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Record W4220955068 · doi:10.1177/2050313x221086316

Blue-grey hyperpigmentation in acne after vandetanib therapy and doxycycline use: A case report

2022· article· en· W4220955068 on OpenAlexaff
Jonah Perlmutter, Rachel C. Cogan, Marni Wiseman

Bibliographic record

VenueSAGE Open Medical Case Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicAcne and Rosacea Treatments and Effects
Canadian institutionsUniversity of ManitobaSKiN HealthUniversity of Winnipeg
Fundersnot available
KeywordsVandetanibMedicineHyperpigmentationDermatologyMedullary thyroid cancerAcneDoxycyclineAdverse effectDomperidoneInternal medicineCancerThyroid cancerTyrosine kinaseAntibiotics

Abstract

fetched live from OpenAlex

Vandetanib is an oral tyrosine kinase inhibitor with cutaneous adverse effects that include the development of acne. We present a patient who underwent vandetanib therapy for stage IV medullary thyroid cancer in conjunction with the use of doxycycline for acne that developed. After vandetanib use, blue-grey pigmentation developed in the acne on his face, chest, back, and arms, which darkened after the use of doxycycline. We review the literature to report that this blue-grey hyperpigmentation was likely vandetanib-induced but may have been the result of both drugs being used in combination.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.032
GPT teacher head0.337
Teacher spread0.305 · 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 designCase report
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

Citations4
Published2022
Admission routes1
Has abstractyes

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