6533b7dcfe1ef96bd127299e
RESEARCH PRODUCT
A complication risk score to evaluate clinical severity of thalassaemia syndromes
Aurelio MaggioVito Di MarcoMahmoud HajipourShahina DaarShahina DaarSaqib Hussain AnsariAmal El-beshlawyGabriella DardanoniSalvatore ScondottoAlessia PepeAldo FilosaSylvia T. SingerZaki A NaserullahFedele BonifaziAntonella MeloniElliott VichinskyWalter Addario PollinaAngela VitranoMehran KarimiAdriana CeciPaolo Ricchisubject
AdultMalemedicine.medical_specialtyAdolescentcomplicationsthalassaemiacomplicationrisk scoreLogistic regressionSeverity of Illness IndexGroup AGroup BHemoglobinsYoung Adult03 medical and health sciences0302 clinical medicineRisk FactorsInternal medicinemedicineHumansprognostic modelBlood TransfusionClinical severityHemoglobinFramingham Risk ScoreEjection fractionReceiver operating characteristicbusiness.industryHematologyMiddle AgedPrognosisChelation TherapyThalassemia ...ROC Curve030220 oncology & carcinogenesisThalassemiaFemalecomplications; prognostic model; risk score; thalassaemiaComplicationbusiness030215 immunologydescription
The thalassaemia syndromes (TS) show different phenotype severity. Developing a reliable, practical and global tool to determine disease severity and tailor treatment would be of great value. Overall, 7910 patients were analysed with the aim of constructing a complication risk score (CoRS) to evaluate the probability of developing one or more complications. Nine independent variables were included in the investigation as predictors. Logistic regression models were used for Group A [transfusion-dependent thalassaemia (TDT)], Group B [transfused non-TDT (NTDT)] and Group C (non-transfused NTDT). Statistically significant predictors included age (years), haemoglobin levels, hepatic transaminases [alanine aminotransferase (ALT) and aspartate aminotransferase] and left-ventricular ejection fraction (LVEF) for Group A; age (years), age at first chelation (months), ALT and LVEF for Group B; and age (years), mean serum ferritin (SF) levels and LVEF for Group C. The area under the receiver operating characteristic curve was 84·5%, 82·1% and 80·0% for Groups A, Group B and Group C respectively, suggesting the models had good discrimination. Finally, the CoRS for each group was categorised into four risk classes (low, intermediate, high, and very high) using the centiles of its distribution. In conclusion, we have developed a CoRS for TS that can assist physicians in prospectively tailoring patients’ treatment.
year | journal | country | edition | language |
---|---|---|---|---|
2020-11-20 | British Journal of Haematology |