Baseline Clinical and Laboratory Predictors of Treatment Requirement in Chronic Lymphocytic Leukemia: A Retrospective Cohort Study Using Hierarchical Modeling

Background/Objectives: Chronic lymphocytic leukemia (CLL) is characterized by a highly heterogeneous clinical course, with some patients remaining stable for years while others require early treatment. Identifying reliable and easily accessible predictors of treatment requirement at diagnosis remains an important clinical challenge. Methods: This retrospective cohort study included 226 patients diagnosed with CLL between 2015 and 2024 at a tertiary care center. Baseline demographic, clinical, and laboratory parameters were analyzed. Univariate and multivariable logistic regression analyses were performed to identify independent predictors of treatment requirement. A hierarchical mixed-effects model was constructed to account for temporal clustering across diagnostic periods. A clinical risk score was derived from independent predictors, using regression coefficient-based weighting, and its discriminative performance was evaluated using receiver operating characteristic (ROC) analysis. Results: A total of 226 patients were included (mean age: 62.4 ± 13.8 years; 56.6% male). During follow-up, 104 patients (46.0%) required treatment. Lower hemoglobin and platelet levels, higher lymphocyte counts and LDH levels, and the presence of B symptoms, splenomegaly, and advanced disease stage were independently associated with treatment requirement. These associations remained significant in hierarchical modeling. The derived risk score demonstrated acceptable discriminative ability (AUC: 0.84; 95% CI: 0.79–0.89), with a cut-off value of ≥4 yielding a sensitivity of 81.7% and specificity of 73.8%. Conclusions: Baseline clinical and laboratory parameters are associated with treatment requirement in CLL. A combination of readily available variables may support risk stratification at diagnosis. The proposed risk score may provide a practical adjunct to routine clinical assessment, particularly in settings where advanced molecular testing is not readily available; however, external validation in independent cohorts is required before clinical implementation.