Assessment of Prostate and Bladder Cancer Genomic Biomarkers Using Artificial Intelligence: a Systematic Review.

PURPOSE OF REVIEW: The aim of the systematic review is to assess AI's capabilities in the genetics of prostate cancer (PCa) and bladder cancer (BCa) to evaluate target groups for such analysis as well as to assess its prospects in daily practice. RECENT FINDINGS: In total, our analysis included 27 articles: 10 articles have reported on PCa and 17 on BCa, respectively. The AI algorithms added clinical value and demonstrated promising results in several fields, including cancer detection, assessment of cancer development risk, risk stratification in terms of survival and relapse, and prediction of response to a specific therapy. Besides clinical applications, genetic analysis aided by the AI shed light on the basic urologic cancer biology. We believe, our results of the AI application to the analysis of PCa, BCa data sets will help to identify new targets for urological cancer therapy. The integration of AI in genomic research for screening and clinical applications will evolve with time to help personalizing chemotherapy, prediction of survival and relapse, aid treatment strategies such as reducing frequency of diagnostic cystoscopies, and clinical decision support, e.g., by predicting immunotherapy response. These factors will ultimately lead to personalized and precision medicine thereby improving patient outcomes.

A systematic review and meta-analysis of placebo effect in clinical trials on chronic prostatitis/chronic pelvic pain syndrome.

BACKGROUND: It is a common practice to control efficacy of pharmacological treatment with a placebo group. However, placebo itself may affect subjective and even objective results. The purpose of this study was to evaluate the placebo effect on symptoms of CP/CPPS to improve future clinical trials. METHODS: A search at three databases (Scopus, MEDLINE, and Web of Science) was conducted to identify double-blind placebo-controlled clinical trials on the treatment of CP/CPPS published until April 2021. The primary outcome - National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) score. SECONDARY OUTCOMES: Qmax, PVR, IPSS, and prostate volume. RESULTS: A total of 3502 studies were identified. Placebo arms of 42 articles (5512 patients, median 31 patients) were included in the systematic review. Systematic review identified positive changes in the primary endpoint, meta-analysis of 10 articles found that NIH-CPSI total score results were significantly influenced by placebo, mean difference -4.2 (95% confidence interval [CI]: -6.31, -2.09). Mean difference of NIH-CPSI pain domain was -2.31 (95% CI: -3.4, -1.21), urinary domain -1.12 (95% CI: -1.62, -0.62), quality of life domain -1.67 (95% CI: -2.38, -0.96); p < 0.001 for all. In case of the objective indicator - Qmax, there were three articles included in the meta-analysis. Qmax mean change from baseline was 0.68 (95% CI: -0.85, 2.22, p = 0.38). Systematic review showed no significant changes in pain, measured by VAS or other scores, IPSS and PVR. CONCLUSIONS: Placebo significantly affected the subjective parameters (NIH-CPSI) and limitedly affected various other measurements of pain (visual analog scale, McGill pain questionnaire). There was no long-term effect on IPSS and objective measurements (Qmax, PVR). This study can be used in further clinical trials to develop general rules of CPPS treatment assessment.

Thermal ablation vs. active surveillance for renal masses: a systematic review and network meta-analysis.

INTRODUCTION: Partial nephrectomy, thermal ablation and active surveillance are acceptable options for T1 stage renal tumor management. Currently, we lack sufficient information to make an accurate comparison of thermal ablation with active surveillance. The study objectives were to compare thermal ablation with active surveillance indirectly using partial nephrectomy as a reference. EVIDENCE ACQUISITION: We performed a systematic literature search using two databases (Scopus and Medline). The detailed search strategy is available at Prospero, CRD42021290055. The primary outcome was cancer-specific survival. Secondary outcomes included overall survival and metastasis-free survival. EVIDENCE SYNTHESIS: The final sample comprised 33 articles. They included the ones that compare: partial nephrectomy to ablation (29 studies), partial nephrectomy to active surveillance (2 studies), and partial nephrectomy vs. active surveillance vs. ablation (2 articles). We assessed 3-year and 5-year cancer-specific survival, and 3-, 5- and 7-year overall survival. The surface under the cumulative ranking curve (SUCRA) treatment benefit ranking was: cancer-specific survival - 48.6% for thermal ablation and 1.6% for active surveillance (5-year follow-up); overall survival - 52% for thermal ablation and 0.6% for active surveillance (7-year follow-up). The results demonstrated a significantly higher 3-year cancer-specific survival (RR 1.55, P=0.02) and 3- and 7-year follow-up overall survival (RR 1.85, P=0.03) in thermal ablation compared to active surveillance. At 5-year follow-up, cancer-specific survival and overall survival were in favor of thermal ablation while no statistically significant difference was reported. CONCLUSIONS: Thermal ablation offers a significantly higher cancer-specific survival and overall survival at mid-term follow-up in the management of T1 renal tumors compared to active surveillance. However, it is necessary to conduct further prospective randomized studies to validate the data.

A Prospective Comparison of Transrectal Standard, Cognitive, Transperineal Fusion, and Mapping Prostate Biopsy for Cancer Detection.

