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Xu H, Yan R, Ye C, Li J, Ji G. Specific mortality in patients with diffuse large B-cell lymphoma: a retrospective analysis based on the surveillance, epidemiology, and end results database. Eur J Med Res 2024; 29:241. [PMID: 38643217 PMCID: PMC11031870 DOI: 10.1186/s40001-024-01833-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 04/06/2024] [Indexed: 04/22/2024] Open
Abstract
BACKGROUND The full potential of competing risk modeling approaches in the context of diffuse large B-cell lymphoma (DLBCL) patients has yet to be fully harnessed. This study aims to address this gap by developing a sophisticated competing risk model specifically designed to predict specific mortality in DLBCL patients. METHODS We extracted DLBCL patients' data from the SEER (Surveillance, Epidemiology, and End Results) database. To identify relevant variables, we conducted a two-step screening process using univariate and multivariate Fine and Gray regression analyses. Subsequently, a nomogram was constructed based on the results. The model's consistency index (C-index) was calculated to assess its performance. Additionally, calibration curves and receiver operator characteristic (ROC) curves were generated to validate the model's effectiveness. RESULTS This study enrolled a total of 24,402 patients. The feature selection analysis identified 13 variables that were statistically significant and therefore included in the model. The model validation results demonstrated that the area under the receiver operating characteristic (ROC) curve (AUC) for predicting 6-month, 1-year, and 3-year DLBCL-specific mortality was 0.748, 0.718, and 0.698, respectively, in the training cohort. In the validation cohort, the AUC values were 0.747, 0.721, and 0.697. The calibration curves indicated good consistency between the training and validation cohorts. CONCLUSION The most significant predictor of DLBCL-specific mortality is the age of the patient, followed by the Ann Arbor stage and the administration of chemotherapy. This predictive model has the potential to facilitate the identification of high-risk DLBCL patients by clinicians, ultimately leading to improved prognosis.
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Affiliation(s)
- Hui Xu
- Department of Hematology, Taixing People's Hospital, No. 98, Runtai South Road, Taixing, 225400, Jiangsu, China
| | - Rong Yan
- Taixing People's Hospital, Taixing, Jiangsu, China
| | - Chunmei Ye
- Department of Hematology, Taixing People's Hospital, No. 98, Runtai South Road, Taixing, 225400, Jiangsu, China
| | - Jun Li
- Department of Hematology, Taixing People's Hospital, No. 98, Runtai South Road, Taixing, 225400, Jiangsu, China
| | - Guo Ji
- Department of Hematology, Taixing People's Hospital, No. 98, Runtai South Road, Taixing, 225400, Jiangsu, China.
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Li M, Mi L, Wang C, Wang X, Zhu J, Qi F, Yu H, Ye Y, Wang D, Cao J, Hu D, Yang Q, Zhao D, Ma T, Song Y, Zhu J. Clinical implications of circulating tumor DNA in predicting the outcome of diffuse large B cell lymphoma patients receiving first-line therapy. BMC Med 2022; 20:369. [PMID: 36280874 PMCID: PMC9594942 DOI: 10.1186/s12916-022-02562-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 09/09/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Circulating tumor DNA (ctDNA) has been proven to be a promising tumor-specific biomarker in solid tumors, but its clinical utility in risk stratification and early prediction of relapse for diffuse large B cell lymphoma (DLBCL) has not been well explored. METHODS Here, using a lymphoma-specific sequencing panel, we assessed the prognostic and predictive utilities of ctDNA measurements before, during, and after first-line therapy in 73 Chinese DLBCL patients. RESULTS The pretreatment ctDNA level serving as an independent prognostic factor for both progression-free survival (PFS, adjusted HR 2.47; p = 0.004) and overall survival (OS, adjusted HR 2.49; p = 0.011) was confirmed in our cohort. Furthermore, the patients classified as molecular responders who presented a larger decrease in ctDNA levels after the initial two treatment cycles had more favorable PFS (unreached vs. 6.25 months; HR 5.348; p = 0.0015) and OS (unreached vs. 25.87; HR 4.0; p = 0.028) than non-responders. In addition, interim ctDNA clearance may be an alternative noninvasive method of positron emission tomography and computed tomography (PET-CT) for predicting better PFS (HR 3.65; p = 0.0033) and OS (HR 3.536; p = 0.016). We also demonstrated that posttreatment ctDNA was a sensitive indicator for detecting minimal residual disease (MRD) in patients with a high risk of recurrence (HR 6.471; p = 0.014), who were otherwise claimed to achieve radiographic CR (complete remission). CONCLUSIONS CtDNA is a promising noninvasive tool for prognosis prediction, response assessment, and early relapse prediction of first-line treatment in DLBCL patients.
