1264MO - Development and validation of a unifying pre-treatment decision tool for intracranial and extracranial metastasis-directed radiotherapy

Background

Metastasis-directed therapy (MDT) has the potential to improve clinical outcomes and even overall survival (OS). However, prognostication and appropriate patient selection for MDT remain challenging. We aimed to develop a unifying model predictive of OS for patients with intracranial and extracranial disease to refine patient selection for MDT and clinical trials.

Methods

We assembled a multi-institutional cohort of patients treated with MDT to spine, brain, and/or lung metastases. Treatments included stereotactic body radiation therapy, radiosurgery, and whole brain radiation therapy. Candidate variables for recursive partitioning analysis were selected per prior studies: ECOG performance status, time from primary diagnosis (TPD), number of additional non-target organ systems involved (NOS), and intracranial metastases.

Results

A database of 1,362 patients was assembled with 424 intracranial, 352 lung, and 607 spinal treatments (n=1,383). Of patients treated for intracranial disease, 75% also had extracranial disease. Treatments were split into training (TC) (70%, n=968) and internal validation (IVC) (30%, n=415) cohorts. The TC had median ECOG of 0 (interquartile range [IQR]: 0-1), NOS of 1 (IQR: 0-1), and OS of 18 months (IQR: 7-35). The resulting model components and weights were: ECOG = 0, 1, and > 1 (0, 1, and 2); 0, 1, and > 1 NOS (0, 1, and 2); and intracranial target (2). The model demonstrated high concordance in the TC (0.72) and IVC (0.72). The score demonstrated concordance of 0.65-0.71 for each target site (spine, brain, and lung), and each variable used in the model met statistical significance (p<0.0001).

Conclusions

This pre-treatment decision tool identifies patients with the longest survival after MDT, indicating a patient population with systemic disease who may benefit most from aggressive local therapy. This model represents a unifying model applicable in settings of both intracranial and extracranial disease. Carefully selected patients may benefit from MDT even in the presence of intracranial disease.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

R.O. Kowalchuk: Financial Interests, Personal, An immediate family member of Dr. Kowalchuk is employed by GE Healthcare: GE Healthcare. All other authors have declared no conflicts of interest.