The prognostic roles of hepatitis B virus antibody in diffuse large B-cell lymphoma patients

Hu, Shunfeng; Chen, Na; Lu, Kang; Zhen, Changqing; Sui, Xiaohui; Fang, Xiaosheng; Li, Ying; Luo, Yingshu; Zhou, Xiangxiang; Wang, Xin

doi:10.1080/10428194.2020.1867726

Cited by 6 publications

(5 citation statements)

References 33 publications

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“…It has been known that the assessment of plasma fibrinogen and fibrinolytic products is helpful for cancer diagnosis, treatment effect and prognosis ( 24 ). Studies have shown that cancer patients with HBeAb + show unique clinical characteristics, which is an independent risk factor affecting the prognosis of the disease ( 25 ). Levothyroxine suppression treatment for benign thyroid nodules alters coagulation showed that D-dimer level increased after treatment ( 26 ).…”

Section: Discussionmentioning

confidence: 99%

A machine learning-based approach to predicting the malignant and metastasis of thyroid cancer

Xie

Zhao

et al. 2022

Front. Oncol.

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BackgroundThyroid Cancer (TC) is the most common malignant disease of endocrine system, and its incidence rate is increasing year by year. Early diagnosis, management of malignant nodules and scientific treatment are crucial for TC prognosis. The first aim is the construction of a classification model for TC based on risk factors. The second aim is the construction of a prediction model for metastasis based on risk factors.MethodsWe retrospectively collected approximately 70 preoperative demographic and laboratory test indices from 1735 TC patients. Machine learning pipelines including linear regression model ridge, Logistic Regression (LR) and eXtreme Gradient Boosting (XGBoost) were used to select the best model for predicting deterioration and metastasis of TC. A comprehensive comparative analysis with the prediction model using only thyroid imaging reporting and data system (TI-RADS).ResultsThe XGBoost model achieved the best performance in the final thyroid nodule diagnosis (AUC: 0.84) and metastasis (AUC: 0.72-0.77) predictions. Its AUCs for predicting Grade 4 TC deterioration and metastasis reached 0.84 and 0.97, respectively, while none of the AUCs for Only TI-RADS reached 0.70. Based on multivariate analysis and feature selection, age, obesity, prothrombin time, fibrinogen, and HBeAb were common significant risk factors for tumor progression and metastasis. Monocyte, D-dimer, T3, FT3, and albumin were common protective factors. Tumor size (11.14 ± 7.14 mm) is the most important indicator of metastasis formation. In addition, GGT, glucose, platelet volume distribution width, and neutrophil percentage also contributed to the development of metastases. The abnormal levels of blood lipid and uric acid were closely related to the deterioration of tumor. The dual role of mean erythrocytic hemoglobin concentration in TC needs to be verified in a larger patient cohort. We have established a free online tool (http://www.cancer-thyroid.com/) that is available to all clinicians for the prognosis of patients at high risk of TC.ConclusionIt is feasible to use XGBoost algorithm, combined with preoperative laboratory test indexes and demographic characteristics to predict tumor progression and metastasis in patients with TC, and its performance is better than that of Only using TI-RADS. The web tools we developed can help physicians with less clinical experience to choose the appropriate clinical decision or secondary confirmation of diagnosis results.

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Section: Discussionmentioning

confidence: 99%

A machine learning-based approach to predicting the malignant and metastasis of thyroid cancer

Xie

Zhao

et al. 2022

Front. Oncol.

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“…HBV increases the risk of NHL and further affects the chemotherapy effect and prognosis of NHL patients. 107 , 108 According to a meta-analysis, 108 DLBCL patients with chronic HBV infection had significantly poorer progression-free survival (PFS) at 2- and 5-years and overall survival (OS). Patients who were seronegative for HBsAg had a lower CR rate, higher progressive disease (PD) rate, and more advanced clinical features.…”

Section: Treatment Of Hbv-associated Nhlmentioning

confidence: 99%

Hepatitis Virus-associated Non-hodgkin Lymphoma: Pathogenesis and Treatment Strategies

