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Record W4206021114 · doi:10.3390/cancers14030484

Therapeutic Perspectives in the Systemic Treatment of Kaposi’s Sarcoma

2022· review· en· W4206021114 on OpenAlexaff
Marc‐Antoine Valantin, Léna Royston, Maxime Hentzien, Aude Jary, Alain Makinson, Marianne Veyri, Sylvie Brégigeon, Stéphane Isnard, Romain Palich, Jean‐Pierre Routy

Bibliographic record

VenueCancers · 2022
Typereview
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineSarcomaContext (archaeology)Adverse effectOncologyClinical trialPopulationSystemic therapyImmunologyInternal medicineCancerPathology

Abstract

fetched live from OpenAlex

In patients with Kaposi's sarcoma (KS), the therapeutic goal is to achieve a durable remission in the size and number of skin and visceral lesions. Although most patients show tumor regression in response to standard systemic chemotherapy regimens, alternative systemic treatments are needed for patients who develop refractory KS. Anti-angiogenic therapies represent attractive therapeutic targets in this context, due to the central role of angiogenesis in KS pathogenesis. Pomalidomide, which exhibits such anti-angiogenic activity through inhibition of VEGF, currently constitutes the most promising agent of this class and has been recently approved by the FDA. In addition, immune checkpoint blockade also represents an interesting alternative therapeutic approach through the restoration of immunity against HHV-8, the causative agent of KS, and improvement of tumor control. Although small series of cases treated successfully with these drugs have been reported, there is no marketing approval for anti-immune checkpoint antibodies for KS to date. In the present review, we will discuss potential therapeutic options for patients with recurrent or refractory KS, including systemic chemotherapies, immune checkpoint inhibitors, anti-herpesvirus agents, and anti-angiogenic drugs. Well-conducted clinical trials in this population are urgently needed to correctly address the efficacy of targeted agents and immunomodulators, while monitoring for adverse effects.

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)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.079
GPT teacher head0.363
Teacher spread0.284 · 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

Citations28
Published2022
Admission routes1
Has abstractyes

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