DIVERGT screening procedure predicts general cognitive functioning in adult long‐term survivors of pediatric acute lymphoblastic leukemia: A PETALE study
Bibliographic record
Abstract
BACKGROUND: Acute lymphoblastic leukemia (ALL) is the most common cancer in children. Because of major improvements in treatment protocols, the survival rate now exceeds 80%. However, ALL treatments can cause long-term neurocognitive sequelae, which negatively impact academic achievement and quality of life. Therefore, cognitive sequelae need to be carefully evaluated. The DIVERGT is a battery of tests proposed as a screening tool, sensitive to executive function impairments in children and adolescent cancer survivors. Our study aimed at verifying the predictive value of the DIVERGT on general cognitive functioning in adult long-term survivors of ALL. METHODS: ALL survivors completed the DIVERGT 13.4 years, on average, after remission (N = 247). In addition, 49 of these survivors (equally selected amongst those with low, average, and high DIVERGT scores) as well as 29 controls completed a more comprehensive neuropsychological evaluation within a 3-year period from DIVERGT administration. Multivariate regression analysis was used to assess the predictive value of the DIVERGT on general intelligence, mathematics, verbal memory, and working memory. As a follow-up analysis, three performance groups were created based on the DIVERGT results. Multivariate analysis of variance (MANOVA) assessed neuropsychological differences between groups. RESULTS: The DIVERGT accurately predicted General Ability Index (GAI) (P < 0.0001), mathematics (P < 0.0001) and verbal memory (P = 0.045). Moreover, the low-performance group consistently had poorer performance than the high-performance and control groups on the neuropsychological tests. CONCLUSION: The DIVERGT is a useful, time-effective screening battery for broader neurocognitive impairments identification in long-term adult ALL survivors. It could be implemented as routine examination in cancer follow-up clinics.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".