Prognostic value of pretreatment neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios in multiple myeloma patients treated with thalidomide-based regimen

How Immunonutritional Markers Are Associated with Age, Sex, Body Mass Index and the Most Common Chronic Diseases in the Hospitalized Geriatric Population-A Cross Sectional Study

The aim of this study was to assess the relationship of different chronic diseases with immunonutritional markers in the senior population.

METHODS

this study included 1190 hospitalized geriatric patients. The criteria to participate were ability to communicate, given consent and C-reactive protein (CRP) lower than 6 mg/dL.

RESULTS

the mean age of the study population was 81.7 ± 7.6 years. NLR (neutrophil-to-lymphocyte ratio), LMR (lymphocyte-to-monocyte ratio), MWR (monocyte-to-white blood cell ratio), SII (systemic immune-inflammation index), PNI (prognostic nutritional index) and CAR (C-reactive protein-to-albumin ratio) were related to age. NLR and MWR were higher, while LMR, PLR (platelet-to-lymphocyte ratio and SII were lower in men. All markers were related to BMI. NLR, LMR, LCR (lymphocyte-to-CRP ratio), MWR, PNI and CAR were related to several concomitant chronic diseases. In multivariate analyses, age and BMI were selected as independent predictors of all studied immunonutritional markers. Atrial fibrillation, diabetes mellitus and dementia appear most often in the models. PNI presented the most consistent statistical association with age, BMI and concomitant chronic diseases.

CONCLUSIONS

this study reveals the pivotal role of aging and BMI in inflammatory marker levels and the association of immunonutritional markers with different chronic diseases. Atrial fibrillation seems to have the most dominant connection to the immunonutritional markers.

An IL-1β-driven neutrophil-stromal cell axis fosters a BAFF-rich protumor microenvironment in individuals with multiple myeloma

Human bone marrow permanently harbors high numbers of neutrophils, and a tumor-supportive bias of these cells could significantly impact bone marrow-confined malignancies. In individuals with multiple myeloma, the bone marrow is characterized by inflammatory stromal cells with the potential to influence neutrophils. We investigated myeloma-associated alterations in human marrow neutrophils and the impact of stromal inflammation on neutrophil function. Mature neutrophils in myeloma marrow are activated and tumor supportive and transcribe increased levels of IL1B and myeloma cell survival factor TNFSF13B (BAFF). Interactions with inflammatory stromal cells induce neutrophil activation, including BAFF secretion, in a STAT3-dependent manner, and once activated, neutrophils gain the ability to reciprocally induce stromal activation. After first-line myeloid-depleting antimyeloma treatment, human bone marrow retains residual stromal inflammation, and newly formed neutrophils are reactivated. Combined, we identify a neutrophil-stromal cell feed-forward loop driving tumor-supportive inflammation that persists after treatment and warrants novel strategies to target both stromal and immune microenvironments in multiple myeloma.

Clinical efficacy of Thalidomide combined with PAD Regimen in patients with multiple Myeloma

Objective

To evaluate the clinical efficacy of thalidomide combined with PAD regimen in patients with multiple myeloma (MM).

Methods

It was a Clinical comparative study. A total of 120 patients with MM were admitted at Beijing Aerospace General Hospital from September 2020 to June 2022 randomly divided into two groups, with 60 patients in each group. The study group was treated with thalidomide combined with a PAD regimen (bortezomib, doxorubicin and dexamethasone), while the control group with a PAD regimen alone. After treatment, the therapeutic effect, adverse drug reactions, bone metabolic markers such as serum alkaline phosphatase (ALP) and osteocalcin (OCN) before and after treatment, as well as T-lymphocyte subsets CD3+, CD4+, CD8+ and CD4+/CD8+ levels before and after treatment were compared and analyzed between the two groups.

