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MP45-16 PHOTOSELECTIVE VAPORIZATION OF THE PROSTATE: FAVOURABILITY OF STUDY RESULTS AS A FUNCTION OF CONFLICTS OF INTEREST AND INDUSTRIAL SPONSORSHIP

2019· article· en· W2942223943 on OpenAlexaboutno aff
Marian S. Wettstein, Clinsy Pazhepurackel, Aline S. Neumann, Dixon Woon, Jaime O. Herrera‐Cáceres, Cédric Poyet, Tullio Sulser, Girish S. Kulkarni, Thomas Hermanns

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSexual Differentiation and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProstateUrologyGynecologyPsychoanalysisInternal medicinePsychologyCancer

Abstract

fetched live from OpenAlex

INTRODUCTION AND OBJECTIVES: Photoselective vaporization of the prostate (PVP) with the so-called 532nm greenlight laser is an accepted treatment modality for non-neurogenic lower urinary tract symptoms secondary to prostate enlargement.Conflicts of interest (COIs) and industrial sponsorship (IS) have been shown to have a significant impact on the favourability of study results.The aim of the current study was to evaluate outcomes of comparative studies on PVP as a function of COIs and IS.METHODS: MEDLINE and EMBASE were systematically searched for records in English language.Comparative studies (randomized controlled trials [RCTs] and non-randomized comparative studies [NRCSs]), in which PVP was one treatment modality, were considered eligible.Sponsorship assessment distinguished between IS and non-industrial sponsoring.Two reviewers screened all abstracts and full-text articles independently.Disagreement was resolved either by discussion or by reference to a third independent reviewer.Favorability of outcome was evaluated on a binary scale (PVP-favourable versus PVP-unfavourable) by two independent board-certified urologists external to the remaining study team.Descriptive statistics were used for data analysis.RESULTS: In total, 749 records were screened after manual deduplication.Of these, 286 articles were eligible for full-text screening.Full-text analysis identified 65 studies (25 RCTs [38%], 40 NRCSs [62%]).The majority of the studies mentioned the absence/presence of potential COIs (78%).In contrast, a sponsorship statement was only found in 29% of the investigations.Our analysis identified 56 conflicted authors.In 24 (37%) studies at least one COI was declared (range 1 to 18).Interestingly, searching the author lists of all included studies a second time for more occurrences of the 56 conflicted authors led to the identification 36 initially undeclared COIs in a total of 6 studies.Fifty-six (86%) and 9 (14%) of all included studies were rated as PVP-favourable and PVP-unfavourable, respectively.Among PVP-favourable studies, we could identify both a higher proportion of COI (39% vs. 32%) and IS (7% vs. 0%).CONCLUSIONS: Within the field of comparative PVP literature, COIs are not only highly prevalent but also more frequent in studies reporting PVP-favourable outcomes.IS was exclusively found in PVPfavourable studies.A majority of all RCTs and NRCSs on PVP mention the absence/presence of potential COIs.However, a sponsorship statement was identifiable in only about one third of all studies.

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)0.164
metaresearch head score (Gemma)0.457
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score0.865

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1640.457
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.003

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 head0.037
GPT teacher head0.268
Teacher spread0.231 · 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.

Study designObservational
DomainEvaluation
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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