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Record W3101508278 · doi:10.1016/j.euros.2020.10.005

Long-term Testis Cancer Survivors in Canada—Mortality Risks in a Large Population-based Cohort

2020· article· en· W3101508278 on OpenAlexaffabout
Arnon Lavi, Roderick Clark, Tina Luu Ly, Shiva M. Nair, Khalil Hetou, Michael Haan, Nicholas Power

Bibliographic record

VenueEuropean Urology Open Science · 2020
Typearticle
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineHazard ratioInternal medicinePopulationCohortCancerNational Death IndexProportional hazards modelConfidence intervalCause of deathStandardized mortality ratioMalignancyDisease

Abstract

fetched live from OpenAlex

Testis cancer (TC) patients are young with excellent cancer prognosis. Hence, the risk of late-onset treatment-related morbidity and mortality is of concern due to longer survival after treatment. We set to characterize long-term survival of TC patients through a Canadian population dataset. We used a population-based dataset, the Canadian Census Health and Environment Cohort (CanCHEC), to identify individuals diagnosed with TC between 1991 and 2010. We compared them with all other male individuals without TC. The primary outcome was mortality due to cardiovascular disease (CVD) or nontesticular malignancy. Mann-Whitney or chi-square test was used where applicable. Data were analyzed using a Cox proportional hazard model with and without matching. We identified 1950 individuals with TC. We compared them with 1 300 295 men with no TC. There were 335 deaths in the study group during the study period (17.2%) with a mean follow-up of 19.6 yr. TC patients were at increased risk of death from secondary malignancies (hazard ratio [HR] 1.63, 95% confidence interval [CI] 1.39–1.91; p < 0.0001) with specific risks for hematologic neoplasms (HR 3.86, 95% CI 2.78–5.37; p < 0.001) and other malignancies (HR 2.41, 95% CI 1.76–3.29; p < 0.001). Gastrointestinal, hematologic, and respiratory toxicities were the most common secondary malignancies leading to death. When stratified according to histology, nonseminoma (NS) patients were at significantly increased risk of death from CVD (HR 2.03, 95% CI 1.27–3.25; p = 0.0032). Individuals with seminoma were at increased risk of death from other nontestis neoplasms (HR 1.46, 95% CI 1.17–1.82; p = 0.0007), specifically hematologic neoplasms (HR 2.09, 95% CI 1.18–3.72; p = 0.0118). NS patients are at increased risk of CVD-related death, whereas seminoma patients are at increased risk of death from non–testis-related malignancies. We report long-term mortality following diagnosis of testis cancer. Nonseminoma patients have an increased risk of death from cardiovascular disease, while seminoma patients have an increased risk of death from secondary malignancies.

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 score0.047
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.053
GPT teacher head0.349
Teacher spread0.296 · 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

Citations7
Published2020
Admission routes2
Has abstractyes

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