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Record W3203195482 · doi:10.30683/1929-2279.2020.09.04

Clinical Analysis of Apatinib in the Treatment of Patients with Residual Tumor after Radical Chemoradiotherapy for Locally Advanced Cervical Cancer

2020· article· en· W3203195482 on OpenAlexvenueno aff
Jun Jiang, Wei Hong Wei, Tao Xu

Bibliographic record

VenueJournal of cancer research updates · 2020
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsApatinibMedicineCervical cancerChemoradiotherapyMesylateRashInternal medicineOncologySurgeryCancer

Abstract

fetched live from OpenAlex

There is no standard treatment for locally advanced cervical cancer, patients with residual tumor after radical concurrent chemoradiotherapy. This study was to investigate the short-term efficacy and safety of the targeted drug apatinib mesylate in patients with tumor residual after radical chemoradiotherapy for locally advanced cervical cancer. Eight patients with residual tumors after localized concurrent chemoradiotherapy with locally advanced cervical cancer were treated with apatinib (250 mg once daily, orally). The short-term efficacy and safety of the eight patients treated with apatinib were initially evaluated. Total Effectiveness (ORR) 37.5% and disease control rate (DCR) 100.0%. The toxicity and side effects were light, mainly manifested as 37.5% of hand-foot syndrome, 37.5% of proteinuria, 25.0% of hypertension, 12.5% of fatigue, 12.5% of rash, and 12.5% of vomiting. No serious toxic side effects associated with the drug were observed. Apatinib mesylate can be safely used in patients with residual tumor after radical chemoradiotherapy for locally advanced cervical cancer. The short-term effect is positive and the side effects are low.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.449
Teacher spread0.379 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

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