A novel prognostic index for extranodal natural killer/T-cell lymphoma in the era of pegaspargase/L-asparaginase.

Aim: This multicenter retrospective study aimed to develop a novel prognostic system for extranodal natural killer/T-cell lymphoma (ENKTL) patients in the era of pegaspargase/L-asparaginase.Materials & methods: A total of 844 newly diagnosed ENKTL patients were included.Results: Multivariable analysis confirmed that Eastern Cooperative Oncology Group performance status, lactate dehydrogenase, Chinese Southwest Oncology Group and Asia Lymphoma Study Group ENKTL (CA) system, and albumin were independent prognostic factors. By rounding up the hazard ratios from four significant variables, a maximum of 7 points were assigned. The model of Huaihai Lymphoma Working Group-Natural killer/T-cell Lymphoma prognostic index (NPI) was identified with four risk groups and the 5-year overall survival was 88.2, 66.7, 54.3 and 30.5%, respectively.Conclusion: Huaihai Lymphoma Working Group-NPI provides a feasible stratification system for patients with ENKTL in the era of pegaspargase/L-asparaginase.

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Prognostic value of prognostic nutritional index on extranodal natural killer/T-cell lymphoma patients: A multicenter propensity score matched analysis of 1022 cases in Huaihai Lymphoma Working Group.

Prognostic nutritional index (PNI), comprised of serum albumin level and lymphocyte count, is associated with the prognosis of several malignant diseases, while the prognostic value of PNI in extranodal natural killer/T cell lymphoma, nasal type (ENKTL) remains unclear. This retrospective multicenter study aimed to investigate the value of PNI in predicting the prognosis of newly diagnosed ENKTL patients by using propensity score matched analysis (PSM). A total of 1022 newly diagnosed ENKTL patients were retrieved from Huaihai Lymphoma Working Group and clinicopathological variables were collected. MaxStat analysis was used to calculate the optimal cut-off points of PNI and other continuous variables. The median age at diagnosis was 47 years and 69.4% were males, with the 5-year OS of 71.7%. According to the MaxStat analysis, 41 was the optimal cut-off point for PNI. The Pseudo R2 before matching was 0.250, and it decreased to less than 0.019 after matching. Confounding factors of the two groups were well balanced after PSM. Multivariable analysis revealed that PNI, Korean Prognostic Index (KPI), eastern cooperative oncology group performance status (ECOG PS), the prognostic index of natural killer lymphoma (PINK) and hemoglobin were independent prognostic factors for ENKTL. The results of subgroup analysis demonstrated that patients with low PNI could predict worse prognosis and re-stratify patients in ECOG PS ≥ 2, EBER-positive, the International Prognostic Index (IPI) (HIR + HR), and PINK (HR) groups. PNI combined with IPI, PINK and KPI could improve the prediction efficiency. In conclusion, PNI could accurately stratify the prognosis of ENKTL by PSM analysis and patients with low PNI had poorer prognosis.

The prognostic value of controlling nutritional status (CONUT) score-based nomogram on extranodal natural killer/T cell lymphoma patients.

Controlling nutritional status (CONUT) score as an original nutritional assessment tool can be used to assess the prognosis of patients with a variety of malignancies. However, the predictive power of CONUT in extranodal natural killer/T cell lymphoma (ENKTL) patients has never been demonstrated. Our retrospective multicenter study aimed to explore the prognostic value of CONUT in newly diagnosed ENKTL. A total of 1085 newly diagnosed ENKTL patients between 2003 and 2021 were retrospectively retrieved. Cox proportional hazard model was used to explore the prognostic factors of overall survival (OS). The survival rate of ENKTL was evaluated using Kaplan-Meier analysis, and log-rank test was applied to the difference between groups. We investigated the prognostic performance of CONUT, the International Prognostic Index (IPI), the Korean Prognostic Index (KPI), and the Prognostic Index of Natural Killer Cell Lymphoma (PINK) using the receiver operating characteristic (ROC) curve and decision curve analysis (DCA). The median age at diagnosis for the whole cohort was 47 years, and the male to female ratio was 2.2:1. The 5-year OS for all patients was 72.2%. Multivariable analysis showed that CONUT, age, bone marrow involvement, ECOG PS score, and Chinese Southwest Oncology Group and Asia Lymphoma Study Group ENKTL stage were identified as independent predictive factors for OS. Based on multivariable results, a prognostic nomogram was developed. Subgroup analysis demonstrated that patients with severe malnutrition had poorest clinical outcome. In addition, ROC curves and DCA analysis proved that compared with IPI, KPI, and PINK models, the CONUT score-based nomogram showed a better prognostic predictive efficiency of ENKTL. CONUT could effectively stratify the prognosis of ENKTL and the proposed nomogram based on CONUT was an effective prognostic model for prediction.

