Clinical scoring systems, molecular subtypes and baseline [18F]FDG PET/CT image analysis for prognosis of diffuse large B-cell lymphoma DOI Creative Commons
Zhenliang Sun, Tianshuo Yang,

Chongyang Ding

и другие.

Cancer Imaging, Год журнала: 2024, Номер 24(1)

Опубликована: Дек. 18, 2024

Abstract Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous hematological malignancy resulting in range of outcomes, and the early prediction these outcomes has important implications for patient management. Clinical scoring systems provide most commonly used prognostic evaluation criteria, value genetic testing also been confirmed by in-depth research on molecular typing. [ 18 F]-fluorodeoxyglucose positron emission tomography / computed ([ F]FDG PET/CT) an invaluable tool predicting DLBCL progression. Conventional baseline image-based parameters machine learning models have FDG PET/CT studies DLBCL; however, numerous shown that combinations clinical systems, subtypes, based image may better predictions aid decision-making patients with DLBCL.

Язык: Английский

Biomarkers for prediction of CAR T therapy outcomes: current and future perspectives DOI Creative Commons
Lucija Levstek, Larisa Janžič, Alojz Ihan

и другие.

Frontiers in Immunology, Год журнала: 2024, Номер 15

Опубликована: Март 15, 2024

Chimeric antigen receptor (CAR) T cell therapy holds enormous potential for the treatment of hematologic malignancies. Despite its benefits, it is still used as a second line therapy, mainly because severe side effects and patient unresponsiveness. Numerous researchers worldwide have attempted to identify effective predictive biomarkers early prediction outcomes adverse in CAR albeit so far only with limited success. This review provides comprehensive overview current state biomarkers. Although existing metrics correlate some extent outcomes, they fail encapsulate complexity immune system dynamics. The aim this six major groups propose their use developing improved efficient models. These include changes mitochondrial dynamics, endothelial activation, central nervous impairment, markers, extracellular vesicles, inhibitory tumor microenvironment. A understanding multiple factors that influence therapeutic efficacy has significantly improve course care, thereby making advanced immunotherapy more appealing convenient favorable patients.

Язык: Английский

Процитировано

9
Should we use nomograms for risk predictions in diffuse large B cell lymphoma patients? A systematic review DOI Creative Commons
Jelena Jelicic, Thomas Stauffer Larsen, Bosko Andjelic

и другие.

Critical Reviews in Oncology/Hematology, Год журнала: 2024, Номер 196, С. 104293 - 104293

Опубликована: Фев. 10, 2024

Models based on risk stratification are increasingly reported for Diffuse large B cell lymphoma (DLBCL). Due to a rising interest in nomograms cancer patients, we aimed review and critically appraise prognostic models DLBCL patients. A literature search PubMed/Embase identified 59 articles that proposed by combining parameters of (e.g., clinical, laboratory, immunohistochemical, genetic) between January 2000 2024. Of them, 40 studies different gene expression signatures incorporated them into nomogram-based models. Although most assessed discrimination calibration when developing the model, many lacked external validation. Current mainly developed from publicly available databases, lack validation, have no applicability clinical practice. However, they may be helpful individual patient counseling, although careful considerations should made regarding model development due possible limitations choosing prognostication.

Язык: Английский

Процитировано

1
A Novel Inflammatory-Nutritional Prognostic Scoring System for Patients with Diffuse Large B Cell Lymphoma DOI Creative Commons
Zanzan Wang,

Yurong Bao,

Zhijuan Xu

и другие.

Journal of Inflammation Research, Год журнала: 2024, Номер Volume 17, С. 1 - 13

Опубликована: Янв. 1, 2024

Purpose: This study aimed to examine the predictive ability of inflammatory and nutritional markers further establish a novel prognostic scoring (INPS) system. Patients Methods: We collected clinicopathological baseline laboratory data 352 patients with DLBCL between April 2010 January 2023 at First affiliated hospital Ningbo University. Eligible were randomly divided into training validation cohorts (n = 281 71, respectively) in an 8:2 ratio. used least absolute shrinkage selection operator (LASSO) Cox regression model determine most important factors among eight inflammatory-nutritional variables. The impact INPS on OS was evaluated using Kaplan–Meier curve Log rank test. A nomogram developed based multivariate method. Then, we concordance index (C-index), calibration plot, time-dependent receiver operating characteristic (ROC) analysis evaluate performance accuracy nomogram. Results: Seven biomarkers, including neutrophil-lymphocyte ratio (NLR), (PNI), body mass (BMI), monocyte-lymphocyte (MLR), prealbumin, C reactive protein, D-dimer selected LASSO construct INPS, In analysis, IPI-High-intermediate group, IPI-High high independently associated OS, respectively. for overall survival consisting above two indicators showed excellent discrimination. C-index 0.94 0.95 cohorts. ROC curves that better than NCCN-IPI Conclusion: seven indexes reliable convenient predictor outcomes patients. Keywords: diffuse large B cell lymphoma, biomarker, nomograms,

Язык: Английский

Процитировано

0
Comparison of Cox regression and generalized Cox regression models to machine learning in predicting survival of children with diffuse large B-cell lymphoma DOI Open Access

Jia-Jia Qin,

Xiao-Xiao Zhu,

Xi Chen

и другие.

Translational Cancer Research, Год журнала: 2024, Номер 13(7), С. 3370 - 3381

Опубликована: Июль 1, 2024

Background: The incidence of diffuse large B-cell lymphoma (DLBCL) in children is increasing globally. Due to the immature immune system children, prognosis DLBCL quite different from that adults. We aim use multicenter retrospective analysis for study disease. Methods: For our analysis, we retrieved data Surveillance, Epidemiology and End Results (SEER) database included 836 patients under 18 years old who were treated at 22 central institutions between 2000 2019. randomly divided into a modeling group validation based on ratio 7:3. Cox stepwise regression, generalized regression eXtreme Gradient Boosting (XGBoost) used screen all variables. selected prognostic variables construct nomogram through regression. importance was ranked using XGBoost. predictive performance model assessed by C-index, area curve (AUC) receiver operating characteristic (ROC) curve, sensitivity specificity. consistency evaluated calibration curve. clinical practicality verified decision (DCA). Results: ROC demonstrated models except non-proportional hazards non-log linearity (NPHNLL) model, achieved AUC values above 0.7, indicating high accuracy. DCA further confirmed strong practicability. Conclusions: In this study, successfully constructed machine learning combining XGBoost with models. This integrated approach accurately predicts multiple dimensions. These findings provide scientific basis accurate prediction.

Язык: Английский

Процитировано

0
Clinical scoring systems, molecular subtypes and baseline [18F]FDG PET/CT image analysis for prognosis of diffuse large B-cell lymphoma DOI Creative Commons
Zhenliang Sun, Tianshuo Yang,

Chongyang Ding

и другие.

Cancer Imaging, Год журнала: 2024, Номер 24(1)

Опубликована: Дек. 18, 2024

Abstract Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous hematological malignancy resulting in range of outcomes, and the early prediction these outcomes has important implications for patient management. Clinical scoring systems provide most commonly used prognostic evaluation criteria, value genetic testing also been confirmed by in-depth research on molecular typing. [ 18 F]-fluorodeoxyglucose positron emission tomography / computed ([ F]FDG PET/CT) an invaluable tool predicting DLBCL progression. Conventional baseline image-based parameters machine learning models have FDG PET/CT studies DLBCL; however, numerous shown that combinations clinical systems, subtypes, based image may better predictions aid decision-making patients with DLBCL.

Язык: Английский

Процитировано

0