A Systematic Review of the Efficacy and Safety of Tenecteplase Versus Streptokinase in the Management of Myocardial Infarction in Developing Countries.

Myocardial infarction (MI) is a significant cause of morbidity and mortality in low- and middle-income countries. Fibrinolytic agents and percutaneous coronary intervention (PCI) are the main approaches for the recanalization and reperfusion of the myocardium following MI. Many studies have shown that PCI is superior to thrombolytics due to better outcomes and decreased mortality. Nevertheless, PCI's mortality gain over thrombolysis decreases as the time between presentation and PCI procedure increases. Furthermore, PCI is not widely available in most developing countries; thus, it cannot be delivered promptly. Most patients in developing countries cannot afford the cost of PCI. Thus, thrombolytic therapy remains essential to managing MI in developing countries and should not be disregarded. Tenecteplase (TNK) and streptokinase (SK) are the two most widely used fibrinolytics in managing MI in underdeveloped nations. Despite their widespread availability, comparative studies on them have been inconclusive. This study aims to review the available literature on the effectiveness and safety of TNK versus SK in managing MI in resource-poor nations. The study is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) extension and analyzed according to Cochrane guidelines on synthesis without meta-analysis. A comprehensive literature search for studies comparing TNK and STK was conducted on EMBASE, Cochrane Library, Web of Science, CINAHL, Scopus, Google Scholar, and Ovid version of MEDLINE databases. A reference list of the eligible articles and systematic reviews was also screened. A narrative synthesis of the available data was done by representing the data on the effect direction plot, followed by vote counting. Of the 2284 references retrieved from the databases, only 17 studies met the inclusion criteria and were selected for final analysis. The study suggested that TNK is more effective in complete ST-segment resolution (80% vs 10% on the effect direction plot) and symptom relief (80% vs 20%) than SK. SK and TNK were comparable in achieving successful fibrinolysis (50% vs 50%). For the safety parameters, TNK is associated with a lesser risk of major bleeding than SK (88.9% vs 11.1%) and minor bleeding (25% vs 75%). SK was linked with a higher risk of hypotension/shock (77.8% vs 11.1%) and anaphylaxis/allergy (100% vs 0%). Long-term mortality was higher in the SK arm (100% vs 0%). In-hospital mortality is comparable between the two agents (37.5% vs 37.5%). There is conflicting evidence regarding other safety and efficacy endpoints. Compared to SK, TNK results in better complete ST-segment resolution and symptom relief. A higher risk of long-term mortality, increased risk of major and minor bleeding, hypotension, and allergy/anaphylaxis was observed in patients who received SK. Both agents were comparable in terms of in-hospital mortality and successful fibrinolysis. Controversy exists regarding which agent is linked with increased risk of 30-35-day mortality benefit and stroke. Randomized controlled trials (RCTs) with large sample sizes are needed to establish TNK vs SK superiority in efficacy and safety. The long-term duration of follow-up of the mortality rate of the two agents is also essential, as most patients in these regions cannot afford the recommended PCI post-fibrinolysis.

Overview of MicroRNA Expression in Predicting Response to Neoadjuvant Therapies in Human Epidermal Growth Receptor-2 Enriched Breast Cancer - A Systematic Review.

