Preoperative characteristics of the P.R.O.S.T.A.T.E. scores: a novel predictive tool for the risk of positive surgical margin after radical prostatectomy

Histogram analysis of MR quantitative parameters: are they correlated with prognostic factors in prostate cancer?

PURPOSE

To investigate the correlation between quantitative MR parameters and prognostic factors in prostate cancer (PCa).

METHOD

A total of 186 patients with pathologically confirmed PCa who underwent preoperative multiparametric MRI (mpMRI), including synthetic MRI (SyMRI), were enrolled from two medical centers. The histogram metrics of SyMRI [T1, T2, proton density (PD)] and apparent diffusion coefficient (ADC) values were extracted. The Mann‒Whitney U test or Student's t test was employed to determine the association between these histogram features and the prognostically relevant factors. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the differentiation performance. Spearman's rank correlation coefficients were calculated to determine the correlations between histogram parameters and the International Society of Urological Pathology (ISUP) grade group as well as pathological T stage.

RESULTS

Significant correlations were found between the histogram parameters and the ISUP grade as well as pathological T stage of PCa. Among these histogram parameters, ADC_minimum had the strongest correlation with the ISUP grade (r = - 0.481, p < 0.001), and ADC_Median showed the strongest association with pathological T stage (r = - 0.285, p = 0.008). The ADC_10th percentile exhibited the highest performance in identifying clinically significant prostate cancer (csPCa) (AUC 0.833; 95% CI 0.771-0.883). When discriminating between the status of different prognostically relevant factors, a significant difference was observed between extraprostatic extension-positive and -negative cancers with regard to histogram parameters of the ADC map (10th percentile, 90th percentile, mean, median, minimum) and T1 map (minimum) (p = 0.002-0.032). Moreover, histogram parameters of the ADC map (90th percentile, maximum, mean, median), T2 map (10th percentile, median), and PD map (10th percentile, median) were significantly lower in PCa with perineural invasion (p = 0.009-0.049). The T2 values were significantly lower in patients with seminal vesicle invasion (minimum, p = 0.036) and positive surgical margin (10th percentile, 90th percentile, mean, median, and minimum, p = 0.015-0.025).

CONCLUSION

Quantitative histogram parameters derived from synthetic MRI and ADC maps may have great potential for predicting the prognostic features of PCa.

Imaging classification of prostate cancer with extracapsular extension and its impact on positive surgical margins after laparoscopic radical prostatectomy

Abstract

To explore the impact of different imaging classifications of prostate cancer (PCa) with extracapsular extension (EPE) on positive surgical margins (PSM) after laparoscopic radical prostatectomy.

Methods

Clinical data were collected for 114 patients with stage PT3a PCa admitted to Ningbo Yinzhou No. 2 Hospital from September 2019 to August 2023. Radiologists classified the EPE imaging of PCa into Type I, Type II, and Type III. A chi-square test or t-test was employed to analyze the factors related to PSM. Multivariate regression analysis was conducted to determine the factors associated with PSM. Receiver operating characteristic curve analysis was used to calculate the area under the curve and evaluate the diagnostic performance of our model. Clinical decision curve analysis was performed to assess the clinical net benefit of EPE imaging classification, biopsy grade group (GG), and combined model.

Results

Among the 114 patients, 58 had PSM, and 56 had negative surgical margins. Multivariate analysis showed that EPE imaging classification and biopsy GG were risk factors for PSM after laparoscopic radical prostatectomy. The areas under the curve for EPE imaging classification and biopsy GG were 0.677 and 0.712, respectively. The difference in predicting PSM between EPE imaging classification and biopsy GG was not statistically significant (P>0.05). However, when used in combination, the diagnostic efficiency significantly improved, with an increase in the area under the curve to 0.795 (P<0.05). The clinical decision curve analysis revealed that the clinical net benefit of the combined model was significantly higher than that of EPE imaging classification and biopsy GG.

Conclusions

EPE imaging classification and biopsy GG were associated with PSM after laparoscopic radical prostatectomy, and their combination can significantly improve the accuracy of predicting PSM.

The Diagnostic Performance of Tumor Stage on MRI for Predicting Prostate Cancer-Positive Surgical Margins: A Systematic Review and Meta-Analysis

PURPOSE

Surgical margin status in radical prostatectomy (RP) specimens is an established predictive indicator for determining biochemical prostate cancer recurrence and disease progression. Predicting positive surgical margins (PSMs) is of utmost importance. We sought to perform a meta-analysis evaluating the diagnostic utility of a high clinical tumor stage (≥3) on magnetic resonance imaging (MRI) for predicting PSMs.

METHOD

A systematic search of the PubMed, Embase databases, and Cochrane Library was performed, covering the interval from 1 January 2000 to 31 December 2022, to identify relevant studies. The Quality Assessment of Diagnostic Accuracy Studies 2 method was used to evaluate the studies' quality. A hierarchical summary receiver operating characteristic plot was created depicting sensitivity and specificity data. Analyses of subgroups and meta-regression were used to investigate heterogeneity.

