# Prognostic biomarkers for overall survival in patients undergoing surgery for bone metastases: a pan-cancer study

## TL;DR

This study identifies biomarkers that help predict survival in patients with bone metastases from various cancers, improving personalized treatment planning.

## Contribution

A pan-cancer prognostic nomogram integrating tumor-specific and host-related biomarkers for bone metastases is developed and validated.

## Key findings

- IGFBP-3, NLR, and RDW are significant predictors of survival in bone metastases patients.
- A prognostic nomogram achieved strong predictive performance with AUC values of 82.3 and 81.0 at 12 and 24 months.
- Biomarkers improve prognostic stratification beyond tumor type alone.

## Abstract

Prompt diagnosis and prognostic assessment of bone metastases (BMs) remain challenging with most studies and prognostic models focusing on a single primary tumor and neglect host-related biomarkers. Therefore, this pan-cancer study aimed to evaluate bone metabolism, inflammatory, and hematological biomarkers in patients undergoing surgery for BMs, identify risk factors for BM development, and create a prognostic nomogram. A prospective cohort of adult patients with histologically confirmed BMs from various cancers was enrolled between 2020 and 2023. Baseline data included demographics, tumor type, and preoperative biomarkers such as bone turnover markers (P1NP, BAP), calcium, LDH, IGFBP-3, HALP, RDW, and NLR. Outcomes were recurrence, metastasis, and overall survival (OS), analyzed with Kaplan–Meier and Cox regression. Prognostic variables were integrated into a nomogram and validated by ROC curves and calibration. Ninety-one patients underwent surgery for BM. The most frequent primary cancers were breast (28.6%), kidney (23.1%), and lung (16.5%). Significant tumor-type differences were observed in BAP (p = 0.015), IGFBP-3 (p = 0.008), and HALP (p = 0.029). Univariate analysis identified P1NP, BAP, calcium, LDH, and RDW as prognostic markers. Multivariate models found age, kidney cancer, IGFBP-3, RDW, and NLR as independent predictors. The nomogram demonstrated strong predictive performance at 12 months (AUC = 82.3) and 24 months (AUC = 81.0). Tumor-specific and host-related biomarkers (IGFBP-3, NLR, and RDW) improved prognostic stratification beyond tumor type. The proposed nomogram demonstrated good discriminatory performance, supporting its potential use in personalized prognostic assessment and treatment planning.