Prognostic nomogram incorporating inflammatory cytokines for overall survival in patients with aggressive non-Hodgkin's lymphoma

A study of the relationship between circulating cytokines (interleukin-2 receptor and tumor necrosis factor receptor 2) and risk of B-cell non-hodgkin lymphoma

Mature B-cell non-Hodgkin lymphoma (B-NHL) occurs due to uncontrolled B-lymphocyte clonal expansion. Cytokines can directly stimulate B-cell proliferation and prevent B-cell apoptosis. Dysregulation of cytokines may play an important role in the development of B-NHL by enhancing chromosomal translocation, which is the hallmark of B-NHL. Both interleukin 2 and tumor necrosis factor-α are proinflammatory cytokines and play important roles in the growth, differentiation, and apoptosis of B cells.We conducted a prospective case-control study applied to 50 patients with B-NHL at Kasr Al Aini Hospital, Cairo University, and 50 age- and sex-matched controls. Clinical, laboratory and imaging data were collected. In all patients and controls, sIL-2R and sTNF-R2 levels were measured by enzyme-linked immunosorbent assay (ELISA). The Spearman correlation test was used to evaluate the correlation between the studied cytokines and clinical, laboratory and imaging findings. Sensitivity analysis was conducted to detect the cutoff values of the studied cytokines.Serum levels of sIL-2R and sTNF-R2 were significantly higher in patients than in controls. Additionally, their levels were significantly higher in aggressive types and advanced stages of lymphoma. Also, the studied cytokines were significantly correlated with different clinical and laboratory parameters of lymphoma. The level of sIL-2R and sTNF-R2 were closely related to the type of lymphoma (P value ˂ 0.001 and 0.012, respectively), further it was also associated with the natural history of lymphoma (aggressive vs. indolent) (P value ˂0.001 and 0.04 respectively).We concluded that Pretreatment levels of sIL-2R and sTNF-R2 may play a role in the natural history and prognosis of lymphoma. They may be used as a prognostic factor for B-NHL patients and may also help with treatment decisions.

Should we use nomograms for risk predictions in diffuse large B cell lymphoma patients? A systematic review

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

Characterization of primary small intestinal lymphoma: a retrospective study based on double balloon endoscopy

BACKGROUND

The diagnosis of primary small intestinal lymphoma (PSIL) is difficult. This study aimed to evaluate the clinical, radiological and endoscopic characteristics of PSIL and provide clue for diagnosis.

METHODS

A total of 30 patients diagnosed with PSIL who underwent double balloon endoscopy (DBE) in the First Affiliated Hospital of Zhejiang University were retrospectively analyzed. Clinical, radiological and endoscopic data were collected. Univariate analysis was used to determine significant indicators for differentiating three main subtypes of PSIL. Cox regression analysis was performed to assess the risk factors for survival.

RESULTS

In this study, 10 patients were pathologically diagnosed as diffuse large B-cell lymphoma (DLBCL), 11 were indolent B-cell lymphoma (BCL) and 9 were T-cell lymphoma (TCL). Compared with DLBCL patients, the body mass index (BMI) of TCL patients was significantly lower (p = 0.004). Meanwhile, compared with patients with DLBCL, the patients with indolent BCL had lower levels of C-reactive protein, lactate dehydrogenase (LDH), fibrinogen and D-Dimer (p = 0.004, p = 0.004, p = 0.006, and p = 0.002, respectively), and lower proportion of thicker intestinal wall and aneurysmal dilation in CT scan (p = 0.003 and p = 0.020, respectively). In terms of ulcer morphology, patients with DLBCL had significantly higher proportion of deep ulcers than patients with indolent BCL (p = 0.020, respectively). Cox regression analysis showed that drink (p = 0.034), concomitant colonic ulcers (p = 0.034) and elevated LDH (p = 0.043) are risk factors for mortality in patients with PSIL.

CONCLUSIONS

This study provides clinical characteristics of patients with PSIL. Thicker intestinal wall and aneurismal dilation detected on CT scan and deeper ulcer on DBE examination helps to establish a diagnosis of DLBCL.

Clinical significance of systemic inflammation response index and platelet-lymphocyte ratio in patients with adenocarcinoma of the esophagogastric junction and upper gastric cancer

Background

Tumor immunity plays an important role in assessing the tumor progression. The purpose of this study was to investigate the prognostic value of combined systemic inflammation response index (SIRI) and platelet-lymphocyte ratio (PLR) of gastroesophageal junction cancer (AEG) and upper gastric cancer (UGC) patients.

Methods

In this retrospective study, patients from 2003 to 2014 were divided into training and validation sets. The prognostic accuracy of each variable was compared using time-independent ROC analysis. The scoring system was calculated by cut-off values of SIRI and PLR in 5-year. Kaplan-Meier and Log-rank tests were used to analyze overall survival (OS). Chi-square test was used to analyze the association between clinical characteristics and the scoring system. Univariate and multivariate analyses based on the competitive risk regression model were used to analyze independent predictors of death due to AGC and UGC. R software was used to construct the Nomogram model of risk assessment.

Results

Patients with SIRI-PLR = 2 had worse survival time than those with 0 and 1 (P < 0.001) and more suitable for postoperative adjuvant chemotherapy (P = 0.002). High PLR patients were more suitable for proximal gastrectomy (P = 0.049). SIRI-PLR were independent predictors in training set (P < 0.001), which could be combined with age, pTNM stage and postoperative chemotherapy to construct Nomogram for predicting OS.

Conclusions

Preoperative SIRI-PLR score was an independent predictor for patients with AEG and UGC. The Nomogram model constructed by age, SIRI-PLR, pTNM stage and postoperative chemotherapy can correctly predict the prognosis of patients.

