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Can polymetastatic disease be arrested using SABR? A dosimetric analysis to inform development of a phase I trial.

2020· article· en· W3029167618 on OpenAlexaff
Mark T. Corkum, Hatim Fakir, David A. Palma, Timothy K. Nguyen, Glenn Bauman

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsLondon Health Sciences CentreWestern UniversityCancer Care Ontario
Fundersnot available
KeywordsSABR volatility modelMedicineRadiation therapyNuclear medicineClinical trialRadiosurgeryMedical physicsAblative caseRadiologyInternal medicineMathematics

Abstract

fetched live from OpenAlex

e21567 Background: Phase II randomized trials suggest that stereotactic ablative radiotherapy (SABR) improves progression-free and overall survival in patients with oligometastatic cancer, with phase III trials currently testing SABR in up to 10 metastases. Whether SABR could provide similar benefits in polymetastatic disease ( > 10 metastases) is unknown. A critical first step is to determine the feasibility of planning SABR for a large number of metastases throughout the body while maintaining acceptable organ at risk (OAR) doses. Therefore, we sought to evaluate the dosimetric feasibility of using SABR in polymetastatic disease ( > 10 sites) while adhering to OAR constraints to be used in a phase I trial (ARREST). Methods: Five craniospinal CT simulations were utilized to retrospectively contour 24 (n = 2), 30 (n = 2) and 50 (n = 1) tumour targets not present on the initial scan. Standard PTV margins were added based on institutional immobilization practices. OAR constraints from published clinical trial protocols were used. Radiotherapy plans for the highest dose level in our planned phase I trial (30Gy in 5 fractions) were created utilizing a minimum number of isocentres. Plans were created using Raystation (RaySearch Laboratories, Stockholm, Sweden) for delivery on linear accelerators using volumetric modulated arc therapy. Results: The gross tumour volumes (GTVs) ranged from 134.8– 184.2cm3 in our five test cases. The first two cases with 24 GTVs have been planned and were deemed to be clinically acceptable. PTV volumes were 483.0cm3 and 417.4cm3, utilizing five and six isocentres for treatment respectively. Median PTV D95 was 29.7Gy and 29.0Gy, whole body V10 was 21.2% and 17.4%, and V5 was 41.8% and 44.8%. All OAR goals were met, though low-dose conformality was less than traditional SABR treatment plans (R100 of 1.04 and 0.93; R50 of 9.90 and 6.98, respectively). The remainder of the test cases will be presented. Conclusions: In our test cases, planning SABR in polymetastatic disease appears dosimetrically feasible. Our phase I clinical trial (ARREST) is under development, which will evaluate the feasibility and toxicity of delivering SABR in polymetastatic disease in a 3+3 dose escalation study. The starting dose level will be 12Gy in 2 weekly fractions, escalating the dose by adding 6Gy weekly until our target dose of 30Gy in 5 weekly fractions. Our study population will include > 10 sites of disease, all tumour types, and patients must have exhausted standard lines of systemic therapy.

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)0.013
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.296
GPT teacher head0.524
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations2
Published2020
Admission routes1
Has abstractyes

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