Evidence map›Paper›PMID 37861735›Full record

ArticleAnnals of hematology2024

Development and validation of a novel risk stratification model and a survival rate calculator for diffuse large B-cell lymphoma in the rituximab era: a multi-institutional cohort study.

Qiaofeng Zhong, Haizhu Chen, Daoguang Chen, Yan Qin, Xiaohui He, Yu Yang, Jianliang Yang, Peng Liu, Shengyu Zhou, Sheng Yang and 4 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Annals of hematology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

14 authors at 2 institutions in 1 country.

Qiaofeng ZhongDepartment 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.
Haizhu ChenDepartment 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.
Daoguang ChenDepartment of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Road, Fuzhou, 350014, China.
Yan QinDepartment 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.
Xiaohui HeDepartment 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.
Yu YangDepartment of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Road, Fuzhou, 350014, China.
Jianliang YangDepartment 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.
Peng LiuDepartment 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.
Shengyu ZhouDepartment 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.
Sheng YangDepartment 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.
Yu ZhouDepartment 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.
Le TangDepartment 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.
Chuanben ChenDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Road, Fuzhou, 350014, China. ccb@fjmu.edu.cn.
Yuankai ShiDepartment 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. syuankai@cicams.ac.cn.ORCID http://orcid.org/0000-0002-3342-4964
Chinese Academy of Medical Sciences & Peking Union Medical College · CNFujian Medical University · CN

Funding

China National Major Project for New Drug Innovation 2017ZX09304015Natural Science Foundation of Fujian Province 2023J05241Postdoctoral Research Foundation of China 2023M734015Scientific Research Foundation of Fujian Cancer Hospital 2021YNY02
6 · The paper itself

Abstract

backgroundThis 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.

methodsWe 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.

findingsAge, 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.

conclusionsIn 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.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsLymphoma, Large B-Cell, DiffuseCohort StudiesCyclophosphamideDoxorubicinHumansPrednisonePrognosisRetrospective StudiesRisk AssessmentRituximabSurvival RateVincristineCyclophosphamideDoxorubicinPrednisoneRituximabVincristineDiffuse large B-cell lymphomaIPINomogramPrognosisWeb-based survival rate calculator

Identifiers

PMID37861735
OpenAlexW4387799255

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.