# Development and validation of a Comprehensive Hematological Scoring System for predicting overall survival in patients with soft tissue sarcomas: a comparison with NLR and PLR

## TL;DR

Researchers developed a new scoring system to predict survival in soft tissue sarcoma patients, which outperforms existing blood-based biomarkers.

## Contribution

A novel Composite Hematological Scoring System (CHSS) was developed and validated for improved survival prediction in soft tissue sarcomas.

## Key findings

- CHSS outperformed NLR and PLR in predicting overall survival at all timepoints.
- High CHSS scores were strongly associated with worse survival (HR=6.197, P<0.001).
- The CHSS-based nomogram achieved a C-index of 0.79 for 3- and 5-year survival prediction.

## Abstract

Soft tissue sarcomas (STS) are rare malignancies with high relapse/metastasis risks and limited treatment efficacy. Current biomarkers like neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) lack comprehensive prognostic value due to their reliance on limited hematological parameters.

This retrospective study analyzed 206 STS patients (2016–2023) to develop a Composite Hematological Scoring System (CHSS) integrating 19 pretreatment markers. LASSO regression selected key variables (glucose, CRP, LDL-C, HDL-C, albumin, platelets, hemoglobin, lymphocytes), weighted by coefficients. CHSS’s prognostic performance was compared to NLR/PLR via Kaplan-Meier, time-dependent ROC, and Cox regression analyses. A nomogram combining CHSS with clinical variables was validated using C-index, calibration, and decision curves.

CHSS outperformed NLR/PLR in predicting overall survival (OS) across all timepoints. High CHSS patients had significantly worse OS (HR=6.197, P<0.001). Multivariate analysis confirmed CHSS, age, tumor size, and FNCLCC grade as independent predictors. The CHSS-based nomogram achieved a C-index of 0.79, with accurate 3-/5-year OS calibration.

CHSS integrates inflammation, metabolism, and nutrition markers to provide superior prognostic stratification for STS patients compared to NLR/PLR. Its integration into a nomogram supports personalized management, though multicenter validation is needed.