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ROCC/GOG-3043: A randomized non-inferiority trial of robotic versus open radical hysterectomy for early-stage cervical cancer.

2022· article· en· W4286297247 on OpenAlexaff
Kristin Bixel, Mario M. Leitão, Dana M. Chase, Allison Quick, Peter Lim, Ramez N. Eskander, Walter H. Gotlieb, Salvatore Lococo, Martin A Martino, Colleen McCormick, Tashanna Myers, Krishnansu S. Tewari, Brian M. Slomovitz, Joan L. Walker, Larry J. Copeland, Bradley J. Monk, Leslie M. Randall

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineRadical HysterectomyCervical cancerSurgeryStage (stratigraphy)PerioperativeRandomized controlled trialLaparoscopyHysterectomyCancerInternal medicine

Abstract

fetched live from OpenAlex

TPS5605 Background: Minimally invasive surgery (MIS) is associated with improved perioperative safety outcomes, but, in 2018, the Laparoscopic Approach to Cervical Cancer (LACC) trial, a non-inferiority study comparing laparoscopic versus open radical hysterectomy for early stage cervical cancer, reported significantly worse disease-specific (DSS) and overall survival (OS) in the MIS group. Criticisms of the LACC trial include lack of proper preoperative imaging and assessment, use of transcervical uterine manipulators, and lack of proper tumor containment leading to peritoneal contamination. Subsequent retrospective studies have reported conflicting results. Given the potential benefit of MIS, the ROCC trial seeks to address the limitations of the LACC trial. Methods: ROCC is a multi-center, prospective, randomized, non-inferiority trial. The primary objective is to determine whether robotic-assisted (RBT) radical hysterectomy is not inferior to abdominal (OPEN) approach with respect to 3-year disease-free survival (DFS). Secondary objectives include DSS, OS, patterns of recurrence, peri- and postoperative complications, long-term morbidity, impact on patient-reported outcome (PRO) measures and development of lower extremity lymphedema (LEL). Key inclusion criteria include patients with histologically confirmed adenocarcinoma, squamous cell, and adenosquamous cell carcinoma of FIGO 2018 stage IA2-IB2. All patients must have a preoperative pelvic MRI confirming that the cervical tumor is < 4 cm in size, no obvious evidence of extracervical extension and no nodal or other regional metastasis. Intraoperatively, the use of transcervical uterine manipulators is not allowed and specific detailed surgical techniques for proper tumor containment is required. Photographic evidence of specimen with tumor contained is mandated. We estimate the 3-year DFS to be 92% in the control (OPEN) arm. If the DFS does not differ by more than 7% and the one-sided 95% CI does not cross the non-inferiority boundary, then the RBT arm will be deemed non-inferior. 840 patients will be enrolled (420 per arm, 89 events total), which provides 90% power to exclude an absolute decrease in DFS by 7% (HR < = 1.375) with a log-rank test for non-inferiority with a one-sided alpha of 0.05. The primary analysis will be conducted in all randomized patients (ITT). Given the LACC findings of worse oncologic outcomes with MIS, a formal DSMC will conduct periodic reviews of safety including two planned formal interim analyses for futility (harm) after accrual of 370 and 640 patients using an aggressive Lan-DeMets beta-spending function similar to a Pocock boundary. Results of this trial may be practice changing and will either support or refute the findings of the LACC trial. The study is currently activating sites for enrollment. Clinical trial information: NCT04831580.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.219
GPT teacher head0.519
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations24
Published2022
Admission routes1
Has abstractyes

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