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Record W2912756512 · doi:10.1186/s13014-019-1237-9

Management of patients with brain metastases from non-small cell lung cancer and adverse prognostic features: multi-national radiation treatment recommendations are heterogeneous

2019· article· en· W2912756512 on OpenAlexaff
Carsten Nieder, Matthias Gückenberger, Laurie E. Gaspar, Chad G. Rusthoven, Dirk De Ruysscher, Arjun Sahgal, Timothy K. Nguyen, Anca‐Ligia Grosu, Minesh P. Mehta

Bibliographic record

VenueRadiation Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRadiosurgeryRadiation therapyLung cancerRandomized controlled trialAdverse effectCancerIntensive care medicineOncologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Different management options exist for patients with brain metastases from non-small cell lung cancer (NSCLC), patients whose treatment with whole brain radiotherapy (WBRT) has become more controversial over the last decade. It is not trivial to find the optimal balance of over- versus undertreatment in these patients. Several recent trials, including the randomized QUARTZ trial now influence the decision to recommend or withhold WBRT for patients with unfavorable prognosis, and similarly, for favorable prognosis patients, the balance between radiosurgery alone or WBRT has become a nuanced decision. Additionally, the availability of intracranially active targeted agent for some subsets of these patients has added another layer of complexity to the decision-making. METHODS: A multinational consortium of expert radiation oncologists was established with the aim of compiling treatment recommendations for challenging scenarios, in this case the choice between optimal supportive care (SC), WBRT and other types of radiation therapy (RT). We distributed 17 cases to 7 radiation oncologists who were allowed to involve coworkers to provide their treatment recommendations. The cases differed in extra- and intracranial disease extent, histology, age and other prognostic factors. Expert recommendations were tabulated with the aim of providing guidance. RESULTS: Regarding willingness to include the 17 patients in the QUARTZ trial, the rates of trial inclusion were low (range 0/7 to 3/7). Experts not recommending trial inclusion provided their treatment recommendations. These suggestions differed widely for most of the patients. It was not uncommon to see 3 or 4 different recommendations. In general, few (0-2) recommended SC. Some kind of local treatment was suggested by the majority of experts for all 17 patients. Commonly, stereotactic single-fraction radiosurgery (SRS) or stereotactic fractionated radiotherapy (SFRT) were recommended by many experts, also for patients with 5-7 lesions. The highest proportion of recommendations towards WBRT in any patient was 3/7. It was also quite common for patients with multiple metastases of varying size that experts suggested combinations of resection, post-operative SRS/SFRT and SRS/SFRT to intact lesions. Despite recommending active treatment, experts were often willing to include the patients in a hypothetical protocol investigating radiotherapy utilization in the last 30 days of life (assessment of factors predicting early death). CONCLUSIONS: WBRT was infrequently recommended. Even in patients with adverse prognostic features that raised the experts' awareness of an increased risk for futile treatment near the end of life, SRS/SFRT were more often recommended than optimal supportive care, unless a patient decided to forego active treatment.

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)0.015
metaresearch head score (Gemma)0.046
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.298
Teacher spread0.285 · 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

Citations33
Published2019
Admission routes1
Has abstractyes

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