Characterization of chronic pain, pain interference, and daily pain experiences in adult survivors of childhood cancer: a report from the Childhood Cancer Survivor Study
Bibliographic record
Abstract
ABSTRACT: Although survivors of childhood cancer are at an increased risk, little is known about the prevalence of chronic pain, associated interference, and daily pain experiences. Survivors (N = 233; mean age = 40.8 years, range 22-64 years; mean time since diagnosis = 32.7 years) from the Childhood Cancer Survivor Study completed pain and psychosocial measures. Survivors with chronic pain completed 2-week, daily measures assessing pain and psychological symptoms using mHealth-based ecological momentary assessment. Multivariable-modified Poisson and linear regression models estimated prevalence ratio estimates (PR) and mean effects with 95% confidence intervals (CI) for associations of key risk factors with chronic pain and pain interference, respectively. Multilevel mixed models examined outcomes of daily pain and pain interference with prior day symptoms. Ninety-six survivors (41%) reported chronic pain, of whom 23 (24%) had severe interference. Chronic pain was associated with previous intravenous methotrexate treatment (PR = 1.6, 95% CI 1.1-2.3), respiratory (PR = 1.8, 95% CI 1.2-2.5), gastrointestinal (PR = 1.6, 95% CI 11.0-2.3), and neurological (PR = 1.5, 95% CI 1.0-2.1) chronic health conditions, unemployment (PR = 1.4, 95% CI 1.0-1.9) and clinically significant depression and anxiety (PR = 2.9, 95% CI 2.0-4.2), as well as a diagnosis of childhood Ewing sarcoma or osteosarcoma (PR = 1.9, 95% CI 1.0-3.5). Higher pain interference was associated with cardiovascular and neurological conditions, unemployment and clinical levels of depression and/or anxiety, and fear of cancer recurrence. For male, but not female survivors, low sleep quality, elevated anxiety, and elevated depression predicted high pain intensity and interference the next day. A substantial proportion of childhood cancer survivors experience chronic pain and significant associated interference. Chronic pain should be routinely evaluated, and interventions are needed.
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 | 0.003 |
| 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 | 0.001 |
| 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".