<scp>A</scp>lberta <scp>B</scp>reakthrough <scp>P</scp>ain <scp>A</scp>ssessment <scp>T</scp>ool: A validation multicentre study in cancer patients with breakthrough pain
Bibliographic record
Abstract
BACKGROUND: Cancer-related breakthrough pain (BTP) is a common and quite challenging pain syndrome, with significant impact on quality of life. To date, no widely recognized and validated tool for the diagnosis and evaluation of BTP exists. The Alberta Breakthrough Pain Assessment Tool (ABPAT) underwent a validation process during its development, but no experience of its implementation in clinical practice has been reported. METHODS: ABPAT was tested in a cohort of cancer patients suffering from chronic severe cancer-related pain in order to assess its acceptability and efficacy as a tool for the characterization of BTP. RESULTS: A total of consecutive 249 patients from seven different centres were included in a 2-month study period and all completed the questionnaire; 231 out of the 249 (92.8%) stated that questions were easily understandable and 217 out of the 249 (87.1%) stated that the tool allowed to explain extensively the BTP problem. Physician-patient correlation tests about baseline BTP intensity and BTP relief by medication showed statistical significance at the level of p = 0.001 and p = 0.0001, respectively. Evaluation of the efficacy of BPT medication revealed a 78.2% of patients declaring a good relief from BTP, with a significant reduction of mean BTP numeric rating scale score (p = 0.0001), but only 55.9% of patients responded to be satisfied about time for onset of the relief. CONCLUSIONS: In this study, ABPAT resulted to be a well-accepted tool for BTP assessment and characterization in a relatively large cohort of cancer patients. It is effective in discovering the unmet needs of cancer patients and in exploring the outcomes of BTP treatment.
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 | 0.021 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".