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Record W2130986759 · doi:10.1200/jco.2011.41.5851

Ocular Toxicity of Targeted Therapies

2012· review· en· W2130986759 on OpenAlexaff
Daniel J. Renouf, Juan P. Velazquez-Martin, Rand Simpson, Lillian L. Siu, Philippe L. Bédard

Bibliographic record

VenueJournal of Clinical Oncology · 2012
Typereview
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineTargeted therapyClinical trialToxicityPharmacologyIntensive care medicineOncologyInternal medicineCancer

Abstract

fetched live from OpenAlex

Molecularly targeted agents are commonly used in oncology practice, and many new targeted agents are currently being tested in clinical trials. Although these agents are thought to be more specific and less toxic then traditional cytotoxic chemotherapy, they are associated with a variety of toxicities, including ocular toxicity. Many of the molecules targeted by anticancer agents are also expressed in ocular tissues. We reviewed the literature for described ocular toxicities associated with both approved and investigational molecularly targeted agents. Ocular toxicity has been described with numerous approved targeted agents and also seems to be associated with several classes of agents currently being tested in early-phase clinical trials. We discuss the proposed pathogenesis, monitoring guidelines, and management recommendations. It is important for oncologists to be aware of the potential for ocular toxicity, with prompt recognition of symptoms that require referral to an ophthalmologist. Ongoing collaboration between oncologists and ocular disease specialists is critical as the use of molecularly targeted agents continues to expand and novel targeted drug combinations are developed.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
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 head0.288
GPT teacher head0.546
Teacher spread0.258 · 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

Citations139
Published2012
Admission routes1
Has abstractyes

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