Establishment and validation of an optimized prognostic model for Chinese patients with chronic myelomonocytic leukemia (Sino-CPSS): A 231-patient single-center study

Q Qingli Ji (1Qilu Hospital of Shandong University, jinan, China) X Xinwen Jiang (1Qilu Hospital of Shandong University, jinan, China) D Dongmei Hu G Guangyue Yao (1Department of Hematology, Qilu Hospital of Shandong University, Jinan, China) X Xiaoqing Li (School of Materials and Energy) X Xinrui Zhang (Gilead Sciences, Foster City, CA) C Chen Cao (Key Laboratory of Advanced Catalysis, Gansu Province; State Key Laboratory of Natural Product Chemistry, College of Chemistry and Chemical Engineering) M Minran Zhou (1Qilu Hospital of Shandong University, jinan, China) S Sai Ma C Chen Chunyan (1Qilu Hospital of Shandong University, jinan, China)

Abstract

Abstract Background: Chronic myelomonocytic leukemia (CMML) exhibits significant survival heterogeneity. Existing prognostic models based on Western populations demonstrate limited applicability in Chinese patients, who present distinct clinicomolecular profiles and therapeutic challenges, necessitating a population-specific prognostic tool. Aims: This study aimed to establish and validate an optimized prognostic scoring system (Sino-CPSS) specifically designed for Chinese CMML patients, integrating both molecular and clinical risk factors to improve risk stratification accuracy. Methods: We retrospectively analyzed 231 CMML patients from Qilu Hospital (2017-2025). Prognostic factors were identified using Cox regression, with risk scores weighted by hazard ratios. Internal validation employed 1000 bootstrap resamples. Model performance was assessed via time-dependent ROC (td-ROC), calibration curves, and decision curve analysis (DCA), compared against established models (CPSS, CPSS-Mol, MMM, GFM). Results: The cohort comprised 231 patients with a median age of 66 years (range 25-92), exhibiting high-frequency mutations in ASXL1 (55%) and TET2 (34%). The allogeneic hematopoietic stem cell transplantation (allo-HSCT) rate was only 5.2%, and the 3-year overall survival (OS) rate was 24.9%. Multivariate analysis identified age >60 years (HR 2.24, P<0.001), platelets <50×10⁹/L (HR 1.72, P=0.012), high-risk cytogenetics (HR 1.72, P=0.028), ASXL1 (HR 2.32, P<0.001), and TP53 mutations (HR 2.55, P=0.001) as independent adverse predictors, while TET2 mutation was protective (HR 0.67, P=0.04). The Sino-CPSS model stratified patients into low- (median OS 20.3 months), intermediate- (5.5 months), and high-risk groups (4.6 months) (Log-rank P<0.0001). The model demonstrated superior discriminative ability (td-AUC 0.754-0.813 at 12-36 months, all P<0.01 vs comparators), excellent calibration (optimal at 36 months), and enhanced net benefit at critical clinical thresholds (25-40%) on DCA. Conclusion: Sino-CPSS is a novel prognostic tool optimized for Chinese CMML patients, integrating key molecular and clinical markers. It demonstrates excellent performance in risk stratification and long-term prediction, providing crucial support for individualized management. Keywords: Chronic myelomonocytic leukemia; Prognostic model; Survival analysis; Molecular markers; Risk stratification

Article Details

Journal Blood
Volume / Issue Vol. 146, Issue Supplement 1
Published November 03, 2025
Pages 7378-7378
ISSN 0006-4971
Publisher Elsevier BV

Journal Info

Blood

Elsevier BV

ISSN: 0006-4971 Health Sciences

Authors (10)

Q

Qingli Ji

1Qilu Hospital of Shandong University, jinan, China

X

Xinwen Jiang

1Qilu Hospital of Shandong University, jinan, China

D

Dongmei Hu

G

Guangyue Yao

1Department of Hematology, Qilu Hospital of Shandong University, Jinan, China

X

Xiaoqing Li

School of Materials and Energy

X

Xinrui Zhang

Gilead Sciences, Foster City, CA

C

Chen Cao

Key Laboratory of Advanced Catalysis, Gansu Province; State Key Laboratory of Natural Product Chemistry, College of Chemistry and Chemical Engineering

M

Minran Zhou

1Qilu Hospital of Shandong University, jinan, China

S

Sai Ma

C

Chen Chunyan

1Qilu Hospital of Shandong University, jinan, China