Predictive Modelling of Overall Survival in Adult Patients with Primary Diffuse Large B-cell Lymphoma of the Breast Using the Surveillance, Epidemiology, and End Results (SEER) Database

OBJECTIVE

We aimed to identify critical clinical features to develop an accurate webbased prediction model for estimating the overall survival (OS) of primary breast diffuse large Bcell lymphoma (PB-DLBCL) adult patients.

METHODS

We first included all PB-DLBCL cases with available covariates retrieved from the Surveillance, Epidemiology, and End Results database. We sequentially performed univariate and multivariate Cox regression approaches to identify the predictors independently associated with prognosis, and all the predictors that passed these tests were then constructed to build a nomogram for predicting 3-, 5-, and 10-year survival rates of patients. The C-index and the receiver operating characteristic curve (ROC) were used to evaluate the prediction discrimination, and the calibration curve was applied to estimate the calibration.

RESULTS

A total of PB-DLBCL adult patients were included (median age was 69 with the interquartile range [IQR] of 57-79 years), of which 466 (70%) were randomly allocated to the development cohort, and the remaining cases were collected for validation. Using three identified independent predictors (i.e., age, stage, and radiation), an accurate nomogram for predicting OS was developed and validated. The C-indices of our nomogram were both relatively acceptable, with 0.74 (95% CI: 0.71-0.78) and 0.72 (95% CI: 0.70-0.75) for the development and validation cohorts, respectively. The calibration curves also accurately predicted the prognosis of PB-DLBCL in all cases. In addition, ROC curves showed our nomogram to possess superior predictive ability compared to any single variable. To visually present this prediction model, a convenient webbased tool was implemented based on our prognostic nomogram.

CONCLUSION

For patients with PB-DLBCL, a more convenient and accurate web-based prediction model was developed and validated, which showed relatively good performances in both discrimination and calibration during model development and validation. External evaluation and validation are warranted by further independent studies.

Development and validation of prediction model for overall survival in patients with lymphoma: a prospective cohort study in China

OBJECTIVE

The survival of patients with lymphoma varies greatly among individuals and were affected by various factors. The aim of this study was to develop and validate a prognostic model for predicting overall survival (OS) in patients with lymphoma.

METHODS

We conducted a prospective longitudinal cohort study in China between January 2014 and December 2018 (n = 1,594). After obtaining the follow-up data, we randomly split the cohort into the training cohort (n = 1,116) and the validation cohort (n = 478). The least absolute shrinkage and selection operator (LASSO) regression analysis was used to select the predictors of the model. Cox stepwise regression analysis was used to identify independent prognostic factors, which were finally displayed as static nomogram and web-based dynamic nomogram. We calculated the concordance index(C-index) to describe how the predicted survival of objectively confirmed prognosis. The calibration plot is used to evaluate the prediction accuracy and discrimination ability of the model. Net reclassification index (NRI) and decision curve analysis (DCA) curves were also used to evaluate the prediction ability and net benefit of the model.

RESULTS

Nine variables in the training cohort were considered to be independent risk factors for patients with lymphoma in the final model: age, Ann Arbor Stage, pathologic type, B symptoms, chemotherapy, targeted therapy, lactate dehydrogenase (LDH), β2-microglobulin and C-reactive protein (CRP). The C-indices of OS were 0.749 (95% CI, 0.729-0.769) in the training cohort and 0.731 (95% CI, 0.762-0.700) in the validation cohort. A good agreement between prediction by nomogram and actual observation was shown in the calibration curve for the probability of survival in both the training cohort and validation cohorts. The areas under curve (AUC) of the area under the receiver operating characteristic (ROC) curves for 1-year, 3-year, and 5-year OS were 0.813, 0.800, and 0.762, respectively, in the training cohort, and 0.802, 0.768, and 0.721, respectively, in the validation cohort. Compared with the Ann Arbor Stage system, NRI and DCA showed that the model had a higher predictive capacity and net benefit.

CONCLUSION

The prediction models reliably estimate the outcome of patients with lymphoma. The model had high discrimination and calibration, which provided a simple and reliable tool for the survival prediction of the patients, and it might help patients benefit from personalized intervention.

A novel nomogram for predicting overall survival in peripheral T cell lymphoma patients.. [DOI: 10.21203/rs.3.rs-2823604/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background The prognosis of peripheral T cell lymphomas (PTCLs) varies greatly. This study aimed at generating a prognostic nomogram based on differentially expressed genes (DEGs).Methods Firstly, we collected RNA transcripts from Gene Expression Omnibus and identified DEGs. Secondly we used univariate Cox regression, Least absolute shrinkage and selection operator (LASSO) to screen the independent risk factors to construct nomogram in the training cohort. Thirdly, we evaluate its prediction accuracy via decision curves analysis (DCA), receiver operating characteristic (ROC) and calibration rate to confirm its performance on survival in training and validation cohort. Then we carried out subgroup analysis in training and validation to eliminate the effects of age, gender, and pathological subtype. Lastly, to verify feasibility of nomogram in practice, we applied immunohistochemistry to clinical samples and analyzed the relationship between IHC scores and prognosis.Results The 702 DEGs between 40 PTCLs and 20 non-tumor patients were identified. Then ANGPTL2, CPSF4, CLIC4 and OTUD6B were screened out as independent risk factors via univariate Cox regression and LASSO. The DCA, ROC, Harrell’s concordance index (c-index) and calibration rate showed nomogram predicting more accurately than any single specific transcript. The results showed PTCLs with higher nomogram-score had a longer survival, regardless of age, gender and pathological subtype. Finally, the high expression level of ANGPTL2, CPSF4 and OTUD6B related to poor prognosis. Higher expression of CLIC4 related to longer survival.Conclusion This nomogram showed the favorable clinical applicability, regardless of age, gender and pathological subtype.

