ATRT-04. CORRELATION OF CLINICOPATHOLOGIC FEATURES AND CUMULATIVE INCIDENCE OF RELAPSE FOR PATIENTS WITH ATYPICAL TERATOID RHABDOID TUMOR ON ACNS0333: A REPORT FROM THE CHILDREN’S ONCOLOGY GROUP
Bibliographic record
Abstract
Abstract Purpose Intensive multi-modal regimens have improved survival for patients with atypical teratoid rhabdoid tumor, however relapse rates remain high. A better understanding of clinical and pathologic features associated with tumor relapse is critical to risk-stratifying patients. Patients and Methods ACNS0333 treatment consisted of multi-agent chemotherapy, high-dose chemotherapy, and radiation therapy, lasting approximately 6 months. Variables including patient age, sex, tumor location, M-stage, degree of resection, order of therapy, germline status, and molecular subgroup were analyzed. Cumulative incidence (CI) of event free survival due to relapse was evaluated for each variable. Results Thirty-three of 65 evaluable patients had tumor relapse. For the entire cohort, the CI of relapse was 21.8% at 6 months, 40.6% at one year and 50.3% at 4 years. For patients with infratentorial tumors, CI of relapse was 26.3%, 34.2% and 37.2%, at 6 months, 1 and 4 years respectfully compared to 15.3%, 49.9%, and 69.7% for those with supratentorial tumors (p 0.051). Patients with SHH subtype had no relapses in the first 6 months and CI of relapse of 37.5% at 4 years, while those with TYR and MYC subgroups had CI of relapse of 33.3% and 26.7% at 6 months and 46.3% and 73.3% at 4 years respectfully (p 0.088). Patients with germline mutations had a cumulative incidence of relapse of 20% at 6 months and 60% at 12 months compared to 22.6% and 37.7% respectfully for those without. No obvious trends were noted based on other analyzed variables. Conclusions ACNS0333 was not powered to determine prognostic indicators of relapse, however, this data suggest interesting trends based on tumor location, subtype and germline status. Infratentorial location and SHH subtype maybe associated with lower risk of relapse. Larger data sets must be compiled to further investigate these variables, perform multivariate analyses and inform risk-stratification on future trials.
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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".