Urological outcomes in nonagenarians with prostate cancer
Bibliographic record
Abstract
INTRODUCTION: Nonagenarians represent a growing patient population. Herein, we report on the largest cohort of Canadian nonagenarian patients, to our knowledge, with prostate cancer. METHODS: A retrospective chart of 44 nonagenarian men diagnosed with localized or metastatic prostate cancer between 2006 and 2019 was performed. Diagnoses were based on pathological specimens or the presence of a high prostate-specific antigen (PSA >20) or abnormal digital rectal exam (DRE) in the setting of metastatic disease on imaging. Patient demographics, presenting complaints, and treatments required were included in the analysis. A descriptive statistical analysis was performed. RESULTS: The median patient age at time of referral was 91.1 years (interquartile range [IQR] 90.2-92.9). The median PSA at time of referral was 54.0 (IQR 18.2-142.6). Metastatic disease was present in 55% of patients at time of diagnosis (n=24). Most patients required at least one urological intervention (n=35). There were 56.8% of patients who received androgen deprivation therapy (ADT) as part of their treatment regime (n=25). Half (50%) of patients were managed with androgen receptor axis-targeted agents (ARAT), as well as ADT (n=22). Five patients (11.4%) underwent surgical castration. Death due to any cause was noted in 52.3% of patients (n=23) throughout the study period, with the median age at death being 94.4 years (IQR 92.3-97.0). Death due to prostate cancer was noted in 18.2% of patients (n=8). CONCLUSIONS: This study highlights common presenting complaints for nonagenarian patients with prostate cancer and that many require urological intervention despite advanced age. Future studies should address patient-reported quality-of-life outcomes in the nonagenarian population with prostate cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".