Can 18F-FDG-Positron Emission Tomography be a Prognostic Tool in Children With Rhabdomyosarcoma Treated With Definitive Radiotherapy?
Bibliographic record
Abstract
BACKGROUND: Persisting residual masses at treatment completion are known in rhabdomyosarcoma (RMS) treated with definitive radiotherapy (RT) to the primary site, but their prognostic significance is uncertain. Tumor response as assessed by anatomic imaging is not prognostic and studies based on 18 F-FDG-PET response are limited. We report the prognostic significance of persistent FDG-avidity in residual masses, assessed 3-month postdefinitive RT, in pediatric RMS. MATERIALS AND METHODS: Children 15 years old or below with Group III/IV RMS who received only definitive radiotherapy for local control from June 2013 to December 2018, and had 18 F-FDG-PET CT at 3 months post-RT were retrospectively analyzed for outcomes and other prognostic factors. RESULTS: Sixty-three children were eligible (Group III-55, Group IV-8). 18 F-FDG-PET CT scan done 3 months postradiotherapy showed FDG-avid residual masses in 10 patients (15.9%), anatomic residual in 24 (38.1%), and no anatomic/FDG-avid residual in 29(46.0%). At a median follow-up of 38 months (interquartile range, 24 to 55 mo), 3-year EFS of patients with FDG-avid residual masses was 40.0% (95% CI: 18.7% to 85.5%) versus the rest of the cohort, which was 71.9% (95% CI: 59.8% to 86.5%) ( P =0.008). Three-year OS of patients with FDG-avid residual masses was 50.8% (95% CI: 25.7% to 100.0%) versus the rest of the cohort, which was 77.0% (95% CI: 65.1% to 91.0%) ( P =0.037). Presence of FDG-avid residual disease persisting post-RT affected both EFS [HR-3.34 (95% CI: 1.29 to 8.68) ( P =0.013)] and OS [HR-3.20 (95% CI: 1.01 to 10.12) ( P =0.048)] on univariate analysis and this significance was retained for EFS in multivariate analysis [HR-3.52 (95% CI: 1.33 to 9.30) ( P =0.011)]. CONCLUSIONS: Persistent metabolic activity in residual disease post-chemoradiotherapy in RMS may portend a poorer prognosis with an increased risk of relapse. This subset of high-risk patients needs to be identified, and further trials are warranted to develop strategies to improve their 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".