Development and Validation of Nomograms Based on Gamma-Glutamyl Transpeptidase to Platelet Ratio for Hepatocellular Carcinoma Patients Reveal Novel Prognostic Value and the Ratio Is Negatively Correlated With P38MAPK Expression

Abstract

BackgroundEarly prediction of recurrence and death risks is significant to the treatment of hepatocellular carcinoma (HCC) patients. We aimed to develop and validate prognosis nomogram models based on the gamma-glutamyl transpeptidase (GGT)-to-platelet (PLT) ratio (GPR) for HCC and to explore the relationship between the GPR and inflammation-related signaling pathways.MethodsAll data were obtained from 2000 to 2012 in the Affiliated Hospital of Qingdao University. In the training cohort, factors included in the nomograms were determined by univariate and multivariate analyses. In the training and validation cohorts, the concordance index (C-index) and calibration curves were used to assess predictive accuracy, and receiver operating characteristic curves were used to assess discriminative ability. Clinical utility was evaluated using decision curve analysis. Moreover, improvement of the predictive accuracy of the nomograms was evaluated by calculating the decision curve analysis, the integrated discrimination improvement, and the net reclassification improvement. Finally, the relationship between the GPR and inflammation-related signaling pathways was evaluated using the independent-samples t-test.ResultsA larger tumor size and higher GPR were common independent risk factors for both disease-free survival (DFS) and overall survival (OS) in HCC (P < 0.05). Good agreement between our nomogram models’ predictions and actual observations was detected by the C-index and calibration curves. Our nomogram models showed significantly better performance in predicting the HCC prognosis compared to other models (P < 0.05). Online webserver and scoring system tables were built based on the proposed nomogram for convenient clinical use. Notably, including the GPR greatly improved the predictive ability of our nomogram models (P < 0.05). In the validation cohort, p38 mitogen-activated protein kinase (P38MAPK) expression was significantly negatively correlated with the GPR (P < 0.01) and GGT (P = 0.039), but was not correlated with PLT levels (P = 0.063). And we found that P38MAPK can regulate the expression of GGT by quantitative real-time PCR and Western blotting experiments.ConclusionsThe dynamic nomogram based on the GPR provides accurate and effective prognostic predictions for HCC, and P38MAPK-GGT may be a suitable therapeutic target to improve the prognosis of HCC patients.

A Novel Nomogram Based on Hepatic and Coagulation Function for Evaluating Outcomes of Intrahepatic Cholangiocarcinoma After Curative Hepatectomy: A Multi-Center Study of 653 Patients

“…Liver function indexes including bilirubin, albumin, alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), aspartate aminotransferase (AST) and alanine aminotransferase (ALT), are essential serum markers to determine the hepatic reserve function and feasibility of liver resection, on the basis of these indexes, several scoring systems including ALBI, FIB-4, AGR, AAPR and APRI, have been validated as efficient prognostic indicators for liver cancer patients ( 17 , 26 , 27 ). Several studies have reported that GPR demonstrated prognostic value in HCC ( 19 , 28 ); however, the predictive capability of GPR for the survival of surgically treated ICC patients is unknown. As a critical indicator of coagulation function, although INR has been proposed as a promising prognostic marker in patients with HCC and biliary tract cancer ( 21 , 29 ), its predictive effect in patients with ICC has not been studied separately.…”

A Potential Prognostic Marker for Recognizing VEGF-Positive Hepatocellular Carcinoma Based on Magnetic Resonance Radiomics Signature

“…Furthermore, we established a nomogram relying on a combined model that can simply calculate the likelihood of VEGF status. The clinical utility of the nomogram was appraised by means of decision curve analysis ( 28 ). By measuring the disparity between the true- and false-positive rate at different thresholds, net benefits were calculated ( 29 ).…”

TROP2 as Patient-Tailoring but Not Prognostic Biomarker for Breast Cancer

“…For analysis, both the staining intensity and percentage of positive tumor cells were graded and multiplied to obtain an overall staining score as described previously. 14 Staining intensity was scored on a scale of 0‐3 as follows: 0 (negative), 1 (weak), 2 (medium) and 3 (strong). Percentage of positive tumor cells was categorized into five semi-quantitative classes: 0 (≤5% positive cells), 1 (6–25% positive cells), 2 (26–50% positive cells), 3 (51–75% positive cells) and 4 (>76% positive cells).…”