Prognostic value of PET using 18F-FDG in Hodgkin's disease for posttreatment evaluation.
Bibliographic record
Abstract
UNLABELLED: Detection of relapse after completion of therapy in patients with Hodgkin's disease (HD) and non-Hodgkin's lymphomas (NHL) constitutes an important challenge in modern medical imaging. An accurate assessment of the presence of residual disease is essential to determine which patients would benefit from additional therapy. The objective of this study was to assess the diagnostic accuracy of (18)F-FDG PET in detecting residual disease or relapse during the posttherapy period in patients with HD in comparison with CT. We also established different predictive values for (18)F-FDG PET according to the time interval between the end of therapy and the PET study. METHODS: Forty-eight patients with HD underwent (18)F-FDG PET after the completion of chemotherapy (median, 58 d) between March 1999 and April 2002. Disease-free intervals and proportions were calculated using the Kaplan-Meier method. Standardized uptake values of the most active lesion in each patient with a positive study were also measured. PET and CT results were compared with clinical follow-up, with relapse being defined by a positive biopsy or the introduction of a second-line treatment. RESULTS: Thirty-four patients were still disease-free during a mean follow-up of 605 d. Fourteen patients relapsed during a mean follow-up of 197 d. The sensitivity and specificity of (18)F-FDG PET to predict relapse were 79% and 97%, respectively. The positive predictive value and the negative predictive value were both equal to 92%. The diagnostic accuracy of (18)F-FDG PET (92%) was significantly higher than the accuracy of CT (56%) (P < 0.0005). Patients with positive (18)F-FDG PET also had a far shorter median disease-free interval (79 d) than those with positive CT (disease-free proportion of 52% at 1,143 d) (P = 0.0046). The 3 cases of false-negative (18)F-FDG PET studies that we observed occurred in patients who underwent their PET study within the first 49 d after the end of chemotherapy. CONCLUSION: Positive (18)F-FDG PET after the end of therapy in HD patients is a strong predictor of relapse. A negative PET study is also an excellent predictor of good prognosis. The diagnostic accuracy of (18)F-FDG PET to assess the presence of residual disease after therapy is superior to that of CT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".