Disparity analysis and prognostic value of pretreatment whole blood Epstein-Barr virus DNA load and Epstein-Barr encoding region status in lymphomas: A retrospective multicenter study in Huaihai Lymphoma Working Group.

Elevated Epstein-Barr virus (EBV) DNA load is common in lymphomas. However, it remains unclear whether the disparity in viral load and its prognostic value in lymphomas are correlated with Epstein-Barr encoding region (EBER) status. In this retrospective multicenter study, we collected the data of pretreatment whole blood EBV DNA (pre-EBV DNA) and EBER status and evaluated their disparity and prognostic values in lymphomas. A total of 454 lymphoma patients from December 2014 to August 2020 were retrospectively retrieved. Mann-Whitney U test, Kruskal-Wallis test and Bonferroni's adjustment were used to explore the disparity of EBV DNA and EBER status in lymphomas. Time-dependent receiver operating characteristic analysis and MaxStat analysis were used to determine optimal cutoff points of pre-EBV DNA load. Univariable and multivariable Cox proportional hazards models were established for the estimation of prognostic factors. The positive rate of EBV DNA in natural killer T-cell lymphoma (NKTL) patients was higher than that in diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL) and Hodgkin lymphoma (HL) patients, and the median positive pre-EBV copy number of NKTL was also higher than that of FL and DLBCL. EBV DNA could clearly distinguish the prognosis of DLBCL, NKTL, HL and peripheral T-cell lymphoma, and the integration of EBER status and EBV DNA could differentiate the prognosis of HL patients. Multivariable results revealed that pre-EBV DNA load had an effect on the prognosis of NKTL, FL and DLBCL. The status of pre-EBV DNA and EBER were disparate. Whole blood pre-EBV DNA predicted the prognosis of lymphomas, and the combination of EBV and EBER status could differentiate the prognosis of HL.

Value of the prognostic nutritional index (PNI) in patients with newly diagnosed, CD5-positive diffuse large B-cell lymphoma: A multicenter retrospective study of the Huaihai Lymphoma Working Group.

BACKGROUND: CD5-positive diffuse large B-cell lymphoma (DLBCL) is a clinically rare subtype of DLBCL with aggressive clinical manifestations and a poor prognosis. It has been demonstrated that the prognostic nutritional index (PNI), an indicator of nutritional status and systemic inflammation, is a significant prognostic factor for several types of lymphoma. The objective of this multicenter retrospective study was to explore the prognostic value of the PNI in patients with CD5-positive DLBCL. METHODS: In total, 207 patients with CD5-positive DLBCL were recruited from 11 centers of the Huaihai Lymphoma Working Group. Maximally selected rank statistics analysis was used to identify optimal cutoff points for the PNI. A Cox proportional hazards model was used for univariable and multivariable analyses. Kaplan-Meier curves were used to calculate survival rates and draw survival curves, and the log-rank test was used to compare differences between groups. RESULTS: The median age at diagnosis was 61 years, and the 5-year overall survival rate was 47.5%. According to the maximally selected rank statistics analysis, a score of 49.7 was the optimal cutoff point for the PNI. Subgroup analysis showed that the PNI could re-stratify patients in BCL-2-negative, MYC-negative, high-intermediate-risk and high-risk International Prognostic Index, BCL-6-positive and BCL-6-negative, high Ki-67 score (≥0.9), Ann Arbor stage III/IV, Eastern Cooperative Oncology Group performance status ≥2, and germinal center B subgroups. Multivariable analysis revealed that PNI, age, Eastern Cooperative Oncology Group performance status, albumin level, and red blood cell count were independent prognostic factors for CD5-positive DLBCL. CONCLUSIONS: The PNI was a significant prognostic indicator for CD5-positive DLBCL and was able to re-stratify the prognosis for clinicopathologic subgroups of patients with CD5-positive DLBCL.