RESULTS

This meta-analysis comprised 13 studies with 3924 individuals in total. The pooled sensitivity and specificity values were 0.40 (95% CI, 0.32-0.49) and 0.75 (95% CI, 0.69-0.80), respectively, with an area under the receiver operating characteristic curve of 0.63 (95% CI, 0.59-0.67). The Higgins I2 statistics indicated moderate heterogeneity in sensitivity (I2 = 75.59%) and substantial heterogeneity in specificity (I2 = 86.77%). Area, prevalence of high Gleason scores (≥7), laparoscopic or robot-assisted techniques, field strength, functional technology, endorectal coil usage, and number of radiologists were significant factors responsible for heterogeneity (p ≤ 0.01).

CONCLUSIONS

T stage on MRI has moderate diagnostic accuracy for predicting PSMs. When determining the treatment modality, clinicians should consider the factors contributing to heterogeneity for this purpose.

Development of a Prediction Model for Positive Surgical Margin in Robot-Assisted Laparoscopic Radical Prostatectomy

A positive surgical margin (PSM) is reported to have some connection to the occurrence of biochemical recurrence and tumor metastasis in prostate cancer after the operation. There are no clinically usable models and the study is to predict the probability of PSM after robot-assisted laparoscopic radical prostatectomy (RALP) based on preoperative examinations. It is a retrospective cohort from a single center. The Lasso method was applied for variable screening; logistic regression was employed to establish the final model; the strengthened bootstrap method was adopted for model internal verification; the nomogram and web calculator were used to visualize the model. All the statistical analyses were based on the R-4.1.2. The main outcome was a pathologically confirmed PSM. There were 151 PSMs in the 903 patients, for an overall positive rate of 151/903 = 16.7%; 0.727 was the adjusted C statistic, and the Brier value was 0.126. Hence, we have developed and validated a predictive model for PSM after RALP for prostate cancer that can be used in clinical practice. In the meantime, we observed that the International Society of Urological Pathology (ISUP) score, Prostate Imaging Reporting and Data System (PI-RADS) score, and Prostate-Specific Antigen (PSA) were the independent risk factors for PSM.

Evaluating Incidence, Location, and Predictors of Positive Surgical Margin Among Chinese Men Undergoing Robot-Assisted Radical Prostatectomy

Purpose

To evaluate the incidence and locations of positive surgical margin (PSM) among Chinese men undergoing RARP and identify the preoperative predictors for PSM.

Methods

We retrospectively identified 393 patients who underwent RARP according to inclusion criteria by single surgeon in our hospital. PSM was defined as the presence of cancer adjacent to inked surface of the specimen and categorized into four groups based on locations: apex, posterolateral, base, and multifocal. Logistic regression analysis was performed to identify the predictors of overall and location-specific PSM.

Results

The overall PSM rate was 133/393 (34%). The PSM rates for pT2, pT3, and pT4 stage were 63/278 (23%), 50/89 (56%), and 20/26 (77%), respectively. The estimated rates for apical, posterolateral, basal, and multifocal PSM were 8%, 4%, 7%, and 14%, respectively. In univariate analysis, overall PSM related to tPSA, f/tPSA, percentage of positive needles, and Gleason score. Multifocal PSM correlated with smoking history, drinking history, tPSA, f/tPSA, percentage of positive needles, and Gleason score. In multivariate analysis, percentage of positive needles reminded the only independent predictor for overall (OR = 10.5, 95% CI: 2.58–44.4) and basal PSM (OR = 24.0, 95% CI: 3.22–179.4). The f/tPSA (OR = 2.59, 95% CI: 2.18–5.71) and percentage of positive needles (OR = 31.0, 95% CI: 3.17–303) were independent risk factors for multifocal PSM.

Conclusion

The multifocal sites were the most common location of positive surgical margin, followed by apical and basal sites among Chinese patients undergoing RARP. The percentage of positive needles was an independent predictor for overall, basal, and multifocal PSM.

Preoperative Predictive Model of Narrow Pelvis in Laparoscopic Radical Prostatectomy Through Computed Tomography

Objective: At present, prostate cancer radical surgery still lacks an objective standard for predicting the anatomic difficulty of surgery through preoperative examination. Due to the poor prognosis and surgical complications caused by "Narrow Pelvis," a pelvic model for prediction is urgently needed. The purpose of this study is to present objective preoperative assessing indicators to predict the surgical difficulty caused by pelvic anatomic abnormalities during laparoscopic radical prostatectomy (LRP). Methods: Patients undergoing LRP were retrospectively analyzed and separated into "Common Pelvis" or "Difficult Pelvis" groups according to the preset criteria. The clinical data and pelvic imaging data of the two groups were compared to obtain statistically significant differences. The results were compared and validated in 500 ordinary males. Logistic regression analysis was performed to optimize these indicators into a scoring model, "Laparoscopic Radical Prostatectomy Narrow Pelvic Predictive Index (LRP-NPPI)" for predicting "Difficult Pelvis." Results: Of the 145 patients undergoing LRP, 22 (15.2%) were included in the "Difficult Pelvis" group. Patients in the "Difficult Pelvis" group were more likely to have a narrower, shorter, deeper, more flattened pelvis, greater body mass index, more history of previous pelvic surgery, and greater prostate volume. Moreover, the larger amount of intraoperative blood loss and longer operation time were related. Compared with the "Common Pelvis" group, patients in the "Difficult Pelvis" have higher score of LRP-NPPI (p < 0.05). Conclusion: With the model we proposed, it is possible to predict patients with pelvic anatomical difficulties during LRP.

