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Record W2097071306 · doi:10.1586/era.11.169

Stereotactic body radiotherapy is an effective treatment in reirradiating spinal metastases: current status and practical considerations for safe practice

2011· review· en· W2097071306 on OpenAlexaff
Giuseppina Laura Masucci, Eugene Yu, Lijun Ma, Eric Chang, D. Létourneau, Simon S. Lo, Eric Leung, Sam Chao, Derek Hyde, Alessandra Gorgulho, A. Muacevic, David A. Larson, Michael G. Fehlings, Arjun Sahgal

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2011
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreToronto Western HospitalPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMedicineRadiosurgeryRadiation therapyRadiologyMedical physics

Abstract

fetched live from OpenAlex

Spinal metastases are a relatively common manifestation in advanced cancer patients. Low-dose conventional radiotherapy has long been the mainstay of treatment under the assumption that patients have a limited life expectancy in the order of 3-6 months. However, with new developments in systemic therapies, patients are surviving longer than expected. As the spinal retreatment rates, secondary to conventional radiation, can approach 20-50%, retreatments are likely to be more frequent. Rather than a second course of even lower-dose conventional radiation, spine stereotactic body radiotherapy (SBRT) has been developed predominantly to overcome the limitations of conventional reirradiation. Spine SBRT permits a second course of high-dose radiation aimed at local tumor control while sparing the spinal cord, and other surrounding normal tissues, of a toxic dose. The focus of this review is to provide an overview of reirradiation spine SBRT, and address key issues surrounding safe and effective practice.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.932
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.144
GPT teacher head0.503
Teacher spread0.359 · 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 teacher head, not a consensus.

Study designOther design
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

Citations52
Published2011
Admission routes1
Has abstractyes

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