Results

The total efficacy in the study group was 90%, which was significantly higher than 70% in the control group (p= 0.00). The incidence of adverse drug reactions was 40% in the study group and 38% in the control group, without statistically significant difference (p= 0.85). After treatment, ALP and OCN levels in the study group were significantly higher than those in the control group (ALP, p= 0.01; OCN, p= 0.00), and CD3+, CD4+ and CD4+/CD8+ in the study group also increased significantly compared with those in the control group (CD3+, p= 0.02; CD4+, p= 0.00; CD4+/CD8+, p= 0.00).

Conclusion

Thalidomide combined with a PAD regimen is definitely effective in patients with MM, it can obviously improve immune function and bone salt metabolism, with no increase in adverse reactions but high safety and effectiveness.

Neutrophil to lymphocyte ratio (NLR) impact on the progression-free survival and overall survival of multiple myeloma patients treated with high-dose chemotherapy and autologous stem cell transplantation

High-dose chemotherapy with autologous stem-cell transplantation (ASCT) remains the standard of care in multiple myeloma (MM) patients. This retrospective study aimed to assess the impact of neutrophil-to-lymphocyte ratio (NLR) and other complete blood count (CBC)-based predictors on PFS and OS of transplant-eligible MM patients. The CBC-based biomarkers were evaluated in a single-center cohort of 176 MM patients at three time points: at the diagnosis, the time of ASCT, and +100 d after ASCT. Univariable and multivariable Cox's regression analyses and Kaplan-Meier estimate were used in statistical analysis. NLR at ASCT (HR 1.15, 95% CI: 1.05-1.26) and hemoglobin at ASCT (HR 0.80, 95% CI: 0.68-0.94) were independent factors influencing PFS. In the model for OS, the only statistically significant factors were NLR at ASCT (HR 1.15, 95% CI: 1.04-1.27), bortezomib administration prior to ASCT (HR 0.52, 95% CI: 0.33-0.83) and age at diagnosis (HR 1.03, 95% CI: 1.00-1.06). NLR at ASCT is an independent predictive factor in MM patients undergoing ASCT.

The advanced lung cancer inflammation index predicts chemotherapy response and infection risk in multiple myeloma patients receiving induction chemotherapy

Objective: This study aims to determine the clinical significance of the advanced lung cancer inflammation index (ALI) in predicting prognosis, chemotherapy response, and infection risk in newly diagnosed multiple myeloma (MM) patients receiving induction therapy. Methods: A retrospective analysis of the clinical characteristics and laboratory data of 111 newly diagnosed MM patients from the Haematology Department of the Third Xiangya Hospital of Central South University from January 2014 to March 2020 was performed. We first determined the relationship between ALI and overall survival (OS), as well as clinical and laboratory parameters. Second, predictive factors for chemotherapy response were analysed by univariate and multivariate regression analyses. Third, univariate regression analysis of risk factors was performed using infection as the evaluable outcome. Results: Of the 111 evaluable patients, the low ALI group (<32.7) exhibited significantly poorer survival than the high ALI group (51 months versus 77 months). Multivariable analysis showed that advanced age, chemotherapy response and serum calcium level were independent prognostic factors for OS. Better chemotherapy efficacy in the high ALI group (89.3%) than in the low ALI group (42.2%) (p < 0.001) was noted. Multivariate analysis suggested that only ALI [HR: 0.110, 95% CI (0.035-0.350), p = 0.000] is an independent predictive factor in evaluating the efficiency of induction chemotherapy. Forty patients (36.04%) presented with infection after induction chemotherapy. Univariate analysis suggested that low ALI and abnormal renal function increase risk of infection in newly diagnosed MM patients. Conclusion: Our study confirmed that ALI is not only a prognostic biomarker for newly diagnosed patients, but also predicts chemotherapy efficacy in newly diagnosed MM patients receiving induction therapy.

