Prognostic significance of preoperative neutrophilia on recurrence-free survival in meningioma

The dural attachment length predict prognosis in patients with recurrent meningiomas

To investigate the prognostic factors of recurrent meningioma patients who underwent reoperation, so as to make relevant recommendations for the treatment. A retrospective analysis was performed on 73 patients with recurrent meningioma. Patients' clinical data were obtained from their medical records. Progression-free Survival (PFS) was defined as the interval from the date of surgery to the date of tumor recurrence, or to the date of the last imaging review. Overall survival (OS) was defined as the time from the date of surgery to death from any cause, or to the date of the last follow-up. The multivariate COX regression showed that dural attachment length (HR = 1.238, 95%CI1.011-1.516, P = 0.039) and WHO grade (HR = 2.184, 95%CI1.135-4.203, P = 0.019) were independent risk factors for tumor progression. The factors associated with survival in multivariate regression analysis were preoperative Karnofsky Performance Scale (KPS) (HR = 0.951, 95%CI0.923-0.979, P = 0.001), dural attachment length (HR = 1.520, 95%CI1.124-2.057, P = 0.007) and WHO grade (HR = 4.829, 95%CI1.891-12.331, P = 0.001). The dural attachment length (OR = 1.843, 95%CI1.236-2.748, P = 0.003) was the only risk factor associated with postoperative pulmonary infection. No correlation was observed between Simpson's grade and either PFS or OS. The dural attachment length is closely related to the prognosis of recurrent meningioma, which should be given importance during the perioperative assessment.

A Nomogram Model for Stratifying the Risk of Recurrence in Patients with Meningioma After Surgery

BACKGROUND

Here, we aimed to investigate the clinical parameters affecting the recurrence of meningiomas, and to construct a predictive nomogram model, so as to predict the recurrence-free survival (RFS) of meningiomas more accurately.

METHODS

The Clinical, imaging, and pathological data of 155 primary meningioma patients treated surgically from January 2014 to March 2021 were retrospectively analyzed. Independent prognostic factors affecting postoperative recurrence of meningioma were identified by univariate and multivariate Cox regression analyses. A predictive nomogram was established based on independent influence parameters. Subsequently, time-dependent receiver operating characteristic curve, calibration curve, and Kaplan-Meier method were utilized to evaluate the predictive ability of the model.

RESULTS

The multivariate Cox regression analysis showed that tumor size, Ki-67 index, and resection extent had independent prognostic significance, and these parameters were subsequently used to construct a predictive nomogram. Receiver operating characteristic curves indicated that the model was more accurate in predicting RFS than independent factors. Calibration curves suggested that the predicted RFS were similar to the actual observed RFS. In the Kaplan-Meier analysis, the RFS of high-risk cases was obviously shorter than that of low-risk cases.

CONCLUSIONS

The tumor size, Ki-67 index, and extent of resection were independent factors affecting the RFS of meningioma. The predictive nomogram based on these factors can be used as an effective method to stratify the recurrence risk of meningioma and provide a reference for patients to choose personalized treatment.

Based on clinical Ki-67 expression and serum infiltrating lymphocytes related nomogram for predicting the diagnosis of glioma-grading

Background

Compelling evidence indicates that elevated peripheral serum lymphocytes are associated with a favorable prognosis in various cancers. However, the association between serum lymphocytes and glioma is contradictory. In this study, a nomogram was established to predict the diagnosis of glioma-grading through Ki-67 expression and serum lymphocytes.

Methods

We performed a retrospective analysis of 239 patients diagnosed with LGG and 178 patients with HGG. Immunohistochemistry was used to determine the Ki-67 expression. Following multivariate logistic regression analysis, a nomogram was established and used to identify the most related factors associated with HGG. The consistency index (C-index), decision curve analysis (DCA), and a calibration curve were used to validate the model.

Results

The number of LGG patients with more IDH1/2 mutations and 1p19q co-deletion was greater than that of HGG patients. The multivariate logistic analysis identified Ki-67 expression, serum lymphocyte count, and serum albumin (ALU) as independent risk factors associated with HGG, and these factors were included in a nomogram in the training cohort. In the validation cohort, the nomogram demonstrated good calibration and high consistency (C-index = 0.794). The Spearman correlation analysis revealed a significant association between HGG and serum lymphocyte count (r = −0.238, P <0.001), ALU (r = −0.232, P <0.001), and Ki-67 expression (r = 0.457, P <0.001). Furthermore, the Ki-67 expression was negatively correlated with the serum lymphocyte count (r = −0.244, P <0.05). LGG patients had lower Ki-67 expression and higher serum lymphocytes compared with HGG patients, and a combination of these two variables was significantly higher in HGG patients.

