Evaluating buprenorphine to treat cancer pain: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Many patients with cancer experience pain related to their disease. Opioids are commonly used for moderate-to-severe cancer-related pain but carry significant side effects that may worsen quality of life. Buprenorphine, a partial mu opioid receptor (MOR) agonist, is increasingly used for the management of cancer-related pain. Although well studied as a treatment for opioid use disorder, its role in managing cancer pain is less understood. METHODS: We aim to systematically gather, assess, and summarize prior studies on the impact of buprenorphine upon cancer-related pain. Cochrane CENTRAL, OVID Medline, EMBASE, EBSCO, and Web of Science will be searched in September 2025 for any studies available to date. Studies involving buprenorphine as an intervention upon cancer-related pain will be included where pain outcomes are measured at two or more timepoints using a validated scale. Exclusions apply to case studies/series with fewer than five subjects, qualitative studies, conference abstracts, review articles, research protocols, studies solely focused on post-operative pain, and studies not available in English translation. After final selection, study type classification, and data extraction, a quality assessment will be conducted using the Cochrane ROB 2 tool for randomized controlled trials (RCTs) and the Newcastle-Ottawa Scale for cohort and case-control studies. The summarized data will be evaluated using Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria. DISCUSSION: The primary objective is to fill a knowledge gap by summarizing literature on buprenorphine for cancer pain management, including a broad range of study designs, drug formulations, and dosing. This systematic review aims to provide a comprehensive understanding of buprenorphine's efficacy and safety in cancer pain management, which could inform clinical practice and future research directions. SYSTEMATIC REVIEW REGISTRATION: This protocol was registered in PROSPERO (CRD42022383591).
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.067 | 0.056 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.017 | 0.014 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.066 | 0.009 |
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 source (direct Gemma or distilled Codex), 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".