Gleason Score 6 - Prostate Cancer or Benign Variant?

Physician Perception of Grade Group 1 Prostate Cancer

BACKGROUND

Despite its low-risk nature, grade group 1 (GG 1) prostate cancer (PCa) remains overtreated. This suggests a disconnect between daily physician practice and the standard of care. We hypothesized that GG 1 disease is overtreated because of common misconceptions regarding its true natural history.

OBJECTIVE

To survey physicians worldwide to better understand their approach to management of GG 1 PCa.

DESIGN, SETTING, AND PARTICIPANTS

A 17-question survey was sent to urology, radiation oncology, and pathology societies on six continents, and was posted on Twitter. Responses were collected and analyzed.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Pearson's χ2 test was used to assess correlation between physician-related variables and the perception of active surveillance (AS) for GG 1 PCa. Logistic regression was used for multivariable analysis. Statistical analysis was performed using SPSS version 21.

RESULTS AND LIMITATIONS

Among 1303 participants, 55% were urologists, 47% had completed fellowship, and 49% practice in an academic setting. Among the clinicians, 724 (83%) routinely recommend AS for GG 1 PCa and have never/rarely regretted it, while 18 (2%) "often" regretted it. Routine AS was more common among physicians aged <40 yr, those in practice for <10 yr, and those living in North America, Europe, or Australia/New Zealand. More than one-third of the respondents practicing in nonacademic settings reported 15-yr PCa mortality in low-risk PCa of >3%. Regarding reclassification of GG 1 to a precancerous lesion, 428 (39%) felt that this is a good idea, 340 (31%) disagreed, and 323 (30%) were uncertain. Those in support were more likely to be aged <40 yr (p = 0.001), in practice for <5 yr (p = 0.005), urologists (p < 0.001), and fellows trained in urologic oncology (p < 0.001). Opposition was common among pathologists (61%). Among terminologies proposed to replace "cancer" for GG 1 are neoplasm of low malignant potential (51% approval), indolent neoplasm rarely requiring treatment (23%), and indolent lesion of epithelial origin (8%).

CONCLUSIONS

AS is more commonly recommended by physicians who are younger, are fellowship-trained in urologic oncology, practice in academic settings, and are based in North America, Europe, or Australia/New Zealand. Misconceptions regarding AS outcomes may hinder its adoption. Frequent use of AS is associated with support for changing the "cancer" nomenclature.

PATIENT SUMMARY

In this study, we found that active surveillance remains underused in the management of low-risk prostate cancer because of incorrect perceptions regarding cancer outcomes. Omitting the word "cancer" for low-risk lesions is a challenging but promising effort that is favored by many clinicians, particularly by those who advocate for active surveillance.

Predictive role of T2WI and ADC-derived texture parameters in differentiating Gleason score 3 + 4 and 4 + 3 prostate cancer

BACKGROUND

Since Gleason score (GS) 4 + 3 prostate cancer (PCa) has a worse prognosis than GS 3 + 4 PCa, differentiating these two types of PCa is of clinical significance.

OBJECTIVE

To assess the predictive roles of using T2WI and ADC-derived image texture parameters in differentiating GS 3 + 4 from GS 4 + 3 PCa.

METHODS

Forty-eight PCa patients of GS 3 + 4 and 37 patients of GS 4 + 3 are retrieved and randomly divided into training (60%) and testing (40%) sets. Axial image showing the maximum tumor size is selected in the T2WI and ADC maps for further image texture feature analysis. Three hundred texture features are computed from each region of interest (ROI) using MaZda software. Feature reduction is implemented to obtain 30 optimal features, which are then used to generate the most discriminative features (MDF). Receiver operating characteristic (ROC) curve analysis is performed on MDF values in the training sets to achieve cutoff values for determining the correct rates of discrimination between two Gleason patterns in the testing sets.

RESULTS

ROC analysis on T2WI and ADC-derived MDF values in the training set (n = 51) results in a mean area under the curve (AUC) of 0.953±0.025 (with sensitivity 0.9274±0.0615 and specificity 0.897±0.069), and 0.985±0.013 (with sensitivity 0.9636±0.0446 and specificity 0.9726±0.0258), respectively. Using the corresponding MDF cutoffs, 95.3% (ranges from 76.5% to 100%) and 94.1% (ranged from 76.5% to 100%) of test cases (n = 34) are correctly discriminated using T2WI and ADC-derived MDF values, respectively.

CONCLUSIONS

The study demonstrates that using T2WI and ADC-derived image texture parameters has a potential predictive role in differentiating GS 3 + 4 and GS 4 + 3 PCa.

Optimizing prostate cancer accumulating model: combined PI-RADS v2 with prostate specific antigen and its derivative data

BACKGROUND

To establish a new accumulating model to enhance the accuracy of prostate cancer (PCa) diagnosis by incorporating prostate-specific antigen (PSA) and its derivative data into the Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2).

METHODS

A total of 357 patients who underwent prostate biopsy between January 2014 and December 2017 were included in this study. All patients had 3.0 T multiparametric magnetic resonance imaging (MRI) and complete laboratory examinations. PI-RADS v2 was used to assess the imaging. PSA, PSA density (PSAD), the free/total PSA ratio (f/t PSA) and the Gleason score (GS) were classified into four-tiered levels, and optimal weights were pursued on these managed levels to build a PCa accumulating model. A receiver operating characteristic curve was generated.

RESULTS

In all, 174 patients (48.7%) had benign prostatic hyperplasia, and 183 (51.3%) had PCa, among whom 149 (81.4%, 149/183) had clinically significant PCa. The established model 6 (PI-RADS v2 + level of PSAD + level of f/t PSA+ level of PSA) had a sensitivity and specificity of 81.4 and 84.5%, respectively, at the cut-off point of 11 in PCa diagnosis. Correspondingly, at the 12 cut-off point, the sensitivity and specificity were 87.7 and 83.0%, respectively, in diagnosing clinically significant PCa. The score of the new accumulating system was significantly different among the defined GS groups (p < 0.001). The mean values and 95% confidence intervals for GS 1-4 groups were 10.20 (9.63-10.40), 12.03 (11.19-12.87), 14.12 (13.60-14.64) and 15.44 (15.09-15.79).

CONCLUSIONS

A new PCa accumulating model may be useful in improving the accuracy of the primary diagnosis of PCa and helpful in the clinical decision to perform a biopsy when MRI results are negative.

The Tumor Microenvironments of Lethal Prostate Cancer

Localized prostate cancer (confined to the gland) generally is considered curable, with nearly a 100% 5-year-survival rate. When the tumor escapes the prostate capsule, leading to metastasis, there is a poorer prognosis and higher mortality rate, with 5-year survival dropping to less than 30%. A major research question has been to understand the transition from indolent (low risk) disease to aggressive (high risk) disease. In this chapter, we provide details of the changing tumor microenvironments during prostate cancer invasion and their role in the progression and metastasis of lethal prostate cancer. Four microenvironments covered here include the muscle stroma, perineural invasion, hypoxia, and the role of microvesicles in altering the extracellular matrix environment. The adaptability of prostate cancer to these varied microenvironments and the cues for phenotypic changes are currently understudied areas. Model systems for understanding smooth muscle invasion both in vitro and in vivo are highlighted. Invasive human needle biopsy tissue and mouse xenograft tumors both contain smooth muscle invasion. In combination, the models can be used in an iterative process to validate molecular events for smooth muscle invasion in human tissue. Understanding the complex and interacting microenvironments in the prostate holds the key to early detection of high-risk disease and preventing tumor invasion through escape from the prostate capsule.