# Correlation between systemic immune inflammatory index and prognostic nutritional index and prognosis of osteosarcoma patients and construction of prediction model

**Authors:** Qingsong Huang, Jinquan Li, Xihong Sun, Zegan Sun

PMC · DOI: 10.1186/s12891-026-09494-6 · BMC Musculoskeletal Disorders · 2026-01-22

## TL;DR

This study shows that combining immune and nutritional markers improves survival predictions for osteosarcoma patients.

## Contribution

A novel nomogram model integrating SII and PNI with clinical factors for improved osteosarcoma prognosis prediction.

## Key findings

- High SII and low PNI are associated with worse 5-year survival in osteosarcoma patients.
- The nomogram model outperforms individual biomarkers with an AUC of 0.976.
- SII, PNI, Enneking stage, recurrence, and metastasis are independent prognostic factors.

## Abstract

To explore the predictive value of systemic immune inflammatory index (SII) and prognostic nutritional index (PNI) for the prognosis of patients with osteosarcoma, and to construct and validate an individualized survival prediction model.

The clinical data of osteosarcoma patients who underwent surgery in the 900th Hospital of the Joint Logistics Support Force from January 2012 to January 2020 were retrospectively analyzed. Preoperative SII (platelets × neutrophils/lymphocytes) and PNI (albumin + 5 × lymphocytes) were calculated, and the optimal cutoff values​were determined by ROC curve. The Kaplan-Meier method was used to draw survival curves to analyze their relationship with the overall survival time of patients. Pearson correlation analysis was used to analyze the correlation between SII and PNI. Cox regression analysis was used to analyze independent prognostic factors, and the nomogram model was constructed using R software and internally validated.

The 5-year overall survival rate of the high SII group was significantly lower than that of the low SII group (27.7% vs. 87.0%, p < 0.05); the 5-year overall survival rate of the low PNI group was significantly lower than that of the high PNI group (23.1% vs. 83.6%, p < 0.05). SII was negatively correlated with PNI (r=-0.410, P < 0.001). The high SII + low PNI group had the worst prognosis, while the low SII + high PNI group had the best prognosis. Cox multivariate analysis showed that SII > 552.60, PNI ≤ 43.38, Enneking stage III, local recurrence, and metastasis were independent risk factors affecting the prognosis of osteosarcoma patients (P < 0.05). A nomogram for predicting the overall survival (OS) of osteosarcoma patients was constructed based on SII, PNI, Enneking stage, local recurrence, and metastasis. The C index of the model was 0.870, and the validation C index was 0.828. The calibration curve showed that the predicted and actual survival rates were highly consistent. The ROC curve shows that the AUC (0.976) of the nomogram prediction model is significantly higher than the indexes such as SII(AUC = 0.811), PNI(AUC = 0.791) and Enneking stage (AUC = 0.761).

SII and PNI are effective biomarkers for the prognosis of osteosarcoma. The nomogram integrating these indices with clinical characteristics better reflects osteosarcoma’s multi-faceted features, providing a stronger basis for individualized treatment.

## Linked entities

- **Diseases:** osteosarcoma (MONDO:0002623)

## Full-text entities

- **Diseases:** inflammatory (MESH:D007249), osteosarcoma (MESH:D012516)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12910910/full.md

## References

3 references — full list in the complete paper: https://tomesphere.com/paper/PMC12910910/full.md

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Source: https://tomesphere.com/paper/PMC12910910