Cancer Stem Cells as a Prognostic Biomarker and Therapeutic Target Using Curcumin/ Piperine Extract for Multiple Myeloma

BACKGROUND

Multiple myeloma (MM) is a hematological bone marrow malignancy that can be treated but is usually fatal. Medication resistance is the major cause of relapses due to cancer stem cells (CSCs). As a result, this study aimed to identify multiple myeloma cancer stem cells (MMCSCs) in the bone marrow of twelve MM patients with pathological complete response (pCR) after chemotherapy and to investigate the potential effect of Curcumin/Piperine (C/P) extract as an anti-MMCSCs treatment in twenty newly diagnosed patients.

METHODS

This study included twenty bone marrow (BM) samples from newly diagnosed MM patients and twelve BM samples from pCR patients after a year of treatment. The MTT test was performed to assess the treatment's effective dosage. A flow cytometer was used to identify MMCSCs, cell cycle profile, extract's apoptotic activity, and proliferation marker in the selected samples. Also,  a colony formation test and stemness protein were investigated.

RESULTS

In newly diagnosed MM patients, the C/P extract suppressed MMCSCs by 64.71% for CD138-/CD19- and 38.31% for CD38++. In MM patients' samples obtained after one year of treatment, the MMCSCs inhibition percentage reached 44.71% (P < 0.008) for CD138-/CD19- and 36.94% (P < 0.221) for CD38++. According to cell cycle analyses, the number of cells treated with C/P extract was significantly reduced in the S and G0/G1 phases (87.38%: 35.15%, and 4.83%: 2.17% respectively), with a rapid increase in the G2/M phases (1.1%: 2.2%.). MMCSCs apoptosis was identified using a flow cytometer and Annexin-V. Multiple myeloma stem cell (MMCSC) proliferation was inhibited. Clonogenicity was suppressed by 60%, and stemness protein expression was reduced by 70%.

CONCLUSION

MMCSCs in the bone marrow of MM-pCR patients can be utilized as a prognostic tool to predict recurrent multiple myeloma incidence. Also, the therapeutic potential of C/P extract as a prospective anti-MM drug targeting MMCSCs.

The Pan-Immune-Inflammation Value predicts the survival of patients with anaplastic lymphoma kinase-positive non-small cell lung cancer treated with first-line ALK inhibitor

BACKGROUND

Anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) have significantly improved the clinical outcomes of patients with ALK-positive non-small cell lung cancer (NSCLC). However, reliable biomarkers to predict the prognostic role of this treatment are lacking. The Pan-Immune-Inflammation Value (PIV) has recently been demonstrated as a novel comprehensive biomarker to predict survival of patients with solid tumors. Our study aimed to evaluate the prognostic power of PIV in this group of patients.

PATIENTS AND METHODS

94 patients with advanced ALK-positive NSCLC who received first-line ALK inhibitors were enrolled in this study. PIV was calculated as the product of peripheral blood neutrophil, monocyte, and platelet counts divided by lymphocyte count. Kaplan-Meier method and Cox hazard regression models were used for survival analyses.

RESULTS

The 1-year progression-free survival (PFS) was 63.5%, and the 5-year overall survival (OS) rate was 55.1%. Patients with higher PIV, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune inflammation index (SII) had worse PFS in univariate analysis, but only the PIV (hazard ratio [HR] = 2.90, 95% confidence interval [CI]: 1.79-4.70, p < 0.001) was an independent prognostic factor in multivariate analysis. Similarly, patients with higher PIV, NLR, PLR, and SII had a worse OS in the univariate analysis, but only the PIV (HR = 4.70, 95% CI: 2.00-11.02, p < 0.001) was significantly associated with worse OS in multivariate analysis.

CONCLUSION

PIV is a comprehensive and convenient predictor of both PFS and OS in patients with ALK-positive advanced NSCLC who received first-line ALK TKIs. Prospective clinical trials are required to validate the value of this new parameter.

Systemic Immune-Inflammation Index Is a Prognostic Factor for Breast Cancer Patients After Curative Resection

Background

The preoperative systemic immune-inflammation index (SII) is correlated with prognosis in several malignancies. The aim of this study was to investigate the prognosis value of SII in patients with resected breast cancer.

