Treatment effects/differences survival data

Each trial that is to be included in the meta-analysis will provide a measure of treatment effect (difference). For continuous data this could be the mean response on the active treatment minus the mean response in the placebo arm. Alternatively, for binary data the treatment effect could be captured by the difference in the cure rates, for example, or by the odds ratio. For survival data, the hazard ratio would often be the measure of treatment difference, but equally well it could be the difference in the two-year survival rates. 

In an elegant paper, Gerdes et al. [59] examined whether the risk of death or a major coronary event in survivors of myocardial infarction (MI) was related to the apo E genotype and whether risk reduction brought about by simvastatin was different between genotypes. They analyzed 5.5 years of follow-up data of 966 Danish and Finish myocardial infarction survivors enrolled in the Scandinavian Simvastatin Survival Study and found that MI survivors with the apo E4 allele have a nearly 2-fold increased risk of death, and that treatment with simvastatin abolished excess mortality. They concluded that the effect of apo E4 may involve mechanisms unrelated to serum lipoproteins because... 

This determination requires an examination of both an old and a new line of cases. In the new line of cases, plaintiffs have argued—in the therapeutic context—that health care providers have a duty to provide comparative data about the effectiveness not only of various treatment alternatives, but also about the qualifications, competence, and experience of the provider. In the one case in which plaintiffs have so far succeeded in surviving a motion to dismiss, the Wisconsin Supreme Court held that a neurosurgeon had a duty to disclose his level of experience with a procedure and the morbidity and mortality differences between himself and more experienced neurosurgeons (Johnson v. Kokemoor, 1996). The Wisconsin court s ruling has been labeled the "second revolution" of the informed consent doctrine (Twerski and Cohen, 1999 Ketler, 2001). 

A statistical technique used to test the significance of differences between the survival curves associated with two different treatments. It is often used to analyze survival (life vs. death) data when there are censored observations (observations that are unknown because a subject has not been in the study long enough for the outcome to be observed) or to analyze the effects of different treatment procedures. ... 

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