Dynamic Prediction of Overall Survival for Patients with Osteosarcoma: A Retrospective Analysis of the EURAMOS-1 Clinical Trial Data

Current prediction models for patients with ostosarcoma are restricted to predictions from a single, static point in time, such as diagnosis or surgery. These approaches discard information which becomes available during follow-up and may have an impact on patient's prognosis. This study aims a...

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Bibliographic Details
Published in:Current oncology (Toronto) 2024-07, Vol.31 (7), p.3630-3642
Main Authors: Spreafico, Marta, Hazewinkel, Audinga-Dea, Gelderblom, Hans, Fiocco, Marta
Format: Article
Language:English
Subjects:
Adolescent
Adult
Bone Neoplasms - mortality
Bone Neoplasms - therapy
Child
clinical trial
Clinical trials
dynamic prediction
Female
Humans
landmark analysis
Male
Metastasis
Middle Aged
Osteosarcoma
Osteosarcoma - mortality
Osteosarcoma - therapy
Patient outcomes
Prognosis
Retrospective Studies
survival
Young Adult
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Summary:Current prediction models for patients with ostosarcoma are restricted to predictions from a single, static point in time, such as diagnosis or surgery. These approaches discard information which becomes available during follow-up and may have an impact on patient's prognosis. This study aims at developing a dynamic prediction model providing 5-year overall survival (OS) predictions from different time points during follow-up. The developed model considers relevant baseline prognostic factors, accounting for where appropriate time-varying effects and time-varying intermediate events such as local recurrence (LR) and new metastatic disease (NM). A landmarking approach is applied to 1965 patients with high-grade resectable osteosarcoma from the EURAMOS-1 trial (NCT00143030). Results show that LR and NM negatively affected 5-year OS (HRs: 2.634, 95% CI 1.845-3.761; 8.558, 95% CI 7.367-9.942, respectively). Baseline factors with strong prognostic value (HRs > 2) included poor histological response (≥10% viable tumor), axial tumor location, and the presence of lung metastases. The effect of poor versus good histological response changed over time, becoming non-significant from 3.25 years post-surgery onwards. This time-varying effect, as well as the strong impact of disease-related time-varying variables, show the importance of including updated information collected during follow-up in the model to provide more accurate survival predictions.
ISSN:1718-7729
1198-0052
1718-7729
DOI:10.3390/curroncol31070267