α‐Fetoprotein as a predictor of outcome for children with germ cell tumors: A report from the Malignant Germ Cell International Consortium
Bibliographic record
Abstract
BACKGROUND: There are several studies describing the correlation between unsatisfactory tumor marker decline and a poor prognosis for adult patients treated for germ cell tumors. In pediatric patients, the data are limited. Therefore, this study retrospectively analyzed data from Children's Oncology Group (COG) protocol AGCT0132 to determine whether a relationship exists between α-fetoprotein (AFP) decline and outcome. METHODS: One hundred thirty-one patients with germ cell tumors who were enrolled in COG protocol AGCT0132 were eligible for this analysis of AFP decline. The serum AFP half-life was calculated from levels collected postoperatively as a baseline and after the start of chemotherapy. AFP decline was defined as automatically satisfactory (AFP normalized within the first 2 AFP measures after the start of chemotherapy), calculated satisfactory (AFP half-life ≤7 days after the start of chemotherapy), and unsatisfactory. RESULTS: The 3-year cumulative incidence of relapse was 11% (95% confidence interval [CI], 6.0%-18%) for patients with a satisfactory decline and 38% (95% CI, 13%-64%) for patients with an unsatisfactory decline (P = .006). In stratified analyses, this effect was limited to patients who were 11 years of age or older and had standard risk 2 (SR2) disease (P = .004 and P = .007, respectively). Three-year overall survival (OS) for patients with a satisfactory decline versus an unsatisfactory decline was not statistically significant. CONCLUSIONS: This study is the first to show an association between AFP decline and the cumulative incidence of relapse in pediatric patients treated for germ cell tumors. Recognition of patients at high risk for relapse may allow for early intensification of therapy, which could affect future clinical trial design.
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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 | 0.002 | 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 | 0.000 |
| 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 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".