Cancer Metastases to the Hand: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Metastatic lesions to the hand or wrist are rare and can mimic inflammatory and benign processes such as gout and infections. This often leads to misdiagnosis, underreporting, and delays in treatment. The purpose of this study was to examine all known cases of metastasis to the hand or wrist available in the literature and to analyze demographic trends, metastasis characteristics, and clinical course, and provide recommendations for management. METHODS: An online systematic review of MEDLINE, Embase, PubMed, and the Cochrane Library from inception to January 7, 2022, was completed. Studies outlining the care of a patient with acrometastases of the hand were included. Data extracted included age, sex, site of primary tumor and metastasis, presence of other metastases, time from primary diagnosis to acrometastasis diagnosis, misdiagnosis, treatment, and survival. RESULTS: Between 1889 and present, 871 lesions were described in 676 patients who met the inclusion criteria. There was no predilection for hand dominance or site of previous trauma. The mean age among patients was 59.5 (1.5-91) years, and male sex was more common (64.6%). The most common primary cancer source was the lung (39.2%), followed by the kidney (10.8%). The distal phalanx was the most frequently cited tumor location (33.7%). Mean survival after diagnosis of acrometastasis was 6.3 months (0.25-50) ± 11.5 months. CONCLUSION: Acrometastasis remains an uncommon presentation of metastatic disease with poor prognosis. Treatment currently focuses on pain management and optimizing functional outcomes. Our review led to the development of 7 treatment recommendations when managing these patients.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.025 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".