Patient Reported Outcomes in Penile Cancer
Bibliographic record
Abstract
Abstract Objective: Patient reports of their symptom burden (i.e., patient-reported outcomes or PROs) have been shown to direct clinicians’ ability to personalize care and improve outcomes. A disciplined assessment of PRO in the population of patients with penile cancer (PeCa) has not previously been undertaken. Our center has both a significant cadre of patients with PeCa and a significant experience with a well-established PRO: the Edmonton Symptom Assessment Scale (ESAS).Methods: After IRB approval, we screened ESAS surveys of 14,781 patients completed between 2/2017 and 2/2021. Of these, those with PeCa were divided into three cohorts: (A) Those after any partial penectomy procedure without lymph node dissection (LND); (B) Those after partial penectomy procedure with LND; and (C) Those after total penectomy and LND. Patients with recurrent disease were analyzed separately. ESAS scores were collated and compared both by individual symptom and cumulatively.Results: 22 PeCa patients completed 122 ESAS surveys in this time and are included in this analysis: a median of 4 ESAS surveys (mean=5, range=1-19) were completed by each patient. The symptom with the highest median ESAS score was Tiredness (3.00). Patients with recurrent disease had the highest cumulative symptom score (median score = 30). Patients after total penectomy with LND had a higher cumulative symptom score (14.4) than those with partial penectomy and LND (7.9).Conclusions: PROs provide an insight into the morbidity of therapies for PeCa, and the most symptoms are reported by patients with recurrent disease.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".