma: novye vspomogatel'nye surrogatnye markery onkogennykh translokatsii.

BACKGROUND: Anomalies of the FOXO1 gene in alveolar rhabdomyosarcoma are associated with a worse clinical prognosis, which determines the high value of studying the status of this gene when choosing a therapy strategy. The «gold standard¼ for determining FOXO1 gene rearrangements is currently the fluorescent in situ hybridization (FISH) technique. OBJECTIVE: Study of the relationship between canonical FOXO1 translocation and immunohistochemical expression of new surrogate markers in alveolar rhabdomyosarcoma to determine their predictive value. MATERIAL AND METHODS: 139 cases of rhabdomyosarcoma were retrospectively studied. The study used tissue matrix technology (TMA). On sections obtained from TMA blocks, the FISH technique was implemented using the locus-specific probe MetaSystems XL FOXO1 Break Apart (Metasystems, Germany). Immunohistochemical studies were performed on similar sections from TMA blocks with OLIG2 (Cell Marque Antibodies, clone 211F1.1) and MUC4 (Cell Marque Antibodies, clone 8G7) antibodies. RESULTS: The final expression analysis and statistical processing using a 2x2 contingency table and Fisher's exact test passed 111 cases (76 without FOXO1 rearrangement and 35 with rearrangement). The specificity of OLIG2 and MUC4 expression for FOXO1-rearranged alveolar rhabdomyosarcoma was 85.53% and 80.26%, respectively (p<0.01). CONCLUSION: The present study confirms the high predictive value of the expression of surrogate markers OLIG2 and MUC4 in determining the genetic status of alveolar rhabdomyosarcoma, which makes it possible to predict with high specificity the detection of the FOXO1 gene rearrangement.

Implementing the meta-analytic approach for the evaluation of surrogate endpoints in SAS and R: a word of caution.

The meta-analytic approach has become the gold-standard methodology for the evaluation of surrogate endpoints and several implementations are currently available in SAS and R. The methodology is based on hierarchical models that are numerically demanding and, when the amount of data is limited, maximum likelihood algorithms may not converge or may converge to an ill-conditioned maximum such as a boundary solution. This may produce misleading conclusions and have negative implications for the evaluation of new drugs. In the present work, we explore the use of two distinct functions in R (lme and lmer) and the MIXED procedure in SAS to assess the validity of putative surrogate endpoints in the meta-analytic framework, via simulations and the analysis of a real case study. We describe some problems found with the lmer function in R that led to a poorer performance as compared with the lme function and MIXED procedure.

Evaluation of longitudinal surrogate markers.

The use of surrogate markers to examine the effectiveness of a treatment has the potential to decrease study length and identify effective treatments more quickly. Most available methods to investigate the usefulness of a surrogate marker involve restrictive parametric assumptions and tend to focus on settings where the surrogate is measured at a single point in time. However, in many clinical settings, the potential surrogate marker is often measured repeatedly over time, and thus, the surrogate marker information is a trajectory of measurements. In addition, it is often difficult in practice to correctly specify the relationship between a treatment, primary outcome, and surrogate marker trajectory. In this paper, we propose a model-free definition for the proportion of the treatment effect on the primary outcome that is explained by the treatment effect on the longitudinal surrogate markers. We propose three novel flexible methods to estimate this proportion, develop the asymptotic properties of our estimators, and investigate the robustness of the estimators under multiple settings via a simulation study. We apply our proposed procedures to an AIDS clinical trial dataset to examine a trajectory of CD4 counts as a potential surrogate.

Identifying possible surrogate markers of COVID19 as a supplement to diagnostic testing in Upstate New York.

INTRODUCTION: COVID19 has raised concerns for resource allocation across various sectors of healthcare. At the frontlines, emergency departments are required to triage a wide range of acuity and non-specific symptomology. METHODS: This retrospective study aimed to pave the way for more concrete detection and triage of patients by analyzing symptomology, physical findings, diagnostic testing and relevant hospital course of the 458 suspected cases that initially presented to an academic level one trauma center emergency department between March and August 2020. A total of 202 COVID positive cases were analyzed. RESULTS: The most common symptoms were cough (70.63%), fatigue (77%), and shortness of breath (59%). There was a significantly higher percentage of abnormal chest imaging in inpatient groups compared to the ED discharge group (42.86% vs 79%, p < 0.01). Laboratory studies, especially markers of inflammation (CRP, ESR), markers of tissue damage (lactic acid, troponin), and markers of infection were markedly higher and above normal reference ranges in complicated cases (p < 0.01). While there is limited data on the sensitivity and specificity of the current nasopharyngeal PCR test, there was no permutation of symptoms, physical findings, diagnostic testing that was more sensitive than that of the current PCR test calculated at 66.1% in our cohort. CONCLUSION: Laboratory studies that otherwise are more commonly conducted inpatient, including markers of inflammation, tissue damage, and infection, may be useful in disposition planning of ED patients in conjunction with clinical correlation of presentation and chest imaging.

