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Record W2516899329 · doi:10.14740/wjon981w

The Impact of Lymphovascular Space Invasion on Recurrence and Survival in Iranian Patients With Early Stage Endometrial Cancer

2016· article· en· W2516899329 on OpenAlexvenueno aff
Setareh Akhavan, Azar Ahmadzadeh, Azamsadat Mousavi, Mitra Modares Gilany, Zohreh Kazemi, Fakher Rahim, Elham Shirali

Bibliographic record

VenueWorld Journal of Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEndometrial cancerStage (stratigraphy)Internal medicineAdjuvant therapyOncologySerous fluidGynecologyCancerGastroenterology

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this study was to assess the impact of lymphovascular space involvement (LVSI) on recurrence and survival in early stage of endometrial cancer (EC). METHODS: Patients with EC referred to Imam Khomeini Hospital in Tehran were examined and enrolled over a 10-year period (2004 - 2015). The effect of LVSI on recurrence and overall survival was analyzed using the Kaplan-Meier and log-rank test methods. RESULTS: A total of 160 patients with early stage EC were identified. Out of 160 women with EC, 135 (84.4%) underwent primary surgery. One hundred and twenty-one (76.2%) patients were not found to have LVSI, whereas 38 (23.8%) were found to have LVSI. Of the 38 patients with LVSI, 21 (55.3%) had endometrioid cell type tumor, 10 (26.3%) had serous, one (2.6%) had clear cell and six (15.8%) had adeno-squamous cell type tumor. CONCLUSION: The presence of LVSI represents a factor strongly associated with high risk of recurrence and poor survival in early stage EC. Patients with lower International Federation of Obstetrics and Gynecology (FIGO) stages may be at increased risk of recurrence and a poor overall survival if the pathological findings confirm the presence of LVSI. Thus, LVSI should be added to the traditional factors used to decide whether patients with early stage EC are at high risk of recurrence and adjuvant therapy planning.

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)0.000
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 score0.165
Threshold uncertainty score0.189

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.027
GPT teacher head0.328
Teacher spread0.301 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of OncologySame topicEndometrial and Cervical Cancer TreatmentsFrench-language works237,207