Genomic‐derived radiation dosage improves prediction of outcomes

Abstract

1 Genomic-derived radiation dosage improves prediction of outcomes U sing the predicted radiation dose effect derived from an individual patient's ge-nomic profile may result in a better outcome according to a new). The study focused on a novel algorithm that a team of researchers developed on the basis of a personalized GARD model using individual tumor ge-nomic parameters rather than the commonly administered "one-size-fits-all" dosages based on the cancer diagnosis. The researchers of this new study noted an incentive for the study: "Patients we treat uniformly do not have a uniform response." The development of GARD was spurred by an understanding that the researchers had uncovered from previous large-scale classification studies showing that the clinical heterogeneity of radiation response was influenced by individual-level differences in genetic variables in the tumors themselves. Using a gene expression-based radiosensi-tivity index that the study authors had developed earlier, they followed with the GARD model, which combined the radiosensitivity index and radiation dosages to pinpoint the biological effect on specific patients. Study Details In this study, researchers from the Cleveland Clinic, Case Western Reserve University, and the Moffitt Cancer Center conducted a pooled analysis of data from 11 previously published clinical cohorts of patients with varying outcomes for 7 different types of cancer: breast cancer (including triple-negative breast cancer), head and neck cancer, non-small cell lung cancer, pancreatic cancer, endometrial cancer, mela-noma, and glioma. They used tumor genomic data from these studies and the clinical information about each patient's treatment to calculate individualized GARD values, and they performed a stratified Cox regression analysis to test for associations of GARD and physical radiation dose with 2 clinical outcomes: time to first recurrence and overall survival. Finally, the researchers estimated the impact that varying GARD would have on 3-year survival for each of the 7 cancer types. With the exception of 3 cohorts, both time to first recurrence (local, regional, and distant metastasis) and overall survival were calculated from the end of treatment. These patients' outcomes were calculated from the date of pathological diagnosis for the glioma and endometrial cancer cohorts and from the date of randomization for the head and neck cancer cohort. There were 1615 patients included overall. Among those patients evaluated for time to first recurrence, 982 received radiotherapy, and 316 did not receive radiotherapy. Among those patients evaluated for overall survival, 424 received radiotherapy, and 253 did not. Study Results The researchers found that although the range of physical radiation doses in the cohorts was limited to values near those of the standard of care and the doses were delivered in standard fraction sizes, the GARD values showed a wide range of predicted biological effects. In analyses of the 7 cancer types combined, the researchers found that GARD was associated with time to first recurrence (hazard ratio [HR] per unit change in GARD, 0.98; 95% CI, 0.97-0.99; P = .0017) and overall survival (HR, 0.97; 95% CI, 0.95-0.99; P = .0007). Although the effects per unit change in GARD were small, patients who had similar or identical physical radiation doses often had GARD values differing by 20 or more units, so differences of this magnitude had clinically meaningful implications for patient outcomes. The GARD values for patients who did not receive radiotherapy (desig-nated as "sham-GARD") were calculated on the basis of usual doses of physical radiation and were intended as controls. These sham-GARD values were not significantly associated with either time to first recurrence