NCOG-23. CLINICIAN AND PATIENT REPORTED OUTCOMES IN YOUNG ADULTS WITH GLIOBLASTOMA: RESULTS FROM A MULTIMODAL PROSPECTIVE STUDY
Bibliographic record
Abstract
Abstract The median age for glioblastoma (GBM) is 65 years old, however, younger patients have a similarly dismal prognosis. The adolescent and young adult (AYA) population (15-39 years) is a unique and understudied population. Our study aimed to identify survivorship needs in adult patients in AYA population (<40 yrs) with GBM through analysis of patient and clinician-reported outcomes (PROs and CROs). The Molecular, Imaging and Neurological assessment Database (MIND-CNS) captures Neurological Assessment in Neuro-Oncology (NANO) scores, MDASI-BT and FACIT-SP12 responses at first clinic visit and follow-ups for patients with GBM. We tested associations of the two age groups (18-39 vs. 40 years and older) with each domain of NANO, MDASI-BT and FACIT-SP12 at baseline and at follow-up visits using multivariate logistic regression models, adjusting for MGMT promoter methylation and extent of resection. There were 104 patients with GBM enrolled, including 11 young adults, (median =30 years) and 93 older adults (median =65 years). Young and older adults scored similarly in the domains of NANO, MDASI-BT, and FACIT-SP12 at baseline. MDASI domains at follow-up showed statistically significant lower scores on weakness, fatigue, distress, irritability, drowsiness, and disturbed sleep in younger vs. older adults (adjusted p<0.05). Younger adults had less difficulty with memory and concentration, and their symptoms interfered less with work, walking, and overall enjoyment of life. They also reported feeling more peaceful, finding greater comfort and strength in their faith and beliefs. A comparison of NANO score at baseline and progression will be performed at data maturation. While PROs were similar at baseline, young adults reported lower severity in their physical symptoms and higher spiritual well-being compared to older adults at follow-up visits, highlighting different survivorship experiences. Data maturation will allow for deeper analysis to better inform supportive strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".