The genomic-adjusted radiation dose (GARD) model can predict outcomes of radiotherapy in patients with cancer, according to results of a study published in The Lancet Oncology.

In fact, GARD outperformed radiation dose for predicting time to first recurrence and overall survival (OS).

The researchers explained that GARD integrates the radiosensitivity index and physical dose of radiation to quantify the biological effect of a given dose in an individual patient.

The researchers compared the predictive utility of GARD with radiation dose alone using 11 previously published datasets.

The data encompassed a total of 1615 patients with 7 cancer types — breast, head and neck, lung, pancreatic, and endometrial cancers, as well as melanoma and glioma.

The researchers found that GARD was significantly associated with time to first recurrence (hazard ratio [HR], 0.98; 95% CI, 0.97-0.99; P =.0017), but the dose of radiation was not (HR, 0.99; 95% CI, 0.97-1.01; P =.53).

GARD was significantly associated with OS as well (HR, 0.97; 95% CI, 0.95-0.99; P =.0007), but the dose of radiation was not (HR, 1.00; 95% CI, 0.96-1.04; P =.95).

“We found that GARD predicts the therapeutic benefit of radiotherapy, quantifies the relative benefit of radiotherapy for each individual patient, and outperforms radiation dose, the current standard of care, in terms of recurrence and survival,” the researchers wrote.

“We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalizing radiotherapy prescription dose,” they added.

Disclosures: Some study authors declared affiliations with biotech, pharmaceutical, and/or device companies. Please see the original reference for a full list of disclosures.

Reference

Scott JG, Sedor G, Ellsorth P, et al. Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): A cohort-based pooled analysis. Lancet Oncol. Published August 4, 2021. doi:10.1016/S1470-2045(21)00347-8

This article originally appeared on Cancer Therapy Advisor