A new prognostic nomogram in patients with mucosa-associated lymphoid tissue lymphoma: a multicenter retrospective study

Background

The present study sought to understand how clinical factors and inflammatory biomarkers affected the prognosis of mucosa-associated lymphoid tissue (MALT) lymphoma and develop a predictive nomogram to assist in clinical practice.

Methods

We conducted a retrospective study on 183 cases of newly diagnosed MALT lymphoma from January 2011 to October 2021, randomly divided into two groups: a training cohort (75%); and a validation cohort (25%). The least absolute shrinkage and selection operator (LASSO) regression analysis was combined with multivariate Cox regression analysis to construct a nomogram for predicting the progression-free survival (PFS) in patients with MALT lymphoma. To evaluate the accuracy of the nomogram model, the area under the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used.

Results

The PFS was significantly associated with the Ann Arbor Stage, targeted therapy, radiotherapy, and platelet-to-lymphocyte ratio (PLR) in MALT lymphoma. These four variables were combined to establish a nomogram to predict the PFS rates at three and five years. Importantly, our nomogram yielded good predictive value with area under the ROC curve (AUC) values of 0.841 and 0.763 in the training cohort and 0.860 and 0.879 in the validation cohort for the 3-year and 5-year PFS, respectively. Furthermore, the 3-year and 5-year PFS calibration curves revealed a high degree of consistency between the prediction and the actual probability of relapse. Additionally, DCA demonstrated the net clinical benefit of this nomogram and its ability to identify high-risk patients accurately.

Conclusion

The new nomogram model could accurately predict the prognosis of MALT lymphoma patients and assist clinicians in designing individualized treatments.

Construction and Validation of a Novel Nomogram for Predicting the Recurrence of Diffuse Large B Cell Lymphoma Treated with R-CHOP

Purpose

To explore recurrence-risk factors of diffuse large B cell lymphoma (DLBCL) and construct a risk nomogram for predicting recurrence.

Patients and Methods

A retrospective analysis was performed on 228 DLBCL patients who achieved complete remission after R-CHOP treatment between January 2015 and December 2019. Univariate and multivariate analyses were applied to identify recurrence-related risk factors from the pretreatment evaluation factors covering patients' demographic characteristics, clinical manifestations, serological indicators, pathological and immunohistochemical results. A nomogram was developed based on the above results and validated by the concordance index (C-index), the receiver operating characteristic (ROC) curve, and the calibration curve.

Results

The training and validation cohorts consisted of 160 and 68 patients (randomized by 7:3). Of the whole cohort, 50 of 228 (21.9%) cases recurred during follow-up. Three recurrence-risk factors including BCL2 expression (P = 0.027), CD10 expression (P = 0.021), LDH level (P = 0.004) were identified from multivariate analysis and entered the final nomogram. The C-index of the nomogram was 0.815 in training cohort and 0.797 in the validation cohort, higher than that of IPI system (0.699) and NCCN-IPI system (0.709). And the 1-year, 2-year, 3-year, and 4-year areas under ROC (AUC) were 0.812, 0.850, 0.837, and 0.801, respectively. The calibration curves also showed a good discrimination capability and accuracy.

Conclusion

The novel nomogram incorporating the three independent risk factors (BCL2 expression, CD10 expression and LDH level) provided a valuable tool for predicting DLBCL recurrence.

Targeting positive cofactor 4 induces autophagic cell death in MYC-expressing diffuse large B-cell lymphoma

MYC-expressing diffuse large B-cell lymphoma (DLBCL) is one of the refractory lymphomas. Currently, the pathogenesis of MYC-expressing DLBCL is still unclear, and there is a lack of effective therapy. We characterized positive cofactor 4 (PC4) as an upstream regulator of c-Myc, and PC4 is overexpressed in DLBCL and is closely related to clinical staging, prognosis, and c-Myc expression. Furthermore, our in vivo and in vitro studies revealed that PC4 knockdown can induce autophagic cell death and enhance the therapeutic effect of doxorubicin in MYC-expressing DLBCL. Inhibition of c-Myc-mediated aerobic glycolysis and activation of the AMPK/mTOR signaling pathway are responsible for the autophagic cell death induced by PC4 knockdown in MYC-expressing DLBCL. Using dual-luciferase reporter assay and electrophoretic mobility shift assay assays, we also found that PC4 exerts its oncogenic functions by directly binding to c-Myc promoters. To sum up, our study provides novel insights into the functions and mechanisms of PC4 in MYC-expressing DLBCL and suggests that PC4 may be a promising therapeutic target for MYC-expressing DLBCL.

Clinical Characteristics, Outcomes, and Risk Factors for Patients with Diffuse Large B-Cell Lymphoma and Development of Nomogram to Identify High-Risk Patients

OBJECTIVES

To analyse the clinical features, outcomes, and risk factors of patients with diffuse large B-cell lymphoma (DLBCL) in China, with the aim to establish a new prognostic model based on risk factors.

METHODS

Clinical features and outcomes of 564 patients newly diagnosed with DLBCL from Jan 2009 to May 2017 were analyzed retrospectively. Variables were screened by LASSO regression and nomogram was constructed.

RESULTS

The 5-year overall survival (OS) of the cohort was 75%. The 5-year OS of patients differentiated by International Prognostic Index (IPI) score was 90% (score 0-2), 73% (score 3), and 51% (score 4-5), respectively. Age > 60, Eastern Cooperative Oncology Group (ECOG) > 1, Ann Arbor stage III-IV, bone marrow involvement, low level of albumin (ALB), and lymphatic/monocyte ratio (LMR) were independent predictors of OS. The predictive model was developed based on factors including age, bone marrow involvement, LMR, ALB, and ECOG scores. The predictive ability of the model (AUC, 0.77) was better than that of IPI (AUC, 0.74) and NCCN-IPI (AUC, 0.69). The 5-year OS of patients in the low-, intermediate-, and high-risk groups identified by the new predictive model was 89%, 70%, and 33%, respectively.

