Testing for differences in multiple quality of life dimensions: generating hypotheses from the experience of hospital staff.

In clinical trials with a quality of life (QoL) component, it is usual to monitor several QoL dimensions at several points in time. Multiple significance tests without formal hypotheses are problematic. It is not always feasible to specify a priori hypotheses for all variables. Can such studies be used to generate hypotheses for testing in later research only? We developed a method which can allow for formal hypothesis testing on a data set collected without a priori hypotheses in the protocol. We surveyed experienced physicians and nurses treating patients, to obtain independent expectations about differences in QoL dimensions. These 'staff expectations' will be used in the analysis of QoL data collected from breast cancer patients taking part in three randomized trials of adjuvant therapy. We propose frameworks for the informal and formal use of the experience of the staff in testing for group differences in patients' QoL scores. The method described here is anticipated to be useful for QoL studies in general, even when a priori hypotheses were specified before the studies were initiated.