Development of new prognostic model based on pretreatment βLRI and LLRI for stage IE/IIE upper aerodigestive tract ENKTL, nasal type

Extranodal lymphoma: pathogenesis, diagnosis and treatment

Approximately 30% of lymphomas occur outside the lymph nodes, spleen, or bone marrow, and the incidence of extranodal lymphoma has been rising in the past decade. While traditional chemotherapy and radiation therapy can improve survival outcomes for certain patients, the prognosis for extranodal lymphoma patients remains unsatisfactory. Extranodal lymphomas in different anatomical sites often have distinct cellular origins, pathogenic mechanisms, and clinical manifestations, significantly influencing their diagnosis and treatment. Therefore, it is necessary to provide a comprehensive summary of the pathogenesis, diagnosis, and treatment progress of extranodal lymphoma overall and specifically for different anatomical sites. This review summarizes the current progress in the common key signaling pathways in the development of extranodal lymphomas and intervention therapy. Furthermore, it provides insights into the pathogenesis, diagnosis, and treatment strategies of common extranodal lymphomas, including gastric mucosa-associated lymphoid tissue (MALT) lymphoma, mycosis fungoides (MF), natural killer/T-cell lymphoma (nasal type, NKTCL-NT), and primary central nervous system lymphoma (PCNSL). Additionally, as PCNSL is one of the extranodal lymphomas with the worst prognosis, this review specifically summarizes prognostic indicators and discusses the challenges and opportunities related to its clinical applications. The aim of this review is to assist clinical physicians and researchers in understanding the current status of extranodal lymphomas, enabling them to make informed clinical decisions that contribute to improving patient prognosis.

A Novel Prognostic Marker for Primary CNS Lymphoma: Lactate Dehydrogenase-to-Lymphocyte Ratio Improves Stratification of Patients Within the Low and Intermediate MSKCC Risk Groups

Background

Primary central nervous system lymphoma (PCNSL) is a highly aggressive and rare extranodal non-Hodgkin lymphoma (NHL). The MSKCC and the IELSG scores represent the most widely used prognostic models, but many changes have occurred in therapeutic protocols since their development. Moreover, many PCNSL patients cannot be classified using the IELSG score. We thus aimed to create a novel, effective and feasible prognostic model for PCNSL.

Methods

We included 248 PCNSL patients diagnosed with PCNSL. Our primary endpoint was the overall survival (OS) and we used the receiver operating characteristic (ROC) analysis to determine the optimal prognostic cut-off value for LLR (lactate dehydrogenase-to-lymphocyte ratio), neutrophil-to-lymphocyte ratio (NLR) and derived neutrophil-to-lymphocyte ratio (dNLR). Variable associated with OS were evaluated by univariate and multivariate analyses. 124 out of 248 patients were randomly selected as the internal validation cohort.

Results

By univariate analysis, an age >60 years, Eastern Cooperative Oncology Group performance status (ECOG PS) >1, treatment with radiotherapy alone, high-risk groups of Memorial Sloan Kettering Cancer Center (MSKCC) score, NLR >4.74, dNLR >3.29, and LLR >166.8 were significantly associated with a worse OS. By multivariate analysis, the MSKCC score and LLR were confirmed as independent prognostic parameters for poorer OS. OS, however, was not significantly different between low- and intermediate-risk groups according to the MSKCC score, while LLR proved to be prognostically relevant and was thus used to develop a novel, effective three-tier PCNSL scoring system. Of 124 patients, 84 patients with survival data and LLR data were successfully validated by newly established PCNSL LLR scoring system.

Conclusions

In the present study, we demonstrate that a high LLR represents an independent unfavorable prognostic parameter in PCNSL patients which can be integrated into an effective prognostic model.

Lactate Dehydrogenase-to-Lymphocyte Ratio Represents a Powerful Prognostic Tool of Metastatic Renal Cell Carcinoma Patients Treated with Tyrosine Kinase Inhibitors

Inflammation parameters were verified to predict clinical outcomes of metastatic renal cell carcinoma (mRCC) patients treated with tyrosine kinase inhibitors (TKIs). Here, we developed a novel marker, lactate dehydrogenase (tumor burden marker) to lymphocytes (inflammation marker) ratio (LLR), aimed to reveal the prognostic role of LLR for mRCC patients treated with TKIs. We collected clinical data of mRCC patients treated with TKIs. Receiver operating curve analysis was used to determine the optimal cut-off value. The c-index method was used to determine the best predictive marker for overall survival (OS). Clinicopathological characteristics on OS and progression-free survival (PFS) were evaluated by univariate analysis, and multivariate analyses. LLR provided the greatest improvement in the c-index, and displayed the best marker of the prognostic accuracy for OS. Univariate analysis revealed that LLR, ECOG PS and IMDC risks were significant predictors of OS and PFS. However, multivariate analysis indicated that IMDC risks failed to predict PFS, and only showed predictor of OS. We finally stratifed patients into low LLR (<150) and high LLR (≥150) group with different clinical outcomes. LLR represents a powerful prognostic tool of clinical outcome in mRCC patients treated with TKIs.

Prognostic nomogram for overall survival in upper aerodigestive tract extranodal natural killer/T-cell lymphoma, nasal type, stages IE and IIE: A SEER-based study

The present study aimed to develop a widely accepted prognostic nomogram for stage IE and IIE extranodal natural killer/T-cell lymphoma (ENKTCL) of the upper aerodigestive tract by using the Surveillance, Epidemiology, and End Results program database. A total of 396 patients with ENKTCL were included in the present study and were divided into training (n=280) and validation (n=116) cohorts. The Kaplan-Meier method and Cox regression model were used to evaluate the prognostic value of multiple clinical parameters on overall survival. The C-index and calibration curves were both used to determine the predictive and discriminatory capacities of the nomogram. In the training cohort, multivariate analysis demonstrated that age, primary site, radiation therapy and stage were independent prognostic factors. Nomograms with a C-index of 0.717 in the training cohort and a C-index of 0.737 in the validation cohort were developed. The calibration curves reported excellent consistency between predicted and real survival in patients with ENKTCL. In addition, a subgroup analysis of 264 patients who were receiving chemotherapy revealed that based on chemotherapy, supplementation with radiation therapy was significantly beneficial to patients survival. In conclusion, the present study demonstrated that this prognostic model may serve as a novel tool for improving prediction of survival outcomes and may therefore be used in clinical applications.