Elevated platelet lymphocyte ratio is a poor prognostic factor in advanced epithelial ovarian cancer

Construction of a Model for Predicting the Risk of pT3 Based on Perioperative Characteristics in cT1 Renal Cell Carcinoma: A Retrospective Study at a Single Institution

INTRODUCTION

This study explored the predictors of upstaging and multiple sites of extension, and constructed a predictive model based on perioperative characteristics to calculate the risk of upstaging of cT1 renal cell carcinoma to pT3.

METHODS

We retrospectively reviewed 1012 patients diagnosed with cT1 renal cell carcinoma who underwent surgical treatment at the Affiliated Hospital of Qingdao University between June 2016 and August 2021. The continuous and categorical variables were analyzed using the Mann-Whitney U test and Chi-square test, respectively. After randomly dividing patients into a training set and an internal validation set with a ratio of 7:3, univariate and multivariate logistic regression analyses were used to explore the predictors of upstaging and multiple sites of extension. A nomogram model was established based on the predictors of upstaging and was validated.

RESULTS

Ninety-one cases (8.99%) of renal cell carcinoma were upstaged to pT3. In the training set, multivariate logistic regression identified the following predictors of upstaging: maximum tumor diameter, hilus involvement, tumor necrosis, tumor edge irregularity, symptoms, smoking, and platelet-lymphocyte ratio. A nomogram model was established based on the predictors. The area under the receiver operating characteristic curve was 0.810 in the training set, and 0.804 in the validation set. A 10-fold internal cross-validation conducted 200 times showed that the mean area under the curve was 0.797. The calibration curve and decision curve analysis suggested that the nomogram had robust clinical predictive power. Analyses showed higher neutrophil-lymphocyte ratio and tumor necrosis were associated with multiple sites of extrarenal extension in patients with pT3a renal cell carcinoma.

CONCLUSIONS

We identified 7 predictors of upstaging to pT3 and 2 predictors of multiple sites of extension. A nomogram model was constructed with satisfactory accuracy for predicting upstaging to pT3.

Prognostic value of systemic inflammation response indexes obtained from the complete blood count in patients treated for advanced ovarian carcinoma in front line

OBJECTIVE

Various systemic inflammation response indexes (SIRI) have repeatedly been described as prognostic factors in ovarian cancer. They have not been validated in prospective trials and published results are sometimes contradictory. We aimed to explore their role in a cohort of patients diagnosed with stage III and IV ovarian cancer treated at our institution.

METHODS

We retrospectively examined the prognostic influence of the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), the monocyte-to-lymphocyte ratio (MLR), the red cell distribution width (RDW), and the mean platelet volume (MPV).

RESULTS

A total of 77 patients were analyzed. NLR > 2.243 at diagnosis, NLR before primary surgery, MLR at diagnosis, PLR > 289.1 at diagnosis, and PLR at diagnosis were significant in univariate Cox regression for progression-free survival, but none of them retained their significance in the multivariate Cox regression analysis. For overall survival, NLR >  = 2.53 at diagnosis, MLR >  = 0.245 at diagnosis, and PLR >  = 198.3 at diagnosis resulted significant in univariate COX regression; only PLR >  = 198.3 at diagnosis retained its significance in the multivariate analysis.

CONCLUSION

In our cohort, PLR >  = 198.3 was an independent prognostic factor for worse OS. The definitive role of SIRI in ovarian cancer has not yet been established. If their value as prognostic factors could finally be established, they would become a simple and economical method to predict prognosis in patients with advanced ovarian cancer. Therefore, it is time to conduct prospective, multicenter studies with larger samples to definitively establish its role in ovarian cancer, if any.

Development of prediction model to estimate future risk of ovarian lesions: A multi-center retrospective study

Background

To develop the preoperative prediction of ovarian lesions using regression-based statistics analyses and machine learning methods based on multiple serological biomarkers in China.