Purpose: Increased appreciation of the human epidermal growth factor receptor-2 (HER2/neu) signalling pathway has led to the development of targeted therapeutic agents used in conjunction with chemotherapy to improve outcomes for HER2 overexpressing (HER2+) breast cancer. For neoadjuvant therapy, response rates can be unpredictable - novel biomarkers predicting effectiveness are required to enhance oncological outcomes for these patients, and microRNA may prove effective. Our objective was to identify microRNA (miRNA) expression patterns predictive of response to neoadjuvant chemotherapy (NAC) and/or anti-HER2 targeted therapies in patients being treated for early-stage HER2+ breast cancer. Methods: A search was performed of the PUBMED, SCOPUS, Web of Science, and EMBASE in accordance to Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Results: Overall, 15 studies including 1335 patients were included. These studies highlighted an expression profile of 73 miRNA and their ability to predict tumour response to neoadjuvant therapies was correlated. Results from 11 studies were in relation to circulatory miRNA and 4 studies included data from tumour tissue. Overall, upregulation and downregulation of 41 miRNA and 29 miRNA, respectively, predicted differential response to neoadjuvant therapy. Expression levels of 3 miRNA (miR-21, miR-210, and miR-376c-3p) were inconclusive in predicting therapeutic response, while 'aberrant' expression of circulating miR-199a predicted pathological complete response (pCR) to NAC. Conclusions: This systematic review outlines expression patterns of a number of miRNA which correlate with response to NAC and/or anti-HER2 therapies. Future translational research evaluating predictive biomarkers of primary response to neoadjuvant therapy in HER2+ breast cancer may consider these results.

Clinicopathological response to neoadjuvant therapies and pathological complete response as a biomarker of survival in human epidermal growth factor receptor-2 enriched breast cancer - A retrospective cohort study.

BACKGROUND: Human epidermal growth factor receptor-2 (HER2) is overexpressed in 20-25% of breast cancers. Complete eradication of disease following neoadjuvant therapies and chemotherapy has been referred to as pathological complete response (pCR). AIMS: To determine clinicopathological predictors of pCR to neoadjuvant therapies and to evaluate pCR as a surrogate to enhanced survival. METHODS: Consecutive female patients with HER2 positive (HER+) breast cancer managed surgically in a single institution between 2005 and 2015 were included. Descriptive statistics and binary logistic regression were used to determine predictors of pCR. Appraisal of pCR as a predictor of survival was performed using Kaplan-Meier curves and Cox regression analysis. RESULTS: 451 patients were included with a mean age of 56.6 ± 13.4 years (range 23-95). Disease-free (DFS) and overall survival (OS) was 82.3% (371/451) and 82.6% (376/451) respectively with a median follow-up of 108.0 months (range 3-184.0). 118 were treated in the neoadjuvant setting (26.2%): tumour size <50 mm (Odds Ratio (OR): 12.156, P = 0.023) and progesterone receptor negativity (OR: 2.762, P = 0.008) independently predicted breast pCR, while ductal carcinoma (OR: 3.203, P = 0.030) and grade 3 disease (OR: 2.788, P = 0.018) predicted axillary pCR. Both breast and axillary pCR predicted enhanced DFS (Hazard Ratio (HR): 0.470 & HR: 0.449) and OS (HR: 0.383 & HR: 0.307). Axillary pCR independently predicted improved OS (HR: 0.326). CONCLUSION: pCR is sensitive biomarker and surrogate to survival outcomes in HER2+ breast cancer. Patients likely to achieve pCR may be predicted from traditional clinicopathological characteristics and molecular parameters.

A comparison of methods to generate adaptive reference ranges in longitudinal monitoring.

In a clinical setting, biomarkers are typically measured and evaluated as biological indicators of a physiological state. Population based reference ranges, known as 'static' or 'normal' reference ranges, are often used as a tool to classify a biomarker value for an individual as typical or atypical. However, these ranges may not be informative to a particular individual when considering changes in a biomarker over time since each observation is assessed in isolation and against the same reference limits. To allow early detection of unusual physiological changes, adaptation of static reference ranges is required that incorporates within-individual variability of biomarkers arising from longitudinal monitoring in addition to between-individual variability. To overcome this issue, methods for generating individualised reference ranges are proposed within a Bayesian framework which adapts successively whenever a new measurement is recorded for the individual. This new Bayesian approach also allows the within-individual variability to differ for each individual, compared to other less flexible approaches. However, the Bayesian approach usually comes with a high computational cost, especially for individuals with a large number of observations, that diminishes its applicability. This difficulty suggests that a computational approximation may be required. Thus, methods for generating individualised adaptive ranges by the use of a time-efficient approximate Expectation-Maximisation (EM) algorithm will be presented which relies only on a few sufficient statistics at the individual level.