The pain of survival: Prevalence, patterns, and predictors of pain in survivors of childhood cancer.
Bibliographic record
Abstract
OBJECTIVE: Survivors of childhood cancer experience late effects as a result of their cancer treatment. Evidence for the prevalence of pain as a late effect has been equivocal. This study aimed to describe the prevalence and patterns of pain and biospsychosocial variables that may be related to pain in this population. METHOD: Survivors of childhood cancer (n = 299; 52.5% male; median age = 16.1[4.6-32.6] years; years off therapy = 9.1[2.0-23.7]) were included. Survivors completed a health assessment questionnaire as part of their long-term survivor clinic appointment (median = 3.0 appointments, range = 1.0-7.0) annually or biannually between 2014 and 2017 (Time 1-Time 4). Prevalence of pain was examined and latent class analysis (LCA) was used to identify patterns of pain based on longitudinal reports of pain. Binary logistic regression examined biopsychosocial variables at Time 1 (T1) associated with class membership. RESULTS: Forty-seven percent of survivors reported pain during at least one clinic visit. Headaches were the most prevalent type of pain (26.4%). Survivors of Wilms' Tumor and Ewing's Sarcoma reported the highest prevalence of pain (51.5% and 50.0%, respectively). LCA revealed two clinically relevant profiles: "infrequent or no pain" (74.3%) and "persistent pain" (25.7%). Logistic regression showed that female sex (odds ratio, OR = 2.69, 95% confidence interval, CI [.99, 7.31]), depressive symptomatology at T1 (OR = 2.27, 95% CI [1.31, 3.94]), and drinking to intoxication at T1 (OR = 3.07, 95% CI [1.03, 9.15]), were related to persistent pain. CONCLUSION: Pain is prevalent among survivors of childhood cancer. Future research should characterize the experience of pain in this population so interventions may be developed. Assessment of pain during regular long-term follow-up appointments is warranted. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".