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Record W2403209462 · doi:10.21037/apm.2016.04.01

Quality of life with Brain Symptom and Impact Questionnaire in patients with brain metastases

2016· article· en· W2403209462 on OpenAlexaff
Ronald Chow, Saurabh Ray, May Tsao, Natalie Pulenzas, Liying Zhang, Arjun Sahgal, David Cella, Hany Soliman, Cyril Danjoux, Carlo DeAngelis, Sherlyn Vuong, Rachel McDonald, Edward Chow

Bibliographic record

VenueAnnals of Palliative Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineQuality of life (healthcare)Brain metastasisIntensive care medicineInternal medicineNursingCancerMetastasis

Abstract

fetched live from OpenAlex

BACKGROUND: To examine the baseline characteristics of patients who underwent different treatments for brain metastases. METHODS: Allocated into group A [whole brain radiation therapy (WBRT) alone], or group B [stereotactic radiosurgery (SRS) or neurosurgery with or without WBRT], brain metastases patients with assigned treatment completed the Brain Symptom and Impact Questionnaire (BASIQ). Items of BASIQ were arranged as a symptom score or function score. RESULTS: Lung, breast, melanoma and renal cancer were the most prevalent primary cancer site among the study population, with 91 (53%), 25 (15%), 17 (10%) and 15 (9%) patients, respectively. Baseline BASIQ results were obtained before patients were treated with WBRT, neurosurgery, or SRS. Seventy-six (44%) and 96 patients (56%) were grouped to A and B, respectively. Group A reported lower quality of life (QOL) in all function scores (P<0.0001) and all symptom scores (P values from <0.0001 to 0.005) with the exception of energy (P=0.1). CONCLUSIONS: Baseline QOL in patients assigned WBRT alone was statistically worse as compared to patients assigned SRS, neurosurgery with or without WBRT.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.060
GPT teacher head0.386
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2016
Admission routes1
Has abstractyes

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