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Record W4368359971 · doi:10.1111/ctr.14998

Impact of newly diagnosed prostate cancer at time of evaluation for renal transplantation

2023· article· en· W4368359971 on OpenAlexaff
Florence Poinard, Thomas Bessède, Benoı̂t Barrou, Sarah Drouin, Georges Karam, Julien Branchereau, É. Alezra, Rodolphe Thuret, G. Verhoest, A. Goujon, C. Millet, R. Boissier, V. Delaporte, F. Sallusto, Thomas Prudhomme, Jean‐Michel Boutin, T. Culty, Marc‐Olivier Timsit

Bibliographic record

VenueClinical Transplantation · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsMedicineProstate cancerOverdiagnosisTransplantationCancerInternal medicineNephrologyProstateRadiation therapyKidney transplantationOncologyIntensive care medicine

Abstract

fetched live from OpenAlex

Systematic screening for prostate cancer is widely recommended in candidates for renal transplant at the time of listing. There are concerns that overdiagnosis of low-risk prostate cancer may result in reducing access to transplant without demonstrated oncological benefits. The objective of the study was to assess the outcome of newly diagnosed prostate cancer in candidates for transplant at the time of listing, and its impact on transplant access and transplant outcomes according to treatment options. This retrospective study was conducted over 10 years in 12 French transplant centers. Patients included were candidates for renal transplant at the time of prostate cancer diagnosis. Demographical and clinical data regarding renal disease, prostate cancer, and transplant surgery were collected. The primary outcome of the study was the interval between prostate cancer diagnosis and active listing according to treatment options. Overall median time from prostate cancer diagnosis to active listing was 25.0 months [16.4-40.2], with statistically significant differences in median time between the radiotherapy and the active surveillance groups (p = .03). Prostate cancer treatment modalities had limited impact on access and outcome of renal transplantation. Active surveillance in low-risk patients does not seem to compromise access to renal transplantation, nor does it impact oncological outcomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.135
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.083
GPT teacher head0.447
Teacher spread0.364 · 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 teacher head, 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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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