Novel prognostic scoring system for diffuse large B-cell lymphoma

HALP score as a novel prognostic factor for patients with myelodysplastic syndromes

Myelodysplastic syndrome (MDS) is a heterogeneous spectrum of clonal hematopoietic disorders with varying degrees of cytopenia and morphologic dysplasia. The hemoglobin, albumin, lymphocyte, and platelet (HALP) score is a prognostic marker in several types of malignant tumors. Prognostic value of HALP score remains unclear for MDS. To determine the prognostic value of baseline HALP score in MDS. We retrospectively analyzed data from 130 newly diagnosed MDS patients evaluated and classified under HALP score. By the receiver operating characteristic (ROC) analysis, the optimal cut-off value of HALP was > 67.5 in predicting mortality. Patients were divided into two groups: with low and high HALP scores, and the characteristics were compared between both groups. Patients' median age was 68 (19-84) years, and 79 (60.8%) were male. Higher HALP score was detected in MDS patients with intermediate-risk under IPSS score, and at high and very high risks under IPSS-R score, and those receiving azacitidine (AZA) treatment. The survival rates of those with a HALP score > 67.5 were significantly lower than those with low HALP score at 17.77 ± 3.98 (median ± SE) (p < 0.001). The 3-, 5- and 10-years survival rates of individuals with HALP scores > 67.5 were found as 25, 18, and 11%, respectively. Median overall survival (OS) was also determined as 33.10 (95% CI 16.34-49.88) months by the Kaplan-Meier method. HALP score has shown an ability to be a useful prognostic biomarker in various cancers, including MDS. The meaningful cut-off value of HALP is disease-specific and largely study-specific. High HALP score is associated with unfavorable clinicopathological characteristics. Also, it may be useful in predicting OS and mortality of MDS.

Artificial intelligence-based prognostic model accurately predicts the survival of patients with diffuse large B-cell lymphomas: analysis of a large cohort in China

BACKGROUND

Diffuse large B-cell lymphomas (DLBCLs) display high molecular heterogeneity, but the International Prognostic Index (IPI) considers only clinical indicators and has not been updated to include molecular data. Therefore, we developed a widely applicable novel scoring system with molecular indicators screened by artificial intelligence (AI) that achieves accurate prognostic stratification and promotes individualized treatments.

METHODS

We retrospectively enrolled a cohort of 401 patients with DLBCL from our hospital, covering the period from January 2015 to January 2019. We included 22 variables in our analysis and assigned them weights using the random survival forest method to establish a new predictive model combining bidirectional long-short term memory (Bi-LSTM) and logistic hazard techniques. We compared the predictive performance of our "molecular-contained prognostic model" (McPM) and the IPI. In addition, we developed a simplified version of the McPM (sMcPM) to enhance its practical applicability in clinical settings. We also demonstrated the improved risk stratification capabilities of the sMcPM.

RESULTS

Our McPM showed superior predictive accuracy, as indicated by its high C-index and low integrated Brier score (IBS), for both overall survival (OS) and progression-free survival (PFS). The overall performance of the McPM was also better than that of the IPI based on receiver operating characteristic (ROC) curve fitting. We selected five key indicators, including extranodal involvement sites, lactate dehydrogenase (LDH), MYC gene status, absolute monocyte count (AMC), and platelet count (PLT) to establish the sMcPM, which is more suitable for clinical applications. The sMcPM showed similar OS results (P < 0.0001 for both) to the IPI and significantly better PFS stratification results (P < 0.0001 for sMcPM vs. P = 0.44 for IPI).

CONCLUSIONS

Our new McPM, including both clinical and molecular variables, showed superior overall stratification performance to the IPI, rendering it more suitable for the molecular era. Moreover, our sMcPM may become a widely used and effective stratification tool to guide individual precision treatments and drive new drug development.

Prognostic Significance of Systemic Immune-Inflammation Index in Patients With Diffuse Large B-Cell Lymphoma

Objective

The systemic immune-inflammation index (SII) based on neutrophil, platelet and lymphocyte counts, is a prognostic biomarker in some solid cancers. However, the prognostic value of SII has not yet been validated. This study was to evaluate the role of SII in predicting survival for patients with diffuse large B cell lymphoma (DLBCL).

