Contrasting the Effect of Ramipril on the Time to Combinations of Various Heart Events Including Death in Patients With Acute Myocardial Infarction (Using AIRE Study Data)

Ghaffari, Jilla (1996) Contrasting the Effect of Ramipril on the Time to Combinations of Various Heart Events Including Death in Patients With Acute Myocardial Infarction (Using AIRE Study Data). MSc(R) thesis, University of Glasgow.

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This research is designed to study the effect of the Ramipril on different 'survival times' of survivors of acute myocardial infarction with heart failure. These different survival times, correspond to different defined end points. The data which is used in this research was gathered under the AIRE study. The AIRE Study tested the hypothesis that patients with acute myocardial infarction complicated by clinical evidence of heart failure would live longer if they received long-term ramipril treatment, initiated between the second and ninth days after infarction. The AIRE study was a multicentre, multinational, double-blind, randomised, placebo-controlled study. 2006 patients with acute myocardial infarction and clinical evidence of heart failure were recruited in 144 centres in 14 countries. The start date of the AIRE study was 7 April 1989 and the end date was 28 February 1993. All patients aged at least 18 years admitted to coronary care, intensive care, or general medical units with a definite AMI and clinical evidence of heart failure, were potentially eligible. The study found that Ramipril had a significant effect on time to death. The study also had a secondary endpoint namely a validated re infarction which was a rigorously defined endpoint(see later). The conclusion was that the drug had no effect on time to this endpoint. It is the purpose of this thesis to explore the consistency of these conclusions across a variety of further endpoints since studies on other drugs have exhibited different conclusions for various but similar endpoints. So in this research a variety of 'survival' times were considered for each patient for a variety of endpoints. In particular the following adverse events were considered; time to 'death', 'first re infarction after treatment' and 'first stroke after treatment'. Then, in later stages, we tried to combine or to change the definition of the end event. An example of these changes, is to define an adverse event to be 'either sudden death or first re infarction or chest pain'. A complete list of end points are presented in chapter 4-1. The time origin for all survival times is the same and that is the date of registration which identifies the time when a patient has been entered in to the study. In chapter 1 we outline background information. In chapter 2 we introduce survival models and some of their key aspects. Then we introduce the various types of these models including hazard models and the Cox proportional hazards model in particular. In chapter 3 the Kaplan-Meier approach was used to estimate the survival curves of those patients who were treated by Ramipril and those who were treated by the placebo. These survival curves were estimated for different adverse events and for each adverse event, the survival curve of the patients treated by Ramipril and the survival curve corresponding to those who were treated by the placebo, were compared using the Generalised Savage (Manted_Cox) test statistic. These analyses and tests were performed by using the BMDP program IL. In chapter 4 we fit 12 different Cox Proportional Models (2 for each endpoint) to the various end points. Six models (one for each endpoint) included a single covariate, namely: "Treatment". These potentially offer a simple comparison between the effects of Ramipril and of the Placebo. In fact all these models, except one of them fitted well. The proportionality of hazards assumption corresponding to most endpoints, was valid. This makes it easier to believe that the results of these models are reliable. All these well fitting models suggest that Ramipril increases the corresponding 'survival' time.

Item Type: Thesis (MSc(R))
Qualification Level: Masters
Additional Information: Adviser: Ben Torsney
Keywords: Biostatistics, Pharmaceutical sciences
Date of Award: 1996
Depositing User: Enlighten Team
Unique ID: glathesis:1996-76443
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 19 Nov 2019 14:20
Last Modified: 19 Nov 2019 14:20

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