Predictive Value of Preoperative Controlling Nutritional Status Score Combined with Fibrinogen-Albumin Ratio in Postoperative Local Recurrence-Free Survival of Patients with Retroperitoneal Liposarcoma

Preoperative Neutrophil-to-Lymphocyte Ratio and a New Inflammatory Biomarkers Prognostic Index for Primary Retroperitoneal Sarcomas: Retrospective Monocentric Study

PURPOSE

Inflammatory biomarkers and neutrophil-to-lymphocyte ratio (NLR) are associated with prognosis in several tumors. Data on sarcomas are limited, and insufficient on retroperitoneal sarcoma (RPS).

EXPERIMENTAL DESIGN

Patients with primary RPS operated between 2002 and 2016 were included. Hemoglobin, monocytes, NLR, platelet-to-lymphocyte ratio (PLR) were retrieved and analyzed both individually and combined into a prognostic index (IBPI). Correlation with clinicopathologic variables was studied, as well as postoperative morbidity according to NLR and IBPI risk categories. The association between overall survival (OS) and biomarkers and, in addition, the 7-year Sarculator-predicted OS probability (pOS) was analyzed using univariable and multivariable Cox models.

RESULTS

423/463 patients had complete data. The median follow-up was 84 months. The median NLR was 3.3 (IQR, 2.4-4.7), with significant variation across histologies. NLR was the only biomarker that independently predicted OS (HR, 1.2; 95% CI, 1.03-1.40; P = 0.02). The IBPI showed good discrimination for subgroups at different OS (log-rank test P < 0.0001). The Cox model for pOS alone showed a 7-year index of prediction accuracy of 26.9, which increased to 29.5 when IBPI was added to pOS as a complementary prognostic tool. IBPI was also associated with the risk of serious infectious postoperative complications (P = 0.0094; noninfectious complications, P = 0.6463).

CONCLUSIONS

NLR was an independent prognostic factor for OS in RPS. When combined into a prognostic index with hemoglobin, monocytes, and PLR, it serves as a readily available prognostic tool addressing tumor-related inflammation and helps in classifying RPS risk in addition to the Sarculator nomogram.

Multidimensional characteristics, prognostic role, and preoperative prediction of peritoneal sarcomatosis in retroperitoneal sarcoma

Background

Peritoneal sarcomatosis (PS) could occur in patients with retroperitoneal sarcomas (RPS). This study aimed to expand the understanding of PS on its characteristics and prognostic role, and develop a nomogram to predict its occurrence preoperatively.

Methods

Data of 211 consecutive patients with RPS who underwent surgical treatment between 2011 and 2019 was retrospectively reviewed. First, the clinicopathological characteristics of PS were summarized and analyzed. Second, the disease-specific survival (DSS) and recurrence-free survival (RFS) of patients were analyzed to evaluate the prognostic role of PS. Third, preoperative imaging, nearly the only way to detect PS preoperatively, was combined with other screened risk factors to develop a nomogram. The performance of the nomogram was assessed.

Results

Among the 211 patients, 49 (23.2%) patients had PS with an incidence of 13.0% in the primary patients and 35.4% in the recurrent patients. The highest incidence of PS occurred in dedifferentiated liposarcoma (25.3%) and undifferentiated pleomorphic sarcoma (25.0%). The diagnostic sensitivity of the preoperative imaging was 71.4% and its specificity was 92.6%. The maximum standardized uptake value (SUVmax) was elevated in patients with PS (P&lt;0.001). IHC staining for liposarcoma revealed that the expression of VEGFR-2 was significantly higher in the PS group than that in the non-PS group (P = 0.008). Survival analysis (n =196) showed significantly worse DSS in the PS group than in non-PS group (median: 16.0 months vs. not reached, P &lt; 0.001). In addition, PS was proven as one of the most significant prognostic predictors of both DSS and RFS by random survival forest algorithm. A nomogram to predict PS status was developed based on preoperative imaging combined with four risk factors including the presentation status (primary vs. recurrent), ascites, SUVmax, and tumor size. The nomogram significantly improved the diagnostic sensitivity compared to preoperative imaging alone (44/49, 89.8% vs. 35/49, 71.4%). The C-statistics of the nomogram was 0.932, and similar C-statistics (0.886) was achieved at internal cross-validation.

Conclusion

PS is a significant prognostic indicator for RPS, and it occurs more often in recurrent RPS and in RPS with higher malignant tendency. The proposed nomogram is effective to predict PS preoperatively.

Development and Validation of a Prognostic Model to Predict the Prognosis of Patients With Retroperitoneal Liposarcoma: A Large International Population-Based Cohort Study

Background

Retroperitoneal liposarcomas (RPLs), sarcoma of mesenchymal origin, are the most common soft tissue sarcomas (STS) of the retroperitoneum. Given the rarity of RPLs, the prognostic values of clinicopathological features in the patients remain unclear. The nomogram can provide a visual interface to aid in calculating the predicted probability that a patient will achieve a particular clinical endpoint and communication with patients.

