The Ability of Prostate Health Index (PHI) to Predict Gleason Score in Patients With Prostate Cancer and Discriminate Patients Between Gleason Score 6 and Gleason Score Higher Than 6-A Study on 320 Patients After Radical Prostatectomy

Preanalytical stability of molecular forms of prostate-specific antigen in serum samples (PSA, free PSA, [-2]proPSA) and their impact on fPSA/tPSA ratio and PHI

BACKGROUND

Prostate cancer is a common cancer in men. Detection methods include the measurement of biomarkers: prostate-specific antigen (PSA), free PSA, [-2]proPSA, and the calculated indices: fPSA/tPSA ratio and Prostate Health Index (PHI). Proper preanalytical conditions are crucial for precise measurement and failure to adhere to protocols or regulations can influence the diagnostic algorithm. We assessed the stability of the above-mentioned biomarkers, fPSA/tPSA ratio and PHI, under various pre-analytical conditions.

METHODS

Serum samples from 45 males were collected and stored under specific conditions before tPSA, fPSA, and [-2]proPSA were measured. Subsequently, the fPSA/tPSA and PHI were calculated.

RESULTS

tPSA, fPSA, and [-2]proPSA remained stable during the two freeze-thaw cycles. Storage at 4°C and 22°C resulted in stable tPSA concentrations. However, fPSA levels decreased and [-2]proPSA levels increased over time. The fPSA/tPSA ratio remained stable for 72 h, at which point a decrease was observed in the samples kept at 4°C and 22°C. A gradual increase in PHI was observed in the samples kept at 4°C and 22°C.

CONCLUSIONS

All biomarkers remained stable during two freeze-thaw cycles. tPSA was the most stable analyte when stored at 4°C, as well as at RT. A gradual increase of [-2]proPSA and a slight decrease in fPSA were observed during the storage test. This led to a decrease in the fPSA/tPSA ratio and an elevation in the PHI. We therefore recommend measuring prostate biomarkers promptly following blood collection.

IMPACT

Understanding the pre-analytical stability of prostate biomarkers helps prevent false positive results and improve the accuracy of diagnostics for prostate cancer.

Relationship between Proclarix and the Aggressiveness of Prostate Cancer

INTRODUCTION

Proclarix is a CE-marked test that provides the risk of clinically significant prostate cancer (csPCa), ranging from 0% to 100%, based on the serum measurement of Thrombospondin-1, cathepsin D, prostate-specific antigen (PSA), and percentage of free PSA in addition to age. We hypothesize that Proclarix could be correlated with PCa aggressiveness. We analyzed the association of this new biomarker with four surrogates of aggressiveness: grade group (GG) in the biopsy, clinical stage, risk of biochemical recurrence after primary treatment of localized PCa, and pathology in the surgical specimen.

MATERIAL AND METHODS

This is a retrospective study from 606 men with suspicion of PCa [PSA of ≥ 3.0 ng/mL and/or abnormal digital rectal examination (DRE)], in whom Proclarix was assessed (0-100%). The GG was defined by the International Society of Urological Pathology categories. The TNM was used for clinical staging (cT based on DRE, whereas cN and cM were established with computed tomography and 99-technetium bone scintigraphy). The risk of biochemical recurrence of localized PCa after primary treatment was defined by combining PSA, GG, and cT. Finally, an unfavorable pathology in a surgical specimen was defined as GG > 2 or pT ≥ 3.

RESULTS

The median age of the cohort was 67 years old, with a median PSA of 7 ng/mL and a rate of abnormal DRE of 23.3%. CsPCa was detected in 254 men (41.9%), with a median Proclarix of 60.1% compared with 37.3% obtained in patients with insignificant PCa and 20.7% in men without PCa. Among patients with GG > 3, Proclarix was significantly higher (58.2%) than in those with GG of 3 or lower (33.1%, p < 0.001). Men with localized tumors exhibited a Proclarix median of 37.3% compared with those with advanced disease (60.1%, p < 0.001). Proclarix levels among 197 patients with low and intermediate risk of biochemical recurrence were 24.9% and 35.0%, respectively, significantly lower compared with patients with high-risk disease (58.7%, p < 0.001). Unfavorable pathology was observed in 35 patients out of the 79 who underwent radical prostatectomy, with a Proclarix median of 35.7% compared with 23.7% obtained in patients with favorable pathology (p = 0.013). Proclarix and magnetic resonance imaging were independent predictors of the four surrogates of aggressiveness analyzed.

CONCLUSION

There is a correlation between Proclarix and the aggressiveness of PCa.

Prostate health index (PHI) as an accurate prostate cancer predictor

PURPOSE

This study aims to compare the ability of the PHI versus tPSA test to predict the presence of PCa in our population.

