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Record W1517732299 · doi:10.1186/s40425-015-0066-0

Safety and efficacy of ipilimumab to treat advanced melanoma in the setting of liver transplantation

2015· article· en· W1517732299 on OpenAlexaff
Rita E Morales, Alexander N. Shoushtari, Michelle M. Walsh, Priya Grewal, Evan J. Lipson, Richard D. Carvajal

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2015
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsColumbia College
FundersNational Cancer Institute
KeywordsIpilimumabMedicineLiver transplantationMelanomaTransplantationMetastatic melanomaOncologyInternal medicineCancerImmunotherapyCancer research

Abstract

fetched live from OpenAlex

Ipilimumab is a first-in-class immunological checkpoint blockade agent and monoclonal antibody against Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) that has demonstrated survival benefit and durable responses in patients with metastatic melanoma. To date, solid organ transplant recipients have been excluded from clinical trials with cancer immunotherapies on the basis of their concurrent treatment with immunosuppressive agents. We present the first case to our knowledge of a patient with advanced cutaneous melanoma receiving ipilimumab status post orthotopic liver transplantation with a partial response. Transaminitis was observed 4 months after administration of ipilimumab that resolved with close observation. No evidence of graft rejection has been observed to date. This case advocates for further investigation of the safety and efficacy of cancer immunotherapies in solid organ transplant recipients.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.330
Teacher spread0.309 · 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 designObservational
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

Citations109
Published2015
Admission routes1
Has abstractyes

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