A simplified prognostic score for T-cell large granular lymphocyte leukaemia.
Ann Med
; 55(2): 2258899, 2023.
Article
de En
| MEDLINE
| ID: mdl-37801616
ABSTRACT
BACKGROUND:
T-cell large granular lymphocyte leukaemia (T-LGLL) generally has a favourable prognosis, but a small proportion of patients are facing a relatively short survival time. This study aimed to identify clinical factors associated with survival in patients with T-LGLL and develop a predictive model for guiding therapeutic decision-making. MATERIALS ANDMETHODS:
We conducted a retrospective study on 120 patients with T-LGLL. Lasso regression was performed for feature selection followed by univariate and multivariate Cox regression analysis. A decision tree algorithm was employed to construct a model for predicting overall survival (OS) in T-LGLL.RESULTS:
The median age of diagnosis for the entire cohort was 59 years, and 76.7% of patients reported disease-related symptoms. After a median follow-up of 75 months, the median OS was not reached. The 5-year OS rate was 82.2% and the 10-year OS rate was 63.8%. Multivariate analysis revealed that an Eastern Cooperative Oncology Group performance status over two and a platelet count below 100 × 109/L were independently associated with worse OS, leading to the development of a simplified decision tree model. The model's performance was adequate when internally validated. The median OS of the high- and intermediate-risk- risk groups was 43 and 100 months respectively, whereas the median OS of the low-risk group was not reached. Furthermore, we found that immunosuppressive agent-based conventional treatment was unsatisfactory for our high-risk patients.CONCLUSIONS:
Our model is an easily applicable clinical scoring system for predicting OS in patients with T-LGLL. However, external validation is essential before implementing it widely.Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Leucémie à grands lymphocytes granuleux
Type d'étude:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limites:
Humans
/
Middle aged
Langue:
En
Journal:
Ann Med
Sujet du journal:
MEDICINA
Année:
2023
Type de document:
Article
Pays d'affiliation:
Chine