CONCLUSIONS

The new prediction model had better predictive performance and could better identify high-risk patients.

Integrated driver mutations profile of chinese gastrointestinal-natural killer/T-cell lymphoma

Background

One of the most common nasal external sites in extranodal Natural Killer/T-cell lymphoma (NKTCL) is in the gastrointestinal (GI) system. Despite this, reports on gastrointestinal-Natural Killer/T-cell lymphoma (GI-NKTCL) are very few. To obtain a better understanding of this manifestation of NKTCL, we conducted a retrospective study on GI-NKTCL to analyze its clinical features, genomic changes and immune infiltration.

Methods

We retrospectively collected patients diagnosed with GI-NKTCL in the Sixth Affiliated Hospital of Sun Yat-sen University from 2010 to 2020. From this cohort we obtained mutation data via whole exome sequencing.

Results

Genomic analysis from 15 patients with GI-NKTCL showed that the most common driving mutations were ARID1B(14%, 2/15), ERBB3(14%, 2/15), POT1(14%, 2/15), and TP53(14%, 2/15). In addition, we found the most common gene mutation in patients with GI-NKTCL to be RETSAT(29%, 4/15) and SNRNP70(21%, 3/15), and the most common hallmark pathway mutations to be G2M checkpoint pathway (10/15, 66.7%), E2F targets (8/15, 53.3%), estrogen response late (7/15, 46.7%), estrogen response early (7/15, 46.7%), apoptosis (7/15, 46.7%) and TNFA signaling via NFKB (7/15, 46.7%). In the ICIs-Miao cohort, SNRNP7-wild-type (WT) melanoma patients had significantly prolonged overall survival (OS) time compared with SNRNP7 mutant type (MT) melanoma patients. In the TCGA-UCEC cohort, the patients with RETSAT-MT or SNRNP7-MT had significantly increased expression of immune checkpoint molecules and upregulation of inflammatory immune cells.

Conclusions

In this study, we explored GI-NKTCL by means of genomic analysis, and identified the most common mutant genes (RETSAT and SNRNP70), pathway mutations (G2M checkpoint and E2F targets) in GI-NKTCL patients. Also, we explored the association between the common mutant genes and immune infiltration. Our aim is that our exploration of these genomic changes will aid in the discovery of new biomarkers and therapeutic targets for those with GI-NKTCL, and finally provide a theoretical basis for improving the treatment and prognosis of patients with GI-NKTCL.

Development and validation of a nomogram to predict the risk of death within 1 year in patients with non-ischemic dilated cardiomyopathy: a retrospective cohort study

Predicting the chances mortality within 1 year in non-ischemic dilated cardiomyopathy patients can be very useful in clinical decision-making. This study has developed and validated a risk-prediction model for identifying factors contributing to mortality within 1 year in such patients. The predictive nomogram was constructed using a retrospective cohort study, with 615 of patients hospitalized in the First Affiliated Hospital of Guangxi Medical University between October 2012 and May 2020. A variety of factors, including presence of comorbidities, demographics, results of laboratory tests, echocardiography data, medication strategies, and instances of heart transplant or death were collected from electronic medical records and follow-up telephonic consultations. The least absolute shrinkage and selection operator and logistic regression analyses were used to identify the critical clinical factors for constructing the nomogram. Calibration, discrimination, and clinical usefulness of the predictive model were assessed using the calibration plot, C-index and decision curve analysis. Internal validation was assessed with bootstrapping validation. Among the patients from whom follow-up data were obtained, the incidence of an end event (deaths or heart transplantation within 1 year) was 171 cases per 1000 person-years (105 out of 615). The main predictors included in the nomogram were pulse pressure, red blood cell count, left ventricular end-diastolic dimension, levels of N-terminal pro b-type natriuretic peptide, medical history, in-hospital worsening heart failure, and use of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers. The model showed excellent discrimination with a C-index of 0.839 (95% CI 0.799-0.879), and the calibration curve demonstrated good agreement. The C-index of internal validation was 0.826, which demonstrated that the model was quite efficacious. A decision curve analysis confirmed that our nomogram was clinically useful. In this study, we have developed a nomogram that can predict the risk of death within 1 year in patients with non-ischemic dilated cardiomyopathy. This will be useful in the early identification of patients in the terminal stages for better individualized clinical decisions.

Prognostic Nomogram for Patients with Hepatitis E Virus-related Acute Liver Failure: A Multicenter Study in China

BACKGROUND AND AIMS

Timely and effective assessment scoring systems for predicting the mortality of patients with hepatitis E virus-related acute liver failure (HEV-ALF) are urgently needed. The present study aimed to establish an effective nomogram for predicting the mortality of HEV-ALF patients.

METHODS

The nomogram was based on a cross-sectional set of 404 HEV-ALF patients who were identified and enrolled from a cohort of 650 patients with liver failure. To compare the performance with that of the model for end-stage liver disease (MELD) scoring and CLIF-Consortium-acute-on-chronic liver failure score (CLIF-C-ACLFs) models, we assessed the predictive accuracy of the nomogram using the concordance index (C-index), and its discriminative ability using time-dependent receiver operating characteristics (td-ROC) analysis, respectively.