Methods

1137 patients with ovarian lesions in Zhujiang Hospital and 518 patients in others hospital in China were randomly assigned to training, test and external validation cohorts. Five machine learning classifiers, including Random Forest (RF), Extreme Gradient Boosting (XGB), Support Vector Classifier (SVC), K-nearest Neighbor (KN), Multi-Layer Perceptron (MLP) and the Lasso-Logistics prediction model (LLRM) were used to derive diagnostic information from 23 predictors.

Results

The RF model had a high diagnostic value (AUC = 0.968) in predicting benign and malignant ovarian disease. Age and MLR were also potential diagnostic indicators for predicting ovarian disease except tumor indicators. The RF model well distinguished borderline ovarian tumors (AUC = 0.742). The RFM had a high predictive power to identify ovarian serous adenocarcinoma (AUC = 0.943) and ovarian endometriosis cysts (AUC = 0.914).

Conclusions

The RF models can effectively predict adnexal lesions, promising to be adjuncts to the preoperative prediction of ovarian cancer.

Prognostic value of preoperative serological biomarkers in patients undergoing cytoreductive surgery for ovarian cancer peritoneal metastases

Objectives

Peritoneal metastases of ovarian cancer (PMOC) are common at initial presentation. Cytoreductive surgery (CRS) of curative intent has been proven to be efficient in increasing the overall survival (OS) and the disease-free survival (DFS) of these patients. Nevertheless, CRS is associated with high postoperative morbidity, which makes patient selection a major concern. Appropriate prognostic factors that can predict patient outcomes after surgery are still lacking. Preoperative biomarkers and their ratios have been shown to be predictive of patient prognosis for various solid tumors. We aimed to study their correlation with the prognosis of patients undergoing CRS for PMOC.

Methods

This retrospective study included patients with PMOC operated by CRS. Preoperative biomarkers and other clinicopathological characteristics were studied to determine their prognostic value in terms OS and DFS.

Results

216 patients were included. Patients with preoperative hemoglobin (Hb) <11.7 g/dL had a poorer prognosis in terms of OS (p=0.0062) and DFS (p=0.0077). Additionally, increased neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR) >0.32, and platelet-to-lymphocyte ratio (PLR) >214.5 were associated with worse OS (p=0.022, p=0.0028, and p=0.0018, respectively) and worse DFS (p=0.028, p=0.003, and p=0.019, respectively). Multivariate analysis showed that the variables mentioned above were independent predictive factors for OS and DFS.

Conclusions

Preoperative Hb level, NLR, MLR, and PLR are prognostic factors for OS and DFS in PMOC patients operated by curative CRS.

Independent predictive value of blood inflammatory composite markers in ovarian cancer: recent clinical evidence and perspective focusing on NLR and PLR

Ovarian cancer (OC) is one of the deadliest malignant tumors affecting women worldwide. The predictive value of some blood inflammatory composite markers in OC has been extensively reported. They can be used for early detection and differential diagnosis of OC and can be used for predicting survival, treatment response, and recurrence in the affected patients. Here, we reviewed the predictive values of composite inflammatory markers based on complete blood count, namely neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio, and systemic inflammation index and markers based on blood protein, namely C-reactive protein-to-albumin ratio and prognostic nutritional index in OC, with a focus on NLR and PLR. We referred to the clinical studies on these six markers, reviewed the patient population, and summarized the marker cut-off values, significance, and limitations of these studies. All these studies were retrospective and most of them were single-center clinical studies with small sample sizes. We found that the cut-off values of these markers have not been unified, and methods used to determine these values varied among studies. The predictive value of these markers on survival was mainly reflected in the postoperative patients of multiple subtypes of ovarian cancer including epithelial OC, high-grade serous ovarian carcinoma, and ovarian clear cell carcinoma. We focused on NLR and PLR and calculated their pooled hazard ratios. NLR and PLR were reliable in predicting overall and progression-free survivals in patients with OC. Therefore, it is necessary to adjust important confounding factors and conduct a long-term follow-up prospective cohort study to further clarify the cut-off values of NLR and PLR and their clinical applications.

