A nomogram model for predicting the efficacy of cyclosporine in patients with pure red cell aplasia.

ABSTRACT

Pure red cell aplasia (PRCA) is a rare bone marrow disorder characterized by a severe reduction or absence of erythroid precursor cells, without affecting granulocytes and megakaryocytes. Immunosuppressive therapies, particularly cyclosporine, have demonstrated efficacy as a primary treatment. This study aims to develop a predictive model for assessing the efficacy of cyclosporine in acquired PRCA (aPRCA). This retrospective study encompasses newly treated aPRCA patients at the General Hospital of Tianjin Medical University. Diagnosis criteria include severe anemia, and absolute reticulocyte count below 10 × 109/L, with normal white blood cell and platelet counts, and a severe reduction in bone marrow erythroblasts. Cyclosporine therapy was administered, with dose adjustments based on blood concentration. Response to cyclosporine was evaluated according to established criteria. Statistical analysis involved logistic multi-factor regression, generating a predictive model. The study included 112 aPRCA patients with a median age of 63.5 years. Patients presented with severe anemia (median Hb, 56 g/L) and reduced reticulocyte levels. Eighty-six patients had no bone marrow nucleated erythroblasts. Primary PRCA accounted for 62 cases (55.4%), and secondary PRCA accounted for 50 cases (44.6%). Univariate analysis revealed that ferritin, platelet to lymphocyte ratio (PLR), and CD4/CD8 ratio influenced treatment response. Multivariate analysis further supported the predictive value of these factors. A prediction model was constructed using ferritin, PLR, and CD4/CD8 ratio, demonstrating high sensitivity and specificity. The ferritin, PLR, and CD4/CD8-based nomogram showed good predictive ability for aPRCA response to cyclosporine. This model has potential clinical value for individualized diagnosis and treatment of aPRCA patients.