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Record W3115885884 · doi:10.21037/apm-20-1036

Narrative review of neurocognitive and quality of life tools used in brain metastases trials

2021· review· en· W3115885884 on OpenAlexaff
Krista Ariello, Hendrick Tan, Hany Soliman

Bibliographic record

VenueAnnals of Palliative Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineNeurocognitiveQuality of life (healthcare)RadiosurgeryClinical trialIntensive care medicineClinical endpointDiseaseRadiation therapyOncologyInternal medicineCognitionPsychiatryNursing

Abstract

fetched live from OpenAlex

Development of brain metastases are common in patients with advanced malignancies leading to significant morbidity and mortality. Although overall survival is an important endpoint in these patients, neurocognition and health related quality of life (HRQoL) more accurately highlights the impact of the disease and its treatment on patients. Whole brain radiotherapy (WBRT) has historically played a key role in the management of these patients, especially those with multiple brain metastases. Clinical trials have supported the use of stereotactic radiosurgery (SRS) alone in patients with limited brain metastases sparing neurocognitive function and HRQoL as compared to the combination of SRS plus WBRT. Furthermore, new systemic agents are increasingly being used in clinical practice and have shown promise in patients with brain metastases. The upcoming clinical trials are tasked with defining treatment guidelines that are more specific to patient and tumour factors incorporating radiation, surgery, and systemic therapy. The validity of findings in these trials rest on the rigor of the study methodology and the utilisation of validated assessment tools for neurocognition and HRQoL. This review aims to appraise and summarise the neurocognitive and HRQoL tools used in modern brain metastases trials.

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)0.010
metaresearch head score (Gemma)0.070
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.510
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.070
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0170.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.643
GPT teacher head0.563
Teacher spread0.080 · 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 designSystematic review
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

Citations3
Published2021
Admission routes1
Has abstractyes

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