RESULTS

Multivariate logistic regression analysis of the development set carried out to predict mortality revealed that γ-glutamyl transpeptidase, albumin, total bilirubin, urea nitrogen, creatinine, international normalized ratio, and neutrophil-to-lymphocyte ratio were independent factors, all of which were incorporated into the new nomogram to predict the mortality of HEV-ALF patients. The area under the curve of this nomogram for mortality prediction was 0.671 (95% confidence interval: 0.602-0.740), which was higher than that of the MELD and CLIF-C-ACLFs models. Moreover, the td-ROC and decision curves analysis showed that both discriminative ability and threshold probabilities of the nomogram were superior to those of the MELD and CLIF-C-ACLFs models. A similar trend was observed in the validation set.

CONCLUSIONS

The novel nomogram is an accurate and efficient mortality prediction method for HEV-ALF patients.

Nomogram Based on Lactate Dehydrogenase-to-Albumin Ratio (LAR) and Platelet-to-Lymphocyte Ratio (PLR) for Predicting Survival in Nasopharyngeal Carcinoma

Purpose

The prognosis of inflammation-related indicators like lactate dehydrogenase/albumin ratio (LAR) and the platelet/lymphocyte ratio (PLR) in nasopharyngeal carcinoma (NPC) is not yet clear. Our objective is to establish and verify the nomogram using LAR and PLR ratio for the first time to explore the prognostic value in NPC.

Patients and Methods

This was a retrospective collection of 1661 patients with non-metastatic NPC admitted to our hospital from 2010 to 2017. The final variables of overall survival (OS) and progression-free survival (PFS) were selected by Cox regression analysis to establish nomograms, and the methods to verify the prediction precision and discriminative ability of the nomograms were concordance index (C index), the receiver operating characteristic (ROC) curve and calibration curve. The risk stratification was carried out through the nomograms and compared with the current staging system by the Kaplan–Meier methods.

Results

Multivariate Cox analysis resulted that age, plasma Epstein–Barr Virus (EBV) DNA, T stage, N stage, white blood cells (WBC), PLR and LAR were independent prognostic risk factors for OS and PFS, and sex is an independent prognostic risk factor for OS. The C-indexes of OS nomogram were 0.722 (95% CI: 0.706–0.738) and 0.747 (95% CI: 0.717–0.777) in the training cohort and validation cohort, which were statistically higher than the current 8th AJCC staging system (0.646 and 0.688). The C-indexes of PFS nomogram were 0.696 (95% CI: 0.680–0.713) and 0.690 (95% CI: 0.660–0.720), which were also statistically higher than the current 8th AJCC staging system (0.632 and 0.666). Otherwise, ROC curves and the calibration curve for probability also confirmed satisfied consistency with actual observations.

Conclusion

LAR is a novel useful independent factor in NPC. The proposed nomogram LAR and PLR resulted in more accurate prognostic prediction than current staging system for NPC patients.

Prognostic Value of Peripheral Blood Lymphocyte/monocyte Ratio in Lymphoma

Objective: Lymphocyte monocyte ratio (LMR) has been considered as a prognostic factor in patients with lymphoma, which focused on diffuse large B-cell lymphoma (DLBCL) and Hodgkin lymphoma (HL). Recently, many relevant clinical studies have been published with inconsistent results. To gain a more comprehensive view of the prognostic value of LMR, we conducted a meta-analysis on the significance of peripheral LMR in all subtypes of lymphoma.

Methods: PubMed, PMC, Web of Science, Embase, and Cochrane Library were searched for relevant articles to conduct a meta-analysis. Hazard ratio (HR) and its 95% confidence interval (CI) of OS and PFS were extracted and pooled on stata12.1.

Results: In the meta-analysis, forty studies were eligible and a total of 10446 patients were included. Low LMR was associated with an inferior OS (HR=2.45, 95%CI 1.95-3.08) and PFS (HR=2.36, 95%CI 1.94-2.88). In the analysis of lymphoma subtypes, similar results were seen in HL, NHL, and its subtypes including DLBCL, NK/T cell lymphoma, and follicular lymphoma. In addition, low LMR was related with higher LDH (OR=2.26, 95%CI 1.66-3.09), advanced tumor staging (OR=0.41, 95%CI 0.36-0.46), IPI score (OR=0.40, 95%CI 0.33-0.48), but not with bone marrow involvement (OR=1.24, 95%CI 0.85-1.81) or pathological subtype (OR=0.69, 95%CI 0.41-1.16).

Conclusion: Low LMR in peripheral blood indicates poor prognosis in patients with lymphoma. As a simple clinical indicator, peripheral blood LMR combined with existing prognostic factors can improve the accuracy of lymphoma prognosis assessment.

Efficacy of traditional herbal medicine versus transcatheter arterial chemoembolization in postsurgical patients with hepatocellular carcinoma: A retrospective study

BACKGROUND

Recurrence is a major obstacle to improve the prognosis of hepatocellular carcinoma (HCC) patients. Transcatheter arterial chemoembolization (TACE) has been routinely used as an adjuvant therapy in treating HCC, but efficacy of TACE in preventing the recurrence of HCC remains unsatisfactory. This study aimed to compare the efficacy of a traditional herbal medicine (THM) therapy and TACE in preventing tumor recurrence and improving survival in postsurgical patients with HCC.

MATERIALS AND METHODS

A total of 1506 HCC patients were enrolled from January 2008 to June 2017, including 262 patients who received THM therapy and 1244 patients who were treated with TACE. All patients were followed up until the occurrence of outcome event or June 30th, 2019. The recurrence-free survival (RFS) and overall survival (OS) were calculated by the Kaplan-Meier method, and the differences of RFS and OS between THM group and TACE group were analyzed by the log-rank test. Factors affecting the RFS or OS among these patients were assessed by the Cox proportional hazard regression model. A nomogram was built with the factors based on the Cox regression analysis to predict the prognosis.

