0113 203 7111       07801 443247

kim@kcstats.co.uk

PRO Consultancy

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Kim has worked in the PRO field for her whole career and has developed the specialist skills required to appropriately design and analyse studies to fully utilise this essential patient experience. She has published widely in the field and consults with a number of pharmaceutical companies in this area.

From Sept 2015 Kim has taken on a new role working part-time with Adelphi Values as a Director and Principal Statistician in the Endpoint Development and Outcomes Assessment team. A greater range of services can now be provided to include full analysis of clinical trial PRO data as well as statistical advice for the design and analysis. Please contact us for more information.

Kim was successfully awarded a UICC ICRETT fellowship for her PhD to visit the University of Technology Sydney. These fellowships from the Union for International Cancer Control are aimed at facilitating rapid international transfer of cancer research and clinical technology, exchange knowledge and enhance skills in basic, clinical, behavioural and epidemiological areas of cancer research cancer control and prevention. Her PhD published interpretation guidelines for one of the most commonly used cancer QOL instruments, the EORTC QLQ-C30.

The inclusion of PRO measures in clinical trials can be expensive and adds to the burden for the patients participating in a clinical trial. Therefore it is key that the most appropriate measure is selected (or developed if needed) for the trial, it is implemented at appropriate intervals and it is then analysed correctly. PRO data tends to be messy; it is repeatedly measured over time and patients may drop out when their quality of life is getting worse and they become too ill to complete the measure or, vice versa, if they leave a study when they are feeling better. If we ignore these reasons for dropout when we analyse the data then we may have a biased view of the real quality of life experienced. Statistical methods to deal with the missing data appropriately are statistically complex. Therefore all too often this crucial part is overlooked and the data is analysed too simply to pick up the trends in quality of life and truly inform the results from the study. This is unethical from a patient perspective and limits the ability of PRO data to influence clinical decision making appropriately.