Materials and Methods

A total of 784 breast cancer patients who underwent surgical resection were consecutively investigated. The optimal cutoff value of SII was evaluated using the receiver operating characteristic (ROC) curve. The collection of SII with clinicopathological characteristic and prognosis was further evaluated.

Results

The optimal cutoff value for SII in the prediction of survival was 514 according to ROC curve analysis. A high SII was significantly correlated with younger age (P = 0.037), PR status (P < 0.001), and HER2 status (P = 0.035). Univariate analysis revealed that SII (P < 0.001), T-stage (P < 0.001), lymph node involvement post-surgery (P = 0.024), and histological grade (P < 0.001) were significantly related to DFS, and SII (P < 0.001), T-stage (P = 0.003), lymph node involvement post-surgery (P = 0.006), and histological grade (P < 0.001) were significantly associated with OS. In multivariate analysis, a high SII was an independent worse prognostic factor for DFS (HR, 4.530; 95% CI, 3.279-6.258; P < 0.001) and OS (HR, 3.825; 95% CI, 2.594-5.640; P < 0.001) in all the enrolled patients. Furthermore, subgroup analysis of molecular subtype revealed that SII was significantly associated with prognosis in all subtypes.

Conclusion

Preoperative SII is a simple and useful prognostic factor for predicting long-term outcomes for breast cancer patients undergoing surgery.

Are the Derived Indexes of Peripheral Whole Blood Cell Counts (NLR, PLR, LMR/MLR) Clinically Significant Prognostic Biomarkers in Multiple Myeloma? A Systematic Review And Meta-Analysis

Background

Multiple myeloma (MM) is an incurable malignant plasma cell tumor. Whole blood cell count (WBCC) derived indexes are widely used as a predictive biomarker for various types of solid and hematological malignant tumors. Our study is to evaluate its effectiveness in MM by meta-analysis.

Methods

Relevant literatures were retrieved from PubMed, Embase and Web of Science databases according to PRISMA guideline. All relevant parameters were extracted and combined for statistical analysis.

Results

Nineteen studies incorporating 3818 MM patients were eventually included in this meta-analysis. 13 studies evaluated that elevated NLR was significantly associated with poor survival outcomes (OS: HR=2.04, P<0.001; PFS: HR=1.96, P=0.003). Elevated NLR was revealed to correlate with ISS stage (ISS III VS I-II, OR=2.23, P=0.003). A total of 7 studies have shown that elevated LMR predicts a better prognosis in MM patients (OS: HR=0.57, P<0.001; PFS: HR=0.49, P<0.05), and two other studies demonstrated that increased MLR was related to poor OS/PFS (OS: HR=1.58, P<0.05; PFS: HR=1.60, P<0.05). However, in the other 6 studies including 1560 patients, the prognostic value of PLR had not been confirmed (OS: HR=0.89, P>0.05; PFS: HR=0.87, P>0.05).

Conclusions

The indexes NLR and LMR/MLR derived from WBCC were validated to be useful biomarkers to predict the prognosis in MM patients, but the evidence of PLR was insufficient.

The Prognostic Role of Prothrombin Time and Activated Partial Thromboplastin Time in Patients with Newly Diagnosed Multiple Myeloma

Purpose

To evaluate the prognostic role of prothrombin time (PT) and activated partial thromboplastin time (APTT) for newly diagnosed multiple myeloma (MM).

Methods

We retrospectively analyzed 354 patients with newly diagnosed MM who received primary treatment in our center. The propensity score matching technique was used to reduce the bias between groups.

