Evidence map›Paper›PMID 34363761›Full record

ArticleThe Lancet. Oncology2021

Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis.

Jacob G Scott, Geoffrey Sedor, Patrick Ellsworth, Jessica A Scarborough, Kamran A Ahmed, Daniel E Oliver, Steven A Eschrich, Michael W Kattan, Javier F Torres-Roca

Open access · greenAbstract read
In one paragraph

Article in The Lancet. Oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed
16.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

85 citing papers in PubMed, 148 citations in OpenAlex.

  1. Re-examining post-operative chemoradiotherapy in head and neck cancer: an updated long-term combined analysis of RTOG 9501/EORTC 22931.Annals of oncology : official journal of the European Society for Medical Oncology · 2025
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  5. Dose escalation based onRadiation oncology (London, England) · 2022
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  9. Radiation Oncology-Biology Integration Network: Bridging the Gap between Biological Research and Clinical Practice.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
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25 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 1 country.

Jacob G ScottTranslational Hematology and Oncology Research, Radiation Oncology Department, Cleveland Clinic, Cleveland, OH, USA; Systems Biology and Bioinformatics, Case Western Reserve University, Cleveland, OH, USA.
Geoffrey SedorSchool of Medicine, Case Western Reserve University, Cleveland, OH, USA.
Patrick EllsworthSchool of Medicine, Case Western Reserve University, Cleveland, OH, USA.
Jessica A ScarboroughTranslational Hematology and Oncology Research, Radiation Oncology Department, Cleveland Clinic, Cleveland, OH, USA; Systems Biology and Bioinformatics, Case Western Reserve University, Cleveland, OH, USA.
Kamran A AhmedDepartment of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA; Department of Oncologic Sciences, University of South Florida College of Medicine, Tampa, FL, USA.
Daniel E OliverDepartment of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA; Department of Oncologic Sciences, University of South Florida College of Medicine, Tampa, FL, USA.
Steven A EschrichDepartment of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA; Department of Oncologic Sciences, University of South Florida College of Medicine, Tampa, FL, USA.
Michael W KattanDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA.
Javier F Torres-RocaDepartment of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA; Department of Oncologic Sciences, University of South Florida College of Medicine, Tampa, FL, USA. Electronic address: Javier.torresroca@moffitt.org.
Cleveland Clinic · USCase Western Reserve University · USMoffitt Cancer Center · USFlorida College · USUniversity of South Florida · US

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI KENNETH Lynn WRIGHT · 1998 to 2026
$93.5M
NCI NIH HHS P30 CA076292
6 · The paper itself

Abstract

backgroundDespite advances in cancer genomics, radiotherapy is still prescribed on the basis of an empirical one-size-fits-all paradigm. Previously, we proposed a novel algorithm using the genomic-adjusted radiation dose (GARD) model to personalise prescription of radiation dose on the basis of the biological effect of a given physical dose of radiation, calculated using individual tumour genomics. We hypothesise that GARD will reveal interpatient heterogeneity associated with opportunities to improve outcomes compared with physical dose of radiotherapy alone. We aimed to test this hypothesis and investigate the GARD-based radiotherapy dosing paradigm.

methodsWe did a pooled, pan-cancer analysis of 11 previously published clinical cohorts of unique patients with seven different types of cancer, which are all available cohorts with the data required to calculate GARD, together with clinical outcome. The included cancers were breast cancer, head and neck cancer, non-small-cell lung cancer, pancreatic cancer, endometrial cancer, melanoma, and glioma. Our dataset comprised 1615 unique patients, of whom 1298 (982 with radiotherapy, 316 without radiotherapy) were assessed for time to first recurrence and 677 patients (424 with radiotherapy and 253 without radiotherapy) were assessed for overall survival. We analysed two clinical outcomes of interest: time to first recurrence and overall survival. We used Cox regression, stratified by cohort, to test the association between GARD and outcome with separate models using dose of radiation and sham-GARD (ie, patients treated without radiotherapy, but modelled as having a standard-of-care dose of radiotherapy) for comparison. We did interaction tests between GARD and treatment (with or without radiotherapy) using the Wald statistic.

findingsPooled analysis of all available data showed that GARD as a continuous variable is associated with time to first recurrence (hazard ratio [HR] 0·98 [95% CI 0·97-0·99]; p=0·0017) and overall survival (0·97 [0·95-0·99]; p=0·0007). The interaction test showed the effect of GARD on overall survival depends on whether or not that patient received radiotherapy (Wald statistic p=0·011). The interaction test for GARD and radiotherapy was not significant for time to first recurrence (Wald statistic p=0·22). The HR for physical dose of radiation was 0·99 (95% CI 0·97-1·01; p=0·53) for time to first recurrence and 1·00 (0·96-1·04; p=0·95) for overall survival. The HR for sham-GARD was 1·00 (0·97-1·03; p=1·00) for time to first recurrence and 1·00 (0·98-1·02; p=0·87) for overall survival.

interpretationThe 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 personalising radiotherapy prescription dose.

fundingNone. VIDEO ABSTRACT.

Indexed as

Radiotherapy DosageDatabases, FactualHumansNeoplasmsPrecision MedicineRadiation GenomicsRecurrenceSurvival Rate

Identifiers

PMID34363761
PMCPMC12818176
OpenAlexW3192108828

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.