Red cell transfusion in outpatients with myelodysplastic syndromes: a feasibility and exploratory randomised trial.
Simon J StanworthSally KillickZoe K McQuiltenMarina KarakantzaRobert WeinkoveHeather SmethurstLaura A PankhurstRenate L HodgeValerie HopkinsHelen L ThomasAlison J DearyJeannie CallumYulia LinErica M WoodRena BucksteinDavid Bowennull nullPublished in: British journal of haematology (2020)
Optimal red cell transfusion support in myelodysplastic syndromes (MDS) has not been tested and established. The aim of this study was to demonstrate feasibility of recruitment and follow-up in an outpatient setting with an exploratory assessment of quality of life (QoL) outcomes (EORTC QLQ-C30 and EQ-5D-5L). We randomised MDS patients to standardised transfusion algorithms comparing current restrictive transfusion thresholds (80 g/l, to maintain haemoglobin 85-100 g/l) with liberal thresholds (105 g/l, maintaining 110-125 g/l). The primary outcomes were measures of compliance to transfusion thresholds. Altogether 38 patients were randomised (n = 20 restrictive; n = 18 liberal) from 12 participating sites in UK, Australia and New Zealand. The compliance proportion for the intention-to-treat population was 86% (95% confidence interval 75-94%) and 99% (95-100%) for restrictive and liberal arms respectively. Mean pre-transfusion haemoglobin concentrations for restrictive and liberal arms were 80 g/l (SD6) and 97 g/l (SD7). The total number of red cell units transfused on study was 82 in the restrictive and 192 in the liberal arm. In an exploratory analysis, the five main QoL domains were improved for participants in the liberal compared to restrictive arm. Our findings support the feasibility and need for a definitive trial to evaluate the effect of different red cell transfusion thresholds on patient-centred outcomes.
Keyphrases
- cardiac surgery
- end stage renal disease
- single cell
- clinical trial
- sickle cell disease
- cell therapy
- study protocol
- ejection fraction
- newly diagnosed
- chronic kidney disease
- machine learning
- open label
- peritoneal dialysis
- prognostic factors
- squamous cell carcinoma
- mesenchymal stem cells
- deep learning
- radiation therapy
- phase ii
- double blind
- rectal cancer
- data analysis
- locally advanced