Cancer-Related Pain: A Longitudinal Study of Time to Stable Pain Control and Its Clinicodemographic Predictors
Bibliographic record
Abstract
CONTEXT: Multidimensional assessment is pivotal in managing cancer-related pain. OBJECTIVES: The objectives of this study were to determine time to stable pain control (SPC) and identify its baseline clinicodemographic predictors in patients with cancer pain. METHODS: This is a prospective longitudinal study of patients attending a cancer pain clinic. Scheduled clinic attendances and weekly investigator-led phone calls enabled monitoring of patients' daily pain diary, opioid use, and other analgesic interventions. Baseline clinicodemographic variables were examined in survival analyses, which included the construction of accelerated failure time models with time ratios [TRs, (95% CIs)], based on time to SPC (pain intensity ≤3 and <3 breakthrough opioid doses over three consecutive days) for variable categories. RESULTS: Of 319 participants, 22 died before achieving SPC and were censored in the survival analysis. The median survival time (95% CI) to SPC was 22 (19-25) days. In multivariable analysis, compared to their respective reference categories, female sex (P = 0.001), substance abuse (P < 0.001), a neuropathic pain component (P < 0.001), and use of ≥1 adjuvant analgesic (P = 0.022) each had TRs > 1 (1.03-2.54), whereas soft tissue pain (P < 0.001) had a TR = 0.71 (0.62-0.82), reflecting longer and shorter time to SPC, respectively. CONCLUSION: SPC is achievable for most patients with cancer pain. Recognition of strong predictors of time to SPC, such as substance abuse, a neuropathic pain component, soft tissue pain, and current use of adjuvant analgesia, may help to triage care services based on therapeutic need and guide analgesic interventions.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".