Prognostic factors in the treatment of gastric mucosal atypical hyperplasia by endoscopic submucosal dissection

Background

Endoscopic submucosal dissection (ESD) is becoming increasingly popular as a treatment for precancerous lesions and early cancers of the stomach. However, there have been few studies on the factors associated with the recurrence of precancerous lesions after ESD.

Methods

To investigate the prognostic factors of gastric intraepithelial neoplasia, we retrospectively analyzed 115 patients who were treated with ESD between February 2018 and January 2020. Chi-square test and Fisher’s extract test were used to select factors for further investigation, and prognostic analysis was carried out with the Kaplan–Meier method and a Cox regression model.

Results

Platelet counts (P = 0.027) and albumin levels (P = 0.011) were both lower in patients with recurrence than in patients without recurrence of gastric mucosal atypical hyperplasia after ESD.

Conclusions

This study reveals that low platelet counts and albumin levels were probably unfavorable prognostic factors in mucosal atypical hyperplasia of the stomach.

Role of reactive thrombocytosis after primary cytoreductive surgery in advanced ovarian cancer

We investigated the incidence of reactive thrombocytosis after maximal cytoreductive surgery in advanced epithelial ovarian cancer (EOC) and its role in patient survival. We retrospectively reviewed the electronic medical records of patients who underwent primary cytoreductive surgery for advanced EOC from 1 January 2012 to 31 December 2017. We analyzed the serum platelet counts at various time points from before surgery, during the peri-operative period, and after each cycle of adjuvant chemotherapy. A total of 474 patients were eligible for the analysis. Among them, 401 patients (84.6%) had FIGO stage III disease status. The most common histology type was serous adenocarcinoma (405 patients, 85.4%). Seventy-nine patients (22.6%) received splenectomy, and optimal cytoreduction was achieved in 326 patients (68.8%). A week after surgery, thrombocytosis was observed in 165 patients (34.8%) in the entire cohort. Higher platelet counts were observed in patients with splenectomy compared with patients without splenectomy. In particular, thrombocytosis on the fifth cycle of adjuvant chemotherapy showed the most significant effects on overall survival in multivariate analysis. In a logistic regression model, splenectomy was significantly attributed to thrombocytosis on the fifth cycle of chemotherapy. Reactive thrombocytosis after primary cytoreductive surgery is associated with poor survival in advanced EOC, particularly when thrombocytosis is observed during adjuvant chemotherapy.

Multivariate logistic regression analysis of the correlation between five biomarkers and ovarian cancer in patients with intermediate-risk: A prospective cross-sectional study

Objective: To find potential diagnostic biomarkers for ovarian cancer (OC), a prospective analysis of the expression of five biomarkers in patients with intermediate-risk and their correlation with the occurrence of OC was conducted.

Method: A prospective observational study was carried out, patients who underwent surgical treatment with benign or malignant ovarian tumors in our hospital from January 2020 to February 2021 were included in this study, and a total of 263 patients were enrolled. Based on the postoperative pathological results, enrolled patients were divided into ovarian cancer group and benign tumor group (n = 135). The ovarian cancer group was further divided into a mid-stage group (n = 46) and an advanced-stage group (n = 82). The basic information of the three groups of patients was collected, the preoperative imaging data of the patients were collected to assess the lymph node metastasis, the preoperative blood samples were collected to examine cancer antigen 125 (CA125), carbohydrate antigen 19–9 (CA19–9), Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and the postoperative pathological data were sorted and summarized.