Comparative analysis of clinicopathologic characteristics and prognosis between nasal and nonnasal extranodal NK/T-cell lymphoma.

BACKGROUND: The clinicopathologic characteristics and prognosis of nasal and nonnasal extranodal natural killer T-cell lymphoma (ENKTL) are considered to be different. However, the underlying features responsible for these differences are not well clarified especially in the era of asparaginase therapy. METHODS: In total, 1007 newly diagnosed ENKTL patients from 11 medical centers were included in this study. Clinicopathologic characteristics and survival data were collected. The chi-squared test and Kruskal-Wallis test were utilized for the comparison of different groups. Univariable and multivariable Cox proportional hazards models were used to screen prognostic factors. RESULTS: Overall, 869 (86.3%) patients were nasal forms. Compared to patients with nasal ENKTL, nonnasal patients were at more advanced stages and had poor performance status, bone marrow involvement, elevated serum lactate dehydrogenase (LDH), and CD56-negative status (p < 0.05). The 5-year overall survival (OS) for nasal and nonnasal patients were 65.6% and 45.0%, respectively. The OS of nasal forms patients were superior to nonnasal patients, especially in Eastern Cooperative Oncology Group performance status (ECOG PS) (≥2), advanced stage, KPI (HIR/HR), IPI (HIR/HR), PINK (HR), and high EBV DNA load groups. In patients treated with pegaspargase/L-asparaginase-based regimens, the OS of nasal patients was better than that of nonnasal patients. After adjusting the covariates of age, stage, ECOG PS score, LDH, B symptoms, and BM involvement, results showed that the nonnasal site was associated with poor survival of ENKTL. CONCLUSIONS: The clinicopathologic characteristics and prognosis of nasal and nonnasal ENKTL patients are different. Nasal forms patients had superior OS than nonnasal patients, especially in the era of asparaginase.

LASSO Model Better Predicted the Prognosis of DLBCL than Random Forest Model: A Retrospective Multicenter Analysis of HHLWG.

Background: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous non-Hodgkin's lymphoma with great clinical challenge. Machine learning (ML) has attracted substantial attention in diagnosis, prognosis, and treatment of diseases. This study is aimed at exploring the prognostic factors of DLBCL by ML. Methods: In total, 1211 DLBCL patients were retrieved from Huaihai Lymphoma Working Group (HHLWG). The least absolute shrinkage and selection operator (LASSO) and random forest algorithm were used to identify prognostic factors for the overall survival (OS) rate of DLBCL among twenty-five variables. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were utilized to compare the predictive performance and clinical effectiveness of the two models, respectively. Results: The median follow-up time was 43.4 months, and the 5-year OS was 58.5%. The LASSO model achieved an Area under the curve (AUC) of 75.8% for the prognosis of DLBCL, which was higher than that of the random forest model (AUC: 71.6%). DCA analysis also revealed that the LASSO model could augment net benefits and exhibited a wider range of threshold probabilities by risk stratification than the random forest model. In addition, multivariable analysis demonstrated that age, white blood cell count, hemoglobin, central nervous system involvement, gender, and Ann Arbor stage were independent prognostic factors for DLBCL. The LASSO model showed better discrimination of outcomes compared with the IPI and NCCN-IPI models and identified three groups of patients: low risk, high-intermediate risk, and high risk. Conclusions: The prognostic model of DLBCL based on the LASSO regression was more accurate than the random forest, IPI, and NCCN-IPI models.

A Novel Prognostic Index Model for Adult Hemophagocytic Lymphohistiocytosis: A Multicenter Retrospective Analysis in China.

