Blood parameters score predicts long-term outcomes in stage II-III gastric cancer patients

Novel prognostic score based on the preoperative total bilirubin-albumin ratio and fibrinogen-albumin ratio in ampullary adenocarcinoma

BACKGROUND

The preoperative total bilirubin-albumin ratio (TBAR) and fibrinogen-albumin ratio (FAR) have been proven to be valuable prognostic factors in various cancers.

AIM

To detect the prognostic value of TBAR and FAR in ampullary adenocarcinoma (AC) patients who underwent curative pancreaticoduodenectomy.

METHODS

AC patients who underwent curative pancreaticoduodenectomy in the National Cancer Center of China between 1998 and 2020 were retrospectively reviewed. The prognostic cutoff values of TBAR and FAR were determined through the best survival separation model. Then, a novel prognostic score combining TBAR and FAR was calculated and validated through the logistic regression analysis and Cox regression analysis.

RESULTS

A total of 188 AC patients were enrolled in the current study. The best cutoff values of TBAR and FAR for predicting overall survival were 1.7943 and 0.1329, respectively. AC patients were divided into a TBAR-low group (score = 0) vs a TBAR-high group (score = 1) and a FAR-low group (score = 0) vs a FAR-high group (score = 1). The total score was calculated as a novel prognostic factor. Multivariable logistic regression analysis revealed that a high score was an independent protective factor for recurrence [score = 1 vs score = 0: Odds ratio (OR) = 0.517, P = 0.046; score = 2 vs score = 0 OR = 0.236, P = 0.038]. In addition, multivariable survival analysis also demonstrated that a high score was an independent protective factor in AC patients (score = 2 vs score = 0: Hazard ratio = 0.230, P = 0.046).

CONCLUSION

A novel prognostic score based on preoperative TBAR and FAR has been demonstrated to have good predictive power in AC patients who underwent curative pancreaticoduodenectomy. However, more studies with larger samples are needed to validate this conclusion.

The Predictive Value of a New Inflammatory-Nutritional Score for Quality of Life after Laparoscopic Distal Gastrectomy for Gastric Cancer

We explored the predictive value of various inflammatory-nutritional indicators for postoperative quality of life (QoL) in gastric cancer (GC) patients undergoing laparoscopic distal gastrectomy (LDG) and developed a novel inflammatory-nutritional score (INS). In this study, 156 GC patients who underwent LDG were included. We used multiple linear regression to analyze the correlation between postoperative QoL and inflammatory-nutritional indicators. Least absolute shrinkage and selection operator (LASSO) regression analysis was performed to construct INS. Hemoglobin was positively correlated with physical functioning (β =8.5; p = 0.003) and cognitive functioning (β = 3.5; p = 0.038) 3 mo, after surgery. Prognostic nutritional index (PNI) was positively associated with global health status (β =5.8; p = 0.043). Albumin-alkaline phosphatase ratio (AAPR) was negatively correlated with emotional functioning 12 mo, after surgery (β = -5.7; p = 0.024). Neutrophil-lymphocyte ratio (NLR), Lymphocyte- monocyte ratio (LMR), AAPR, hemoglobin and PNI were selected using LASSO regression analysis to construct INS. The C-index values of the model in the training group and the validation group were 0.806 (95% CI, 0.719-0.893) and 0.758 (95% CI: 0.591-0.925), respectively. INS had particular predictive value for postoperative QoL in patients undergoing LDG and provided a reference for risk stratification and clinical practice.

Development and validation of metabolic scoring to individually predict prognosis and monitor recurrence early in gastric cancer: A large-sample analysis

PURPOSE

To develop and validate a simple metabolic score (Metabolic score, MS) for use in evaluating the prognosis of gastric cancer (GC) patients and dynamically monitor for early recurrence.

METHODS

We retrospectively collected general clinicopathological data of patients who underwent radical gastrectomy for GC between September 2012 and December 2017 in the Department of Gastric Surgery of the Fujian Medical University Union Hospital. Using a random forest algorithm to screen preoperative blood indicators into the Least absolute shrinkage and selection operator (LASSO) model, we developed a novel MS to predict prognosis.

RESULTS

Data of 1974 patients were used to develop and validate the model. Total cholesterol (TCHO), bilirubin (TBIL), direct bilirubin (DBIL), and 15 other metabolic indicators had significant predictive value for the prognosis using the random forest algorithm. In the overall population, 533 patients (27.0%) had high and 1441 (73%) had low MS status. High MS status was related to tumor progression. The KM curves of 3-year OS and RFS for training set patients showed low MS had a better prognosis than high MS (OS: 79.4% vs 59.7%, P < 0.001; RFS: 76.0% vs 56.2%, P < 0.001).

CONCLUSIONS

We have developed and validated MS to predict the long-term survival of GC patients and allow early monitoring of recurrence. This will provide physicians with simple, economical, and dynamic tumor monitoring information.

