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    In: American Journal of Hematology, Wiley, Vol. 98, No. 9 ( 2023-09), p. 1394-1406
    Abstract: Chronic myelomonocytic leukemia (CMML) is a clonal hematopoietic stem cell malignancy, and allogeneic hematopoietic stem cell transplantation (allo‐HSCT) is the only curable treatment. The outcomes after transplant are influenced by both disease characteristics and patient comorbidities. To develop a novel prognostic model to predict the post‐transplant survival of CMML patients, we identified risk factors by applying univariable and multivariable Cox proportional hazards regression to a derivation cohort. In multivariable analysis, advanced age (hazard ratio [HR] 3.583), leukocyte count (HR 3.499), anemia (HR 3.439), bone marrow blast cell count (HR 2.095), and no chronic graft versus host disease (cGVHD; HR 4.799) were independently associated with worse survival. A novel prognostic model termed ABLAG (Age, Blast, Leukocyte, Anemia, cGVHD) was developed and the points were assigned according to the regression equation. The patients were categorized into low risk (0–1), intermediate risk (2, 3), and high risk (4–6) three groups and the 3‐year overall survival (OS) were 93.3% (95%CI, 61%–99%), 78.9% (95%CI, 60%–90%), and 51.6% (95%CI, 32%–68%; p   〈  .001), respectively. In internal and external validation cohort, the area under the receiver operating characteristic (ROC) curves of the ABLAG model were 0.829 (95% CI, 0.776–0.902) and 0.749 (95% CI, 0.684–0.854). Compared with existing models designed for the nontransplant setting, calibration plots, and decision curve analysis showed that the ABLAG model revealed a high consistency between predicted and observed outcomes and patients could benefit from this model. In conclusion, combining disease and patient characteristic, the ABLAG model provides better survival stratification for CMML patients receiving allo‐HSCT.
    Type of Medium: Online Resource
    ISSN: 0361-8609 , 1096-8652
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 1492749-4
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