Result: The average during of disease in the advanced ovarian cancer group was 0.55 ± 0.18 years higher than the benign tumor group (0.43 ± 0.14 years), p < 0.001. In the advanced ovarian cancer group, the ratio of patients with the tumor, node, metastasis (TNM) stage IV (64.63%), with tumor Grade stage II and III (93.90%), and without lymph node metastasis (64.63%) was respectively more than that in the mid-stage group (accordingly 0.00, 36.96, 23.91%) (p < 0.001); The ratio of patients with TNM grade III in the mid-stage group (73.91%) was more than that in the advanced group (35.37%) (p < 0.001). The levels of the five biomarkers: CA19-9, CA125, NLR, PLR, and BDNF were different among the three groups (p < 0.001).

Conclusion: CA19-9, CA125, NLR, PLR, BDNF are five biomarkers related to the occurrence of ovarian cancer and are risk factors for it. These five biomarkers and their Combined-Value may be suitable to apply in the diagnosis and the identification of ovarian cancer in patients with intermediate-risk.

Prognostic Role of Systemic Inflammatory Markers in Patients Undergoing Surgical Resection for Oral Squamous Cell Carcinoma

Background: A high platelet−lymphocyte ratio (PLR) is a marker of systemic inflammation and, together with the neutrophil−lymphocyte ratio (NLR), is associated with poor outcomes in several cancers. We investigated the prognostic value of PLR and other systemic inflammatory markers, such as NLR, systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI), in oral squamous cell carcinoma (OSCC) patients undergoing surgical resection. Methods: We derived PLR, NLR, SII, and SIRI from a retrospective chart review of 269 consecutive OSCC patients. The complete blood count examined in the immediate preoperative period was used to compute PLR, NLR, SII, and SIRI. We analyzed the relationship between these systemic inflammatory markers and the clinicopathologic characteristics, disease-specific survival (DSS), and progression-free survival (PFS) of patients. Results: In the univariate analysis, high PLR and SII were significantly associated with worse DSS and PFS (all p < 0.05). In the multivariate analysis, PLR (HR 2.36, 95% CI 1.28−4.36 for DSS; HR 1.80, 95% CI 1.06−3.06 for PFS) was an independent predictor of survival outcomes. When PLR was analyzed as a continuous variable, the relationship between the outcome and preoperative PLR was not monotonically linear. In the subgroup analysis, PLR was more strongly associated with DSS and PFS in patients who were male, had stage III/IV OSCC, or had lymph node metastasis. Conclusion: Our data suggest that in OSCC patients, the pretreatment PLR is an independent predictor of DSS and PFS. The PLR is a readily available biomarker that will improve prognostication and risk stratification in OSCC.

Signature of arylacetamide deacetylase expression is associated with prognosis and immune infiltration in ovarian cancer

Objective

The role of the protein-coding gene arylacetamide deacetylase (AADAC) in the prognostication of ovarian cancer remains uncertain. We aimed to identify and validate its prognostic value using integrated bioinformatics analyses.

Methods

Gene expression profiles of RNA-sequencing and microarray data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus. Univariate and multivariate Cox regression models were used to evaluate the prognostic value of gene expression. The predictive accuracy of the gene signature model was evaluated using a time-dependent receiver operating characteristic (ROC) curve. In addition, the correlation between immune infiltration and AADAC was identified. A nomogram of the gene signature with clinical parameters was constructed to estimate the clinical application of the signature for survival prediction in patients with ovarian cancer.

Results

Univariate and multivariate Cox regression analyses in the training and validation cohorts indicated that a high AADAC expression signature was significantly and independently correlated with better survival outcomes in ovarian cancer. AADAC upregulation positively correlated with the infiltration of CD4+ memory T cells. Immunological signature gene sets were significantly enriched in CD4+ T cell regulation pathways. The area under the curve of the time-dependent ROC for overall survival indicated that the constructed nomogram had a moderate predictive ability for prognostic prediction in ovarian cancer.

Conclusion

AADAC expression signature significantly and independently correlated with the survival outcome and CD4+ memory T cell infiltration in ovarian cancer, indicating its potential applicability in the prediction of prognosis and immunotherapy efficacy.

