Post–breast surgery pain syndrome: establishing a consensus for the definition of post-mastectomy pain syndrome to provide a standardized clinical and research approach — a review of the literature and discussion
Bibliographic record
Abstract
BACKGROUND: Post-mastectomy pain syndrome (PMPS) is a frequent complication of breast surgery. There is currently no standard definition for this chronic pain syndrome. The purpose of this review was to establish a consensus for defining PMPS by identifying the various elements included in the definitions and how they vary across the literature, determining how these definitions affect the methodological components therein, and proposing a definition that appropriately encompasses all of the appropriate elements. METHODS: We searched PubMed to retrieve all studies and case reports on PMPS, and we analyzed definitions of PMPS, inclusion/exclusion criteria, and methods of measuring PMPS. RESULTS: Twenty-three studies were included in this review. We identified 7 independent domains for defining PMPS: surgical breast procedure, neuropathic nature, pain of at least moderate intensity, protracted duration, frequent symptoms, appropriate location of the symptoms and exacerbation with movement. These domains were used with varying frequency. Inclusion/exclusion criteria and methods for assessing PMPS also varied markedly. CONCLUSION: To prevent future discrepancies in both the clinical and research settings, we propose a new and complete definition based on the results of our review: PMPS is pain that occurs after any breast surgery; is of at least moderate severity; possesses neuropathic qualities; is located in the ipsilateral breast/chest wall, axilla, and/or arm; lasts at least 6 months; occurs at least 50% of the time; and may be exacerbated by movements of the shoulder girdle.
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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 | 0.031 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.019 | 0.012 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| 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 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".