RESULTS

The 1-, 3-, and 5-year RFS were 91.0%, 68.3%, and 49.7%, respectively, in the THM group and 79.4%, 38.6%, and 19.3%, respectively, in the TACE group. The RFS in the THM group was significantly higher than that of the TACE group (P = 6.2 × 10^-11). The 1-, 3-, and 5-year OS were significantly improved in the THM group as compared to those in the TACE group (94.3%, 65.2%, and 41.4% vs. 82.7%, 46.0%, and 25.4%, P = 2.2 × 10^-11). Multivariate analysis revealed that serum AFP level ≥400 ng/mL, HBV DNA load ≥500 copies/mL, TNM stage III-IV, tumor diameter ≥5 cm, presence of MVI, and multiple tumor nodules were independent risk factors for RFS, while complete tumor encapsulation and THM therapy were protective factors for RFS and OS. The nomogram demonstrated good accuracy in predicting RFS and OS, with the adjusted C-index of 0.748 and 0.796, respectively.

CONCLUSION

The efficacy of THM therapy was superior to that of TACE in preventing recurrence and improving survival for HCC patients after hepatectomy.

A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation

BACKGROUND

The use of anticoagulants and antiplatelet therapies is associated with a higher risk of bleeding in atrial fibrillation (AF) patients after percutaneous coronary intervention, especially after stent implantation. However, no accurate bleeding risk prediction tool has been developed for these patients. The aim of this study was thus to establish a bleeding risk prediction model (predictive nomogram) for patients with AF after stent implantation.

METHODS

Construction of the predictive nomogram was based on a retrospective study, which enrolled 943 AF patients who underwent drug-eluting stent implantation between May 2012 and September 2016. A range of factors, including demographics, comorbidities, medication strategies, arterial access, and laboratory tests, were collected as baseline data. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis were used to identify the key clinical features for construction of the predictive nomogram. The concordance index (C-index) and internal validation were used to evaluate the efficacy of the nomogram.

RESULTS

Of the 943 AF patients that underwent stent implantation, the occurrence of bleeding events was 8.2% (77 out of 943). Key predictors included the number of antiplatelet drugs, peptic ulcer, cerebral infarction, type 2 diabetes, thrombocytopenia, anemia, prior myocardial infarction, sex (male), use of anticoagulant drugs, liver dysfunction, hypertension, and acute myocardial infarction. These predictors were used to construct the nomogram. The C-index for the prediction of bleeding risk by the nomogram was 0.841 (95% CI: 0.79-0.89), which indicated good discrimination and calibration. The C-index of internal validation was 0.795, which demonstrated good efficacy of the model.

CONCLUSIONS

This study suggests that our novel nomogram can accurately predict bleeding risk in AF patients after stent implantation during hospitalization, thereby helping to avoid complications. The nomogram may also be helpful for the creation of individualized post-discharge medication strategies.

Development and Validation of a Novel Risk Stratification Model for Cancer-Specific Survival in Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogenous disease. Identifying more precise and individual survival prognostic models are still needed. This study aimed to develop a predictive nomogram and a web-based survival rate calculator that can dynamically predict the long-term cancer-specific survival (CSS) of DLBCL patients. A total of 3,573 eligible patients with DLBCL from 2004 to 2015 were extracted from the Surveillance, Epidemiology and End Results (SEER) database. The entire group was randomly divided into the training (n = 2,504) and validation (n = 1,069) cohorts. We identified six independent predictors for survival including age, sex, marital status, Ann Arbor stage, B symptom, and chemotherapy, which were used to construct the nomogram and the web-based survival rate calculator. The C-index of the nomogram was 0.709 (95% CI, 0.692–0.726) in the training cohort and 0.700 (95% CI, 0.671–0.729) in the validation cohort. The AUC values of the nomogram for predicting the 1-, 5-, and 10- year CSS rates ranged from 0.704 to 0.765 in both cohorts. All calibration curves revealed optimal consistency between predicted and actual survival. A risk stratification model generated based on the nomogram showed a favorable level of predictive accuracy compared with the IPI, R-IPI, and Ann Arbor stage in both cohorts according to the AUC values (training cohort: 0.715 vs 0.676, 0.652, and 0.648; validation cohort: 0.695 vs 0.692, 0.657, and 0.624) and K-M survival curves. In conclusion, we have established and validated a novel nomogram risk stratification model and a web-based survival rate calculator that can dynamically predict the long-term CSS in DLBCL, which revealed more discriminative and predictive accuracy than the IPI, R-IPI, and Ann Arbor stage in the rituximab era.

CREBBP/EP300 mutations promoted tumor progression in diffuse large B-cell lymphoma through altering tumor-associated macrophage polarization via FBXW7-NOTCH-CCL2/CSF1 axis

