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Record W2943592582 · doi:10.3389/fonc.2019.00337

Stereotactic Body Radiotherapy (SBRT) for Oligometastatic Spine Metastases: An Overview

2019· review· en· W2943592582 on OpenAlexaff
Kang Zeng, Chia‐Lin Tseng, Hany Soliman, Yonatan Weiss, Arjun Sahgal, Sten Myrehaug

Bibliographic record

VenueFrontiers in Oncology · 2019
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRadiosurgeryRadiation therapyRandomized controlled trialRadiologySurgery

Abstract

fetched live from OpenAlex

The oligometastatic state is hypothesized to represent an intermediary state of cancer between widely metastatic disease and curable, localized disease. Advancements in radiotherapy have allowed for delivery of high precision, dose escalated treatment known as stereotactic body radiotherapy (SBRT) to targets throughout the body with excellent rates of local control. Recently, the first phase II randomized trial comparing conventional radiotherapy to comprehensive SBRT of oligometastatic disease demonstrated an overall survival and progression free survival advantage. The spine is a common site of metastasis, and a complex site for SBRT given the adjacent spinal cord and the tumor embedded within the bone tissue putting the patient at risk of fracture. Although there are expert spine SBRT guidelines for practice, there are as yet no reported randomized trials that proves superiority as compared to conventional radiation. The use of SBRT in patients with oligometastatic disease and spinal metastases is the focus of this review.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.132
GPT teacher head0.456
Teacher spread0.323 · 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

Citations115
Published2019
Admission routes1
Has abstractyes

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