METHODS

A prospective observational study was performed. We included patients with tPSA ≥ 2.5 ng/ml, biopsy naïve or previous negative biopsy, undergoing a blood test, which includes tPSA, fPSA, and p2PSA, and a prostate biopsy between March 2019 and March 2022. Patients with PCa found in the biopsy-Group A-were compared with patients with a negative biopsy result-Group B. Diagnostic accuracy of tPSA and PHI was assessed by receiver operating characteristic [ROC] curves and logistic regression.

RESULTS

140 men were included. Fifty-seven (40.7%) had a positive prostate biopsy result (Group A), and 83 (59.3%) had a negative biopsy result (Group B). The mean age was similar in both groups (mean ± standard deviation), 66.86 ± 6.61 years. No difference was found in the tPSA value between the groups (Group A PSA: 6.11 ng/ml (3.56-17.01); Group B: 6.42 ng/ml (2.46-19.45), p = 0.41). The mean value of PHI was statistically different between groups (Group A 65.50 (29-146) vs. Group B 48 (16-233), p = 0.0001). The area under the curve 0.44 for tPSA and 0.77 for PHI. The multivariate logistic regression model applied to PHI showed a significant increase in its predictive accuracy: 72.14% in the model without PHI, 76.09% with PHI.

CONCLUSION

The PHI test improves PCa detection compared to tPSA in our population.

Multimodal convolutional neural networks based on the Raman spectra of serum and clinical features for the early diagnosis of prostate cancer

We collected surface-enhanced Raman spectroscopy (SERS) data from the serum of 729 patients with prostate cancer or benign prostatic hyperplasia (BPH), corresponding to their pathological results, and built an artificial intelligence-assisted diagnosis model based on a convolutional neural network (CNN). We then evaluated its value in diagnosing prostate cancer and predicting the Gleason score (GS) using a simple cross-validation method. Our CNN model based on the spectral data for prostate cancer diagnosis revealed an accuracy of 85.14 ± 0.39%. After adjusting the model with patient age and prostate specific antigen (PSA), the accuracy of the multimodal CNN was up to 88.55 ± 0.66%. Our multimodal CNN for distinguishing low-GS/high-GS and GS = 3 + 3/GS = 3 + 4 revealed accuracies of 68 ± 0.58% and 77 ± 0.52%, respectively.

Serum multi-cytokines screening identifies TRAIL and IL-10 as probable new biomarkers for prostate health index diagnostic utility adjustment in grey zone aggressive prostate cancer detection: A single-center data in China

Objective

To identify less invasive and easily applicable serum cytokine-derived biomarkers which contribute to the diagnostic utility and risk assessment ability of the prostate health index (PHI) based multivariable model in grey zone aggressive prostate cancer (AG PCa) early detection.

Methods

Serum 45 cytokines screening was performed in a small training cohort consisting of 10 sera by Luminex liquid array-based multiplexed immunoassays and identified TRAIL and IL-10 as new biomarkers for PHI diagnostic utility adjustment for further validation with a multivariable predictive model in a cohort including 79 aggressive prostate cancer patients and 209 benign prostatic hyperplasia or indolent PCa patients within the PSA grey zone.

Results

TRAIL and IL-10 were identified as potential serum biomarkers for AG PCa detection by the result of multi-cytokines screening in the univariate analysis, while multivariable logistic regression confirmed the AUC of the full risk predictive model (0.915) including tPSA, fPSA, PHI, TRAIL, and IL-10 was higher than various diagnostic strategies. DCA suggested a superior net benefit and indicated a good discriminative ability of the full risk model consistently with the result of the nomogram.

Conclusion

We suggest a significant advantage for the PHI-based multivariate combinations of serum TRAIL and IL-10 comparing to PHI or other serum-derived biomarkers alone in the detection and risk stratification of grey zone AG PCa.

Prostate health index (PHI) as a reliable biomarker for prostate cancer: a systematic review and meta-analysis

OBJECTIVES

Prostate cancer (PCa) represents the second most common solid cancer in men worldwide. In the last decades, the prostate health index (PHI) emerged as a reliable biomarker for detecting PCa and differentiating between non-aggressive and aggressive forms. However, before introducing it in clinical practice, more evidence is required. Thus, we performed a systematic review and meta-analysis for assessing the diagnostic performance of PHI for PCa and for detecting clinically significant PCa (csPCa).

METHODS

Relevant publications were identified by a systematic literature search on PubMed and Web of Science from inception to January 11, 2022.

RESULTS

Sixty studies, including 14,255 individuals, met the inclusion criteria for our meta-analysis. The pooled sensitivity and specificity of PHI for PCa detection was 0.791 (95%CI 0.739-0.834) and 0.625 (95%CI 0.560-0.686), respectively. The pooled sensitivity and specificity of PHI for csPCa detection was 0.874 (95%CI 0.803-0.923) and 0.569 (95%CI 0.458-0.674), respectively. Additionally, the diagnostic odds ratio was 6.302 and 9.206, respectively, for PCa and csPCa detection, suggesting moderate to good effectiveness of PHI as a diagnostic test.