Epigenetic alterations play an important role in tumor progression of diffuse large B-cell lymphoma (DLBCL). However, the biological relevance of epigenetic gene mutations on tumor microenvironment remains to be determined. The core set of genes relating to histone methylation (KMT2D, KMT2C, EZH2), histone acetylation (CREBBP, EP300), DNA methylation (TET2), and chromatin remodeling (ARID1A) were detected in the training cohort of 316 patients by whole-genome/exome sequencing (WGS/WES) and in the validation cohort of 303 patients with newly diagnosed DLBCL by targeted sequencing. Their correlation with peripheral blood immune cells and clinical outcomes were assessed. Underlying mechanisms on tumor microenvironment were investigated both in vitro and in vivo. Among all 619 DLBCL patients, somatic mutations in KMT2D (19.5%) were most frequently observed, followed by mutations in ARID1A (8.7%), CREBBP (8.4%), KMT2C (8.2%), TET2 (7.8%), EP300 (6.8%), and EZH2 (2.9%). Among them, CREBBP/EP300 mutations were significantly associated with decreased peripheral blood absolute lymphocyte-to-monocyte ratios, as well as inferior progression-free and overall survival. In B-lymphoma cells, the mutation or knockdown of CREBBP or EP300 inhibited H3K27 acetylation, downregulated FBXW7 expression, activated the NOTCH pathway, and downstream CCL2/CSF1 expression, resulting in tumor-associated macrophage polarization to M2 phenotype and tumor cell proliferation. In B-lymphoma murine models, xenografted tumors bearing CREBBP/EP300 mutation presented lower H3K27 acetylation, higher M2 macrophage recruitment, and more rapid tumor growth than those with CREBBP/EP300 wild-type control via FBXW7-NOTCH-CCL2/CSF1 axis. Our work thus contributed to the understanding of aberrant histone acetylation regulation on tumor microenvironment as an alternative mechanism of tumor progression in DLBCL.

Development and Validation of Prognostic Nomograms for Patients with Primary Gastrointestinal Non-Hodgkin Lymphomas

BACKGROUND AND AIMS

The objective of this study was to construct and authenticate nomograms to project overall survival (OS) and cancer-specific survival (CSS) in primary gastrointestinal non-Hodgkin lymphomas (PGINHL).

METHODS

Suitable patients were chosen from the Surveillance, Epidemiology and End Results database and Wannan Medical College Yijishan Hospital. The Cox regression model was used to acquire independent predictive factors to develop nomograms for projecting OS and CSS. The performance of the nomograms was validated using the Harrell's concordance index (C-index), calibration curves, and decision curve analysis (DCA) and was compared with that of the AJCC 7th staging system. Survival curves were obtained using the Kaplan-Meier method, while the log-rank test was used to compare the difference among the groups.

RESULTS

The C-index of the nomograms for OS and CSS was 0.735 (95% CI = 0.719-0.751) and 0.761 (95% CI = 0.739-0.783), respectively, signifying substantial predictive accuracy. These outcomes were reproducible when the nomograms were used for the internal and external validation cohorts. Moreover, assessments of the C-index, AUC, and DCA between the nomogram results and the AJCC 7th staging system showed that the former was better for evaluation and was more clinically useful.

CONCLUSIONS

We constructed the nomogram which could predict 1-, 3-, and 5-year OS and CSS of patients with PGINHL. Our nomogram showed good performance, suggesting that it can be used as an efficacious instrument for predictive assessment of patients with PGINHL.

Prognostic significance of plasma IL-2 and sIL-2Rα in patients with first-ever ischaemic stroke

Background

An imbalance between circulating neuroprotective and neurotoxic T cell subsets leads to poor prognosis in acute ischaemic stroke (AIS). Preclinical studies have indicated that the soluble form of the interleukin-2 receptor α (sIL-2Rα)-IL-2 complex regulates T cell differentiation. However, the association between sIL-2Rα levels and AIS remains unclear.

Methods

A total of 201 first-ever AIS patients within 24 h after stroke onset and 76 control subjects were recruited. The National Institutes of Health Stroke Scale (NIHSS) score and 3-month functional outcome (modified Rankin Scale [mRS] score) at admission were assessed. Plasma sIL-2Rα and IL-2 levels at admission were measured. Prognostic significance was identified by using univariate and multivariate logistic regression analyses.

Results

Patients with poor functional outcomes at 3 months had significantly higher levels of sIL-2Rα and lower levels of IL-2 than patients with good outcomes. Moreover, sIL-2Rα levels showed a strong positive correlation with NIHSS and mRS scores (p < 0.0001), whereas IL-2 levels were negatively correlated with mRS scores (p < 0.01). Univariate analyses showed that higher sIL-2Rα and IL-2 levels were associated with an increased and reduced risk of unfavourable outcomes, respectively. After adjusting for confounding variables, the sIL-2Rα level remained independently associated with an increased risk of an unfavourable outcome, and adding sIL-2Rα levels to the conventional risk factor model significantly improved risk reclassification (net reclassification improvement 17.56%, p = 0.003; integrated discrimination improvement 5.78%, p = 0.0003).

Conclusions

sIL-2Rα levels represent a novel, independent prognostic marker that can improve the currently used risk stratification of AIS patients. Our findings also highlight that elevated plasma sIL-2Rα and IL-2 levels manifested opposite correlations with functional outcome, underlining the importance of IL-2/IL-2R autocrine loops in AIS.

Nomogram for Predicting the Overall Survival of Adult Patients With Primary Gastrointestinal Diffuse Large B Cell Lymphoma: A SEER- Based Study

Background: The aim of this study was to establish a precise prognostic model, based on significant clinical parameters, for predicting the overall survival (OS) of adult patients with primary gastrointestinal diffuse large B cell lymphoma (GI DLBCL).

Materials and Methods: The data of 7,121 GI DLBCL patients, diagnosed between 1997 and 2015, were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. These patients were randomly divided into two sequential cohorts: training (n = 5,697) set and validation (n = 1,424) set. ROC methodology and calibration curves were explicitly used to evaluate the predictive performance of nomogram.

Results: The median OS in the training cohort was 76 months (1–239 months), and 3, 5, and 10-year OS rates were 60.3, 53.9, and 39.5%, respectively. Age at diagnosis, Ann Arbor stage, and marital status were important clinical predictors of OS. These characteristics were used to build a nomogram. The AUC of the nomogram for predicting 3, 5, and 10-year OS were 0.669, 0.692, and 0.740, respectively. All RUC and calibration curves revealed good accuracy in predicting prognosis of GI DLBCL.

