Power survival data

The power of a study where the primary endpoint is time-to-event depends not so much on the total patient numbers, but on the number of events. So a trial with 1000 patients with 100 deaths has the same power as a trial with only 200 patients, but with also 100 deaths. The sample size calculation for survival data is therefore done in two stages. Firstly, the required number of patients suffering events is... 

Power calculations for survival data are more complex due to the nature of the analyses as well as factors that are involved in the accrual of participants (i.e., follow-up time, prevalence of risk factor, etc.). The following example is based on the method discussed by Simon and Altman (41) using an 18-month overall survival rate of 40%, two-sided alpha level of 5%, and no attrition for varying levels of risk factor prevalence and hazard ratios. 

As discussed earlier, the historical meta-survival data can be partially borrowed through the two common parameters Yq and under the random effects model but through only one common parameter Yo under the fixed effects model. This implies that under the same value of ag, that is, the same amount of incorporation of the historical meta-survival data, the power is higher under the random effects model than under the fixed effects model. On the other hand, the design value of Yo in the current metatrial is more comparable to the value of Yo in the historical meta-data under the fixed effects model than under the random effects model, which explains why more historical meta-survival data can be allowed to be borrowed under the fixed effects model than the random effects model. From Figure 2.1, it is interesting to see that (1) both the power and type I error... 

Negative results on mortality from bladder cancer might be caused by limited power due to high survival from this disease. Therefore, differences between results of analyses based on mortality and morbidity data might reflect the lower sensitivity of the former.]... 

At least one well-conducted study must show reproductive or developmental toxicity in a mammalian species. When the study data are insufficient, improper study design or execution, inadequate doses or duration of exposure, poor survival, or too few animals to achieve statistical power are often the cause. At present, no nonmammalian or in vitro systems are considered to be predictive of human responses, and are not accepted by... 

Orthopedics has recognized the importance of measuring outcomes in terms of quality-adjusted life-years instead of length of implant survival.Similarly, pharmacy must implement software documentation solutions that facilitate outcomes monitoring beyond cost savings. Software is needed with the ability to calculate, in a cost-benefit analysis, the clinical impact of pharmacist interventions as they affect therapeutic, financial, and humanistic outcomes. The current array of products could be better integrated into documentation software to facilitate tabulation of these data. With the power of the Internet to manipulate data in a dynamic database, it would even be possible for hospitals to compare their outcomes on a local, regional, or national basis. Furthermore, the database could... 

The combination of direct excitation or cross-polarization NMR experiments with off-MAS sample spinning seems to be the most powerful approach for the study of rotational diffusion of all system constituents. It allows for a chemical identification of all organic system components and simultaneously yields data on their rotational diffusion. Hence, for detailed studies on particle tumbling in complex systems, it represents the preferred experimental condition for all particle dispersions which are stable enough to survive the inertial field during sample spinning for an adequate period of time. ... 

This is of course a specific instance of the iterative process we associate with the scientific method. The postulated mechanisms surviving this process can be considered consistent with the experimental data. Kinetics provides a powerful method for eliminating putative reaction mechanisms, but kinetic methods alone can never establish a mechanism unambiguously. Other chemical and physical methods can be of help in this regard, but it must be acknowledged that all our models, at some level, are tentative and subject to revision. In practice, one must accept a certain amount of ambiguity, but for many, if not most, applications this is not crucial. 

In stable, medically-treated patients with confirmed CAD, Iskandrian et al. (32) found that the extent of perfusion defect conveyed incremental and independent prognostic information above clinical, exercise, and catheterization data combined. Event-free survival over a period of 28 15 months was 95% in those with a defect <15% of the myocardium versus 75% for those with a >15% defect (P <0.001). Interestingly, combining gender, clinical, and SPECT data appeared to provide equivalent predictive power (chi-square statistic) regardless of whether or not catheterization data was added. As expected, an exercise capacity of >6 METs, an ejection fraction of >50%, and a lesser extent of CAD were all also associated with improved survival. 

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