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Record W2050276479 · doi:10.5489/cuaj.1585

Clinical and pathological features of primary renal angiosarcoma.

2014· article· en· W2050276479 on OpenAlexvenueno aff
Roberto Iacovelli, Valentina Orlando, Antonella Palazzo, Enrico Cortesi

Bibliographic record

VenueCanadian Urological Association Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicVascular Tumors and Angiosarcomas
Canadian institutionsnot available
Fundersnot available
KeywordsPathologicalAngiosarcomaPrimary (astronomy)MedicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: We review all cases of renal angiosarcoma described in the medical literature to describe its clinical and histological features. METHODS: The search term was "angiosarcoma of the kidney." All articles or case reports in English, French, German or Spanish published until March 15, 2013 were considered. When available, data that focused on clinical and pathological features were extracted. RESULTS: In total, the final cohort included 42 cases. The median overall survival (OS) was 5.0 months (95% confidence interval [CI], 2.1-7.9). Patients with metastatic disease had more than a threefold increase in the risk of death compared to patients without meta-static disease (hazard ratio: 3.27, 95% CI, 1.48-7.24; p = 0.004). Non-metastatic patients had dismal disease-free survival (DFS) rates, with a median DFS of 6.0 months (95% CI, 4.3-7.7); despite this, chemotherapy was effective to increase survival in eligible patients (4.0 vs. 1.0 months; p = 0.001). Microscopic examination found epithelioid and spindled cell in 44% and 56% of cases, respectively; there was a statistically insignificant increase in survival in patients with epithelioid patterns compared to spindled ones (9.0 vs. 4.0 months; p = 0.077). The tumour grading was related to OS; the lower the grade, the longer the survival (13 vs. 4 months; p = 0.029). CONCLUSIONS: Renal angiosarcoma is a rare disease with defined clinical and pathological features. It has a very poor prognosis in patients with metastatic disease and a high recurrence rate in patients with non-metastatic disease.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.037
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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)0.0000.000

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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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