The impact of intraductal carcinoma of the prostate on the site and timing of recurrence and cancer‐specific survival
Bibliographic record
Abstract
BACKGROUND: To investigate the effect of intraductal carcinoma of the prostate (IDC-P) in radical prostatectomy (RP) specimens in the context of the site of recurrence, time to recurrence, and cancer-specific survival in two academic cohorts of locally, regionally, or distantly recurrent prostate cancer. METHODS: Our cohort included men enrolled into two academic tissue repositories from 1993 to 2011, who were treated with first-line RP who later experienced local recurrence, regional recurrence, or distant metastasis (together termed clinical recurrence, CR). RP material was reviewed to identify IDC-P and to update grading to current standards. The primary endpoint was the initial location of CR. Secondary endpoints included time to CR and cancer-specific survival. Pearson's chi-square, Welch's t-test, Mann-Whitney U test and Fisher's exact test were performed for univariate analyses. Multinomial logistic regression was used for multivariate analyses. Cancer-specific survival was analyzed with the generalized Wilcoxon test and Cox regression. RESULTS: Eighty-five patients with CR were included in the analysis. IDC-P was present in 78.5% of patients from Center 1 and 70.0% from Center 2 (P = 0.547). IDC-P was independently associated with distant metastasis at initial CR (multivariate odds ratio = 6.27, P = 0.015). IDC-P status did not affect time to recurrence; median survival without recurrence was at 53 months for IDC-P(+) and at 50 months for IDC-P(-) (P = 0.441). Distant metastases at the initial CR event had a 36% reduction of cancer-specific survival compared to local recurrences (P = 0.007). Additionally, prostatic-bed radiotherapy (adjuvant or salvage for biochemical recurrence before distant metastasis) was associated with a 25% reduction in cancer-specific mortality compared to no radiotherapy (P = 0.023). Similar reduction in cancer-specific mortality was observed in the subgroup of patients with distant metastasis and IDC-P when treated with radiotherapy (29%, P = 0.050). CONCLUSIONS: In our cohort, presence of IDC-P was an independent factor for distant metastasis at initial CR, but did not have a significant impact on time to CR. Furthermore, metastatic patients showed statistically reduced cancer-specific mortality when treated with radiotherapy. This reduction in cancer-specific mortality was also identified in patients with IDC-P. Future large scale validation studies should take into account the presence of IDC-P and confirm its impact on disease progression.
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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 | 0.001 | 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 | 0.001 |
| 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".