Conclusion

The constructed nomogram is capable of predicting the diagnosis of glioma-grade. A decrease in the level of serum lymphocyte count and increased Ki-67 expression in HGG patients indicate that their immunological function is diminished and the tumor is more aggressive.

Prognostic value of pretreatment serum albumin−globulin ratio in urothelial carcinoma: A systematic review and meta-analysis

Objective

To evaluate whether pretreatment albumin−globulin ratio (AGR) can be used as a biomarker for predicting the prognosis of patients with urothelial carcinoma (UC).

Methods

We systematically searched PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Google Scholar and Cochrane Library; the search time was up to May 2022. Stata 16.0 was used for data processing and statistical analysis.

Results

We identified 12 studies with 5,727 patients from 317 unique citations during the meta-analysis. Our results suggested that a low AGR before treatment was significantly associated with poor overall survival (OS) [hazard ratio (HR) = 1.99, 95% confidence interval (CI) = 1.45-2.75, P < 0.001], cancer-specific survival (CSS) [HR=2.01, 95% CI = 1.50-2.69, P < 0.001] and recurrence-free survival (RFS) [HR=1.39, 95% CI = 1.12-1.72, P = 0.002]. Furthermore, we defined different subgroups according to ethnicity, cancer type, cut-off value, sample size and stage. Similar prognostic outcomes for OS and CSS were observed in most subgroups. However, for subgroup of stage, the low pretreatment AGR only predicted the poor survival of patients with non-metastatic UC.

Conclusion

Our meta-analysis revealed that the AGR before treatment could be used as a predictive biomarker to indicate the prognosis of UC patients during clinical practice, especially in patients with non-metastatic UC.

Preoperative hematological inflammatory markers associated with grade and survival in Meningiomas

Meningiomas represent the most frequently diagnosed intracranial tumors. Inflammatory cells present in the tumor can modulate both antitumor and protumor functions, and modify the therapeutic response. Hematological inflammatory parameters have provided prognostic information useful in the treatment and clinical evaluation of several tumors. The aim of this study was to evaluate preoperative hematological markers of patients with meningiomas and to relate them to clinical variables and recurrence-regrowth free survival. Eighty-nine patients without corticosteroid therapy were included. Blood test results and tumor characteristics were collected from medical records. Associations between clinical characteristics and the recurrence-regrowth free survival (RFS) were evaluated using Cox proportional hazard analysis and Kaplan-Meier curves. The receiver operating characteristic (ROC) curves were constructed. Of the 89 cases, 73 (82%) were grade I and 16 (18%) grade II. The mean age was 53 ± 13.9 years, with higher frequency in women. Anemia was observed in 23.6% and neutrophilia in 42% of the patients. In univariate analysis, anemia (p = 0.04), neutrophilia (p = 0.02) and neutrophil/lymphocyt ratio (NLR) (p = 0.02) were associated with an increased risk of recurrence-regrowth and shorter RFS. In multivariate analysis, anemia and NLR > 4.1 represented a higher risk of recurrence-regrowth (p = 0.003). The ROC curve analysis showed that only the lymphocyte/monocyte (L/M) > 2.5 was able to predict the tumor grade. The preoperative presence of anemia, neutrophilia, NLR > 4.1 and L/M > 2.5 were associated with a worse prognosis in meningiomas. The use of preoperative hematological inflammatory parameters as prognostic factors can be promissing for evaluation and follow-up of meningiomas.

Identification of diagnostic and prognostic signatures derived from preoperative blood parameters for oral squamous cell carcinoma

Background

We aimed to develop novel diagnostic and prognostic signatures based on preoperative inflammatory, immunological, and nutritional parameters in blood (PIINPBs) by machine learning algorithms for patients with oral squamous cell carcinoma (OSCC).

Methods

A total of 486 OSCC patients and 200 age and gender-matched non-OSCC patients who were diagnosed and treated at our institution for noninfectious, nontumor diseases were retrospectively enrolled and divided into training and validation cohorts. Based on PIINPB, 6 machine learning classifiers including random forest, support vector machine, extreme gradient boosting, naive Bayes, neural network, and logistic regression were used to derive diagnostic models, while least absolute shrinkage and selection operator (LASSO) analyses were employed to construct prognostic signatures. A novel prognostic nomogram integrating a PIINPB-derived prognostic signature and selected clinicopathological parameters was further developed. Performances of these signatures were assessed by receiver operating characteristic (ROC) curves, calibrating curves, and decision tree.