Conclusion: In summary, the established nomogram was validated to predict OS for adult patients with GI DLBCL. This predictive model could help clinicians identify high-risk patients to improve their prognosis.

Statistical Challenges in Development of Prognostic Models in Diffuse Large B-Cell Lymphoma: Comparison Between Existing Models - A Systematic Review

Background and Aim

Based on advances in the diagnosis, classification, and management of diffuse large B-cell lymphoma (DLBCL), a number of new prognostic models have been proposed. The aim of this study was to review and compare different prognostic models of DLBCL based on the statistical methods used to evaluate the performance of each model, as well as to analyze the possible limitations of the methods.

Methods and Results

A literature search identified 46 articles that proposed 55 different prognostic models for DLBCL by combining different clinical, laboratory, and other parameters of prognostic significance. In addition, six studies used nomograms, which avoid risk categorization, to create prognostic models. Only a minority of studies assessed discrimination and/or calibration to compare existing models built upon different statistical methods in the process of development of a new prognostic model. All models based on nomograms reported the c-index as a measure of discrimination. There was no uniform evaluation of the performance in other prognostic models. We compared these models of DLBCL by calculating differences and ratios of 3-year overall survival probabilities between the high- and the low-risk groups. We found that the highest and lowest ratio between low- and high-risk groups was 6 and 1.31, respectively, while the difference between these groups was 18.9% and 100%, respectively. However, these studies had limited duration of follow-up and the number of patients ranged from 71 to 335.

Conclusion

There is no universal statistical instrument that could facilitate a comparison of prognostic models in DLBCL. However, when developing a prognostic model, it is recommended to report its discrimination and calibration in order to facilitate comparisons between different models. Furthermore, prognostic models based on nomograms are becoming more appealing owing to individualized disease-related risk estimations. However, they have not been validated yet in other study populations.

New biomarkers in non-Hodgkin lymphoma and acute leukemias

Biomarkers play a critical role in the medical care of patients with cancer, including in early detection of the disease, diagnostic accuracy, risk stratification, treatment, and follow-up. Biomarkers in hematological malignancies can support the redefinition of the diagnosis and adjustments in the treatment plan. Biomarkers can be classified into 4 categories: (1) protein antigens, (2) cytogenetic abnormalities, (3) genetic polymorphisms, and (4) gene expression. Efforts in genomics, proteomics, and metabolomics to observe new biomarkers that contribute to the development of clinical medicine with greater precision in the strategies that improve prevention, diagnosis, and treatment of patients with malignant hematological disease. New biomarkers should accomplish several issues such as the biological plausibility, methodology used, analytical validation, intellectual property registry, and legal framework of application. This knowledge should be transferred to health professionals who can carry out the process of its implementation in clinical practice.

Development and validation of a novel nomogram to predict overall survival in gastric cancer with lymph node metastasis

Gastric cancer (GC) with lymph node metastasis (LNM) at diagnosis is associated with a unstable prognosis and indefinite survival times. The aim of the present study was to construct and validate a model for the Overall survival (OS) estimation for patients with LNM. The nomogram was constructed to predict the OS for LNM-positive GC using the primary group of 836 patients and validated using an independent cohort of 411 patients. Factors in the nomogram were identified by multivariate Cox hazard analysis. The predictive capability of nomogram was evaluated by calibration analysis and decision curve analysis. Multivariate analysis suggested that eight pre-treatment characteristics were used for developing the nomogram. In the primary cohort, the C-index for OS prediction was 0.788 (95% CI: 0.753-0.823), while in validation cohort, the C-index for OS prediction was 0.769 (95% CI: 0. 720-0.818). The calibration plot for the probability of OS and decision curve analyses showed an optimal agreement. Based on the nomogram, we could divided patients into three groups: low-risk group, middle-risk group and a high-risk group(p <0.001).Taken together, we have provided an easy-to-used and accurate tool for predicting OS, furthermore could be used for risk stratification of OS of LNM-positive GC patients.

Prognostic Nomogram and Predictive Factors in Refractory or Relapsed Diffuse Large B-Cell Lymphoma Patients Failing Front-Line R-CHOP Regimens

Background: The clinical course of relapsed or refractory (r/r) diffuse large B-cell lymphoma (DLBCL) is variable, with limited efficacy data of second-line treatment in a post-rituximab real-world context. Hence, we explored the predictors and constructed a nomogram for risk stratification in this population.

Patients and methods: Among 296 r/r DLBCL patients pretreated with R-CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) at the Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College between 2006 and 2017, 231 were included for nomogram construction. After randomization, we constructed the prognostic nomogram in the primary cohort (n=161) based on a multivariate analysis and confirmed it in the validation cohort (n=70). Additionally, we explored predictive factors for second-line therapy using a ordinal regression analysis.

Results: Four independent prognostic factors including rituximab in the second-line setting, initial Eastern Cooperative Oncology Group (ECOG) performance status (PS), response to front-line treatment, and invasion on progression/recurrence were used to construct the nomogram. The nomogram had a C index of 0.70 with AUC values of 0.73 and 0.71 for the primary and validation cohorts, respectively. Subsequently, three risk groups (low, intermediate, and high) were determined with median overall survival (OS) of 38.0, 25.0, and 7.0 months, respectively. Additionally, we conducted a multivariate ordinal regression analysis and identified prior response to front-line treatment (odds ratio=4.50, 95% CI: 1.84-11.27, p=0.001) and bulky disease at diagnosis (odds ratio=0.36, 95% CI: 0.182-0.702, p=0.003) were two independent factors for second-line treatment efficacy.

Conclusions: The established predictors for treatment efficacy and the novel nomogram for survival in r/r DLBCL patients could potentially be applied for risk stratification and treatment guidance in the post-rituximab era.