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Record W4210251105 · doi:10.31917/2204244

Neoadjuvant anti PD-1 / PD-L1 immune checkpoint inhibitors in locally advanced gastric cancer with microsatellite instability

2021· article· en· W4210251105 on OpenAlexaff
A.Y. Navmatulya, Vyacheslav Chubenko, Solomiia Savchuk, F.R. Almukhametova, P.Y. Tsuprun, Е.М. Zykov, В. Моисеенко, A.I. Kuznetsov, Gamzat Inusilaev, V.A. Heinstein, Ksenya V. Shelekhova

Bibliographic record

VenuePractical oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsCanadian Association of Nurses in Oncology
Fundersnot available
KeywordsPembrolizumabNivolumabMicrosatellite instabilityMedicineCancerInternal medicineImmune checkpointOncologyGastroenterologyImmunotherapyMicrosatelliteBiology

Abstract

fetched live from OpenAlex

Gastric cancer is an aggressive malignant neoplasm of the digestive system. These tumors are genetically heterogeneous,and they could be subdivided into four groups. One of such groups, microsatellite instable (MSI) gastric cancer, is of interest considering prognosis and response to therapy. Immune checkpoint inhibitors present a perspective strategy in treating these tumors, however, there is currently insufficient data on their use in microsatellite instable gastric cancer. Aim of this study was to evaluate objective response to neoadjuvant checkpoint inhibitors treatment in patients with MSI gastric cancer. Eleven patients were enrolled. They received Nivolumab or Pembrolizumab (investigator choice) in a neoadjuvant setting. Objective response was registered in 9 (81,8%) patients, two patients had stabilization. Nine patients (81,8%) underwent radical surgery. Pathologic complete response (pCR) was registered in 3 (33,3%). Postoperative complications were tracked and registered in accordance with Clavien-Dindo classification: grade 1 – 2 patients, grade 2 – 2 patients, grade 3 – 1 patient.

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)0.001
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 score0.374
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.341
Teacher spread0.318 · 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
Published2021
Admission routes1
Has abstractyes

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