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Record W3032917453 · doi:10.1001/jamaoncol.2020.1694

Survival After Minimally Invasive vs Open Radical Hysterectomy for Early-Stage Cervical Cancer

2020· review· en· W3032917453 on OpenAlexaboutno aff
Roni Nitecki, Pedro T. Ramírez, Michael Frumovitz, Kate J. Krause, Ana I. Tergas, Jason D. Wright, Jose Alejandro Rauh‐Hain, Alexander Melamed

Bibliographic record

VenueJAMA Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsMedicineCervical cancerObservational studyHysterectomyRandomized controlled trialMeta-analysisRadical HysterectomyConfoundingStage (stratigraphy)SurgeryCancerInternal medicine

Abstract

fetched live from OpenAlex

Importance: Minimally invasive techniques are increasingly common in cancer surgery. A recent randomized clinical trial has brought into question the safety of minimally invasive radical hysterectomy for cervical cancer. Objective: To quantify the risk of recurrence and death associated with minimally invasive vs open radical hysterectomy for early-stage cervical cancer reported in observational studies optimized to control for confounding. Data Sources: Ovid MEDLINE, Ovid Embase, PubMed, Scopus, and Web of Science (inception to March 26, 2020) performed in an academic medical setting. Study Selection: In this systematic review and meta-analysis, observational studies were abstracted that used survival analyses to compare outcomes after minimally invasive (laparoscopic or robot-assisted) and open radical hysterectomy in patients with early-stage (International Federation of Gynecology and Obstetrics 2009 stage IA1-IIA) cervical cancer. Study quality was assessed with the Newcastle-Ottawa Scale and included studies with scores of at least 7 points that controlled for confounding by tumor size or stage. Data Extraction and Synthesis: The Meta-analysis of Observational Studies in Epidemiology (MOOSE) checklist was used to abstract data independently by multiple observers. Random-effects models were used to pool associations and to analyze the association between surgical approach and oncologic outcomes. Main Outcomes and Measures: Risk of recurrence or death and risk of all-cause mortality. Results: Forty-nine studies were identified, of which 15 were included in the meta-analysis. Of 9499 patients who underwent radical hysterectomy, 49% (n = 4684) received minimally invasive surgery; of these, 57% (n = 2675) received robot-assisted laparoscopy. There were 530 recurrences and 451 deaths reported. The pooled hazard of recurrence or death was 71% higher among patients who underwent minimally invasive radical hysterectomy compared with those who underwent open surgery (hazard ratio [HR], 1.71; 95% CI, 1.36-2.15; P < .001), and the hazard of death was 56% higher (HR, 1.56; 95% CI, 1.16-2.11; P = .004). Heterogeneity of associations was low to moderate. No association was found between the prevalence of robot-assisted surgery and the magnitude of association between minimally invasive radical hysterectomy and hazard of recurrence or death (2.0% increase in the HR for each 10-percentage point increase in prevalence of robot-assisted surgery [95% CI, -3.4% to 7.7%]) or all-cause mortality (3.7% increase in the HR for each 10-percentage point increase in prevalence of robot-assisted surgery [95% CI, -4.5% to 12.6%]). Conclusions and Relevance: This systematic review and meta-analysis of observational studies found that among patients undergoing radical hysterectomy for early-stage cervical cancer, minimally invasive radical hysterectomy was associated with an elevated risk of recurrence and death compared with open surgery.

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)0.017
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.020
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.109
GPT teacher head0.425
Teacher spread0.315 · 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 designSystematic review
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

Citations209
Published2020
Admission routes1
Has abstractyes

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