Results

Among 354 patients, lengthened PT or APTT was observed in 154 (43.5%) patients and 200 (56.5%) patients had normal PT and APTT. Patients with lengthened PT or APTT had significantly shorter median overall survival (OS) (37.5 vs. 73.8 months, p < 0.001) and progression-free survival (PFS) (23.1 vs. 31.6 months, p = 0.001) than those with normal PT and APTT. Univariate Cox proportional hazards regression analyses showed that lengthened PT or APTT was associated with shorter OS (HR = 2.100, 95% CI: 1.525-2.893, p < 0.001). Lengthened PT or APTT was also a poor prognostic factor for OS (HR = 3.183, 95% CI: 1.803-5.617, p < 0.001) in multivariable analyses. The poor effect of lengthened PT or APTT on PFS was confirmed in univariate analysis (HR = 1.715, 95% CI: 1.244-2.365, p = 0.001), but it had no impact on PFS in multivariate analysis (p = 0.197). In the propensity score matching analysis, 154 patients, 77 in each group, were identified. Among 154 matched patients, the OS of patients with lengthened PT or APTT was shorter (38.4 vs. 51.0 months, p = 0.030), but PFS was similar (29.0 vs. 35.0 months, p = 0.248).

Conclusion

These results demonstrated that lengthened PT or APTT was an independent poor prognostic factor for patients with newly diagnosed MM.

Systemic Inflammation Response Index Is a Predictor of Poor Survival in Locally Advanced Nasopharyngeal Carcinoma: A Propensity Score Matching Study

Introduction

Nasopharyngeal carcinoma (NPC) is a common malignancy in China and known prognostic factors are limited. In this study, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune inflammation index (SII), and systemic inflammation response index (SIRI) were evaluated as prognostic factors in locally advanced NPC patients.

Materials and Methods

NPC patients who received curative radiation or chemoradiation between January 2012 and December 2015 at the Second Xiangya Hospital were retrospectively reviewed, and a total of 516 patients were shortlisted. After propensity score matching (PSM), 417 patients were eventually enrolled. Laboratory and clinical data were collected from the patients' records. Receiver operating characteristic curve analysis was used to determine the optimal cut-off value. Survival curves were analyzed using the Kaplan-Meier method. The Cox proportional hazard model was used to identify prognostic variables.

Results

After PSM, all basic characteristics between patients in the high SIRI group and low SIRI group were balanced except for sex (p=0.001) and clinical stage (p=0.036). Univariate analysis showed that NLR (p=0.001), PLR (p=0.008), SII (p=0.001), and SIRI (p<0.001) were prognostic factors for progression-free survival (PFS) and overall survival (OS). However, further multivariate Cox regression analysis showed that only SIRI was an independent predictor of PFS and OS (hazard ratio (HR):2.83; 95% confidence interval (CI): 1.561-5.131; p=0.001, HR: 5.19; 95% CI: 2.588-10.406; p<0.001), respectively.

Conclusion

Our findings indicate that SIRI might be a promising predictive indicator of locally advanced NPC patients.

Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients

Multiple myeloma (MM) is a malignant plasma cell tumor with high heterogeneity, characterized by anemia, hypercalcemia, renal failure, and lytic bone lesions. Although various powerful prognostic factors and models have been exploited, the development of more accurate prognosis and treatment for MM patients is still facing many challenges. Given the essential roles of super-enhancer (SE) associated genes in the tumorigenesis of MM, we tried to initially screen and identify the significant prognostic factors from SE associated genes in MM by the least absolute shrinkage and selection operator (Lasso) penalized Cox regression, univariate and multivariate Cox regression analysis using GSE24080 and GSE9782 datasets. Risk score model of five genes including CSGALNACT1, FAM53B, TAPBPL, REPIN1, and DDX11, was further constructed and the Kaplan-Meier (K-M) curves showed that the low-risk group seems to have better clinical outcome of survival compared to the high-risk group. Time-dependent receiver operating characteristic (ROC) curves presented the favorable performance of the model. An interactive nomogram consisting of the five-gene risk group and eleven clinical traits was established and identified by calibration curves. Therefore, the risk score model of SE associated five genes developed here could be used to predict the prognosis of MM patients, which may assist the clinical treatment of MM patients in the future.