Molecular Lymph Node Status for Prognostic Stratification of Prostate Cancer Patients Undergoing Radical Prostatectomy with Extended Pelvic Lymph Node Dissection
Bibliographic record
Abstract
Abstract Purpose: Molecular lymph node (LN) analysis using quantitative polymerase chain reaction (qPCR) detects LN metastases with higher sensitivity than histopathology. However, the prognostic role of molecular LN status in prostate cancer patients treated with radical prostatectomy (RP) and extended pelvic LN dissection (ePLND) is unclear. To investigate the association of molecular compared with histopathologic LN status with biochemical recurrence. Experimental Design: Patients with intermediate and high-risk prostate cancer were prospectively enrolled and underwent RP with ePLND, including the obturator, internal, external, and the common iliac region. LNs ≥3 mm were bisected and examined by standard histopathology and qPCR for Kallikrein3 (KLK3) expression. Biochemical recurrence was defined by confirmed postoperative PSA > 0.2 ng/mL. Results: In 111 patients, 2,411 of 3,173 removed LNs were examined by both methods. Histopathology detected 68 LN metastases in 28 (25%) patients. Molecular analysis confirmed elevated KLK3 expression in 65 histopathologic LN metastases of all 28 pN1 patients (pN1/molN1) and additionally reclassified 224 histopathologic negative LNs and 32 (29%) pN0 patients as LN-positive (pN0/molN1). At a median follow-up of 48 months, 52 (47%) patients developed biochemical recurrence. Median biochemical recurrence-free survival was 9 months [95% confidence interval (CI), 0.0–20.1] in pN1/molN1 patients, 24 months (95% CI, 1.7–46.3) in pN0/molN1 patients and was not reached in pN0/molN0 patients (P < 0.001). On multivariable Cox regression analysis, molecular LN status [HR 4.1 (95% CI, 1.9–8.8), P < 0.001] but not histopathologic LN status [HR 1.5 (95% CI, 0.8–3.0), P = 0.198] was confirmed as independent predictor of biochemical recurrence. Conclusions: Molecular LN analysis identified pN0 patients with a high risk of biochemical recurrence and provided superior prognostic information in comparison with histopathology alone. Clin Cancer Res; 24(10); 2342–9. ©2018 AACR.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".