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Record W3126970712 · doi:10.1093/jjco/hyaa273

Sex- and age-related differences in the distribution of bladder cancer metastases

2020· article· en· W3126970712 on OpenAlexaff
Giuseppe Rosiello, Carlotta Palumbo, Marina Deuker, Lara Franziska Stolzenbach, Thomas G. Martin, Zhe Tian, Andrea Gallina, Francesco Montorsi, Peter C. Black, Wassim Kassouf, Shahrokh F. Shariat, Fred Saad, Alberto Briganti, Pierre I. Karakiewicz

Bibliographic record

VenueJapanese Journal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsUniversity of British ColumbiaSurgical Specialties (Canada)McGill University Health CentreUniversité de Montréal
Fundersnot available
KeywordsMedicineBladder cancerCancerLung cancerInternal medicinePerformance statusOncology

Abstract

fetched live from OpenAlex

OBJECTIVE: Our objective was to investigate age- and sex-related differences in the distribution of metastases in patients with metastatic bladder cancer. METHODS: Within the National Inpatient Sample database (2008-2015), we identified 7040 patients with metastatic bladder cancer. Trend test and Chi-square test analyses were used to evaluate the relationship between age and site of metastases, according to sex. RESULTS: Of 7040 patients with metastatic bladder cancer, 5226 (74.2%) were men and 1814 (25.8%) were women. Thoracic, abdominal, bone and brain metastases were present in 19.5 vs. 23.0%, 43.6 vs. 46.9%, 23.9 vs. 18.7% and 2.4 vs. 2.9% of men vs. women, respectively. Bone was the most common metastatic site in men (23.9%) vs. lung in women (22.4%). Increasing age was associated with decreasing rates of abdominal (from 44.9 to 40.2%) and brain (from 3.2 to 1.4%) metastases in men vs. decreasing rates of bone (from 21.0 to 13.3%) and brain (from 5.1 to 2.0%) metastases in women (all P < 0.05). Finally, rates of metastases in multiple organs also decreased with age, in both men and women. CONCLUSIONS: The distribution of metastases in bladder cancer varies according to sex. Moreover, differences exist according to patient age and these differences are also sex-specific. In consequence, patient age and sex should be considered in the interpretation of imaging, especially when findings are indeterminate.

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)0.001
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 score0.060
Threshold uncertainty score0.165

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.133
GPT teacher head0.433
Teacher spread0.301 · 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

Citations23
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJapanese Journal of Clinical OncologySame topicBladder and Urothelial Cancer TreatmentsFrench-language works237,207