Hemophagocytic lymphohistiocytosis (HLH) is an immune disorder with rapid progression and poor survival. Individual treatment strategy is restricted, due to the absence of precise stratification criteria. In this multicenter retrospective study, we aimed to develop a feasible prognostic model for adult HLH in China. A total of 270 newly diagnosed patients of adult HLH were retrieved from the Huaihai Lymphoma Working Group (HHLWG), of whom 184 from 5 medical centers served as derivation cohort, and 86 cases from 3 other centers served as validation cohort. X-Tile program and Maxstat analysis were used to identify optimal cutoff points of continuous variables; univariate and multivariate Cox analyses were used for variable selection, and the Kaplan-Meier curve was used to analyze the value of variables on prognosis. The C-index, Brier Score, and calibration curve were used for model validation. Multivariate analysis showed that age, creatinine, albumin, platelet, lymphocyte ratio, and alanine aminotransferase were independent prognostic factors. By rounding up the hazard ratios from 6 significant variables, a maximum of 9 points was assigned. The final scoring model of HHLWG-HPI was identified with four risk groups: low risk (≤3 pts), low-intermediate risk (4 pts), high-intermediate risk (5-6 pts), and high risk (≥7 pts), with 5-year overall survival rates of 68.5%, 35.2%, 21.3%, and 10.8%, respectively. The C-indexes were 0.796 and 0.758 in the derivation and validation cohorts by using a bootstrap resampling program. In conclusion, the HHLWG-HPI model provides a feasible and accurate stratification system for individualized treatment strategy in adult HLH.

[Analysis of Predictive Value of Laboratory Indexes for Malignant Lymphoma Patients with Bone Marrow Involvement].

OBJECTIVE: To analyze the influence of bone marrow involvement (BMI) in patients with malignant lymphoma (ML) on laboratory indexes, and evaluate the laboratory markers that can be used to predict/diagnose BMI. METHODS: The clinical characteristics and laboratory indexes of 137 ML patients were analyzed retrospectively, from which the indexes of BMI in ML patients was studied. The logistic regression analysis and receiver operating curve (ROC) were used to evaluate independent risk factors and predictors of BMI diagnosis in ML patients. RESULTS: Compared with non-BMI group, the red blood cell distribution width, C-reactive protein, erythrocyte sedimentation rate, D-dimer, lactate dehydrogenase, alkaline phosphatase, ß2-microglobulin, transferrin, CA153, CA125, and soluble interleukin-2 receptor (sIL-2R) levels were increased while platelet (PLT) count was decreased in BMI group, and the difference was statistically significant (P<0.05). The blood indexes related to BMI and the statistically significant indexes in the univariate regression analysis were corrected by multivariate logistic regression analysis. The corrected results showed that T cell-related non-Hodgkin lymphoma (adjusted OR=2.18, 95%CI: 1.48-4.90, P＜0.001), clinical stage Ⅲ-Ⅳ (adjusted OR=3.32, 95%CI: 2.16-5.83, P＜0.001), sIL-2R (adjusted OR=4.26, 95%CI: 2.95-12.85, P＜0.001) were the risk factors for ML patients with BMI, while PLT (adjusted OR=0.89, 95%CI: 0.55-0.96, P= 0.003) was a protective factor. ROC analysis showed that the areas under the ROC curve of PLT and sIL-2R predicting BMI in ML patients was 0.712 (95%CI: 0.646-0.776, P<0.001) and 0.796 (95%CI: 0.739-0.853, P<0.001), respectively. The best cut-off point of PLT and sIL-2R was 160×109/L and 2 568 U/ml, respectively. The diagnostic specificities of the two indexes here were both greater than 80%. CONCLUSION: PLT and sIL2R show good diagnostic value for ML patients with BMI.

The Value of Prognostic Nutritional Index (PNI) on Newly Diagnosed Diffuse Large B-Cell Lymphoma Patients: A Multicenter Retrospective Study of HHLWG Based on Propensity Score Matched Analysis.

