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Record W3107628190 · doi:10.1016/j.jtho.2020.11.002

Cardiac Toxicity of Thoracic Radiotherapy: Existing Evidence and Future Directions

2020· review· en· W3107628190 on OpenAlexaff
Kathryn Banfill, Meredith Giuliani, Marianne Aznar, K. Franks, Alan McWilliam, Matthias Schmitt, Fei Sun, Marie‐Catherine Vozenin, Corinne Faivre‐Finn

Bibliographic record

VenueJournal of Thoracic Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Institute for Health and Care ResearchCancer Research UKLes Laboratories Pierre FabreAstraZenecaManchester Biomedical Research CentreEli Lilly and CompanyBristol-Myers Squibb
KeywordsMedicineRadiation therapyCardiac toxicityToxicityLung cancerIntensive care medicineDiseaseCardiologyInternal medicineOncology

Abstract

fetched live from OpenAlex

The impact of radiotherapy on the heart has become an area of interest in recent years. Many different cardiac dose-volume constraints have been associated with cardiac toxicity and survival; however, no consistent constraint has been found. Many patients undergoing treatment for lung cancer have risk factors for cardiovascular disease or known cardiac comorbidities; however, there is little evidence on the effects of radiotherapy on the heart in these patients. We aim to provide a summary of the existing literature on cardiac toxicity of lung cancer radiotherapy, propose strategies to avoid and manage cardiac toxicity, and suggest avenues for future research.

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)0.002
metaresearch head score (Gemma)0.005
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: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.085
GPT teacher head0.471
Teacher spread0.386 · 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

Citations255
Published2020
Admission routes1
Has abstractyes

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