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MP22-12 ONCOLOGICAL OUTCOMES IN PATIENTS WITH HIGH LYMPH NODE BURDEN AFTER RADICAL PROSTATECTOMY

2019· article· en· W2942284158 on OpenAlexaboutno aff
Raisa Pompe, Pierre I. Karakiewicz, Zhe Tian, Felix Preißer, Philipp Mandel, Philipp Gild, Thomas Steuber, Georg Salomon, Markus Graefen, Margit Fisch, Hartwig Huland, Derya Tilki

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProstatectomyLymph nodeDissection (medical)General surgeryAdjuvant therapyCancerProstate cancerOncologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyProstate Cancer: Advanced (including Drug Therapy) II (MP22)1 Apr 2019MP22-12 ONCOLOGICAL OUTCOMES IN PATIENTS WITH HIGH LYMPH NODE BURDEN AFTER RADICAL PROSTATECTOMY Raisa Pompe*, Pierre I. Karakiewicz, Zhe Tian, Felix Preisser, Philipp Mandel, Philipp Gild, Thomas Steuber, Georg Salomon, Markus Graefen, Margit Fisch, Hartwig Huland, and Derya Tilki Raisa Pompe*Raisa Pompe* More articles by this author , Pierre I. KarakiewiczPierre I. Karakiewicz More articles by this author , Zhe TianZhe Tian More articles by this author , Felix PreisserFelix Preisser More articles by this author , Philipp MandelPhilipp Mandel More articles by this author , Philipp GildPhilipp Gild More articles by this author , Thomas SteuberThomas Steuber More articles by this author , Georg SalomonGeorg Salomon More articles by this author , Markus GraefenMarkus Graefen More articles by this author , Margit FischMargit Fisch More articles by this author , Hartwig HulandHartwig Huland More articles by this author , and Derya TilkiDerya Tilki More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555597.85110.fbAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: To describe oncological outcomes of patients with high lymph node burden (≥4 positive nodes) and to assess the impact of adjuvant therapies. METHODS: We retrospectively analyzed 273 patients with ≥4 positive lymph nodes after radical prostatectomy (RP) and lymph node dissection between 2007 and 2015. Patients received adjuvant androgen deprivation therapy (aADT), aADT plus adjuvant radiation (aRT) or observation (including salvage ADT). Kaplan-Meier curves as well as multivariable Cox-regression analyses compared biochemical recurrence (BCR), metastatic progression (MP) and overall mortality (OM) between the different treatment modalities. RESULTS: Overall 55 patients received aADT, 34 aADT + aRT and 184 observation (including 96 with salvage ADT). For the entire cohort 2-year BCR-free survival, MP-free survival and overall survival rates were 33.0% (27.2-40.1%), 76.6% (71.0-82.8%) and 90.3% (86.1-94.8%). While patients with aADT + aRT had significantly better BCR-free survival rates (78.6% vs. 29.7% (aADT) vs. 25.8% (observation), p<0.001) MP-free survival and overall survival did not differ between the groups (p>0.05). In multivariable Cox regression analyses aADT+aRT was significantly associated with a lower BCR rate (HR aADT: 5.55, HR observation: 6.15, both p<0.001), while there was no effect on MP or overall mortality (p>0.05). CONCLUSIONS: In patients with high lymph node burden, combination of aADT+aRT might lower BCR risk. However, further oncological outcomes, namely MP and overall mortality, were not affected by the addition of radiation therapy. Source of Funding: none Hamburg, Germany; Montreal, Canada; Frankfurt, Germany; Hamburg, Germany© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e321-e321 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Raisa Pompe* More articles by this author Pierre I. Karakiewicz More articles by this author Zhe Tian More articles by this author Felix Preisser More articles by this author Philipp Mandel More articles by this author Philipp Gild More articles by this author Thomas Steuber More articles by this author Georg Salomon More articles by this author Markus Graefen More articles by this author Margit Fisch More articles by this author Hartwig Huland More articles by this author Derya Tilki More articles by this author Expand All Advertisement PDF downloadLoading ...

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0230.003

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 head0.010
GPT teacher head0.274
Teacher spread0.264 · 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 designObservational
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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