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. 2025 Aug 1:15:1505485.
doi: 10.3389/fonc.2025.1505485. eCollection 2025.

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

Ying Qiu  1 , Jiquan Liu  1 , Shuang Chai  1 , Lili Liu  1   2 , Longqing Li  2 , Yan Zhang  2
Affiliations

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

Ying Qiu et al. Front Oncol. .

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Keywords: Comprehensive Hematological Scoring System (CHSS); neutrophil-to-lymphocyte ratio (NLR); platelet-to-lymphocyte ratio (PLR); prognosis; soft tissue sarcoma (STS).

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
(A) The optimal cutoff value of the CHSS score. The KM survival curves show overall survival in patients grouped by (B) CHSS, (C) NLR, and (D) PLR.
Figure 2
Figure 2
(A) The time-dependent ROC curves demonstrate the predictive abilities of different biomarkers; (B) The forest plot illustrates the predictive ability of CHSS across different subgroups; (C) The forest plot illustrates the predictive ability of NLR across different subgroups; (D) The forest plot illustrates the predictive ability of PLR across different subgroups.
Figure 3
Figure 3
(A) The forest plot shows the univariate analysis results of CHSS and clinical variables; (B) The forest plot shows the multivariate analysis results of CHSS and clinical variables; (C) The time-dependent ROC curve demonstrates the predictive ability of independent prognostic factors.
Figure 4
Figure 4
(A) The nomogram predicting overall survival in soft tissue sarcoma patients based on independent risk factors; (B) The calibration curve of the nomogram; (C) The net benefit curve of the nomogram; (D) The net reduction curve of the nomogram.
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