En Bloc Resection of Solitary Functional Secreting Spinal Metastasis
Bibliographic record
Abstract
Study Design Literature review. Objective Functional secretory tumors metastatic to the spine can secrete hormones, growth factors, peptides, and/or molecules into the systemic circulation that cause distinct syndromes, clinically symptomatic effects, and/or additional morbidity and mortality. En bloc resection has a limited role in metastatic spine disease due to the current paradigm that systemic burden usually determines morbidity and mortality. Our objective is to review the literature for studies focused on en bloc resection of functionally active spinal metastasis as the primary indication. Methods A review of the PubMed literature was performed to identify studies focused on functional secreting metastatic tumors to the spinal column. We identified five cases of patients undergoing en bloc resection of spinal metastases from functional secreting tumors. Results The primary histologies of these spinal metastases were pheochromocytoma, carcinoid tumor, choriocarcinoma, and a fibroblast growth factor 23-secreting phosphaturic mesenchymal tumor. Although studies of en bloc resection for these rare tumor subtypes are confined to case reports, this surgical treatment option resulted in metabolic cures and decreased clinical symptoms postoperatively for patients diagnosed with solitary functional secretory spinal metastasis. Conclusion Although the ability to formulate comprehensive conclusions is limited, case reports demonstrate that en bloc resection may be considered as a potential surgical option for the treatment of patients diagnosed with solitary functional secretory spinal metastatic tumors. Future prospective investigations into clinical outcomes should be conducted comparing intralesional resection and en bloc resection for patients diagnosed with solitary functional secretory spinal metastasis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".