Establishing the Evidence Bar for Molecular Diagnostics in Personalised Cancer Care.

While personalised cancer medicine holds great promise, targeting therapies to the biological characteristics of patients is limited by the number of validated biomarkers currently available. The implementation of biomarkers has undergone many challenges with few biomarkers reaching cancer patients in the clinic. There have been many biomarkers that have been published and claimed to be therapeutically useful, but few become part of the clinical decision-making process due to technical, validation and market access issues. To reduce this attrition rate, there is a significant need for policy makers and reimbursement agencies to define specific evidence requirements for the introduction of biomarkers into clinical practice. Once these requirements are more clearly defined, in an analogous manner to pharmaceuticals, researchers and diagnostic companies can better focus their biomarker research and development on meeting these specific requirements, which should lead to the more rapid introduction of new molecular oncology tests for patient benefit.

Computerised assessment of maximum urinary flow: an efficient, consistent and valid approach.

OBJECTIVES: To evaluate the relative accuracy of a computerised method to quantitatively assess maximum urinary flow. METHODS: A total of 1147 uroflows were evaluated by the computerised method and by three experts from different European countries. The sample consisted of uroflows from the respective visits by a 20% sample of randomly chosen patients (n = 223) with lower urinary tract symptoms with participation in two clinical trials in which the efficacy and safety of Permixon was evaluated. The proportions of automated maximum flow values included in the 10% extended range of experts (and their 95% confidence intervals) were assessed, as well as the concordance coefficients between experts and the computerised method and the paired Student's t-test for the average differences between experts and computer. RESULTS: The rate of agreement between experts and computer varied between about 95 and 100% over factor levels for visit, type of machine and country. Concordance coefficients indicated good agreement between experts and the automated method. When looking at average differences between experts and the computer, the smallest differences were observed between experts 2, 3 and the computer (differences not statistically significant). Statistically significant average differences were observed between expert 1 and the other experts as well as between expert 1 and the computer. CONCLUSIONS: The computerised assessment decreases the fraction of variability of maximum urinary flow caused by artifacts as well as intra- and inter-expert variation. The computerised assessment of maximum urinary flow is an efficient, consistent and valid approach to quantitatively assess maximum urinary flow in clinical trials.