Serum Inflammatory Biomarkers Contribute to the Prognosis Prediction in High-Grade Glioma

Background

To evaluate the prognostic value of serum inflammatory biomarkers and develop a risk stratification model for high-grade glioma (HGG) patients based on clinical, laboratory, radiological, and pathological factors.

Materials and Methods

A retrospective study of 199 patients with HGG was conducted. Patients were divided into a training cohort (n = 120) and a validation cohort (n = 79). The effects of potential associated factors on the overall survival (OS) time were investigated and the benefits of serum inflammatory biomarkers in improving predictive performance was assessed. Univariable and multivariable Cox regression analyses, the least absolute shrinkage and selection operator (LASSO) regression analysis, and support vector machines (SVM) were used to select variables for the final nomogram model.

Results

After multivariable Cox, LASSO, and SVM analysis, in addition to 3 other clinico-pathologic factors, platelet-to-lymphocyte ratio (PLR) >144.4 (hazard ratio [HR], 2.05; 95% confidence interval [CI], 1.25–3.38; P = 0.005) were left for constructing the predictive model. The model with PLR exhibited a better predictive performance than that without them in both cohorts. The nomogram based on the model showed an excellent ability of discrimination in the entire cohort (C-index, 0.747; 95%CI, 0.706–0.788). The calibration curves showed good consistency between the predicted and observed survival probability.

Conclusion

Our study confirmed the prognostic value of serum inflammatory biomarkers including PLR and established a comprehensive scoring system for the OS prediction in HGG patients.

A Novel Nutrition-Based Nomogram to Predict Prognosis After Curative Resection of Gastric Cancer

Objective: We sought to investigate the prognostic significance of body composition and weight change during the first 6 months of adjuvant chemotherapy after R0 resection and develop novel nomograms to accurately predict relapse-free survival (RFS) and overall survival (OS).

Methods: This retrospective study included 190 patients who underwent curative radical gastrectomy for gastric cancer and received adjuvant chemotherapy. The changes in weight and body composition including skeletal muscle index (SMI), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) were analyzed for 6 months. LASSO Cox regression and multivariate Cox regression were conducted to evaluate other clinical characteristics, which were used to construct a nomogram for the prediction of 3- and 5-year RFS and OS. The constructed nomogram was subjected to 1,000 resamples bootstrap for internal validation. The Concordance index (C-index) and time-dependent receiver operating characteristic (t-ROC) curves were used to evaluate and compare the discriminative abilities of the new nomograms, non-nutritional nomograms, and pTNM stage.

Results: The median follow-up duration was 42.0 (25.2–55.1) months. Factors included in the newly-built nomogram for RFS were pT stage, pN stage, tumor site, tumor size, nerve invasion or not, surgery type, and change of L3SMI, while factors included in the nomogram for OS were pT stage, pN stage, tumor size, nerve invasion or not, surgery type, and change of L3SMI. The C-index and t-ROC indicated that our newly-built nomograms had greater potential to accurately predict prognosis than the non-nutritional nomograms and pTNM stage system. Besides, oral nutritional supplements can reduce the degree of weight and L3SMI loss.

Conclusion: Change in skeletal muscle mass during adjuvant chemotherapy can be incorporated into predictive prognostic nomograms for RFS and OS in GC patients after radical resection. Dynamic changes in body composition and weight during adjuvant chemotherapy contribute to the early detection of poor outcomes.

Prognostic significance of the systemic immune-inflammation index in pancreatic carcinoma patients: A meta-analysis

Background: Systemic immune-inflammation index (SII) is a prognostic indicator for several malignancies, including pancreatic carcinoma; however, there is no consensus on its significance. In the current study, a systematic meta-analysis was used to explore the correlation between SII and prognosis in pancreatic carcinoma patients.

Methods: PubMed, Embase and Cochrane Library databases were screened from inception to May 2020. Studies describing the prognostic role of SII in pancreatic carcinoma were then retrieved. The pooled hazard ratio (HR) and 95% confidence interval (CI) was calculated using random- or fixed-effects models to determine the correlation between SII and prognosis.

Results: A total of four studies, comprising 1749 patients, met the inclusion criteria of the study and were therefore included in this meta-analysis. The meta-analysis showed that high SII indicated was correlated with worse overall survival (OS) in patients with pancreatic carcinoma (HR: 1.43, 95% CI: 1.24–1.65, P<0.001). These findings were validated through subgroup analyses, stratified by the American Joint Committee on Cancer (AJCC) stage. In addition, patients with high SII showed poorer cancer-specific survival (HR: 2.32, 95% CI: 1.55–3.48, P<0.001). However, analysis showed no significant correlations between SII and disease-free and relapse-free survival (RFS).

Conclusion: These findings indicate that SII is a potential non-invasive and a promising tool for predicting clinical outcomes of pancreatic carcinoma patients. However, the current research did not explore whether neoadjuvant therapy has an effect on the prognostic value of SII. Further studies using adequate designs and larger sample sizes are required to validate these findings.