Ethnic differences in acute promyelocytic leukaemia between New Zealand Polynesian and European patients.
Chris VargheseValery Yizhuo LiuTracey ImmanuelNicole ChienTaryn GreenGeorge ChanEdward TheakstonMaggie L Kalev-ZylinskaPublished in: Hematology (Amsterdam, Netherlands) (2021)
Ethnic differences in haematologic malignancies remain poorly elucidated, hence research in this area is important. This was a retrospective study into potential ethnic disparity in the presentation and outcomes of acute promyelocytic leukaemia (APL) between New Zealand (NZ) Polynesian and European patients. Data were analysed for patients treated at Auckland City Hospital (ACH; n = 55) and recorded in the New Zealand Cancer Registry (NZCR; n = 173), both for the period 2000-2017. We found that Polynesian patients treated at ACH presented at a younger age than European (P = 0.005), showed higher blast counts (P = 0.033), and a marginally higher prothrombin ratio (P = 0.02). Treatment with all-trans retinoic acid (ATRA) was started faster in Polynesian patients than European (P = 0.021), suggesting Polynesians were sicker at presentation but were managed accordingly. There were no differences in bleeding events, transfusion requirements and early deaths during the first month of treatment. Long-term survival was also similar. Data extracted from the NZCR confirmed NZ Polynesian patients with APL were younger than European (P < 0.001), but long-term survival was similar (P = 0.920). In summary, this study indicates a discrepancy in the presentation and severity of APL between NZ Polynesian and European patients but treatment initiation was rapid with no difference in outcomes. The distinctive features of APL in NZ Polynesians raise the possibility of a predisposing genetic factor or a different risk factor profile, elucidation of which is important for all patients with APL.
Keyphrases
- end stage renal disease
- ejection fraction
- chronic kidney disease
- peritoneal dialysis
- squamous cell carcinoma
- prognostic factors
- healthcare
- risk factors
- gene expression
- machine learning
- metabolic syndrome
- liver failure
- emergency department
- risk assessment
- big data
- young adults
- electronic health record
- acute respiratory distress syndrome
- respiratory failure
- lymph node metastasis
- mechanical ventilation