Chronic Obstructive Pulmonary Disease as a Predictor of Cardiovascular Risk: A Case-Control Study.

Chronic obstructive pulmonary disease (COPD) is a complex multi-morbid disorder with significant cardiac mortality. Current cardiovascular risk prediction models do not include COPD. We investigated whether COPD modifies future cardiovascular risk to determine if it should be considered in risk prediction models.Case-control study using baseline data from two randomized controlled trials performed between 2012 and 2015. Of the 90 eligible subjects, 26 COPD patients with lung hyperinflation were propensity matched for 10-year global cardiovascular risk score (QRISK2) with 26 controls having normal lung function. Patients underwent cardiac magnetic resonance imaging, arterial stiffness and lung function measurements. Differences in pulse wave velocity (PWV), total arterial compliance (TAC) and aortic distensibility were main outcome measures.PWV (mean difference 1.0 m/s, 95% CI 0.02-1.92; p = 0.033) and TAC (mean difference -0.27 mL/m2/mmHg, 95% CI 0.39-0.15; p < 0.001) were adversely affected in COPD compared to the control group. The PWV difference equates to an age, sex and risk-factor adjusted increase in relative risk of cardiovascular events and mortality of 14% and 15%, respectively.There were no differences in aortic distensibility. In the whole cohort (n = 90) QRISK2 (ß = 0.045, p = 0.005) was associated with PWV in multivariate analysis. The relationship between QRISK2 and PWV were modified by COPD, where the interaction term reached significance (p = 0.014). FEV1 (ß = 0.055 (0.027), p = 0.041) and pulse (B = -0.006 (0.002), p = 0.003) were associated with TAC in multivariate analysis.Markers of cardiovascular outcomes are adversely affected in COPD patients with lung hyperinflation compared to controls matched for global cardiovascular risk. Cardiovascular risk algorithms may benefit from the addition of a COPD variable to improve risk prediction and guide management.HAPPY London ClinicalTrials.gov: NCT01911910 and HZC116601; ClinicalTrials.gov: NCT01691885.

Comparison of treatment effect sizes from pivotal and postapproval trials of novel therapeutics approved by the FDA based on surrogate markers of disease: a meta-epidemiological study.

BACKGROUND: The U.S. Food and Drug Administration (FDA) often approves new drugs based on trials that use surrogate markers for endpoints, which involve certain trade-offs and may risk making erroneous inferences about the medical product's actual clinical effect. This study aims to compare the treatment effects among pivotal trials supporting FDA approval of novel therapeutics based on surrogate markers of disease with those observed among postapproval trials for the same indication. METHODS: We searched Drugs@FDA and PubMed to identify published randomized superiority design pivotal trials for all novel drugs initially approved by the FDA between 2005 and 2012 based on surrogate markers as primary endpoints and published postapproval trials using the same surrogate markers or patient-relevant outcomes as endpoints. Summary ratio of odds ratios (RORs) and difference between standardized mean differences (dSMDs) were used to quantify the average difference in treatment effects between pivotal and matched postapproval trials. RESULTS: Between 2005 and 2012, the FDA approved 88 novel drugs for 90 indications based on one or multiple pivotal trials using surrogate markers of disease. Of these, 27 novel drugs for 27 indications were approved based on pivotal trials using surrogate markers as primary endpoints that could be matched to at least one postapproval trial, for a total of 43 matches. For nine (75.0%) of the 12 matches using the same non-continuous surrogate markers as trial endpoints, pivotal trials had larger treatment effects than postapproval trials. On average, treatment effects were 50% higher (more beneficial) in the pivotal than the postapproval trials (ROR 1.5; 95% confidence interval CI 1.01-2.23). For 17 (54.8%) of the 31 matches using the same continuous surrogate markers as trial endpoints, pivotal trials had larger treatment effects than the postapproval trials. On average, there was no difference in treatment effects between pivotal and postapproval trials (dSMDs 0.01; 95% CI -0.15-0.16). CONCLUSIONS: Many postapproval drug trials are not directly comparable to previously published pivotal trials, particularly with respect to endpoint selection. Although treatment effects from pivotal trials supporting FDA approval of novel therapeutics based on non-continuous surrogate markers of disease are often larger than those observed among postapproval trials using surrogate markers as trial endpoints, there is no evidence of difference between pivotal and postapproval trials using continuous surrogate markers.

