Bibliographic record
Abstract
Introduction: Important advances in prostate cancer (PCa) diagnosis and treatment have resulted in increased patient survival.However, it remains difficult to identify accurately patients better suited for less-aggressive therapy (active surveillance) from those at higher risk of disease progression.Over the past several years, our group has published several studies supporting an association between the nuclear NF-kB p65 and poor prognosis.In this study, we present validating results confirming a direct association between NF-kB p65 and biochemical recurrence (BCR) in a large independent cohort.Methods: Primary tumors from radical prostatectomy were obtained from a large European prostate cancer cohort and tumor specimens were spotted on tissue microarrays.NF-kB p65 expression was detected by immunohistochemistry on a final number of 1,850 cores containing suitable malignant tissue.Results: We observed a significant correlation between an increase in the nuclear frequency of NF-kB p65 and overall BCR (p<0.001,T-Test), metastasis (p=0.001,T-Test) and mortality (p=0.008,T-Test).In univariate COX regressions, the nuclear frequency and the nuclear intensity of NF-kB p65 were both associated with overall BCR (p<0.001,each).For the multivariate analyses, the clinical model included the following parameters: preoperative PSA (continuous), Gleason score, extra-capsular extension, lymph node invasion, seminal vesicle involvement and surgical margin status.We found that the nuclear frequency of NF-kB p65 was retained in the multivariate model (p<0.001) and that it improved the fitness of the clinical model when performing a Likelihood ratio test and an Akaike Information Criterion (AIC) test.Furthermore, we observed that the fitness of the clinical model was improved in sub-cohorts of: (i) 1023 lymph node negative patients, (ii) 1242 patients with negative margins, (iii) 194 patients with Gleason score ≥ 4+3.Finally, the cytoplasmic intensity improved the clinical model in a sub-cohort of 72 lymph node positive patients.Conclusions: Our study offers validating results linking the nuclear frequency of NF-kB p65 with disease progression using a large cohort of European man.These results, and others in the scientific literature, suggest that NF-kB p65 can be useful as a molecular marker in the clinical decision process for PCa patients.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.665 | 0.501 |
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".