Integrating Health-Related Quality of Life into Cross-National Clinical Trials

When planning to implement health-related quality of life (HRQL) assessment in a multinational clinical trial, there are at least four general considerations: the natural history of the disease or condition, the characteristics of the population, the treatment under consideration, and the structure and function of the clinical trial organization. Each of these considerations must be addressed simultaneously when planning, implementing and analysing a cross-national clinical trial. There are five relevant polar components of the natural history of a given disease or condition: (1) time frame (acute versus chronic); (2) life threat (yes versus no); (3) symptomatology (present versus absent); (4) symptom expression (episodic versus constant); and (5) functional impact (present versus absent). Differences in population characteristics, (e.g., age, conditions, co-morbidity), embedded within any cross-national trial, must be addressed conceptually prior to initiating the trial, methodologically when planning implementation, and statistically after the collection of the data. In terms of treatment, issues such as adverse and positive effects and timing of effects must be considered. The methods entailed in planning, implementing and analysing HRQL data will depend upon the degree of centralization of personnel and resources within any given clinical trial. The range of possibilities runs from complete centralization, in which all planning and coordination of data collection and transmittal is done by one office, to complete decentralization, in which the work is distributed to participating sites and interested investigators. Finally, successful implementation of HRQL data collection is enhanced by heightening awareness of the importance of, and value in, assessing HRQL in clinical trials. The investigator embarking on a treatment trial can extend the outcome inquiry into broader areas of function and well-being than those defined by the more traditional symptom profiles, morbidity and mortality outcomes.