The role of magnetic resonance imaging and endoscopic retrograde cholangiography in the evaluation of disease activity and severity in primary sclerosing cholangitis.

BACKGROUND & AIMS: Endoscopic retrograde cholangiography (ERCP) has been considered the gold standard for the diagnosis and follow-up of primary sclerosing cholangitis, but it has been replaced by less invasive magnetic resonance imaging and cholangiopancreatography (MRI-MRCP). However, the role of these two techniques in the evaluation of disease activity and severity needs to be elucidated. METHODS: Patients with primary sclerosing cholangitis (n: 48, male 31, median age: 35.7; 28.0-44.2) who underwent ERCP and MRI-MRCP within ±3 months for diagnosis or follow-up, were reviewed. ERCP and MRI-MRCP images were scored using the modified Amsterdam score. Serum and biliary cytology markers of disease activity and severity were related to the imaging findings. Agreement on the assessment of the ERCP/MRCP score was calculated by kappa-statistics. Spearman's ρ was calculated when appropriate. RESULTS: The agreement between ERCP and MRCP in scoring bile duct changes for disease severity was only moderate (weighted kappa: 0.437; 95% CI: 0.211-0.644 for intra- and 0.512; 95% CI: 0.303-0.720 for extra-hepatic bile ducts). ERCP and MRCP intra-hepatic scores were associated to the surrogate marker alkaline phosphatase (P = .02 for both). A weak correlation between MRCP score for extra-hepatic bile ducts and liver transplantation/death was found (Spearman's ρ = .362, 95% CI: 0.080-0.590, P = .022). A weak correlation between intra- (Spearman's ρ = .322, 95% CI: 0.048-0.551, P = .022) and extra-hepatic (Spearman`s ρ = .319, 95% CI: 0.045-0.549, P = .025) peribiliary enhancement on contrast-enhanced MRI and severity of biliary cytologic classification was found. CONCLUSIONS: The overall agreement between ERCP and MRI-MRCP in assessing disease severity was moderate for intra- and extra-hepatic bile ducts. MRI-MRCP seems to have a minor role as surrogate marker of disease activity and progression in PSC.

Biomarker research to improve clinical outcomes of peritoneal dialysis: consensus of the European Training and Research in Peritoneal Dialysis (EuTRiPD) network.

Peritoneal dialysis (PD) therapy substantially requires biomarkers as tools to identify patients who are at the highest risk for PD-related complications and to guide personalized interventions that may improve clinical outcome in the individual patient. In this consensus article, members of the European Training and Research in Peritoneal Dialysis Network (EuTRiPD) review the current status of biomarker research in PD and suggest a selection of biomarkers that can be relevant to the care of PD patients and that are directly accessible in PD effluents. Currently used biomarkers such as interleukin-6, interleukin-8, ex vivo-stimulated interleukin-6 release, cancer antigen-125, and advanced oxidation protein products that were collected through a Delphi procedure were first triaged for inclusion as surrogate endpoints in a clinical trial. Next, novel biomarkers were selected as promising candidates for proof-of-concept studies and were differentiated into inflammation signatures (including interleukin-17, M1/M2 macrophages, and regulatory T cell/T helper 17), mesothelial-to-mesenchymal transition signatures (including microRNA-21 and microRNA-31), and signatures for senescence and inadequate cellular stress responses. Finally, the need for defining pathogen-specific immune fingerprints and phenotype-associated molecular signatures utilizing effluents from the clinical cohorts of PD patients and "omics" technologies and bioinformatics-biostatistics in future joint-research efforts was expressed. Biomarker research in PD offers the potential to develop valuable tools for improving patient management. However, for all biomarkers discussed in this consensus article, the association of biological rationales with relevant clinical outcomes remains to be rigorously validated in adequately powered, prospective, independent clinical studies.

Links between causal effects and causal association for surrogacy evaluation in a gaussian setting.

