Smooth Muscle Tumor of Uncertain Malignant Potential (STUMP): A Systematic Review of the Literature in the Last 20 Years
Bibliographic record
Abstract
Smooth Muscle Tumor of Uncertain Malignant Potential (STUMP) is a rare uterine tumor primarily affecting perimenopausal and postmenopausal women, typically aged between 45 and 55 years. Characterized by ambiguous histological features, STUMPs present diagnostic challenges as they cannot be definitively classified as benign or malignant based on morphology alone. This systematic review aims to elucidate the clinical, pathological, immunohistochemical, and treatment-related characteristics of STUMPs through an analysis of the literature from the past 20 years. The study follows PRISMA guidelines, utilizing comprehensive searches of PubMed and Scopus databases, yielding 32 studies that meet the inclusion criteria. From the analysis of these studies, it was revealed that the clinical presentations vary from common symptoms such as abnormal uterine bleeding and pelvic pain to incidental detection of uterine mass. Histologically, STUMPs demonstrate features overlapping with both leiomyomas and leiomyosarcomas, including mild nuclear atypia, low mitotic indices, and focal necrosis. Immunohistochemical markers such as p16 and p53 have been investigated for prognostic significance. Elevated p16 expression, often associated with aggressive behavior, was observed in a subset of STUMPs. Surgical management, typically involving hysterectomy or tumorectomy, is the primary treatment, though the extent of resection is variable. Adjuvant therapies are not routinely recommended, but long-term surveillance is advised, especially for high-risk patients. Recurrence rates for STUMPs are approximately 12%, with factors such as high mitotic counts and coagulative necrosis indicating higher risk. This review highlights the complexity of STUMP diagnosis and management, emphasizing the need for more precise diagnostic criteria and individualized treatment strategies. Understanding the morphological, immunohistochemical, and clinical behavior of STUMPs can improve patient outcomes and guide future research in this diagnostically challenging area.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".