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Genomic-Adjusted Radiation Dose Model to Predict Radiotherapy Benefit Across Cancer Types


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In a study reported in The Lancet Oncology, Scott et al found that application of the genomic-adjusted radiation dose (GARD) model to cohorts of patients with different types of cancer showed a significant association of GARD with benefit of radiotherapy.

As stated by the investigators, “We previously introduced the gene expression-based radiosensitivity index (RSI), a biomarker of tumor radiosensitivity that has been validated in multiple cohorts spanning various cancer types by classifying patients as either being radiosensitive or radioresistant. Subsequently, we developed the GARD, a novel model that integrates RSI and physical dose of radiation to quantify the biological effect of a given dose in an individual patient.”

Study Details

In the pooled pan-cancer analysis, data were collected from a series of 11 previously published datasets of patients with seven types of cancer (breast, head and neck, non–small cell lung, pancreatic, and endometrial cancers, as well as melanoma and glioma) that had sufficient information to calculate GARD (ie, gene expression via microarray, physical radiation dose, and dose per fraction) and clinical outcome. The overall data set included 1,615 patients; of these, 1,298 (982 with radiotherapy, 316 without radiotherapy) were assessed for time to first recurrence and 677 (424 with radiotherapy, 253 without radiotherapy) were assessed for overall survival.

GARD was calculated for each patient who received radiotherapy in each cohort. Associations of GARD with outcomes were assessed in separate models, using radiation dose and sham-GARD (patients treated without radiotherapy who were modeled as receiving a standard-of-care dose of radiotherapy) for comparisons.

Key Findings

Pooled analysis showed that GARD as a continuous variable was significantly associated with time to first disease recurrence (hazard ratio [HR] = 0.98, 95% CI = 0.97­–0.99, P = .0017) and overall survival (HR = 0.97, 95% CI = 0.95–0.99, P = .0007) among patients receiving radiotherapy.

Interaction tests showed a significant interaction between GARD and radiotherapy treatment status for overall survival (P = .011 for interaction) but not for time to first recurrence (P = .22 for interaction).

The same analysis in patients not treated with radiotherapy (sham-GARD) showed no association between GARD and either time to first recurrence (HR = 1.00, 95% CI = 0.97–1.03, P = 1.00) or overall survival (HR = 1.00, 95% CI = 0.98–1.02, P = .87). Analysis by physical dose of radiation showed no significant association with time to first recurrence (HR = 0.99, 95% CI = 0.97–1.01, P = .53) or overall survival (HR = 1.00, 95% CI = 0.96–1.04, P = .95).

The investigators concluded, “The biological effect of radiotherapy, as quantified by GARD, is significantly associated with time to first recurrence and overall survival for patients with cancer treated with radiation. It is predictive of radiotherapy benefit, and physical dose of radiation is not. We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalizing radiotherapy prescription dose.”

Javier F. Torres-Roca, MD, of the Department of Radiation Oncology, Moffitt Cancer Center, is the corresponding author for The Lancet Oncology article.

Disclosure: The investigators reported that there was no external funding for the study. For full disclosures of the study authors, visit thelancet.com.

The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
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