Psychosocial characteristics of chronic pain in cancer survivors referred to an Australian multidisciplinary pain clinic
Bibliographic record
Abstract
OBJECTIVE: To describe the clinical and psychosocial characteristics of chronic pain in cancer survivors referred to one Australian hospital's ambulatory pain clinic over a 7-year period (2013-19), and to compare cancer treatment-related pain with comorbid non-malignant pain. METHOD: Retrospective chart review including responses to standardized self-report questionnaires (Brief Pain Inventory, Depression Anxiety Stress Scale, Pain Self-Efficacy Questionnaire, Pain Catastrophizing Scale), routinely collected in all patients referred to pain clinics at Australian and New Zealand hospitals. RESULTS: Of 3510 new referrals during the study period, 267 (7.5%) had a history of cancer and 176 (5.0%) met the study's eligibility criteria. Their average age was 63 ± 13 years, with 55% female. Breast cancer survivors were commonest, followed by hematological, prostate, melanoma, and colorectal, a median of 3 years post-diagnosis. Pain was attributed to cancer treatment in 87 (49%), surgery being the commonest modality. Multimodal treatment (n = 89, 58%) was significantly commoner in the treatment-related pain group (p < 0.001). Average pain severity was moderate, as was pain-related disability and distress. Pain cognitions were often maladaptive (low pain self-efficacy, high pain catastrophizing), predicted by pre-existing anxiety and depression. Associations between pain cognitions and outcomes were medium-to-large. Differences between treatment pain and comorbid pain were small-to-medium. Their scores were similar to Australian pain clinic norms. CONCLUSION: Cancer treatment causes tissue damage, but pain-related distress and disability in survivors is associated with maladaptive pain cognitions. Survivors with poor pain outcomes should be evaluated for unhelpful thoughts and beliefs especially when they have pre-existing depression or anxiety.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".