The Association between the Preoperative Prognostic Nutritional Index and the Controlling Nutritional Status Score on Tumor Stage, Chemotherapeutic Response and Overall Survival in Ovarian Cancer

Prognostic and clinicopathological impacts of Controlling Nutritional Status (CONUT) score on patients with gynecological cancer: a meta-analysis

BACKGROUND

The Controlling Nutritional Status (CONUT) score has proven to be a potential biomarker for determining the prognosis of patients with various types of cancer. Its value in determining the prognosis of patients with gynecological cancer, however, remains unknown. The present study was a meta-analysis that aimed to evaluate the prognostic and clinicopathological significance of the CONUT score in gynecological cancer.

METHODS

The Embase, PubMed, Cochrane Library, Web of Science, and China National Knowledge Infrastructure databases were comprehensively searched through November 22, 2022. A pooled hazard ratio (HR), together with a 95% confidence interval (CI), was used to determine whether the CONUT score had prognostic value in terms of survival outcomes. Using odds ratios (ORs) and 95% CIs, we estimated the relationship between the CONUT score and clinicopathological characteristics of gynecological cancer.

RESULTS

We evaluated 6 articles, involving a total of 2,569 cases, in the present study. According to the results of our analyses, higher CONUT scores were significantly correlated with decreased overall survival (OS) (n = 6; HR = 1.52; 95% CI = 1.13-2.04; P = 0.006; I2 = 57.4%; Ph = 0.038) and progression-free survival (PFS) (n = 4; HR = 1.51; 95% CI = 1.25-1.84; P < 0.001; I2 = 0; Ph = 0.682) in gynecological cancer. Moreover, higher CONUT scores were significantly correlated with a histological grade of G3 (n = 3; OR = 1.76; 95% CI = 1.18-2.62; P = 0.006; I2 = 0; Ph = 0.980), a tumor size ≥ 4 cm (n = 2; OR = 1.50; 95% CI = 1.12-2.01; P = 0.007; I2 = 0; Ph = 0.721), and an advanced International Federation of Gynecology and Obstetrics (FIGO) stage (n = 2; OR = 2.52; 95% CI = 1.54-4.11; P < 0.001; I2 = 45.5%; Ph = 0.175). The correlation between the CONUT score and lymph node metastasis, however, was not significant.

CONCLUSIONS

Higher CONUT scores were significantly correlated with decreased OS and PFS in gynecological cancer. The CONUT score, therefore, is a promising and cost-effective biomarker for predicting survival outcomes in gynecological cancer.

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.

Development of Nomogram Models Based on Peripheral Blood Score and Clinicopathological Parameters to Predict Preoperative Advanced Stage and Prognosis for Epithelial Ovarian Cancer Patients

Purpose

Nutritional and inflammatory states are crucial in cancer development. The purpose of this study is to construct a scoring system grounded on peripheral blood parameters associated with nutrition and inflammation and explore its value in stage, overall survival (OS), and progression-free survival (PFS) prediction for epithelial ovarian cancer (EOC) patients.

Patients and Methods

Four hundred and fifty-three EOC patients were retrospectively identified and their clinical data and relevant peripheral blood parameters were collected. The ratio of neutrophil to lymphocyte, lymphocyte to monocyte, fibrinogen to lymphocyte, total cholesterol to lymphocyte and albumin level were calculated and dichotomized. A scoring system named peripheral blood score (PBS) was constructed. Univariate and multivariate Logistic or Cox regression analyses were used to select independent factors; these factors were then used to develop nomogram models of advanced stage and OS, PFS, respectively. The internal validation and DCA analysis were performed to evaluate models.

Results

Lower PBS indicated a better prognosis and higher PBS indicated inferior. High PBS is associated with advanced stage, high CA125, serous histological type, poor differentiation, and accompanied ascites. The logistic regression showed age, CA125, and PBS were independent factors for the FIGO III-IV stage. The nomogram models for advanced FIGO stage based on these factors showed good efficiency. FIGO stage, residual disease, and PBS were independent factors affecting OS and PFS, the nomogram models composed of these factors had good performance. DCA curves revealed the models augmented net benefits.

Conclusion

PBS can be a noninvasive biomarker for EOC patients' prognosis. The related nomogram models could be powerful, cost-effective tools to provide information of advanced stage, OS, and PFS for EOC patients.

The Prognostic Value of Prognostic Nutritional Index in Patients with Ovarian Cancer: A Systematic Review and Meta-Analysis

Controversy still exists with regard to the prognostic value of prognostic nutritional index (PNI) in ovarian cancer. A systematic search based on the databases of Web of Science, Embase, PubMed, Chinese National Knowledge Infrastructure (CNKI) and WanFang Dataset were conducted up to March 22, 2022. We included both retrospective and prospective observational studies with comparison of prognosis of patients who were divided into two groups: low and high PNI group. The Newcastle-Ottawa Scale (NOS) was applied to evaluate the quality of enrolled studies. All analyses were performed using Stata software. The pooled results were reported as hazard ratios (HRs) with the 95% confidence intervals (95% CIs). Finally, 12 studies involving 3,190 patients were included. High PNI group had a significantly improved overall survival (OS, HR: 0.67, 95% CI: 0.53-0.84), progression-free survival (PFS, HR: 0.74, 95% CI: 0.63-0.87), and cancer-specific survival (CSS, HR: 0.43, 95% CI: 0.20-0.94) compared with the low PNI group. The sensitivity analysis and publication bias indicated our results were reliable. PNI could be applied as a promising index to predict prognosis in ovarian cancer. Our results need to be validated in future studies.