Results

Diagnostic models developed by machine learning algorithms from 13 PIINPBs, which included counts of white blood cells (WBC), neutrophils (N), monocytes (M), lymphocytes (L), platelets (P), albumin (ALB), and hemoglobin (Hb), along with albumin-globulin ratio (A/G), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI), displayed satisfactory discriminating capabilities in patients with or without OSCC, and among OSCC patients with diverse pathological grades and clinical stages. A prognostic signature based on 6 survival-associated PIINPBs (L, P, PNI, LMR, SII, A/G) served as an independent factor to predict patient survival. Moreover, a novel nomogram integrating prognostic signature and tumor size, pathological grade, cervical node metastasis, and clinical stage significantly enhanced prognostic power [3-year area under the curve (AUC) =0.825; 5-year AUC =0.845].

Conclusions

Our results generated novel and robust diagnostic and prognostic signatures derived from PIINPBs by machine learning for OSCC. Performance of these signatures suggest the potential for PIINPBs to supplement current regimens and provide better patient stratification and prognostic prediction.

Prognostic Significance of Preoperative Neutrophil-to-Lymphocyte Ratio in Patients With Meningiomas

Background

Meningiomas are the most common benign intracranial tumors. However, even WHO grade I meningiomas occasionally show local tumor recurrence. Prognostic factors for meningiomas have not been fully established. Neutrophil-to-lymphocyte ratio (NLR) has been reported as a prognostic factor for several solid tumors. The prognostic value of NLR in meningiomas has been analyzed in few studies.

Materials and Methods

This retrospective study included 160 patients who underwent surgery for meningiomas between October 2010 and September 2017. We analyzed the associations between patients’ clinical data (sex, age, primary/recurrent, WHO grade, extent of removal, tumor location, peritumoral brain edema, and preoperative laboratory data) and clinical outcomes, including recurrence and progression-free survival (PFS).

Results

Forty-four meningiomas recurred within the follow-up period of 3.8 years. WHO grade II, III, subtotal removal, history of recurrence, Ki-67 labeling index ≥3.0, and preoperative NLR value ≥2.6 were significantly associated with shorter PFS (P < 0.001, < 0.001, 0.002, < 0.001, and 0.015, respectively). Furthermore, NLR ≥ 2.6 was also significantly associated with shorter PFS in a subgroup analysis of WHO grade I meningiomas (P = 0.003). In univariate and multivariate analyses, NLR ≥2.6 remained as a significant predictive factor for shorter PFS in patients with meningioma (P = 0.014).

Conclusions

NLR may be a cost-effective and novel preoperatively usable biomarker in patients with meningiomas.

DNA repair and cell synthesis proteins: immunohistochemical expression and correlation with recurrence-regrowth in meningiomas

Meningiomas are considered the second most common neoplasm of the central nervous system in adults. Most of them are benign with slow growth, frequent in women and with a high recurrence rate. In tumors, DNA error repair processes lose efficacy, providing mutagenesis and genomic instability. This work evaluated the expression of proteins involved in cell synthesis (cyclin D1) and DNA errors repair (MUTYH, XPF, XPG) in meningiomas, relating them to clinical, tumor and survival variables. The study included 85 patients, with a mean age of 52 ± 13.3 years and most of them women (2:1 ratio). Sixty-seven cases were grade I (79%). Grade II tumors were independent predictors of recurrence-regrowth (HR: 2.8; p = 0.038). The high expression of cyclin D1 was associated with grade II (p = 0.001) and low MUTYH expression with grade I (p = 0.04). Strong expression of XPF and XPG was associated with grade II (p = 0.002; p < 0.001) and with recurrence-regrowth (p = 0.04; p = 0.003). Strong XPF expression was significantly related to large tumors (p = 0.03). An association of cyclin D1, MUTYH and XPF were found. Survival was not associated with the expression of any of the proteins studied. To know the role of DNA repair proteins and cell synthesis is important for understanding the processes of origin and tumor development. Grade II meningiomas and strong expression of XPF and XPG were predictors of recurrence or regrowth and may assist in clinical management, considering the high recurrence of meningiomas and the absence of consensus regarding treatment.

microRNAs and Markers of Neutrophil Activation as Predictors of Early Incidental Post-Surgical Pulmonary Embolism in Patients with Intracranial Tumors

