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Updated: Jul 12, 2025
An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Development and validation of a novel risk stratification model and a survival rate calculator for diffuse large
Qiaofeng Zhong1,2,3, Haizhu Chen1, Daoguang Chen4
1Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
Background:
This study aimed to develop and validate a novel risk stratification model and a web-based survival rate calculator to improve discriminative and predictive accuracy for diffuse large B-cell lymphoma (DLBCL) in the rituximab era.
Methods:
We retrospectively collected pre-treatment data from 873 primary DLBCL patients who received R-CHOP-based immunochemotherapy regimens at the Cancer Hospital, Chinese Academy of Medical Sciences, from January 1, 2005, to December 31, 2018. An independent cohort of 175 DLBCL patients from Fujian Cancer Hospital was used for external validation.
Findings:
Age, ECOG PS, number of extranodal sites, Ann Arbor stage, bulky disease, and LDH levels were screened to develop the nomogram and web-based survival rate calculator. The C-index of the nomogram in the training, internal validation, and external validation cohorts was 0.761, 0.758, and 0.768, respectively. The risk stratification model generated based on the nomogram effectively stratified patients into three distinct risk groups. K-M survival curves demonstrated that the novel risk stratification model exhibited a superior level of predictive accuracy compared to IPI, R-IPI, and NCCN-IPI both in training and two validation cohorts. Additionally, the area under the curve (AUC) value of the novel model (0.763) for predicting 5-year overall survival rates was higher than those of IPI (0.749), R-IPI (0.725), and NCCN-IPI (0.727) in the training cohort. Similar results were observed in both internal and external validation cohort.
Conclusions:
In conclusion, we have successfully developed and validated a novel risk stratification model and a web-based survival rate calculator that demonstrated superior discriminative and predictive accuracy compared to IPI, R-IPI, and NCCN-IPI in the rituximab era.