Purpose: The aim of this research was to compare the clinically significant prostate cancer (csPCa) detection rate (International Society of Urological Pathology [ISUP] ≥2) for the four biopsy methods: transrectal ultrasound-guided biopsy (TRUS-GB), cognitive transrectal biopsy (COG-TB), fusion transperineal biopsy (FUS-TB), and transperineal template mapping biopsy (TPMB). Materials and Methods: The inclusion criteria were as follows: prostate-specific antigen (PSA) >2 ng/mL, and/or positive digital rectal examination (DRE), and/or suspicious lesion on transrectal ultrasound (TRUS) and Prostate Imaging Reporting and Data System (Pi-RADS) v2.1 ≥ 3 score. In total, 102 patients were enrolled in the study. Biopsies were performed by two urologists. In a single procedure, the first urologist performed a FUS-TB and TPMB followed by second urologist who performed TRUS-GB and COG-TB. All specimens were obtained within a single procedure. Results: The csPCa detection rate and overall cancer detection rate (CDR) per patient were comparable among the respective biopsy methods (p > 0.05). Compared with other biopsy methods, a lower clinically insignificant prostate cancer (cisPCa) was detected using COG-TB (p = 0.004). The positive cores percentage ratio (p < 0.001) as well as positive cores containing csPCa percentage ratio (p < 0.001) significantly increased for the targeted biopsy methods. The median maximum cancer core length (MCCL; p = 0.52) as well the median for the MCCL of csPCa (p = 0.47) did not differ significantly among the respective biopsy methods. Concordance of the Gleason scores between biopsy and postprostatectomy pathology did not differ significantly among biopsy methods (p = 0.87). For TRUS-GB, FUS-TB, and TPMB, the common predictive factors for csPCa were positive DRE, suspicious lesion on ultrasound and Pi-RADS 5. As for COG-TB, the only predictor was Pi-RADS 5. Conclusion: The targeted methods did not show an increase in detection of csPCa and overall CDR over systematic ones in patients with Pi-RADS ≥3. A lower cisPCa was detected using COG-TB in comparison with the other methods. The sampling efficiency increased for the targeted biopsy methods, which used only a proportion of positive cores and cores containing csPCa. There was no statistical difference in histology concordance among the biopsies. One common predictive factor of increased csPCa detection for all biopsy methods was Pi-RADS 5.

A systematic review and meta-analysis of artificial intelligence diagnostic accuracy in prostate cancer histology identification and grading.

BACKGROUND: Artificial intelligence (AI) is a promising tool in pathology, including cancer diagnosis, subtyping, grading, and prognostic prediction. METHODS: The aim of the study is to assess AI application in prostate cancer (PCa) histology. We carried out a systematic literature search in 3 databases. Primary outcome was AI accuracy in differentiating between PCa and benign hyperplasia. Secondary outcomes were AI accuracy in determining Gleason grade and agreement among AI and pathologists. RESULTS: Our final sample consists of 24 studies conducted from 2007 to 2021. They aggregate data from roughly 8000 cases of prostate biopsy and 458 cases of radical prostatectomy (RP). Sensitivity for PCa diagnostic exceeded 90% and ranged from 87% to 100%, and specificity varied from 68% to 99%. Overall accuracy ranged from 83.7% to 98.3% with AUC reaching 0.99. The meta-analysis using the Mantel-Haenszel method showed pooled sensitivity of 0.96 with I2 = 80.7% and pooled specificity of 0.95 with I2 = 86.1%. Pooled positive likehood ratio was 15.3 with I2 = 87.3% and negative - was 0.04 with I2 = 78.6%. SROC (symmetric receiver operating characteristics) curve represents AUC = 0.99. For grading the accuracy of AI was lower: sensitivity for Gleason grading ranged from 77% to 87%, and specificity from 82% to 90%. CONCLUSIONS: The accuracy of AI for PCa identification and grading is comparable to expert pathologists. This is a promising approach which has several possible clinical applications resulting in expedite and optimize pathology reports. AI introduction into common practice may be limited by difficult and time-consuming convolutional neural network training and tuning.

A Systematic Review of Circulating Tumor Cells Clinical Application in Prostate Cancer Diagnosis.

The purpose of the review is to summarize the recent data on circulating tumor cells (CTC) use in clinical practice. We performed a systematic literature search using two databases (Medline and Scopus) over the past five years and the following terms: (CTC OR "circulating tumor cells" OR "liquid biopsy") AND prostate. The primary outcome was CTC predictive value for prostate cancer (PC) progression and survival. The secondary outcomes were the CTC predictive value for therapy response and the results of CTC detection depending on the assessment method. In metastatic PC, the CTC count showed itself to be a prognostic marker in terms of clinically important features, namely survival rates and response to treatment. CTC concentration was significantly associated with the overall survival and progression-free survival rates. A strong association between the overall survival or progression-free survival rate and CTC concentration could be observed. Variant-7 androgen receptors-positive (AR-V7-positive) patients showed a poor response to androgen receptor signaling (ARS) inhibitors, but this did not compromise their response to taxanes. In localized PC, only positive Cluster of Differentiantion 82 protein (CD82+) correlated with a higher survival rate. CTC count and AR-V7 expression showed itself to be a valuable biomarker for survival in metastatic PC and response to ARS-inhibitors. CTC diagnostic performance for localized PC or for screening and early detection is not high enough to show additional value over the other biomarkers.