Modern Treatment of Skeletal Metastases: Multidisciplinarity and the Concept of Oligometastasis in the Recent Literature
Bibliographic record
Abstract
Bone metastases are a major concern in cancer management since they significantly contribute to morbidity and mortality. Metastatic lesions, commonly arising from breast, prostate, lung, and kidney cancers, affect approximately 25% of cancer patients, leading to severe complications such as pain, fractures, and neurological deficits. This narrative review explores contemporary approaches to bone metastases, emphasizing a multidisciplinary strategy and the evolving concept of oligometastatic disease. Oligometastases, defined by limited metastatic spread (1-5 lesions), offer a potential window for curative treatment through aggressive interventions, including stereotactic ablative radiotherapy and resection surgery. Tumor boards, integrating systemic therapies with local interventions, are crucial to optimize treatment. Despite promising results, gaps remain in defining optimal treatment sequences and refining patient selection criteria. Future research should focus on personalized approaches, leveraging biomarkers and advanced imaging to enhance outcomes and the quality of life in patients with bone metastases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".