Inflammatory Biomarkers as Promising Predictors of Prognosis in Cervical Cancer Patients

INTRODUCTION

Increasing evidence demonstrates a crucial role of inflammation in inducing and promoting several cancers. Pro-inflammatory upregulation of cytokines such as IL-6 has been implicated in cervical cancer development and progression through several mechanisms, for example, by inducing platelet production, activation, and aggregation. The aim of the study was to evaluate the effective prognostic impact of inflammatory biomarkers such as platelet count, platelet to lymphocyte ratio (PLR), and IL-6 in cervical cancer patients.

MATERIALS AND METHODS

Between 2016 and 2019, 108 out of 159 patients with cervical cancer have been enrolled. Cutoff level of pretreatment platelet count and PLR was identified by using the ROC curve. IL-6 tumoral and peritumoral expression was analyzed and stratified as low and high (low expression: 0 and +1; marked expression: +2 and +3).

RESULTS

Median follow-up duration was 30 months (range 16-44). Patients with higher platelet counts showed worse DFS and OS (DFS p < 0.001; OS p < 0.001). Cumulative rates of DFS and OS in patients with lower PLR were higher than in patients with higher values of PLR (DFS p = 0.032; OS p < 0.001). Survival analysis showed a better prognosis in patients with lower IL-6 expression (DFS p < 0.001; OS p < 0.001).

CONCLUSION

Nowadays, causal relationship between inflammation, innate immunity, and cancer is more widely accepted. However, many of the molecular and cellular mechanisms mediating this relationship remain unresolved. Ongoing inflammatory response was associated with poor outcomes in cervical cancer patients. A higher pretreatment platelet count and PLR value associated with higher IL-6 tumoral expression could be used to predict poor prognosis in cervical cancer patients.

Inexpensive Systemic Inflammatory Biomarkers in Ovarian Cancer: An Umbrella Systematic Review of 17 Prognostic Meta-Analyses

The association of several inflammation-based biomarkers [lymphocyte-to-monocyte, neutrophil-to-lymphocyte, and platelet-to-lymphocyte ratios (LMR, NLR, and PLR, respectively)] with the survival of epithelial ovarian cancer (EOC) patients has been extensively investigated in several systematic reviews and meta-analyses (MAs) of observational studies. The aim of this umbrella systematic review is to appraise all available results in published MAs that explored the association between these biomarkers and EOC outcomes. An umbrella systematic review of the current evidence for systemic inflammatory biomarkers in the peripheral blood of EOC patients was performed by searching several databases including PubMed/Medline and Web of Science. The quality of the MAs was appraised using the AMSTAR-2 tool as well as other qualitative criteria. The evidence was graded from convincing (Class I) to weak (Class IV). Our umbrella review appraised 17 MAs of retrospective studies (range: 7-16) with a number of enrolled patients ranging from 1,636 to 4,910 patients in each MA. All these MAs demonstrated that pretreatment high NLR and PLR, as well as low LMR, were independent predictors of poor overall survival and progression-free survival in EOC. Nearly all published MAs were conducted by Chinese researchers (16/17) and were redundant in their character. Another issue in these MAs is the absence of prior PROSPERO database registration as well as the earlier exclusion of the gray literature. On the other hand, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analyses Of Observational Studies in Epidemiology (MOOSE)-based reporting guidelines were used in nine out of the 17 MAs. A good number of MAs have transparently provided funding acknowledgment. The AMSTAR-2-based assessment showed low quality in 11 out of the 17 reviewed MAs. This negative rating was largely due to the absence of critical domains. Finally, all evaluated MAs were rated as Class III or IV (suggestive and weak, respectively). Despite the power of MAs in increasing sampling and precision, the quality of the current non-randomized evidence on this topic is still weak.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO, identifier CRD42020201493.