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Updated: Jun 19, 2025
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Nomogram models predicting prognosis for patients with t(8;21) acute myeloid leukemia: a SEER-based study
Jiapeng Yang1, Xiaohua Zhu1, Honghong Zhang1
1Department of Hematology and Oncology, National Children's Medical Center, Children's Hospital of Fudan University, Shanghai, People's Republic of China.
Background:
Acute myeloid leukemia (AML) with t(8;21) manifests as a diverse hematological malignancy. Although it was categorized into a favorable subtype, 30-40% of patients experience relapse. The objective of this research was to devise a nomogram for the accurate anticipation of both overall survival (OS) and cancer-specific survival (CSS) in t(8;21) AML.
Methods:
From the Surveillance, Epidemiology, and End Results (SEER) database, individuals diagnosed with t(8;21) AML from 2000 to 2018 were selected. Prognostic factors for t(8;21) AML were identified using Cox regression analysis and Akaike Information Criterion (AIC), forming the basis for constructing prognostic nomograms.
Results:
Key variables, including first primary tumor, age group, race, and chemotherapy, were identified and integrated into the nomogram. The C-index values for the nomograms predicting OS and CSS were 0.753 (validation: 0.765) and 0.764 (validation: 0.757), respectively. Ultimately, based on nomogram scores, patients were stratified into high-risk and low-risk groups, revealing significant disparities in both OS and CSS between these groups (P < 0.001).
Conclusion:
This study innovatively crafted nomograms, incorporating clinical and therapeutic variables, to forecast the 1-, 3-, and 5-year survival rates for individuals with t(8;21) AML.
