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Stereotactic Body Radiation Therapy for Spinal Metastases: Benefits and Limitations

2023· review· en· W4361027355 on OpenAlexaff
Matthias Gückenberger, Max Dahele, Wee Loon Ong, Arjun Sahgal

Bibliographic record

VenueSeminars in Radiation Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRadiosurgerySpinal cord compressionRadiation therapyRadiologyMyelopathyVertebral compression fractureSpinal cord

Abstract

fetched live from OpenAlex

Progress in biological cancer characterization, targeted systemic therapies and multimodality treatment strategies have shifted the goals of radiotherapy for spinal metastases from short-term palliation to long-term symptom control and prevention of compilations. This article gives an overview of the spine stereotactic body radiotherapy (SBRT) methodology and clinical results of SBRT in cancer patients with painful vertebral metastases, metastatic spinal cord compression, oligometastatic disease and in a reirradiation situation. Outcomes after dose-intensified SBRT are compared with results of conventional radiotherapy and patient selection criteria will be discussed. Though rates of severe toxicity after spinal SBRT are low, strategies to minimize the risk of vertebral compression fracture, radiation induced myelopathy, plexopathy and myositis are summarized, to optimize the use of SBRT in multidisciplinary management of vertebral metastases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.140
GPT teacher head0.434
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations49
Published2023
Admission routes1
Has abstractyes

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