Two paradigms for the evaluation of surrogate markers in randomized clinical trials have been proposed: the causal effects paradigm and the causal association paradigm. Each of these paradigms rely on assumptions that must be made to proceed with estimation and to validate a candidate surrogate marker (S) for the true outcome of interest (T). We consider the setting in which S and T are Gaussian and are generated from structural models that include an unobserved confounder. Under the assumed structural models, we relate the quantities used to evaluate surrogacy within both the causal effects and causal association frameworks. We review some of the common assumptions made to aid in estimating these quantities and show that assumptions made within one framework can imply strong assumptions within the alternative framework. We demonstrate that there is a similarity, but not exact correspondence between the quantities used to evaluate surrogacy within each framework, and show that the conditions for identifiability of the surrogacy parameters are different from the conditions, which lead to a correspondence of these quantities.

Invited Commentary: Troubling Trends in Birth Weight.

Birth weight is a strong predictor of the health of newborns. Consequently, the report by Catov et al. in this issue of the Journal (Am J Epidemiol. 2016;183(1):15-23), in which they showed downward trends in birth weights in a Pittsburgh, Pennsylvania, hospital from 1997 to 2011, raises concerns. The widening gap reported between birth weights of babies born to white and African-American women could correspond to a widening gap in actual health outcomes. However, if the relation between birth weight and health outcomes is not causal, these trends may be epiphenomena of limited concern.

Comparing biomarkers as trial level general surrogates.

An intermediate response measure that accurately predicts efficacy in a new setting can reduce trial cost and time to product licensure. In this article, we define a trial level general surrogate, which is an intermediate response that can be used to accurately predict efficacy in a new setting. Methods for evaluating general surrogates have been developed previously. Many methods in the literature use trial level intermediate responses for prediction. However, all existing methods focus on surrogate evaluation and prediction in new settings, rather than comparison of candidate general surrogates, and few formalize the use of cross validation to quantify the expected prediction error. Our proposed method uses Bayesian non-parametric modeling and cross-validation to estimate the absolute prediction error for use in evaluating and comparing candidate trial level general surrogates. Simulations show that our method performs well across a variety of scenarios. We use our method to evaluate and to compare candidate trial level general surrogates in several multi-national trials of a pentavalent rotavirus vaccine. We identify at least one immune measure that has potential value as a trial level general surrogate and use it to predict efficacy in a new trial where the clinical outcome was not measured.

Exploring the relationship between the causal-inference and meta-analytic paradigms for the evaluation of surrogate endpoints.

Nowadays, two main frameworks for the evaluation of surrogate endpoints, based on causal-inference and meta-analysis, dominate the scene. Earlier work showed that the metrics of surrogacy introduced in both paradigms are related, although in a complex way that is difficult to study analytically. In the present work, this relationship is further examined using simulations and the analysis of a case study. The results indicate that the extent to which both paradigms lead to similar conclusions regarding the validity of the surrogate, depends on a complex interplay between multiple factors like the ratio of the between and within trial variability and the unidentifiable correlations between the potential outcomes. All the analyses were carried out using the newly developed R package Surrogate, which is freely available via CRAN.

Markers for silent atrial fibrillation in esophageal long-term electrocardiography.

PURPOSE: Paroxysmal atrial fibrillation (PAF) often remains undiagnosed. Long-term surface ECG is used for screening, but has limitations. Esophageal ECG (eECG) allows recording high quality atrial signals, which were used to identify markers for PAF. METHODS: In 50 patients (25 patients with PAF; 25 controls) an eECG and surface ECG was recorded simultaneously. Partially A-V blocked atrial runs (PBARs) were quantified, atrial signal duration in eECG was measured. RESULTS: eECG revealed 1.8‰ of atrial premature beats in patients with known PAF to be PBARs with a median duration of 853ms (interquartile range (IQR) 813-1836ms) and a median atrial cycle length of 366ms (IQR 282-432ms). Even during a short recording duration of 2.1h (IQR 1.2-17.2h), PBARs occurred in 20% of PAF patients but not in controls (p=0.05). Left atrial signal duration was predictive for PAF (72% sensitivity, 80% specificity). CONCLUSIONS: eECG reveals partially blocked atrial runs and prolonged left atrial signal duration - two novel surrogate markers for PAF.

[New paradigms and metaphors in cutaneous melanoma treatment]. / Nouveaux paradigmes et métaphores du traitement du mélanome cutané.

