The ability of prostate‐specific antigen (PSA) density to predict an upgrade in Gleason score between initial prostate biopsy and prostatectomy diminishes with increasing tumour grade due to reduced PSA secretion per unit tumour volume
Bibliographic record
Abstract
UNLABELLED: Study Type - Diagnostic (exploratory cohort) Level of Evidence 2b What's known on the subject? and What does the study add? Due to sampling error, the Gleason score of clinically localized prostate cancer is frequently underestimated at the time of initial biopsy. Given that this may lead to inappropriate surveillance of patients with high-risk disease, there is considerable interest in identifying predictors of significant undergrading. Recently PSAD has been proposed to be an accurate predictor of subsequent upgrading in patients diagnosed with Gleason 6 disease on biopsy. We examined the predictive characteristics of PSAD in patients with low- and intermediate-risk disease on biopsy subsequently treated with radical prostatectomy. We found that although PSAD was a significant predictor of upgrade of biopsy Gleason 6 and 3 + 4 = 7 tumours, it failed to predict upgrading in patients with Gleason 7 tumours taken as a whole. When we explored reasons for this discrepancy, we found that the amount of PSA produced per unit tumour volume decreased with increasing Gleason score, thereby diminishing the predictive value of PSAD. OBJECTIVES: To analyse the performance of PSA density (PSAD) as a predictor of Gleason score upgrade in a large cohort stratified by Gleason score. We and others have shown that an upgrade in Gleason score between initial prostate biopsy and final radical prostatectomy (RP) pathology is a significant risk factor for recurrence after local therapy. PATIENTS AND METHODS: Patients undergoing RP with matching biopsy information were identified from two prospective databases. Patients were analysed according to the concordance between biopsy and final pathology Gleason score in three paired groups: 6/>6, 3 + 4/>3 + 4, 7/>7. Receiver-operating characteristic (ROC) curves were generated stratified by Gleason score, and the area under the curve (AUC) calculated. Logistic regression models were fitted to identify significant predictors of tumour upgrade. RESULTS: From 1516 patients, 435 (29%) had an upgrade in Gleason score. ROC analysis showed a decline in AUC with increasing biopsy Gleason score, from 0.64 for biopsy Gleason score 6, to 0.57 for Gleason score 7. In logistic regression models containing pretreatment variables, e.g. clinical stage and number of positive cores, for Gleason score 6 and 3 + 4, PSAD was the strongest predictor of subsequent tumour upgrade (odds ratio [OR] 1.46, 95% confidence interval [95% CI] 1.18-1.83, P= 0.001 and OR 1.37, 95% CI 1.14-1.67, P= 0.002, respectively). Surprisingly, in tumours upgraded from Gleason score 7 to >7, PSAD was not predictive even on univariable analysis, whereas clinical stage and number of positive cores were significant independent predictors. To explore the relationship between serum PSA and Gleason score, tumour volume was calculated in 669 patients. There was a strong association between Gleason score and tumour volume, with the median volume of Gleason score 7 and Gleason score >7 tumours being approximately twice and four-times that of Gleason score 6 tumours, respectively (P < 0.001). In contrast, the median serum PSA level per millilitre tumour volume decreased significantly with increasing grade, from 5.4 ng/mL for Gleason score 6 to 2.1 ng/mL for >7 (P < 0.001). CONCLUSIONS: There is a strong correlation between Gleason score and tumour volume in well/intermediate differentiated tumours, and as they produce relatively high amounts of PSA per unit volume of cancer, high PSAD is the strongest single predictor of tumour undergrading. However, as higher grade tumours produce less PSA per unit volume, PSAD loses its predictive ability, and other clinical markers of tumour volume such as palpable disease and numbers of positive cores become more predictive.
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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) | 0.001 | 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 | 0.001 |
| 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".