Long-term Neurocognitive Outcomes in Young Adult Survivors of Childhood Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Five-year survival rates of childhood acute lymphoblastic leukemia (ALL) exceed 80% due to central nervous system-directed treatment including cranial radiation (CRT) and chemotherapy. However, these treatments are associated with neurocognitive compromise, the extent of which is correlated with higher dose and younger age at treatment. The aims of this study were to explore long-term neurocognitive outcomes in adult survivors of childhood ALL, and to identify measures sensitive to neurotoxicity in long-term survivors. We examined 24 adults who received 18 Gy CRT and chemotherapy for treatment of ALL between ages 2 and 15 years (median, 5.5). Time since diagnosis ranged from 6 to 26 years (median, 16.6). Younger age at diagnosis and longer time since diagnosis were associated with lower scores on a computerized battery that requires speed and accuracy across a number of domains (MicroCog), and other standardized neurocognitive tests. When compared with population norms, MicroCog indices were below average in survivors diagnosed with ALL before age 5, but only the reasoning/calculation index was below average in survivors diagnosed with ALL after age 5. In contrast, intelligence quotient (IQ) scores were average. In addition to confirming earlier studies showing that younger children are more vulnerable to treatment-related neurotoxicity, here we show that deficits exist many years post treatment even with a relatively lower dose of CRT, and that these deficits are especially evident on tasks involving rapid processing of information.
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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 | 0.000 | 0.002 |
| 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".