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Record W4401280680

Libtayo<sup>®</sup> (Cemiplimab-rwlc) Injection for Intravenous Use.

2024· article· en· W4401280680 on OpenAlexaff
Aditya K. Gupta, Avantika Mann, Kimberly Vincent, William Abramovits

Bibliographic record

VenuePubMed · 2024
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsGeology
DOInot available

Abstract

fetched live from OpenAlex

(cemiplimab-rwlc) injection for intravenous use was recently approved by the US Food and Drug Administration (FDA) for locally advanced basal cell carcinoma (laBCC) and metastatic basal cell carcinoma (mBCC), both being the advanced stages of BCC. In the past, it was approved by the FDA for the treatment of metastatic cutaneous squamous cell carcinoma (mCSCC) and locally advanced cutaneous squamous cell carcinoma (laCSCC), both being the advanced stages of CSCC. Cemiplimab is a monoclonal antibody that works by blocking the programmed death-1 pathway. In two open-label, single-arm, phase 2 studies, cemiplimab was investigated for the treatment of advanced stages of BCC (study 1620, NCT03132636) and advanced stages of CSCC (study 1540, NCT02760498). The primary endpoint was objec-tive response rate (ORR) per independent central review. In the study 1620, both mBCC and laBCC received cemiplimab 350 mg every 3 weeks. ORR was 21% (6/28) and 31% (26/84) in the mBCC and laBCC groups, respectively. In the study 1520, mCSCC was divided into two groups: one receiving cemiplimab 350 mg every 3 weeks (Q3W) and another receiving 3-mg/kg cemiplimab every 2 weeks (Q2W); the third group, laCSCC, received cemiplimab 3 mg/kg every 2 weeks. ORR was 41% (23/56) in the Q3W group, 49% (29/59) in the Q2W group, and 44% (34/78) in the laCSCC group. An acceptable safety profile and antitumor activity was discovered in patients treated with cemiplimab. The recommended dosage for cemiplimab to treat advanced stages of BCC and CSCC is 350 mg every 3 weeks administered intravenously over 30 min.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.037
GPT teacher head0.260
Teacher spread0.223 · 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 designOther design
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

Citations1
Published2024
Admission routes1
Has abstractyes

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