Venous thromboembolism (VTE) is a common complication of cancer that severely increases morbidity and mortality. Patients with intracranial tumors are more likely to develop VTE than patients with cancers at other sites. Conversely, limited tools exist to identify patients with high thrombotic risk. Upon activation, neutrophils release their content through different mechanisms triggering thrombosis. We explored the ability of microRNAs (miRNAs) and plasma markers of neutrophil activation measured before surgery to predict the risk of early post-surgical pulmonary embolism (PE) in glioma and meningioma patients. We recruited and prospectively followed 50 patients with glioma and 50 with meningioma, 34% of whom in each group developed an early objectively-diagnosed post-surgical PE. We measured miRNA expression and neutrophil markers (cell-free DNA, nucleosomes, calprotectin and myeloperoxidase) before surgery. In glioma patients, we adjusted and validated a predictive model for post-surgical PE with 6 miRNAs: miR-363-3p, miR-93-3p, miR-22-5p, miR-451a, miR-222-3p and miR-140-3p (AUC = 0.78; 95% Confidence Interval (CI) [0.63, 0.94]) and another with cfDNA and myeloperoxidase as predictors (AUC = 0.71; 95% CI [0.52, 0.90]). Furthermore, we combined both types of markers and obtained a model with myeloperoxidase and miR-140-3p as predictors (AUC = 0.79; 95% CI [0.64, 0.94]). In meningioma patients we fitted and validated a predictive model with 6 miRNAs: miR-29a-3p, miR-660-5p, miR-331-3p, miR-126-5p, miR-23a-3p and miR-23b-3p (AUC = 0.69; 95% CI [0.52, 0.87]). All our models outperformed the Khorana score. This is the first study that analyzes the capability of plasma miRNAs and neutrophil activation markers to predict early post-surgical PE in glioma and meningioma patients. The estimation of the thrombotic risk before surgery may promote a tailored thromboprophylaxis in a selected group of high-risk patients, in order to minimize the incidence of PE and avoid bleedings.

Meningioma transcription factors link cell lineage with systemic metabolic cues

Background

Tumor cells recapitulate cell-lineage transcriptional programs that are characteristic of normal tissues from which they arise. It is unclear why such lineage programs are fatefully maintained in tumors and if they contribute to cell proliferation and viability.

Methods

Here, we used the most common brain tumor, meningioma, which is strongly associated with female sex and high body mass index (BMI), as a model system to address these questions. We screened expression profiling data to identify the transcription factor (TF) genes which are highly enriched in meningioma, and characterized the expression pattern of those TFs and downstream genes in clinical meningioma samples as well as normal brain tissues. Meningioma patient-derived cell lines (PDCLs) were used for further validation and characterization.

Results

We identified 8 TFs highly enriched in meningioma. Expression of these TFs, which included sine oculis homeobox 1 (SIX1), readily distinguished meningiomas from other primary brain tumors and was maintained in PDCLs and even in pulmonary meningothelial nodules. In meningioma PDCLs, SIX1 and its coactivator eyes absent 2 (EYA2) supported the expression of the leptin receptor (LEPR), the cell-surface receptor for leptin (LEP), the adipose-specific hormone that is high in women and in individuals with high BMI. Notably, these transcriptional regulatory factors, LEPR and LEP, both contributed to support meningioma PDCLs proliferation and survival, elucidating a survival dependency on both a core transcriptional program and a metabolic cell-surface receptor.

Conclusions

These findings provide one rationale for why lineage TF expression is maintained in meningioma and for the epidemiological association of female sex and obesity with meningioma risk.

A comprehensive study of risk factors for post-operative pneumonia following resection of meningioma

BACKGROUND

Post-operative pneumonia (Pop) following meningioma surgery is the dominant systemic complication which could cause serious threats to patients. It is unclear whether hematological biochemical markers are independently associated with the Pop. This study attempted to perform a more comprehensive study of taking both clinical factors and hematological biomarkers into account to promote the management of patients after meningioma surgery.

METHODS

We collected clinical and hematological parameters of 1156 patients undergoing meningioma resection from January 2009 to January 2013. According to whether the symptoms of pneumonia had manifested,patients were divided into the Pop group and the Non-Pop group. We analyzed the distinctions of clinical factors between the two groups. We successively performed univariate and multivariate regression analysis to identify risk factors independently associated with the Pop.

RESULTS

4.4% patients infected with the Pop (51 of 1156). The median age at diagnosis of the Pop patients was significantly older than the Non-Pop group (p = 0.002). There were strike distinctions of post-operative hospital stays between two groups, with 21 days and 7 days each (p < 0.001). On multivariate analysis, tumor relapse (p < 0.001), skull base lesions (p = 0.001), intra-operative blood transfusion (p = 0.018) and cardiovascular diseases (p = 0.001) were linked with increased risk of the Pop following meningioma resection. For hematological biochemical markers, it was the factor of Red blood cell distribution width-standard deviation (RDW-SD) (OR 5.267, 95%CI 1.316, 21.078; p = 0.019) and Neutrophils lymphocytes ratio (NLR) (OR 2.081, 95%CI 1.063, 4.067; p = 0.033) that could appreciably predict the Pop.

CONCLUSIONS

Apart from tumor recurrence, localizations, intra-operative blood transfusion and cardiovascular diseases are independent risk factors for the Pop. We initially found hematological RDW-SD and NLR are also important predictors.