Zhang¹,

Du²,

Li³

et al. 2023

J Clin Transl Hepatol

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Over the last decade, epidemiological studies have discovered a link between hepatitis C virus (HCV) and hepatitis B virus (HBV) infection and non-Hodgkin lymphoma (NHL). The regression of HCV-associated NHL after HCV eradication is the most compelling proof supporting HCV infection’s role in lymphoproliferative diseases. HBV infection was found to significantly enhance the incidence of NHL, according to the epidemiological data. The exact mechanism of HCV leading to NHL has not been fully clarified, and there are mainly the following possible mechanisms: (1) Indirect mechanisms: stimulation of B lymphocytes by extracellular HCV and cytokines; (2) Direct mechanisms: oncogenic effects mediated by intracellular HCV proteins; (3) hit-and-run mechanism: permanent genetic B lymphocytes damage by the transitional entry of HCV. The specific role of HBV in the occurrence of NHL is still unclear, and the research on its mechanism is less extensively explored than HCV, and there are mainly the following possible mechanisms: (1) Indirect mechanisms: stimulation of B lymphocytes by extracellular HBV; (2) Direct mechanisms: oncogenic effects mediated by intracellular HBV DNA. In fact, it is reasonable to consider direct-acting antivirals (DAAs) as first-line therapy for indolent HCV-associated B-NHL patients who do not require immediate chemotherapy. Chemotherapy for NHL is affected by HBV infection and replication. At the same time, chemotherapy can also activate HBV replication. Following recent guidelines, all patients with HBsAg positive/HBV DNA≥2,000 IU/mL should be treated for HBV. The data on epidemiology, interventional studies, and molecular mechanisms of HCV and HBV-associated B-NHL are systematically summarized in this review.

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“… 7 A multitude of gene‐based signatures and biochemical markers have been considered to improve the risk assessment, while those are often unavailable and expensive. 8 , 9 , 10 Hence, it is critical to seek more accurate, feasible, and easily obtainable markers to distinguish patients who suffer a particularly aggressive course. Besides, clinical complications of PGI‐DLBCL could trigger specific management difficulties, such as perforation and massive bleeding.…”

Section: Introductionmentioning

confidence: 99%

“…Although PGI‐DLBCL is viewed as a potentially curable disease compared with other extranodal lymphoma types, several patients still present unfavorable outcomes and require early risk assessment 7 . A multitude of gene‐based signatures and biochemical markers have been considered to improve the risk assessment, while those are often unavailable and expensive 8–10 . Hence, it is critical to seek more accurate, feasible, and easily obtainable markers to distinguish patients who suffer a particularly aggressive course.…”

Section: Introductionmentioning

confidence: 99%

Prognosis and complications of patients with primary gastrointestinal diffuse large B‐cell lymphoma: Development and validation of the systemic inflammation response index‐covered score

et al. 2023

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Background This study aimed to evaluate the predictive value of systemic inflammation response index (SIRI) in primary gastrointestinal diffuse large B‐cell lymphoma (PGI‐DLBCL) patients and establish a highly discriminating risk prediction model. Methods This retrospective analysis included 153 PGI‐DCBCL patients diagnosed between 2011 and 2021. These patients were divided into a training set ( n = 102) and a validation set ( n = 51). Univariate and multivariate Cox regression analyses were conducted to examine the significance of variables on overall survival (OS) and progression‐free survival (PFS). An inflammation‐covered score system was established according to the multivariate results. Results The presence of high pretreatment SIRI (≥1.34, p < 0.001) was significantly associated with poorer survival and identified as an independent prognostic factor. Compared with NCCN‐IPI, the prognostic and discriminatory capability of the novel model SIRI‐PI showed a more precise high‐risk assessment with a higher area under the curve (AUC) (0.916 vs 0.835) and C ‐index (0.912 vs 0.836) for OS in the training cohort, and similar results were obtained in the validation cohort. Moreover, SIRI‐PI also showed good discriminative power for efficacy assessment. This new model identified patients at risk of developing severe gastrointestinal complications following chemotherapy. Conclusions The results of this analysis suggested that the pretreatment SIRI may be a potential candidate for identifying patients with a poor prognosis. And we established and validated a better‐performing clinical model, which facilitated the prognostic stratification of PGI‐DLBCL patients and can serve as a reference for clinical decision‐making.

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The prognostic roles of hepatitis B virus antibody in diffuse large B-cell lymphoma patients

Cited by 6 publications

References 33 publications

A machine learning-based approach to predicting the malignant and metastasis of thyroid cancer

A machine learning-based approach to predicting the malignant and metastasis of thyroid cancer

Hepatitis Virus-associated Non-hodgkin Lymphoma: Pathogenesis and Treatment Strategies

Prognosis and complications of patients with primary gastrointestinal diffuse large B‐cell lymphoma: Development and validation of the systemic inflammation response index‐covered score

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