In recent years, new drugs have been designed for treating advanced cutaneous malignant melanoma, in particular the metastases. They afford modest benefits despite the fact they are commonly heralded as breakthroughs in the lay press and by some medical opinion leaders. Unfortunately, the use of inflated descriptors of the drug efficacy leads to misunderstandings among the clinicians in charge of patients. Currently, vemurafenib, ipilimumab, pembrolizumab and nivolumab have demonstrated their relative activity in the control of advanced malignant melanoma. The results expected from surrogate markers of efficacy are magnified and idealized regarding the expectations from many patients. The recent therapeutic advance improves the median overall survival for a few months. Some combined treatments could possibly boost the current beneficial effects.

Au cours des récentes années, de nouveaux médicaments ont été offerts pour le traitement du mélanome cutané avancé et, en particulier, de ses métastases. Ils apportent des bénéfices qualifiés de modestes par certains malgré leur présentation en tant qu'innovations par divers médias et par quelques médecins et biologistes élevés au rang de leaders d'opinion. Malheureusement, l'emploi de descripteurs inflationnistes de l'efficacité des médicaments entraîne certaines incompréhensions parmi les cliniciens en charge de ces patients. A ce jour, le vémurafénib, l'ipilimumab, le pembrolizumab et le nivolumab ont démontré leurs activités relatives dans le contrôle du mélanome avancé. Le bénéfice escompté par certains marqueurs de substitution de l'efficacité est magnifié et idéalisé par rapport aux attentes de beaucoup de patients. Les avancées thérapeutiques récentes procurent un accroissement de quelques mois à la survie médiane. Des traitements combinés pourraient améliorer le bénéfice dès à présent atteint.

Echo response and clinical outcome in CRT patients.

BACKGROUND: Change in left ventricular end-systolic volume (∆LVESV) is the most frequently used surrogate marker in measuring response to cardiac resynchronisation therapy (CRT). We investigated whether ∆LVESV is the best measure to discriminate between a favourable and unfavourable outcome and whether this is equally applicable to non-ischaemic and ischaemic cardiomyopathy. METHODS: 205 CRT patients (age 65 ± 12 years, 69 % men) were included. At baseline and 6 months echocardiographic studies, exercise testing and laboratory measurements were performed. CRT response was assessed by: ∆LVESV, ∆LV ejection fraction (LVEF), ∆ interventricular mechanical delay, ∆VO2 peak, ∆VE/VCO2, ∆BNP, ∆creatinine, ∆NYHA, and ∆QRS. These were correlated to the occurrence of major adverse cardiac events (MACE) between 6 and 24 months. RESULTS: MACE occurred in 19 % of the patients (non-ischaemic: 13 %, ischaemic: 24 %). ∆LVESV remained the only surrogate marker for CRT response for the total population and patients with non-ischaemic cardiomyopathy, showing areas under the curve (AUC) of 0.69 and 0.850, respectively. For ischaemic cardiomyopathy, ∆BNP was the best surrogate marker showing an AUC of 0.66. CONCLUSION: ∆LVESV is an excellent surrogate marker measuring CRT response concerning long-term outcome for non-ischaemic cardiomyopathy. ∆LVESV is not suitable for ischaemic cardiomyopathy in which measuring CRT response remains difficult.

Multipronged quantitative proteomic analyses indicate modulation of various signal transduction pathways in human meningiomas.

Meningiomas (MGs) are frequent tumors of the CNS originating from the meningeal layers of the spinal cord and the brain. In this study, comparative tissue proteomic analysis of low and high grades of MGs was performed by using iTRAQ-based quantitative proteomics in combination with ESI-quadrupole-TOF and Q-Exactive MS, and results were validated by employing ELISA. Combining the results obtained from two MS platforms, we were able to identify overall 4308 proteins (1% false discover rate), among which 2367 exhibited differential expression (more than and equal to 2 peptide and ≥ 1.5-fold in at least one grade) in MGs. Several differentially expressed proteins were found to be associated with diverse signaling pathways, including integrin, Wnt, Ras, epidermal growth factor receptor, and FGR signaling. Proteins, such as vinculin or histones, which act as the signaling activators to initiate multiple signaling pathways, were found to be upregulated in MGs. Quite a few candidates, such as protein S-100A6, aldehyde dehydrogenase mitochondrial, AHNAK, cytoskeleton-associated protein 4, and caveolin, showed sequential increase in low- and high-grade MGs, whereas differential expressions of collagen alpha-1 (VI), protein S100-A9, 14 kDa phosphohistidine phosphatase, or transgelin-2 were found to be grade specific. Our findings provide new insights regarding the association of various signal transduction pathways in MG pathogenesis and may introduce new opportunities for the early detection and prognosis of MGs.