Studies have found that combining patient-reported outcomes (PROs) with more traditional disease classification systems, such as the International Prognostic Scoring System (IPSS), can improve accuracy of prognoses. In fact, a study published in Leukemia in February 2020 found that patients with high-risk myelodysplastic syndromes (MDS) who reported their fatigue on the European Organization for Research and Treatment of Cancer Quality of Life-Core 30 (QLQ-C30) could be reliably stratified into groups with different survival outcomes.
At the 62nd ASH Annual Meeting & Exposition, a group of researchers presented a related study that sought to validate that model in the Canadian MDS Registry.
The study also sought to determine whether a similar model using the IPSS-R and the Edmonton Symptom Self-Assessment Scale (ESAS) Global Fatigue Scale (GFS) could also identify subgroups by overall survival (OS). The ESAS GFS is easier to deploy and has been recommended by the National Comprehensive Cancer Network to screen for fatigue in all patients with cancer, said lead presenter Irina Amitai, MD, of the Odette Cancer Centre at the Sunnybrook Health Sciences Centre in Toronto, Canada.
The researchers included all adult patients with MDS and a score higher than 3.5 on the revised IPSS (IPSS-R) within the six months leading up to registration in the dataset. The researchers collected data on:
- Patient fatigue as assessed by both the QLQ-C30 and GFS
- Frailty as assessed by the Rockwood Clinical Frailty Scale
Among the 331 patients included, median age was 73 years (range, 30-98 years). Median IPSS-R score was 5.2 (range, 3.5-10), and IPSS groupings were as follows:
- 55% had high risk or intermediate-2 risk.
- 68% had high risk or very high IPSS-R risk disease.
Overall, 59% reported high fatigue, and fatigue scores increased along with frailty scores. At a median follow-up of 17 months, 233 patients had died, with a median OS of 19.3 months.
Analyses revealed a significant difference in OS between groups with low fatigue and high fatigue in both models. Therefore, the study validated the model as described in Leukemia and also supports use of the ESAS GFS.
“This emphasizes the power of self-reported fatigue at refining OS predictions in higher-risk MDS and further bolsters the importance of considering PROs in global assessments,” Dr. Amitai said.