Measuring Cancer Patient Survival: Methodology Matters

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Mar 04, 2014
from 05:30 PM to 06:30 PM


Ken Edwards Building, Lecture Theatre 1

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0116 252 2320

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Professor Paul Lambert 

Department of Health Sciences

Lecture Summary

Estimation of cancer patient survival using population-based registry data is vital in evaluating progress against cancer. Comparison of cancer survival between different population groups can be distorted for various reasons; for example differences in population structure, differences in mortality due to other causes, differences in exposure to other risk factors, and by differences in the way data is collected. It is vital that these differences are controlled for to ensure that any comparisons are “fair”.

My research is based around the development and application of statistical methods to make better use of data from population-based cancer studies. Underpinning my work is the development of statistical models that help to quantify differences between population groups. The use of appropriate statistical methods can lead to better understanding of cancer patient survival at both a population and an individual level. Even though the statistical methods may be complex, it is a key role of the statistician to present the results of the analysis in ways that are relevant to the different “consumers” of the statistics. For example, the needs of someone responsible for planning future cancer services are very different to those of a patient recently diagnosed with cancer. I will explain how the methods we have developed can give a greater insight to cancer survival than traditional methods through a number of examples of my research over the past decade.



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