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Record W4297964923 · doi:10.1001/jamaoncol.2022.4394

Treatment With Stereotactic Ablative Radiotherapy for Up to 5 Oligometastases in Patients With Cancer

2022· article· en· W4297964923 on OpenAlexaff
Robert Olson, Will Jiang, Mitchell Liu, Alanah Bergman, Devin Schellenberg, Benjamin Mou, Abraham Alexander, Hannah Carolan, Fred Hsu, Stacy Miller, Siavash Atrchian, Elisa Chan, Clement Ho, Islam Mohamed, Angela Lin, Tanya Berrang, Andrew Bang, Nick Chng, Quinn Matthews, Sarah Baker, Vicky Huang, Ante Mestrovic, Derek Hyde, C. Lund, Howard Pai, Boris Valev, Shilo Lefresene, Scott Tyldesley

Bibliographic record

VenueJAMA Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsPositive Living NorthKelowna General HospitalUniversity of British Columbia
Fundersnot available
KeywordsSABR volatility modelMedicinePopulationProstate cancerRadiation therapyCancerAblative caseBreast cancerLung cancerCohortOncologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Importance: After the publication of the landmark SABR-COMET trial, concerns arose regarding high-grade toxic effects of treatment with stereotactic ablative body radiotherapy (SABR) for oligometastases. Objective: To document toxic effects of treatment with SABR in a large cohort from a population-based, provincial cancer program. Design, Setting, and Participants: From November 2016 to July 2020, 381 patients across all 6 cancer centers in British Columbia were treated in this single-arm, phase 2 trial of treatment with SABR for patients with oligometastatic or oligoprogressive disease. During this period, patients were only eligible to receive treatment with SABR in these settings in trials within British Columbia; therefore, this analysis is population based, with resultant minimal selection bias compared with previously published SABR series. Interventions: Stereotactic ablative body radiotherapy to up to 5 metastases. Main Outcomes and Measures: Rate of grade 2, 3, 4, and 5 toxic effects associated with SABR. Findings: Among 381 participants (122 women [32%]), the mean (SD; range) age was 68 (11.1; 30-97) years, and the median (range) follow-up was 25 (1-54) months. The most common histological findings were prostate cancer (123 [32%]), colorectal cancer (63 [17%]), breast cancer (42 [11%]), and lung cancer (33 [9%]). The number of SABR-treated sites were 1 (263 [69%]), 2 (82 [22%]), and 3 or more (36 [10%]). The most common sites of SABR were lung (188 [34%]), nonspine bone (136 [25%]), spine (85 [16%]), lymph nodes (78 [14%]), liver (29 [5%]), and adrenal (15 [3%]). Rates of grade 2, 3, 4, and 5 toxic effects associated with SABR (based on the highest-grade toxic effect per patient) were 14.2%; (95% CI, 10.7%-17.7%), 4.2% (95% CI, 2.2%-6.2%), 0%, and 0.3% (95% CI, 0%-0.8%), respectively. The cumulative incidence of grade 2 or higher toxic effects associated with SABR at year 2 by Kaplan-Meier analysis was 8%, and for grade 3 or higher, 4%. Conclusions and Relevance: This single-arm, phase 2 clinical trial found that the incidence of grade 3 or higher SABR toxic effects in this population-based study was less than 5%. Furthermore, the rates of grade 2 or higher toxic effects (18.6%) were lower than previously published for SABR-COMET (29%). These results suggest that SABR treatment for oligometastases has acceptable rates of toxic effects and potentially support further enrollment in randomized phase 3 clinical trials. Trial Registration: ClinicalTrials.gov Identifier: NCT02933242.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.024
GPT teacher head0.332
Teacher spread0.309 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations69
Published2022
Admission routes1
Has abstractyes

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