Development and external validation of a prognostic tool for prediction of cancer‐specific mortality after complete loco‐regional pathological staging for squamous cell carcinoma of the penis
Bibliographic record
Abstract
OBJECTIVE: To develop a novel postoperative prognostic tool, which attempts to integrate both pathological tumour stage and histopathological factors, for prediction of cancer-specific mortality (CSM) of squamous cell carcinoma of the penis (SCCP). PATIENTS AND METHODS: Patients with SCCP treated with inguinal lymph node dissection (ILND) or sentinel LN biopsy at a single institution were used for nomogram development and internal validation (n = 434), while a second cohort was used for external validation (n = 338). Multivariable Cox proportional hazards were used to examine the prognostic ability of patient age, a modified tumour staging that distinguishes between spongiosum and cavernosum body ingrowth tumours, a modified LN staging that integrates information on presence/absence of LN metastasis, extent of inguinal LN metastases, pelvic LN involvement, and extranodal involvement, and tumour grade. Model performance was quantified using measures of discrimination and calibration. RESULTS: Overall, 36% of patients had positive LN metastases (n = 156). In univariable analyses, the modified tumour and LN staging systems were statistically significantly associated with CSM, and remained in the final model with a discrimination of 89% within internal validation, and 95% within external validation. Calibration was nearly perfect. CONCLUSIONS: The newly developed model integrates important prognostic factors, which existing models do not consider. Its performance was highly accurate using measures of discrimination and calibration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".