Primary Results of NRG-RTOG1106/ECOG-ACRIN 6697: A Randomized Phase II Trial of Individualized Adaptive (chemo)Radiotherapy Using Midtreatment <sup>18</sup> F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Stage III Non–Small Cell Lung Cancer
Bibliographic record
Abstract
PURPOSE NRG-RTOG0617 demonstrated a detrimental effect of uniform high-dose radiation in stage III non–small cell lung cancer. NRG-RTOG1106/ECOG-ACRIN6697 (ClinicalTrials.gov identifier: NCT01507428 ), a randomized phase II trial, studied whether midtreatment 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) can guide individualized/adaptive dose-intensified radiotherapy (RT) to improve and predict outcomes in patients with this disease. MATERIALS AND METHODS Patients fit for concurrent chemoradiation were randomly assigned (1:2) to standard (60 Gy/30 fractions) or FDG-PET–guided adaptive treatment, stratified by substage, primary tumor size, and histology. All patients had midtreatment FDG-PET/CT; adaptive arm patients had an individualized, intensified boost RT dose to residual metabolically active areas. The primary therapeutic end point was 2-year centrally reviewed freedom from local-regional progression (FFLP), defined as no progression in or near the planning target volume and/or regional nodes. FFLP was analyzed on a modified intent-to-treat population at a one-sided Z -test significance level of 0.15. The primary imaging end point was centrally reviewed change in SUV peak from baseline to midtreatment; its association with FFLP was assessed using the two-sided Wald test on the basis of Cox regression. RESULTS Of 138 patients enrolled, 127 were eligible. Adaptive-arm patients received a mean 71 Gy in 30 fractions, with mean lung dose 17.9 Gy. There was no significant difference in centrally reviewed 2-year FFLP (59.5% and 54.6% in standard and adaptive arms; P = .66). There were no significant differences in protocol-specified grade 3 toxicities, survival, or progression-free survival ( P > .4). Median SUV peak and metabolic tumor volume (MTV) in the adaptive arm decreased 49% and 54%, from pre-RT to mid-RT PET. However, ΔSUV peak and ΔMTV were not associated with FFLP (hazard ratios, 0.997; P = .395 and .461). CONCLUSION Midtreatment PET-adapted RT dose escalation as given in this study was safe and feasible but did not improve efficacy outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".