The prognostic nomogram including MRI for locally advanced prostate cancer treated by radical prostatectomy

The prognostic value of mean apparent diffusion coefficient measured with diffusion-weighted magnetic resonance image in patients with prostate cancer treated with definitive radiotherapy

PURPOSE

To assess the correlation between initial tumor apparent diffusion coefficient (ADC) values and clinicopathological parameters in prostate cancer (PCa) patients treated with definitive radiotherapy (RT). Additionally, the prognostic factors for freedom from biochemical failure (FFBF) and progression-free survival (PFS) in this patient cohort were analyzed.

MATERIALS AND METHODS

The clinical data of 503 patients with biopsy-confirmed PCa were evaluated retrospectively. All patients had clearly evident tumors on diffusion-weighted magnetic resonance imaging (DW-MRI) for ADC values. Univariable and multivariable analyses were used to determine prognostic factors for FFBF and PFS.

RESULTS

The median follow-up was 72.9 months. The 5-year FFBF and PFS rates were 93.2% and 86.2%, respectively. Significantly lower ADC values were found in patients with a high PSA level; advanced clinical stage; higher ISUP score, and higher risk group than their counterparts. Receiver operating characteristic (ROC) curve analysis revealed an ADC cut-off value of 0.737 × 10^-3 mm²/sec for tumor recurrence. Patients who progressed had a lower mean ADC value than those who did not (0.712±0.158 vs. 1.365±0.227 × 10^-3 mm²/sec; p<0.001). There was a significant difference in 5-year FFBF (96.3% vs. 90%; p<0.001) and PFSrates (83.8% vs. 73.5%; p=0.002) between patients with higher and lower mean ADC values. The FFBF and PFS were found to be correlated with tumor ADC value and ISUP grades in multivariable analysis. Additionally, older age was found to be a significant predictor of worse PFS.

CONCLUSIONS

Lower ADC values were found in patients with high-risk characteristics such as a high serum PSA level, stage or grade of tumor, or high-risk disease, implying that ADC values could be used to predict prognosis. Lower ADC values and higher ISUP grades were associated with an increased risk of BF and progression, implying that treatment intensification may be required in these patients.

Benign prostate hyperplasia as a potential protective factor against prostate cancer: Insights from a magnetic resonance imaging study of compositional characteristics

PURPOSE

The structural relationship between benign prostate hyperplasia (BPH) and prostate cancer (Pca) is controversial. The purpose of our study was to examine the association between quantitative prostate compositional metrics by magnetic resonance imaging (MRI) and Pca.

METHODS

We identified 405 patients who underwent prostate MRI and biopsy and/or prostatectomy from January 2019 to January 2021 at our institution. Segmentation volumetric methods were used to assess central gland (CG) and peripheral zone (PZ) volume. PZ mean thickness and mean apparent diffusion coefficient (ADC), marker of underlying histologic components, were measured. Multivariable logistic regression was performed with outcomes of ≥Grade Group (GG) 2 Pca and for multifocal disease.

RESULTS

On multivariable analysis, higher CG volumes were at lower odds of ≥GG2 disease (n = 227) (OR: 0.97, 95% CI 0.96-0.98, p < 0.0001), taking into account PZ volume (p = 0.18) and thickness (p = 0.70). For every one cc increase in CG volume, there was an approximately 3% decrease in odds of ≥GG2 disease. Similar findings were noted for multifocal disease (n = 180) (OR: 0.97, 95% CI 0.96-0.98, p < 0.0001). Notably, ADC of the normal PZ was not significantly associated with CG volume (p = 0.21) nor a predictor of disease (p = 0.49).

CONCLUSIONS

Increasing central gland volume, driven by BPH, is associated with lower odds of significant Pca, including multifocal disease, while PZ anatomic and histologic surrogate changes were noncontributory. Findings support BPH impediment of global tumor growth predicted by theoretical mechanobiological model. This potential stabilizing factor should be further studied for risk stratification and in consideration for BPH therapy.

Development and Validation of a Prognostic Model for Predicting Overall Survival in Patients With Bladder Cancer: A SEER-Based Study

OBJECTIVE

To establish a prognostic model for Bladder cancer (BLCA) based on demographic information, the American Joint Commission on Cancer (AJCC) 7th staging system, and additional treatment using the surveillance, epidemiology, and end results (SEER) database.

METHODS

Cases with BLCA diagnosed from 2010-2015 were collected from the SEER database, while patient records with incomplete information on pre-specified variables were excluded. All eligible cases were included in the full analysis set, which was then split into training set and test set with a 1:1 ratio. Univariate and multivariate Cox regression analyses were conducted to identify prognostic factors for overall survival (OS) in BLCA patients. With selected independent prognosticators, a nomogram was mapped to predict OS for BLCA. The nomogram was evaluated using receiver operating characteristic (ROC) analysis and calibration plot in both the training and test sets. The area under curve [AUC] of the nomogram was calculated and compared with clinicopathological indicators using the full analysis set. Statistical analyses were conducted using the R software, where P-value <0.05 was considered significant.

RESULTS

The results indicated that age, race, sex, marital status, histology, tumor-node-metastasis (TNM) stages based on the AJCC 7th edition, and additional chemotherapy were independent prognostic factors for OS in patients with BLCA. Patients receiving chemotherapy tend to have better survival outcomes than those without. The proposed nomogram showed decent classification (AUCs >0.8) and prediction accuracy in both the training and test sets. Additionally, the AUC of the nomogram was observed to be better than that of conventional clinical indicators.

CONCLUSIONS

The proposed nomogram incorporated independent prognostic factors including age, race, sex, marital status, histology, tumor-node-metastasis (TNM) stages, and additional chemotherapy. Patients with BLCA benefit from chemotherapy on overall survival. The nomogram-based prognostic model could predict overall survival for patients with BLCA with accurate stratification, which is superior to clinicopathological factors.