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Record W2573482360 · doi:10.1097/spc.0000000000000255

Neurocognitive impact of cranial radiation in adults with cancer: an update of recent findings

2017· review· en· W2573482360 on OpenAlexaff
Kim Edelstein, Nadine Richard, Lori J. Bernstein

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2017
Typereview
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsNeurocognitiveMedicineCognitionRadiation therapyAdverse effectPsychological interventionOncologyIntensive care medicineBioinformaticsInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Radiation to the brain is associated with adverse effects on cognition in cancer patients. Advances in technology have improved treatment efficacy, while new or adjuvant approaches continue to be developed. The long-term impact of both established and newer treatments on cognition is an active area of research. RECENT FINDINGS: The article reviews the 15 studies published between January 2015 and October 2016 that include data on neurocognitive functions following radiation to the brain in adults with brain metastases, primary brain tumors, or other cancers. These studies examine neurocognitive outcomes in relation to radiation treatment delivery, pharmacological interventions, and biomarkers of brain injury. SUMMARY: Advances in radiotherapy protocols have reduced neurotoxic side-effects. Implementation of standardized, validated neurocognitive measures and biomarkers of brain injury provide new insights into the impact of cranial radiation on cognitive functions. Several promising new lines of research will benefit from further study to address common challenges in the field, including high rates of attrition in longitudinal trials, absence of control groups, small sample sizes, and heterogeneous patient groups.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.869
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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 head0.193
GPT teacher head0.496
Teacher spread0.302 · 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 designOther design
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

Citations16
Published2017
Admission routes1
Has abstractyes

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