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Affiliation(s)
- Miaomiao Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Lan Mi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Chunyang Wang
- Jichenjunchuang Clinical Laboratory, Hangzhou, Zhejiang, China
| | - Xiaojuan Wang
- Jichenjunchuang Clinical Laboratory, Hangzhou, Zhejiang, China
| | - Jianhua Zhu
- Jichenjunchuang Clinical Laboratory, Hangzhou, Zhejiang, China
| | - Fei Qi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Hui Yu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Yingying Ye
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Dedao Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Jiaowu Cao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Dingyao Hu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Quanyu Yang
- Jichenjunchuang Clinical Laboratory, Hangzhou, Zhejiang, China
| | - Dandan Zhao
- Jichenjunchuang Clinical Laboratory, Hangzhou, Zhejiang, China
| | - Tonghui Ma
- Jichenjunchuang Clinical Laboratory, Hangzhou, Zhejiang, China.
| | - Yuqin Song
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China.
| | - Jun Zhu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, 100142, China.
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Shi X, Liu X, Li X, Li Y, Lu D, Sun X, Li Y, Hu S, Zhang Y, Zhou X, Wang X, Chen H, Fang X. Risk Stratification for Diffuse Large B-Cell Lymphoma by Integrating Interim Evaluation and International Prognostic Index: A Multicenter Retrospective Study. Front Oncol 2021; 11:754964. [PMID: 34976802 PMCID: PMC8716489 DOI: 10.3389/fonc.2021.754964] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 11/24/2021] [Indexed: 01/01/2023] Open
Abstract
The baseline International Prognostic Index (IPI) is not sufficient for the initial risk stratification of patients with diffuse large B-cell lymphoma (DLBCL) treated with R‐CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone). The aims of this study were to evaluate the prognostic relevance of early risk stratification in DLBCL and develop a new stratification system that combines an interim evaluation and IPI. This multicenter retrospective study enrolled 314 newly diagnosed DLBCL patients with baseline and interim evaluations. All patients were treated with R-CHOP or R-CHOP-like regimens as the first-line therapy. Survival differences were evaluated for different risk stratification systems including the IPI, interim evaluation, and the combined system. When stratified by IPI, the high-intermediate and high-risk groups presented overlapping survival curves with no significant differences, and the high-risk group still had >50% of 3-year overall survival (OS). The interim evaluation can also stratify patients into three groups, as 3-year OS and progression-free survival (PFS) rates in patients with stable disease (SD) and progressive disease (PD) were not significantly different. The SD and PD patients had significantly lower 3-year OS and PFS rates than complete remission and partial response patients, but the percentage of these patients was only ~10%. The IPI and interim evaluation combined risk stratification system separated the patients into low-, intermediate-, high-, and very high-risk groups. The 3-year OS rates were 96.4%, 86.7%, 46.4%, and 40%, while the 3-year PFS rates were 87.1%, 71.5%, 42.5%, and 7.2%. The OS comparison between the high-risk group and very high-risk group was marginally significant, and OS and PFS comparisons between any other two groups were significantly different. This combined risk stratification system could be a useful tool for the prognostic prediction of DLBCL patients.
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Affiliation(s)
- Xue Shi
- Department of Hematology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiaoqian Liu
- Department of Hematology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Xiaomei Li
- Dongying People’s Hospital, Medical Records Department, Dongying, China
| | - Yahan Li
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Dongyue Lu
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Xue Sun
- Department of Hematology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Ying Li
- Department of Hematology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Shunfeng Hu
- Department of Hematology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yuanfeng Zhang
- Department of Hematology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Xiangxiang Zhou
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- Department of Hematology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xin Wang
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- Department of Hematology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- School of Medicine, Shandong University, Jinan, China
| | - Haiping Chen
- Department of Infectious Diseases, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- *Correspondence: Haiping Chen, ; Xiaosheng Fang,
| | - Xiaosheng Fang
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- *Correspondence: Haiping Chen, ; Xiaosheng Fang,
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