Exploration of Morbidity in a Serial Study of Long-Term Brain Tumor Survivors: A Focus on Pain
Bibliographic record
Abstract
PURPOSE: Children surviving brain tumors are frequently identified as having substantially decreased health-related quality of life (HRQL) in cross-sectional studies. This study explored the HRQL of a cohort of such survivors, who were recruited as adolescents and followed for a decade, in order to determine the trajectory of their morbidities. METHOD: Children diagnosed between January 1, 1985, and December 31, 1998, more than 2 years from diagnosis (N = 40), were recruited in 2000/2001 (T1) aged 16.74 ± 4.23 years. Health Utilities Index questionnaires (HUI2/3) were completed in 2000/2001 and again at 5 years (T2) and 10 years (T3), with 37 and 25 participants then aged 21.54 ± 4.29 and 27.97 ± 4.07 years, respectively. In addition to study subjects, parental proxies completed questionnaires at T1 and T2, while study subjects selected proxies at T3. Single attributes (domains/dimensions) of HRQL and details of pain were analyzed. RESULTS: Cognition was the attribute compromised most often (T1 = 66.7% of participants, T2 = 62.2%, T3 = 60.0%). Pain was also reported frequently (T1 = 35%, T2 = 25%, T3 = 52%), and at T3 correlated moderately with HUI2 sensation (0.77) and HUI3 vision (0.44), speech (0.51), and ambulation (0.50). The lower median utility score for pain at T3 than at T1/T2 was a clinically important difference. Severe pain was identified in the lower extremities, back, upper extremities, and abdomen. Morbidity was observed also in emotion (worry HUI2 and unhappiness HUI3), sensation, and vision. CONCLUSION: Decreased HRQL in survivors of brain tumors in childhood is multifaceted. Pain is a prominent burden, along with morbidity in cognition, emotion, sensation, and vision. Further studies should explore pain and neurologic deficits, and potential opportunities for therapeutic intervention.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".