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Record W1600981931 · doi:10.1002/jso.23686

Forearm soft tissue sarcoma: Tumors characteristics and oncologic outcomes following limb salvage surgery

2014· article· en· W1600981931 on OpenAlexaff
Maher Baroudi, Peter C. Ferguson, Jay S. Wunder, Marc Isler, Sophie Mottard, Joel Werier, Robert Turcotte

Bibliographic record

VenueJournal of Surgical Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsOttawa HospitalHôpital Maisonneuve-RosemontMount Sinai HospitalMontreal General Hospital
Fundersnot available
KeywordsMedicineSoft tissue sarcomaSarcomaSoft tissueRadiation therapySurgeryForearmMetastasisContext (archaeology)RadiologyCancerInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Complex anatomy of the forearm may impact on local control and survivals of soft tissue sarcoma. Little is known about characteristics and oncologic outcomes following surgical treatment. METHODS: Demographic and tumor data of 117 patients with forearm soft tissue sarcoma were collected and analyzed. Following limb salvage, survivals, and prognostic factors were studied. RESULTS: Seventy-three patients were males (62%) and 53 (45%) were referred after unplanned excision. Pleomorphic undifferentiated sarcoma was most frequent (45%). The average tumor size was 5.1 cm and grade III histology was mostly identified (53%). With radiotherapy, local recurrence occurs in 8 patients (7%) and 30 patients (24%) developed metastasis. Overall survival, disease free survival, local recurrence free survival, and metastasis free survival were 83%, 74%, 93%, and 74%, respectively. Better survival was found for grade I (80% vs. 60%) and small size (<5 cm) (72% vs. 47%). Large size tumor, extra-compartmental site, extramuscular, and virgin tumor were positive predictors of metastasis. CONCLUSION: Soft tissue sarcomas of the forearm are often referred after unplanned excision. Limb salvage was achieved for most and local recurrence remained low in context of radiotherapy. Metastatic progression remained frequent. Low grade and small size were predictors of survival.

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 score0.276
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.030
GPT teacher head0.326
Teacher spread0.295 · 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

Citations37
Published2014
Admission routes1
Has abstractyes

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