Pain in long‐term survivors of childhood cancer: A systematic review of the current state of knowledge and a call to action from the Children's Oncology Group
Bibliographic record
Abstract
Survivors of childhood cancer may be at risk of experiencing pain, and a systematic review would advance our understanding of pain in this population. The objective of this study was to describe: 1) the prevalence of pain in survivors of childhood cancer, 2) methods of pain measurement, 3) associations between pain and biopsychosocial factors, and 4) recommendations for future research. Data sources for the study were articles published from January 1990 to August 2019 identified in the PubMed, PsycINFO, EMBASE, and Web of Science data bases. Eligible studies included: 1) original research, 2) quantitative assessments of pain, 3) articles published in English, 4) cancers diagnosed between birth and age 21 years, 5) survivors at 5 years from diagnosis and/or at 2 years after therapy completion, and 6) a sample size >20. Seventy-three articles were included in the final review. Risk of bias was considered using the Cochrane risk of bias tool. The quality of evidence was evaluated according to Grading of Recommendations Assessment Development and Evaluation (GRADE) criteria. Common measures of pain were items created by the authors for the purpose of the study (45.2%) or health-related quality-of-life/health status questionnaires (42.5%). Pain was present in from 4.3% to 75% of survivors across studies. Three studies investigated chronic pain according the definition in the International Classification of Diseases. The findings indicated that survivors of childhood cancer are at higher risk of experiencing pain compared with controls. Fatigue was consistently associated with pain, females reported more pain than males, and other factors related to pain will require stronger evidence. Theoretically grounded, multidimensional measurements of pain are absent from the literature.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".