Measuring quality of life in people living with and beyond cancer in the UK

Purpose The aim of this study was to identify the most appropriate measure of quality of life (QoL) for patients living with and beyond cancer. Methods One hundred eighty-two people attending cancer clinics in Central London at various stages post-treatment, completed a series of QoL measures: FACT-G, EORTC QLQ-C30 , IOCv2 (positive and negative subscales) and WEMWBS, a wellbeing measure. These measures were chosen as the commonest measures used in previous research. Correlation tests were used to assess the association between scales. Participants were also asked about pertinence and ease of completion. Results There was a significant positive correlation between the four domain scores of the two health-related QoL measures (.32 <= r <= .72, P < .001), and a significant large negative correlation between these and the negative IOCv2 subscale scores (- .39 <= r <= - .63, P < .001). There was a significant moderate positive correlation between positive IOCv2 subscale and WEMWBS scores (r = .35, P < .001). However, neither the FACT-G nor the EORTC showed any significant correlation with the positive IOCv2 subscale. Participants rated all measures similarly with regards to pertinence and ease of use. Conclusion There was little to choose between FACT-G, EORTC, and the negative IOC scales, any of which may be used to measure QoL. However, the two IOCv2 subscales capture unique aspects of QoL compared to the other measures. The IOCv2 can be used to identify those cancer survivors who would benefit from interventions to improve their QoL and to target specific needs thereby providing more holistic and personalised care beyond cancer treatment.

Automated summary

This study aimed to identify the most appropriate measure of quality of life for cancer patients living with and beyond cancer. Measures including FACT-G, EORTC QLQ-C30, IOCv2 (positive and negative subscales) and WEMWBS were completed by 182 patients in Central London, showing significant correlations between different scales. The study concluded that FACT-G, EORTC, and the negative IOC scales can all be used to measure QoL, with the unique aspects of QoL being captured by the two IOCv2 subscales. Participants rated all measures similarly in terms of relevance and ease of use.