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Record W4387806221 · doi:10.3390/curroncol30100674

Local Treatment Efficacy for Single-Area Squamous Cell Carcinoma of the Unknown Primary Site

2023· article· en· W4387806221 on OpenAlexvenueno aff
Tomoko Kurita, Mayu Yunokawa, Yuji Tanaka, Kota Okamoto, Motoko Kanno, Atsushi Fusegi, Makiko Omi, Sachiho Netsu, Hidetaka Nomura, Akiko Tonooka, Hiroyuki Kanao

Bibliographic record

VenueCurrent Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBasal cellChemotherapyCarcinomaMedical recordCancerInternal medicineOncologyDermatology

Abstract

fetched live from OpenAlex

The prognosis for cancer of unknown primary site (CUP) is poor, and squamous cell carcinoma of the unknown primary site (SCCUP) is a rare histological type. CUP is often treated with aggressive multimodal treatments, while the treatment of single-area localized CUP remains controversial. We retrospectively reviewed the medical records of patients with CUP. SCCUP in women was classified according to several definitions. Based on the histologic type and site, they were classified into favorable and unfavorable subsets. We further divided SCCUP into two types (single and multiple areas) and reviewed treatment and efficacy. Among the 227 female CUP patients, 36 (15%) had SCCUP. The median age was 59.9 years (range, 31-90 years). Most patients (61.1%) had a good performance status. Of the SCCUP patients, 22 had cancer in a single area, and 14 in multiple areas. Single-area SCCUP was further divided into favorable (16 cases) and unfavorable subsets (6 cases). In the favorable subset, local treatment was predominant, and almost all cases had a good prognosis. Even in the unfavorable subset, local therapy was combined with systemic chemotherapy in only two cases, and four cases showed no recurrences. Local treatment may be effective for single-area SCCUP, even in the unfavorable subset.

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 score0.731
Threshold uncertainty score0.442

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 head0.121
GPT teacher head0.367
Teacher spread0.247 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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