NCOG-12. COGNITIVE FUNCTION (CF) & QUALITY OF LIFE (QOL) IN PATIENTS TREATED WITH PROCARBAZINE, CCNU, & VINCRISTINE (PCV) + RADIOTHERAPY (RT) VS. RT FOR ANAPLASTIC OLIGODENDROGLIOMA (AO) ON NRG RTOG TRIAL 9402
Bibliographic record
Abstract
Abstract BACKGROUND PCV+RT substantially prolongs survival in AO patients, but long-term CF and QOL implications are unclear. We compared CF and QOL by treatment arm in RTOG 9402 participants and evaluated the impact that baseline characteristics had on CF, QOL, and survival. METHODS CF and QOL were evaluated using the Mini Mental State Exam (MMSE) and Brain-Quality of Life (B-QOL) scale at baseline and annually. Scores were analyzed between treatment arms at each time point for patients with ≥ 10 years of follow-up data. Shared parameter models evaluated MMSE and B-QOL scores and survival for all patients. RESULTS 42/148 (28.4%) participants in PCV+RT and 20/143 (14%) in RT alone arms survived ≥ 10 years. 35/42 and 39/42 (PCV+RT) and 18/20 and 17/20 (RT) participants completed baseline B-QOL and MMSE assessments, respectively. B-QOL scores did not differ between treatment groups at any time-point. Among 16 patients (10 PCV+RT, 6 RT) who completed year 10 MMSE evaluations, mean MMSE score at 10 years was higher in the RT arm (29.83 [95% CI 22.1, 30.0] vs. 26.50 [95% CI 29.4, 30.0], P= 0.04). Change in MMSE and B-QOL scores from baseline did not differ significantly between treatment groups at any time. In shared parameter models including all patients with baseline assessments, MMSE and B-QOL scores decreased over time (MMSE P= 0.0189, B-QOL P= 0.0005), but this did not differ by treatment group (MMSE P= 0.5727, B-QOL P= 0.3592). Younger age and higher KPS predicted better scores (MMSE P < 0.0001, P = 0.0002; B-QOL P = 0.0043, P = 0.0007). PCV+RT predicted better survival in both models. CONCLUSIONS PCV+RT improves survival in AO. Shared parameter models show decrease in MMSE and B-QOL over time. However, relative to RT alone, the addition of PCV did not impact change in CF and QOL over time.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".