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Record W2998053810 · doi:10.21873/invivo.11766

Low-grade Fibromyxoid Sarcoma: Treatment Outcomes and Efficacy of Chemotherapy

2019· article· en· W2998053810 on OpenAlexaff
Florence Chamberlain, Bodil Elisabeth Engelmann, Omar Al‐Muderis, Christina Messiou, Khin Thway, Aisha Miah, Shane Zaidi, Anastasia Constantinidou, Charlotte Benson, Spyridon Gennatas, Robin L. Jones

Bibliographic record

VenueIn Vivo · 2019
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsInstitute of Cancer Research
FundersNational Institute for Health and Care ResearchRoyal Marsden NHS Foundation Trust
KeywordsMedicineSarcomaChemotherapyRadiation therapySurgeryOverall survivalRetrospective cohort studySystemic therapyOncologyInternal medicinePathologyCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Low-grade fibromyxoid sarcoma (LGFMS) is a rare sarcoma subtype with a generally indolent pattern of clinical behaviour, but treatments for advanced disease are limited. PATIENTS AND METHODS: A retrospective search of a prospectively maintained institutional database identified 102 patients treated from December 1994 to August 2018. We evaluated the outcome of patients and the efficacy and safety of non-surgical therapies in LGFMS. RESULTS: Ninety-four out of 102 (92.2%) underwent primary resection, seven (6.9%) were treated with systemic therapy and one (1.0%) is currently being treated with pre-operative radiotherapy. The RECIST 1.1 response rate to first-line chemotherapy was 0%, and median progression-free survival was 1.84 months (95% confidence intervaI=0.10-3.6 months). CONCLUSION: Conventional systemic therapy has limited efficacy in advanced LGFMS.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.369

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 head0.016
GPT teacher head0.290
Teacher spread0.275 · 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

Citations50
Published2019
Admission routes1
Has abstractyes

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