OBJECTIVES: Computer-adaptive testing (CAT) is an advanced method for measuring patient-reported outcomes. With help of an algorithm CAT selects the items most relevant for an individual patient from an item bank. Our study aim was the development of a CAT version of the EORTC QLQ-C30 Fatigue scale, its implementation in a software package and its use in daily clinical routine. METHODS: Our project is part of a large project on CAT development conducted by the EORTC Quality of Life Group. To set up an initial English fatigue item list an extensive literature research was performed. These items were refined through multi-stage expert reviews, translated to German, Danish, Spanish, French and Dutch, and filled in by a pilot patient sample to collect feedback. In a next step a large patient sample is recruited for all language versions to gain data for development of the item bank and the CAT algorithm. RESULTS: Literature research resulted in 588 fatigue items, from which 44 were selected after comprehensive expert reviews. Based on feedback from 52 oncological patients wording and translation of several items were revised. Data has been collected from about 1200 patients. Preliminary results of the CAT-analysis will be presented. CONCLUSIONS: By generating individually tailored item sets, CAT reduces patient burden and assessment duration, and increases measurement precision. In addition, electronic data capture increases data quality and reduces the amount of human resources required for data collection.