• Hailing Liu, Jingjing Guo, Lei Cao, Huayuan Zhu, Yi Miao, Xinyi Du, Yujie Wu, Wei Xu, Jianyong Li, and Lei Fan.
• Department of Hematology, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, China.
• Ann. Med. 2023 Jan 1; 55 (2): 22588992258899.

BackgroundT-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 And MethodsWe 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.ResultsThe 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.ConclusionsOur 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.

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