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Record W2029924265 · doi:10.1097/gco.0b013e3280115f40

Cytoreductive surgery for recurrent ovarian cancer

2007· review· en· W2029924265 on OpenAlexaff
Jan Hauspy, Allan Covens

Bibliographic record

VenueCurrent Opinion in Obstetrics & Gynecology · 2007
Typereview
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentreHealth Sciences Centre
Fundersnot available
KeywordsMedicineCytoreductive surgeryOvarian cancerConfoundingDiseaseRandomized controlled trialIntensive care medicineProspective cohort studySurgeryCancerOncologyGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The issue facing clinicians managing ovarian cancer has evolved over the past three decades from treatment for cure and subsequently palliation, to prolongation of survival for most patients. The purpose of this paper is to review the data, rationale, and issues surrounding cytoreductive surgery in recurrent ovarian cancer and its potential role in this new paradigm shift. RECENT FINDINGS: Abundant retrospective series report prolongation of survival with secondary cytoreductive surgery in recurrent ovarian cancer. Selection bias, publication bias, and subsequent therapies, however, are confounding factors for survival. As management of ovarian cancer has recently evolved to a treatment of a 'chronic disease', surgery (which has a definite role in primary therapy) should be considered. SUMMARY: No prospective randomized studies have been performed to date, and therefore adoption of this method of management has been limited. The absence of good data leaves clinicians without clear direction on how to best manage patients. Patients with favorable characteristics such as a long disease-free interval, good performance status, a single or few small intra-abdominal recurrences may benefit from secondary cytoreduction. A prospective randomized study is needed.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.243
GPT teacher head0.467
Teacher spread0.224 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations19
Published2007
Admission routes1
Has abstractyes

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