SUVR (SUVmax Lymphoma/SUVmax Liver) Vs Deauville Score for Predicting Relapse in Hodgkin Lymphoma
Bibliographic record
Abstract
Background The Deauville score (DS) assessed by fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) is the current standard method for evaluating treatment response in patients with Hodgkin lymphoma (HL). However, DS is a qualitative and somewhat subjective evaluation. Recent evidence supports the use of the standardized uptake value ratio (SUVR) as a more quantitative and objective assessment of treatment response. Objective To compare the diagnostic performance of DS and SUVR at the EOT FDG PET/CT in predicting PFS in patients with HL. Methods We included patients with classical HL treated with curative intent between 2000 and 2019 who had EOT PET/CT scans. Each EOT scan was re-scored according to DS and SUVR. SUVR was defined as lesional SUVmax divided by liver SUVmax. Receiver operator curve (ROC) analysis determined the optimal SUVR cut-off value using Youden's index. We computed sensitivity, specificity, positive, and negative predictive values (PPV & NPV) for DS (positive ≥ 4) and SUVR (positive ≥ 1.13). Kaplan-Meier curves and Cox-regression analysis evaluated the PFS predictive ability of the two response-assessment modalities. Informed consent was obtained from all patients. Results 157 patients had available data at the EOT timepoint. Median age was 31, and 30% had limited favorable disease at diagnosis, defined as Stage I-IIA, non-bulky. Most patients received frontline ABVD chemotherapy (4-6 cycles) and 16 patients (10%) received radiation therapy. There were 35 PFS events, including 5 deaths. The optimal SUVR cut-off at EOT was 1.13. Median PFS among patients with positive DS or SUVR was 8.1 and 8.2 months, respectively. Diagnostic parameters for DS and SUVR were similar (PPV: 77% and 78%, respectively). Both DS and SUVR predicted PFS (HR 2.46 [95% CI 0.29-20.66] and HR 9.06 [95% CI 1.08-75.87], respectively). Conclusion Both SUVR with a positivity threshold of 1.13 and DS are predictive of PFS at EOT and have similar diagnostic parameters in patients with HL. However, SUVR offers a more objective assessment of treatment response.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".