Methods

We retrospectively investigated 224 patients with DLBCL between August 2005 and October 2018. Kaplan–Meier analysis and Cox proportional hazard models were used to assess the prognostic value of SII.

Results

In the ROC curve analysis, SII had the highest AUC and was more accurate as a prognostic factor. Patients with higher SII tended to have higher level of LDH, more advanced stage, poor PS, and high IPI score compared with low SII group. In univariate analyses, SII, PLR and NLR were all prognostic for progression-free survival and overall survival. Moreover, only SII, older age, HBSAg-positive and IPI were the independent prognostic factors for patients in multivariate analysis. The nomogram based on SII, older age, HBSAg status and IPI showed accurate prognostic ability for predicting 3-years and 5-years survival rates (c-index, 0.791) compared to the IPI alone (c-index, 0.716).

Conclusion

SII was a powerful tool for predicting outcome in patients with DLBCL. It might assist the separation of high-risk patients among patients with the same IPI.

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.

Primary Gastric Diffuse Large B-Cell Lymphoma: Prognostic Factors in the Immuno-Oncology Therapeutics Era

Objective:

This study aimed to explore the prognostic factors for primary gastric diffuse large B-cell lymphoma (PG-DLBCL).

Materials and Methods:

This retrospective study analyzed 72 PG-DLBCL patients between January 2012 and December 2017 in the Shanxi Cancer Hospital of Shanxi Medical University to identify the different prognostic factors in PG-DLBCL. The clinical features, treatment, and follow-up information were analyzed.

Results:

The low CD4:CD8 ratio group (median subsequent overall survival [OS]: 36.06 months; 95% confidence interval [CI]: 25.73-46.40) showed a significant decrease in subsequent OS compared to the normal group among PG-DLBCL patients who were newly diagnosed and did not receive rituximab (median OS: 52.58 months; 95% CI: 44.18-60.97; p=0.029). Event-free survival status 24 months after the date of diagnosis (EFS24) also decreased significantly in the low CD4:CD8 group (median EFS24: 16.27 months; 95% CI: 13.09-19.45) compared to the normal group (median EFS24: 20.34 months; 95% CI: 17.05-23.63; p=0.014). Multivariate analysis showed that low CD4:CD8 at diagnosis was an independent poor prognostic factor for subsequent OS and EFS24.

Conclusion:

Our data suggest that identifying prognostic factors, especially host immunity, may provide useful information for assessing prognosis or clinical management.

Prognostic impact of platelet-to-lymphocyte ratio on diffuse large B-cell lymphoma: a meta-analysis

Background

Recently, some studies reported the prognostic value of platelet-to-lymphocyte ratio (PLR) in patients with diffuse large B-cell lymphoma (DLBCL), however, the results varied from different studies. Therefore, we performed a meta-analysis to explore the prognostic value of PLR in DLBCL.

Methods

A comprehensive literature retrieval was conducted by using PubMed, Embase, Web of Science, the Cochrane Library, the China National Knowledge Infrastructure (CNKI), and Wanfang. Pooled hazard ratio (HR) and 95% confidence interval (CI) were used to evaluate the association of PLR and overall survival (OS) and progression-free survival (PFS). Odd ratios (ORs) and 95% CIs for clinicopathological characteristics were statistically analyzed.

Results

Eight studies with 1931 patients were included for meta-analysis. The pooled analysis indicated that elevated PLR was significantly associated with poor OS (HR = 1.73, 95% CI 1.29–2.31, p < 0.001), but not PFS (HR = 0.85, 95% CI 0.57–1.27, p = 0.438). Furthermore, elevated PLR was significantly associated with presentation of B symptoms (OR = 2.27, 95% CI 1.29–3.98, p = 0.004), elevated lactate dehydrogenase (LDH) (OR = 2.76, 95% CI 2.05–3.72, p < 0.001), higher tumor stage (OR = 2.22, 95% CI 1.66–2.98, p < 0.001), and Eastern Cooperative Oncology Group (ECOG) performance status (PS) ≥ 2 (OR = 1.71, 95% CI 1.09–2.69, p = 0.019). However, elevated PLR was not significantly correlated with gender, age or cell of origin.

Conclusion

This meta-analysis revealed that PLR may be an effective and noninvasive biomarker for poor prognosis and aggressive disease characteristics for patients with DLBCL.