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Record W3013443403 · doi:10.1136/bmjopen-2019-034612

Does Gleason score of positive surgical margin after radical prostatectomy affect biochemical recurrence and oncological outcomes? Protocol for systematic review

2020· article· en· W3013443403 on OpenAlexaboutno aff
Athul John, Michael O’Callaghan, Rick Catterwell, Luke A. Selth

Bibliographic record

VenueBMJ Open · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProstatectomyBiochemical recurrenceProstate cancerMEDLINEMeta-analysisCochrane LibrarySystematic reviewGrading (engineering)DiseaseCritical appraisalGynecologyOncologyInternal medicineCancerAlternative medicinePathology

Abstract

fetched live from OpenAlex

Introduction Positive surgical margins (PSM) in cancer patients are commonly associated with worse prognosis and a higher risk of secondary treatment. However, the relevance of this parameter in prostate cancer patients undergoing radical prostatectomy (RP) remains controversial, given the inconsistencies in its ability to predict biochemical recurrence (BCR) and oncological outcomes. Hence, further assessment of the utility of surgical margins for prostate cancer prognosis is required to predict these outcomes more accurately. Over the last decade, studies have used the Gleason score (GS) of positive margins to predict outcomes. Herein, the authors aim to conduct a systematic review investigating the role of GS of PSM after radical prostatectomy in predicting BCR and oncological outcomes. Methods and analysis We will perform a search using MEDLINE, EMBASE, SCOPUS and COCHRANE databases. The review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We will screen titles and abstracts to select articles appropriate for full-text review. Studies discussing GS of PSM after RP will be included. Given the change in reporting of GS, only articles from 2005 to 2019 will be included. The quality of the studies chosen will be assessed using the Newcastle Ottawa tool for non-randomised and Cochrane risk of bias for randomised control studies. We will adopt the grading of recommendations, assessment, development and evaluation framework to comment on quality of cumulative evidence. The primary outcome measure will be time to BCR. Secondary outcome measures include secondary treatment, disease-specific survival, disease progression-free and overall mortality at follow-up period. We aim to perform a meta-analysis if the level of heterogeneity is acceptable (I 2 <50%). Ethics and dissemination The review does not require ethics approval as it is a review of published literature. The findings of the review will be submitted for peer-reviewed publications and presented at scientific meetings. PROSPERO registration number CRD42019131800.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.052
metaresearch head score (Gemma)0.081
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: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.055
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.081
Meta-epidemiology (narrow)0.0060.005
Meta-epidemiology (broad)0.0250.023
Bibliometrics0.0160.014
Science and technology studies0.0040.006
Scholarly communication0.0090.010
Open science0.0050.006
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0550.006

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 head0.082
GPT teacher head0.444
Teacher spread0.363 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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

Citations4
Published2020
Admission routes1
Has abstractyes

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