Inverse Stage Migration in Radical Prostatectomy—A Sustaining Phenomenon
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective: To investigate temporal trends in prostate cancer (PCa) radical prostatectomy (RP) candidates. Materials and Methods: Patients who underwent RP for PCa between January 2014 and December 2019 were identified form our institutional database. Trend analysis and logistic regression models assessed RP trends after stratification of PCa patients according to D'Amico classification and Gleason score. Patients with neoadjuvant androgen deprivation or radiotherapy prior to RP were excluded from the analysis. Results: Overall, 528 PCa patients that underwent RP were identified. Temporal trend analysis revealed a significant decrease in low-risk PCa patients from 17 to 9% (EAPC: −14.6%, p < 0.05) and GS6 PCa patients from 30 to 14% (EAPC: −17.6%, p < 0.01). This remained significant even after multivariable adjustment [low-risk PCa: (OR): 0.85, p < 0.05 and GS6 PCa: (OR): 0.79, p < 0.001]. Furthermore, a trend toward a higher proportion of intermediate-risk PCa undergoing RP was recorded. Conclusion: Our results confirm that inverse stage migration represents an ongoing phenomenon in a contemporary RP cohort in a European tertiary care PCa center. Our results demonstrate a significant decrease in the proportion of low-risk and GS6 PCa undergoing RP and a trend toward a higher proportion of intermediate-risk PCa patients undergoing RP. This indicates a more precise patient selection when it comes to selecting suitable candidates for definite surgical treatment with RP.
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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 | 0.001 |
| 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 it