Video Experimental Relacionado

Updated: Jan 7, 2026

Modeling Primary Bone Tumors and Bone Metastasis with Solid Tumor Graft Implantation into Bone

Modeling Primary Bone Tumors and Bone Metastasis with Solid Tumor Graft Implantation into Bone

Published on: September 9, 2020

Reevaluación del punto de corte de 8 cm: El riesgo continuo de mortalidad por tamaño tumoral apoya la estadificación

Ezekiel Dingle¹, Kole Joachim¹, Othneil Sparks¹

¹David Geffen School of Medicine at the University of California, Los Angeles, California, USA.

Journal of surgical oncology

|December 30, 2025

Abstracto

Background And Objectives:

Primary tumor size is a key prognostic factor in osteosarcoma, but quantitative risk estimates and optimal thresholds remain undefined. We quantified the size-survival relationship in high-grade osteosarcoma.

Methods:

We analyzed 1,807 high-grade osteosarcoma patients from the Surveillance, Epidemiology, and End Results (SEER) database (2000-2021) using Cox regression, systematic threshold testing (40-150 mm with multiple testing corrections), and propensity score matching at the AJCC 80 mm threshold.

Results:

Each 10 mm increase in tumor size was associated with a 6.6% increased hazard of death after adjusting for age, sex, tumor site, surgery, radiation, and chemotherapy (Hazard ratio [HR] = 1.066, p < 0.001; adjusted C-index = 0.694). Binary AJCC staging demonstrated limited mortality discrimination (34.4% vs 44.4%, 10-percentage-point spread), while three-tier soft tissue sarcoma (STS)-adapted staging revealed a 21-percentage-point mortality gradient (26.6% to 47.7%) with superior adjusted discrimination (C-index = 0.695 vs 0.680, p < 0.001). All tested thresholds demonstrated significant associations, with no single optimal cutpoint identified. Polynomial testing indicated a linear relationship (p = 0.334). Propensity score matching at the AJCC 8 cm threshold of 666 patient pairs confirmed the effect (HR = 1.443, 95%-confidence interval: 1.214-1.715, p < 0.001). Polynomial testing indicated a linear relationship (p = 0.253).

Conclusion:

Tumor size demonstrates a continuous dose-response relationship with survival. Three-tier STS staging outperforms binary AJCC classification for risk stratification.

Palabras clave:

osteosarcoma tamaño del tumor supervivencia estadificación riesgo

Más Videos Relacionados

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Videos de Conceptos Relacionados

Cancer Survival Analysis

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

Tumor Progression

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...