Evidence-based guidelines for interpreting change scores for the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30

Aim: To use published literature and experts' opinion to investigate the clinical meaning and magnitude of changes in the Quality of Life (QOL) of groups of patients measured with the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). Methods: An innovative method combining systematic review of published studies, expert opinions and meta-analysis was used to estimate large, medium, and small mean changes over time for QLQ-C30 scores. Results: Nine hundred and eleven papers were identified, leading to 118 relevant papers. One thousand two hundred and thirty two mean changes in QOL over time were combined in the meta-analysis, with timescales ranging from four days to five years. Guidelines were produced for trivial, small, and medium size classes, for each subscale and for improving and declining scores separately. Estimates for improvements were smaller than respective estimates for declines. Conclusions: These guidelines can be used to aid sample size calculations and interpretation of mean changes over time from groups of patients. Observed mean changes in the QLQ-C30 scores are generally small in most clinical situations, possibly due to response shift. Careful consideration is needed when planning studies where QOL changes over time are of primary interest; the timing of follow up, sample attrition, direction of QOL changes, and subscales of primary interest are key considerations. (C) 2012 Elsevier Ltd. All rights reserved.

Structure- and Ligand-Based Structure-Activity Relationships for a Series of Inhibitors of Aldolase

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r(2) = 0.98 and q(2) = 0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pK(i) values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.