Methods

We included a total of 1,392 RPLs patients diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. For nomogram construction and validation, patients in the SEER database were divided randomly into the training cohort and internal validation cohort at a ratio of 7:3, while 65 patients with RPLs from our center between 2010 and 2016 served as the external validation cohort. The OS curves were drawn using the Kaplan–Meier method and assessed using the log-rank test. Moreover, Fine and Gray’s competing-risk regression models were conducted to assess CSS. Univariate and multivariate analyses were performed to select the prognostic factors for survival time. We constructed a predictive nomogram based on the results of the multivariate analyses.

Results

Through univariate and multivariate analyses, it is found that age, histological grade, classification, SEER stage, surgery constitute significant risk factors for OS, and age, classification, SEER stage, AJCC M stage, surgery, and tumor size constitute risk factors for CSS. We found that the nomogram provided a good assessment of OS and CSS at 1, 3, and 5 years in patients with RPLs (1-year OS: (training cohort: AUC = 0.755 (95% CI, 0.714, 0.796); internal validation cohort: AUC = 0.754 (95% CI, 0.681, 0.827); external validation cohort: AUC = 0.793 (95% CI, 0.651, 0.935)); 3-year OS: (training cohort: AUC = 0.782 (95% CI, 0.752, 0.811); internal validation cohort: AUC = 0.788 (95% CI, 0.736, 0.841); external validation cohort: AUC = 0.863 (95% CI, 0.773, 0.954)); 5-year OS: (training cohort: AUC = 0.780 (95% CI, 0.752, 0.808); internal validation cohort: AUC = 0.783 (95% CI, 0.732, 0.834); external validation cohort: AUC = 0.854 (95% CI, 0.762, 0.945)); 1-year CSS: (training cohort: AUC = 0.769 (95% CI, 0.717, 0.821); internal validation cohort: AUC = 0.753 (95% CI, 0.668, 0.838); external validation cohort: AUC = 0.799 (95% CI, 0.616, 0.981)); 3-year CSS: (training cohort: AUC = 0.777 (95% CI, 0.742, 0.811); internal validation cohort: AUC = 0.787 (95% CI, 0.726, 0.849); external validation cohort: AUC = 0.808 (95% CI, 0.673, 0.943)); 5-year CSS: (training cohort: AUC = 0.773 (95% CI, 0.741, 0.805); internal validation cohort: AUC = 0.768 (95% CI, 0.709, 0.827); external validation cohort: AUC = 0.829 (95% CI, 0.712, 0.945))). The calibration plots for the training, internal validation, and external validation cohorts at 1-, 3-, and 5-year OS and CSS indicated that the predicted survival rates closely correspond to the actual survival rates.

Conclusion

We constructed and externally validated an unprecedented nomogram prognostic model for patients with RPLs. The nomogram can be used as a potential, objective, and supplementary tool for clinicians to predict the prognosis of RPLs patients around the world.

The Fibrinogen/Albumin Ratio Index as an Independent Prognostic Biomarker for Patients with Combined Hepatocellular Cholangiocarcinoma After Surgery

Purpose

The fibrinogen/albumin ratio (FAR) is increasingly considered as a potential biomarker for predicting prognosis in various malignant tumors, whereas the value of the FAR in predicting the recurrence-free survival (RFS) in patients with combined hepatocellular cholangiocarcinoma (cHCC-CCA) after surgery has not been studied.

Patients and Methods

A total of 104 patients with surgical-pathologically proved cHCC-CCA were retrospectively analyzed. The best cut-off value of the FAR was calculated via receiver operating characteristic (ROC) curve analysis, and the cohort was then divided into two groups as high-FAR (H-FAR) group and low-FAR (L-FAR) group. The correlation between the preoperative FAR and clinicopathological characteristics was analyzed. Uni- and multi-variable analyses for RFS were evaluated using a Cox proportional hazards model to verify the predictive value of FAR on the RFS of cHCC-CCA. Additionally, a novel clinical nomogram based on FAR was developed to preoperatively predict the RFS of HCC-CCA. The C-index and calibration were conducted to evaluate the performance of the developed nomogram.

Results

According to the cut-off value of the FAR, the patients were grouped into the H-FARI (>0.075) and L-FARI (≤0.075) groups. FAR was significantly correlated with several clinical-pathological features, including age, cirrhosis, AFP, CA19-9, BCLC staging, NLR, and PLR. In the multi-variate analysis, FAR, cirrhosis and tumor size were independent prognostic predictors for poor RFS in cHCC-CCA patients after surgery. Moreover, the clinical nomogram based on FAR was constructed, showing well-predictive accuracy.

Conclusion

The preoperative FAR is a convenient and feasible serum biomarker for predicting the RFS of cHCC-CCA after surgery. Such developed FAR-based nomogram integrating tumor size and cirrhosis could be served as a feasible and convenient tool to assist the decision-making of clinical strategy.