The value of transperineal apical prostate biopsy in predicting urethral/apical margin status after radical prostatectomy

PURPOSE

To investigate potential preoperative predictors of urethral or apical positive surgical margin (PSM) and the value of apical prostate biopsy in predicting urethral/apical margin status after radical prostatectomy (RP).

METHODS

A total of 531 patients who underwent RP during 2010 to 2017 at West China Hospital were enrolled in this retrospective study. Preoperative and postoperative factors including age, BMI, PSA, clinical T stage and biopsy Gleason score were analyzed. Univariate analysis and logistic regression were used to find out the potential predictive factors for PSM. Two logistic regression models were built to evaluate the role of apical prostate biopsy in predicting urethral/apical margin status.

RESULTS

The overall PSM rate was about 30.1% (160/531) and 97 of them were reported urethral/apical PSM. The incidence of urethral or apical PSM in patients with positive cores in the apical prostate was higher than those without (23.0% vs 9.9%, P < .001). We further found that the multivariable model with positive apical prostate biopsy could significantly increase the predictive value of urethral or apical PSM status (AUC: 0.744 vs 0.783, P = .016). Our analysis also showed that neo-adjuvant hormone therapy was an independent protective factor for urethral or apical PSM in patients with positive apical prostate biopsy, but not all patients.

CONCLUSION

This study revealed the necessity of apical prostate biopsy to predict the risk of apical or urethral PSM. In clinical practice, neo-adjuvant hormone therapy should be given when patients with positive apical prostate biopsy to reduce the presence of PSM, especially patients with high/very high risk prostate cancer.

Development and validation of a preoperative nomogram for predicting positive surgical margins after laparoscopic radical prostatectomy

BACKGROUND

Positive surgical margins are independent risk factor for biochemical recurrence, local recurrence, and distant metastasis after radical prostatectomy. However, limited predictive tools are available. This study aimed to develop and validate a preoperative nomogram for predicting positive surgical margins after laparoscopic radical prostatectomy (LRP).

METHODS

From January 2010 to March 2016, a total of 418 patients who underwent LRP without receiving neoadjuvant therapy at Peking University Third Hospital were retrospectively involved in this study. Clinical and pathological results of each patient were collected for further analysis. Univariable and multivariable logistic regression (backward stepwise method) were used for the nomogram development. The concordance index (CI), calibration curve analysis and decision curve analysis were used to evaluate the performance of our model.

RESULTS

Of 418 patients involved in this study, 142 patients (34.0%) had a positive surgical margin on final pathology. Based on the backward selection, four variables were included in the final multivariable regression model, including the percentage of positive cores in preoperative biopsy, clinical stage, free prostate specific antigen (fPSA)/total PSA (tPSA), and age. A nomogram was developed using these four variables. The concordance index (C-index) of the nomogram was 0.722 in the development cohort and 0.700 in the bootstrap validations. The bias-corrected calibration plot showed a limited departure from the ideal line with a mean absolute error of 2.0%. In decision curve analyses, the nomogram showed net benefits in the range from 0.2 to 0.7.

CONCLUSION

A nomogram to predict positive surgical margins after LRP was developed and validated, which could help urologists plan surgical procedures.

Preoperative PROSTATE scoring system: a potential predictive tool for the risk of biochemical recurrence after radical prostatectomy

Purpose

To study the association between the preoperative PROSTATE scoring system and the prediction of biochemical recurrence (BCR) risk, after radical prostatectomy (RP) in prostate cancer patients.

Patients and methods

A total of 340 patients who underwent a laparoscopic radical prostatectomy in Peking University First Hospital between November 2007 and March 2016 were included in the study. The preoperative PROSTATE scoring system was measured and calculated. The performance of the scoring system to predict BCR risk was estimated using the receiver operating characteristic curve (ROC curve). BCR-free survival was analyzed using the Kaplan– Meier method, and the log-rank test was applied to compare the differences in risk among the patient groups. The Cox proportional hazards regression was used to analyze the performance of the grouped PROSTATE scores.

Results

Of the total population, 91 (26.8%) patients had BCR. The PROSTATE score was significantly different between the BCR-developed and BCR-free groups (P<0.001). The ROC curve analysis of the scoring system showed an accuracy of 70.7% (95% CI 0.643–0.771) (P<0.001). The percentage of BCR in the high-risk (10–15), moderate-risk (5–9) and low-risk (0–4) groups was 63.3%, 24.6% and 10.3% respectively (P<0.001). The Cox proportional hazards regression analysis revealed that the grouped score was an independent predictor of BCR after RP (HR=2.002; 95% CI 1.222–3.280) (P=0.006).

Conclusion

The PROSTATE scoring system performed adequately in predicting the risk of BCR after RP. The scoring system can assist in decision-making about the operation and post- operative follow-up for patients with high-risk.