Tenecteplase and alteplase in acute ischaemic stroke thrombolysis: clinical and imaging study

Introduction: Intravenous thrombolysis in acute ischaemic stroke with alteplase improves clinical outcomes, but it has limited efficacy and is associated with increased risk of intracranial haemorrhage. An improved tissue plasminogen activator, tenecteplase, was evidenced to be at least equally effective with lower risk of haemorrhage in acute myocardial infarction thrombolysis. To date, two completed phase II randomised controlled studies comparing tenecteplase and alteplase in acute ischaemic strokes showed variable results. Methods: A literature review of thrombolytic agents used in myocardial infarction and acute ischaemic stroke was performed, followed by a retrospective investigation of the bolus-to- infusion delay of alteplase administration. The main focus of this thesis is the report of our single centre phase II randomised controlled trial that compared tenecteplase (0.25mg/kg, maximum 25mg) and alteplase (0.9mg/kg, maximum 90mg, 10% as the initial bolus, following by one hour infusion with the rest of the dose) in acute ischaemic stroke thrombolysis using advanced imaging as biomarkers. Imaging comprised baseline computed tomography (CT), CT perfusion (CTP) and CT angiography (CTA), and CT+CTA at 24-48 hours. The primary end-point was penumbral salvage (CTP-defined penumbra volume minus follow-up CT infarct volume). A sub-study of coagulation and fibrinolysis analysis of the two agents was performed by comparing a group of coagulation variables measured pre-treatment, 3-12 hours, and 24±3 hours post thrombolysis. An individual patient data (IPD) meta-analysis was carried out using all three completed tenecteplase/alteplase comparison studies in stroke thrombolysis. We compared clinical outcomes including modified Rankin scale at 3 months, early neurological improvement at 24 hours, intracerebral haemorrhage rate and mortality at 3 months between all three tenecteplase doses (0.1mg/kg, 0.25 mg/kg, and 0.4mg/kg) examined and standard alteplase. Imaging outcomes including penumbra salvage, recanalisation rates were also compared using the data from the two studies that had advance imaging carried out. Results: Delay between the initial bolus and the subsequent infusion in administration of alteplase is common. This may reduce the likelihood of achieving a good functional outcome. Among the 104 patients recruited in ATTEST trial, 71 contributed to the imaging primary outcome. No significant differences were observed for penumbral salvage [68 (SD 28) % tenecteplase vs 68 (SD 23) % alteplase], mean difference 1% (95% confidence interval -10%, 12%, p=0·81) or for any secondary end-point. The SICH incidence (1/52, 2% vs 2/51, 4%, by SITS-MOST definition, p=0·55; by ECASS-2 definition, 3/52, 6% tenecteplase vs 4/51, 8% alteplase, p=0.59) did not differed significantly. There was a trend towards lower ICH risk in the tenecteplase group (8/52 tenecteplase, 15% vs 14/51 alteplase, 29%, p=0·091). Compared to baseline, alteplase caused significant hypofibrinogenaemia (p=0.002), prolonged Prothrombin Time (PT) (p=0.011), hypoplasminogenaemia (p=0.001) and lower Factor V (p=0.002) at 3-12 hours after administration with persistent hypofibrinogenaemia at 24h (p=0.011), while only minor hypoplasminogenaemia (P=0.029) was seen in the tenecteplase group. Tenecteplase consumed less plasminogen (p<0.001) and fibrinogen (p=0.002) compared with alteplase. In a pooled analysis, tenecteplase 0.25mg/kg had the greatest odds to achieve early neurological improvement (OR [95%CI] 3.3 [1.5, 7.2], p=0.093), excellent functional outcome (mRS 0-1) at three months (OR [95%CI] 1.9 [0.8, 4.4], p= 0.28), with reduced odds of ICH (OR [95%CI] 0.6 [0.2, 1.8], P=0.43) compared with alteplase. Only 19 patients were treated with tenecteplase 0.4mg/kg, which showed increased odds of SICH compared with alteplase (OR [95% CI] 6.2 [0.7, 56.3]). In the two studies where advanced imaging was performed, the imaging outcomes did not differ in the IPD analysis. Conclusion: Tenecteplase 0.25 mg/kg has the potential to be a better alternative to alteplase. It can be given as a single bolus, does not cause disruption to systemic coagulation, and is possibly safer and more effective in clot lysis. Further phase III study to compare tenecteplase and alteplase in acute ischaemic stroke is warranted.

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.