• Qual Life Res · Apr 2014

    Review Meta Analysis Comparative Study

    Reporting of health-related quality of life (HRQOL) data in oncology trials: a comparison of the European Organization for Research and Treatment of Cancer Quality of Life (EORTC QLQ-C30) and the Functional Assessment of Cancer Therapy-General (FACT-G).

    • Adam B Smith, Kim Cocks, David Parry, and Matthew Taylor.
    • Research Innovation Office, University of York, York, UK, adam.smith@york.ac.uk.
    • Qual Life Res. 2014 Apr 1;23(3):971-6.

    PurposeThe inclusion of patient-reported outcome (PRO) instruments to record patient health-related quality of life (HRQOL) data has virtually become the norm in oncology randomised controlled trials (RCTs). Despite this fact, recent concerns have focused on the quality of reporting of HRQOL. The primary aim of this study was to evaluate the quality of reporting of HRQOL data from two common instruments in oncology RCTs.DesignA meta-review was undertaken of systematic reviews reporting HRQOL data collected using PRO instruments in oncology randomised controlled trials (RCTs). English language articles published between 2000 and 2012 were included and evaluated against a methodology checklist.ResultsFour hundred and thirty-five potential articles were identified. Six systematic reviews were included in the analysis. A total of 70,403 patients had completed PROs. The European Organization for Research and Treatment of Cancer QLQ-C30 and Functional Assessment of Cancer Therapy-General questionnaire accounted for 55 % of RCTs. Eighty per cent of RCTs had used psychometrically validated instruments; 70 % reported culturally valid instruments and almost all reported the assessment timing (96 %). Thirty per cent of RCTS reported clinical significance and missing data. In terms of methodological design, only 25 % of RCTs could be categorised as probably robust.ConclusionThe majority of oncology RCTs has shortcomings in terms of reporting HRQOL data when assessed against regulatory and methodology guidelines. These limitations will need to be addressed if HRQOL data are to be used to successfully support clinical decision-making, treatment options and labelling claims in oncology.

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