Influence of Tumor Burden on Serum Prostate-Specific Antigen in Prostate Cancer Patients Undergoing Radical Prostatectomy
Bibliographic record
Abstract
OBJECTIVE: We aimed to assess the correlation between serum prostate-specific antigen (PSA) and tumor burden in prostate cancer (PCa) patients undergoing radical prostatectomy (RP), because estimation of tumor burden is of high value, e.g., in men undergoing RP or with biochemical recurrence after RP. PATIENTS AND METHODS: From January 2019 to June 2020, 179 consecutive PCa patients after RP with information on tumor and prostate weight were retrospectively identified from our prospective institutional RP database. Patients with preoperative systemic therapy (n=19), metastases (cM1, n=5), and locally progressed PCa (pT4 or pN1, n=50) were excluded from analyses. Histopathological features, including total weight of the prostate and specific tumor weight, were recorded by specialized uro-pathologists. Linear regression models were performed to evaluate the effect of PSA on tumor burden, measured by tumor weight after adjustment for patient and tumor characteristics. RESULTS: Overall, median preoperative PSA was 7.0 ng/ml (interquartile range [IQR]: 5.41-10) and median age at surgery was 66 years (IQR: 61-71). Median prostate weight was 34 g (IQR: 26-46) and median tumor weight was 3.7 g (IQR: 1.8-7.1), respectively. In multivariable linear regression analysis after adjustment for patients and tumor characteristics, a significant, positive correlation could be detected between preoperative PSA and tumor weight (coefficient [coef.]: 0.37, CI: 0.15-0.6, p=0.001), indicating a robust increase in PSA of almost 0.4 ng/ml per 1g tumor weight. CONCLUSION: Preoperative PSA was significantly correlated with tumor weight in PCa patients undergoing RP, with an increase in PSA of almost 0.4 ng/ml per 1 g tumor weight. This might help to estimate both tumor burden before undergoing RP and in case of biochemical recurrence.
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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) | 0.001 | 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 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".