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Record W4293235936 · doi:10.1177/20514158221090040

Incidence of dural metastases in castrate-resistant prostate cancer

2022· article· en· W4293235936 on OpenAlexaff
Adree Khondker, Jethro C.C. Kwong, Christopher Tran, Emily C. Evans, Ishan Aditya, Lucshman Raveendran, Yingming A Chen, Amna Ali, Andrew Feifer

Bibliographic record

VenueJournal of Clinical Urology · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsCredit Valley HospitalTrillium Health CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineProstate cancerIncidence (geometry)CohortContext (archaeology)Internal medicineLogistic regressionLactate dehydrogenaseCancer

Abstract

fetched live from OpenAlex

Purpose: The natural history and clinical manifestations of dural metastases (DM) in castrate-resistant prostate cancer (CRPC) will change with advances in new hormonal therapy. Here, we characterised the incidence, clinical presentation, and outcomes of patients with DM in a contemporary patient cohort with CRPC. Methods: We retrospectively reviewed our CRPC database from 2012 to 2020. The primary outcome was the diagnosis of DM, defined as metastasis to the dura mater in the brain or spine. We describe the presenting symptoms, biochemistry, radiologic findings, and therapy sequence for all DM patients. Multivariable logistic regression was performed to identify predictors of DM. Results: Six of the 275 patients (2.2%) with CRPC developed DM. The average age of CRPC diagnosis for patients with DM was 65.6 years. Mean patient survival was 4.5 months after the diagnosis of DM. At the time of CRPC diagnosis, patients who developed DM were significantly younger, had lower baseline haemoglobin, higher lactate dehydrogenase (LDH), and elevated alkaline phosphatase (ALP) compared to those without DM. On multivariable analysis, younger age of CRPC diagnosis was found to be a predictor for DM. Conclusion: The presence of neurological symptoms in the context of younger age, anaemia, and elevated baseline LDH and ALP are associated with DM in CRPC. Level of Evidence: 4

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)0.002
metaresearch head score (Gemma)0.001
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 score0.026
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.094
GPT teacher head0.468
Teacher spread0.374 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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