MétaCan
Menu
Back to cohort
Record W2811470123 · doi:10.1097/spc.0000000000000371

Local ablative stereotactic body radiotherapy for oligometastatic prostate cancer

2018· review· en· W2811470123 on OpenAlexaff
Tamim Niazi, Sara Elakshar, Gabriela Stroian

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2018
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsMcGill UniversityJewish General Hospital
FundersAstellas PharmaSanofiAstraZenecaAmgen
KeywordsMedicineProstate cancerAblative caseRadiation therapyProstateOncologyCancerRadiologyInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The oligometastases is considered an intermediate state of the disease between localized and wide spread metastases. Local ablative therapy to oligometastatic prostate cancer is gaining significant traction and stereotactic body radiotherapy (SBRT) is an emerging treatment modality for this patient population. In this review, we report our literature review of SBRT to prostate oligometastases. Current evidence on the role of SBRT in oligometastatic prostate cancer reported in the last 10 years was summarized. Criteria for inclusion included studies with prostate cancer only as the primary site. RECENT FINDINGS: The unique properties of the oligometastatic prostate cancer appear to carry a better prognosis than wide spread metastatic disease, especially if these metastases are amenable to local ablative therapies. Our literature review revealed that local ablative therapy, using SBRT to prostate oligometastases, is associated with significant 2-years local control and acceptable toxicity profile. SUMMARY: SBRT to oligometastatic prostate cancer patients is feasible and carries an acceptable toxicity profile. The randomized phase II and III trials, currently underway, should clearly define the real benefit of this approach on progression-free and overall survival outcomes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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 head0.141
GPT teacher head0.466
Teacher spread0.326 · 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 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

Citations9
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in Supportive and Palliative CareSame topicProstate Cancer Diagnosis and TreatmentFrench-language works237,207