Predicting factors of survival rates among alpha- and beta-thalassemia patients: a retrospective 10-year data analysis - Iam-arunthai, Kunapa; Suwanban, Tawatchai; Thungthong, Pravinwan; Chamnanchanunt, Supat; Fucharoen, Suthat (Frontiers in Hematology, 2024)
Background Thalassemia is a genetic hemoglobinopathy in which a defective globin chain can cause transfusion-dependent anemia and other complications. As genotype interactions lead to variations in the clinical course among patients with thalassemia, clinical factors may help predict survival in the types of thalassemia complicated by gene interactions. Aim This study aimed to determine the clinical factors associated with survival in patients with thalassemia. We retrospectively reviewed the medical records of patients with thalassemia older than 15 years between 2002 and 2020 that were available at the Rajavithi Hospital. Data on the clinical parameters, laboratory tests, treatments, and survival status were collected and analyzed. Results Of the 478 thalassemia patients included, 68.8% were women, and the mean age was 41 ± 17 years. The most common type of thalassemia was β-thalassemia (53.3%). Male sex, low body mass index, the thalassemia type, comorbidities, low hemoglobin level, high ferritin level, and regular blood transfusion were significantly associated with short-term survival. However, only the thalassemia type (β-thalassemia, p = 0.048) and the co-inheritance of the α- and β-thalassemia genotypes (p = 0.03) were independently associated with death. The overall survival rates among patients with α-thalassemia, β-thalassemia, and co-inheritance of the α- and β-thalassemia genotypes were 98.1%, 90.6%, and 75.0%, respectively. The death rate was 6.3%, and the most common cause of death was infection. Conclusion The thalassemia genotype was a predictive factor of survival, and co-inheritance of the α- and β-thalassemia genotypes results in a shorter-term survival compared with other types, especially transfusion-dependent thalassemia. These results can be applied in clinical settings to predict and possibly extend the life expectancy of patients with thalassemia.