INTRODUCTION: Immunonutritional status is associated with the survival of DLBCL. This multicenter retrospective study aimed to explore the prognostic value of Prognostic Nutrition Index (PNI) in DLBCL patients by using propensity score matched analysis (PSM). METHODS: A total of 990 DLBCL cases were recruited from 5 centers of Huaihai Lymphoma Working Group (HHLWG). A 1:1 PSM analysis was performed using the nearest-neighbor method, with a caliper size of 0.02. Cox regression analysis was used to examine factors associated with survival. RESULTS: The median age at diagnosis was 62 years and 52.5% were males, with the 3-y overall survival of 65.1%. According to the MaxStat analysis, 44 was the optimal cut-off point of PNI. After PSM analysis, a total of 282 patients in PNI < 44 group could be propensity matched to PNI ≥ 44 patients, creating a group of 564 patients. Multivariable analysis revealed that PNI, age, central nervous system involvement and International Prognostic Index (IPI) were independent prognostic factors for DLBCL. Kaplan-Meier analysis indicated that patients with low PNI in Ann Arbor Stage (III/VI), ECOG (<2), IPI (LR+LIR), GCB, and BCL-2 negative groups had a poor prognosis. DISCUSSION: PNI could accurately stratify the prognosis of DLBCL after PSM analysis.

The Addition of Ferritin Enhanced the Prognostic Value of International Prognostic Index in Diffuse Large B-Cell Lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous non-Hodgkin lymphoma, and the prognosis of DLBCL patients is widely affected by multivariables. Clinical-factors-based prognostic systems stratify the prognosis of DLBCL with certain limitations, and the value of ferritin on the prognosis of DLBCL is unclear. In this study, 225 cases were retrieved from 4 centers of Huaihai Lymphoma Working Group (HHLWG) as the derivation cohort, and 66 cases were from the other 6 centers of HHLWG as external validation cohort. X-Tile program divided ferritin into three groups when applying 175.00 and 391.90 µg/L as the optimal cutoff points. Based on multivariable analysis, ferritin appeared to be a stronger predictor. A total of three variables (ferritin, age, and lactate dehydrogenase) were included for the development of the nomogram. The C-indexes were 0.73 and 0.70 in the derivation and validation cohort, and the calibration curve showed the consistency between the nomogram prediction and the actual observation. In conclusion, Ferritin-based nomogram enhanced the prognostic value of IPI in DLBCL.

Development and Validation of a Novel Prognostic Nomogram for CD5-Positive Diffuse Large B-Cell Lymphoma: A Retrospective Multicenter Study in China.

BACKGROUND: CD5-positive diffuse large B-cell lymphoma (CD5+ DLBCL) is a rare subtype of DLBCL with invasive clinical features and poor prognosis. Current clinical variables based on prognostic systems for DLBCL are inadequate to accurately stratify the prognosis of CD5+ DLBCL. METHODS: A total of 195 CD5+ DLBCL patients were retrospectively recruited from nine centers in Huaihai Lymphoma Working Group. MaxStat analysis was used to identify optimal cutoff points for continuous variables; univariable and multivariable Cox analyses were used for variable selection; Kaplan-Meier curve was used to analyze the value of variables on prognosis; and C-index, Brier score, and decision curve analysis were measured for predicting model performance. RESULTS: The derivation and validation cohorts consisted of 131 and 64 patients. Of the whole cohort, median age at diagnosis was 61 years, of whom 100 (51.28%) were males and the 5-year overall survival rate was 42.1%. MYC, BCL-2, and the coexpression of MYC/BCL-2 could distinguish the survival of CD5+ DLBCL. Multivariable analysis showed that age, IPI, red blood cell count, neutrophil count, MYC expression, and hepatosplenomegaly were independent predictors, and the prognostic nomogram was developed. The C-index of the nomogram was 0.809 in the derivation and 0.770 in the validation cohort. Decision curve analysis proved that compared with IPI, the specific nomogram showed a better identification in CD5+ DLBCL. CONCLUSION: The proposed nomogram provided a valuable tool for prognosis prediction in patients with CD5+ DLBCL.