Opioid Risk Screening in an Oncology Palliative Medicine Clinic
Bibliographic record
Abstract
PURPOSE: Little information exists on factors that predict opioid misuse in oncology. We adopted the Screener and Opioid Assessment for Patients With Pain-Short Form (SOAPP-SF) and toxicology testing to assess for opioid misuse risk. The primary objective was to (1) identify characteristics associated with a high-risk SOAPP-SF score and noncompliant toxicology test, and (2) determine SOAPP-SF utility to predict noncompliant toxicology tests. METHODS: From July 1, 2017, to December 31, 2017, new patients completed the Edmonton Symptom Assessment Scale (ESAS), SOAPP-SF, and narcotic use agreement. Toxicology test results were collected at subsequent visits. RESULTS: Of 223 distinct patients, 96% completed SOAPP-SF. Mean age was 61 ± 12.7 years, 58% were female, 68% were White, and 28% were Black. Eighty-three eligible patients (38%) completed toxicology testing. Younger age, male sex, and increased ESAS depression scores were associated with high-risk SOAPP-SF scores. Smoking habit was associated with an aberrant test. An SOAPP-SF score ≥ 3 predicted a noncompliant toxicology test. CONCLUSION: Male sex, young age, and higher ESAS depression score were associated with a high SOAPP-SF score. Smoking habit was associated with an aberrant test. An SOAPP-SF of ≥ 3 (sensitivity, 0.74; specificity, 0.64), not ≥ 4, was predictive of an aberrant test; however, performance characteristics were decreased from those published by Inflexxion, for ≥ 4 (sensitivity, 0.86; specificity, 0.67). The specificity warrants caution in falsely labeling patients. The SOAPP-SF may aid in meeting National Comprehensive Cancer Network recommendations to screen oncology patients for opioid misuse.
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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 | 0.003 | 0.012 |
| 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) | 0.001 | 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".