CONCLUSIONS

PHI has a high accuracy for detecting PCa and discriminating between aggressive and non-aggressive PCa. Thus, it could be useful as a biomarker in predicting patients harbouring more aggressive cancer and guiding biopsy decisions.

Diagnostic accuracy of [-2]proPSA versus Gleason score and Prostate Health Index versus Gleason score for the determination of aggressive prostate cancer: a systematic review

OBJECTIVE

The objective of this review was to determine the diagnostic accuracy of [-2]proPSA (p2PSA) and the Prostate Health Index compared to the Gleason score in determining the aggressiveness of prostate cancer.

INTRODUCTION

Prostate cancer is the most commonly diagnosed cancer in men. However, the utility of currently available biomarkers for determining the aggressive form of the disease remains unknown. This review sought to determine the diagnostic accuracy of two new biomarkers in determining the aggressive form of prostate cancer.

INCLUSION CRITERIA

Diagnostic accuracy studies that enrolled men of any age and any prostate specific antigen (PSA) level with histologically confirmed prostate cancer in which Prostate Health Index and p2PSA were assessed in comparison to Gleason score for the determination of aggressive prostate cancer were considered for inclusion. There was no time limitation on study inclusion.

METHODS

A three-step search strategy was utilized to identify both published and unpublished studies in the English language in the following sources: PubMed, Cochrane Central Register of Controlled Trials, CINAHL, Web of Science, Google Scholar, MedNar, and SIGLE. Databases were searched from inception to January 2019. Study selection, critical appraisal, data extraction, and data synthesis were done according to the approach recommended by JBI.

RESULTS

A total of 12 studies (n = 8462) that recruited men with aggressive prostate cancer were considered in this review. The majority of included subjects had a total PSA level of 2 to 10ng/mL. The sensitivity of the Prostate Health Index ranged from 67% to 97% while specificity ranged from 6% to 64%. At a Prostate Health Index threshold of 25 and below (three studies, n = 3222), pooled sensitivity was 97% (95% confidence interval [CI], 95% to 98%) and specificity was 10% (95% CI, 6% to 16%). At a Prostate Health Index threshold of between 26 and 35 (six studies, n = 6030), pooled sensitivity was 87% (95% CI, 8% to 91%) and specificity was 45% (95% CI, 39% to 50%). At a Prostate Health Index threshold of 36 and above (five studies, n = 1476), pooled sensitivity was 72% (95% CI, 64% to 79%) and specificity was 74% (95% CI, 68% to 80%). Only one study assessed p2PSA. Sensitivity ranged from 80% to 95%, and specificity ranged from 9.9% to 27.9% with increasing threshold values from 7.9 to 10.9ng/mL.

CONCLUSIONS

Overall, both Prostate Health Index and p2PSA have acceptable accuracy for the determination of the likelihood of aggressive prostate cancer. However, the inverse relationship between sensitivity and specificity makes it difficult to determine an optimum cut-off value for positivity. Further research is warranted to determine their utility in the management of prostate cancer.

Prostate Cancer Diagnostic Algorithm as a "Road Map" from the First Stratification of the Patient to the Final Treatment Decision

The diagnostics of prostate cancer are currently based on three pillars: prostate biomarker panel, imaging techniques, and histological verification. This paper presents a diagnostic algorithm that can serve as a "road map": from initial patient stratification to the final decision regarding treatment. The algorithm is based on a review of the current literature combined with our own experience. Diagnostic algorithms are a feature of an advanced healthcare system in which all steps are consciously coordinated and optimized to ensure the proper individualization of the treatment process. The prostate cancer diagnostic algorithm was created using the prostate specific antigen and in particular the Prostate Health Index in the first line of patient stratification. It then continued on the diagnostic pathway via imaging techniques, biopsy, or active surveillance, and then on to the treatment decision itself. In conclusion, the prostate cancer diagnostic algorithm presented here is a functional tool for initial patient stratification, comprehensive staging, and aggressiveness assessment. Above all, emphasis is placed on the use of the Prostate Health Index (PHI) in the first stratification of the patients as a predictor of aggressiveness and clinical stage of prostrate cancer (PCa). The inclusion of PHI in the algorithm significantly increases the accuracy and speed of the diagnostic procedure and allows to choose the optimal pathway just from the beginning. The use of advanced diagnostic techniques allows us to move towards to a more advanced level of cancer care. This diagnostics algorithm has become a standard of care in our hospital. The algorithm is continuously validated and modified based on our results.

Genetic predisposition and prediction protocol for epithelial neoplasms in disease-free individuals: A systematic review

Background

Epithelial neoplasm is an important global health-care problem, with high morbidity and mortality rates. Early diagnosis and appropriate treatment are essential for increased life survival. Prediction of occurrence of malignancy in a disease-free individual by any means will be a great breakthrough for healthy living.

Aims and Objectives

The aims and objectives were to predict the genetic predisposition and propose a prediction protocol for epithelial malignancy of various systems in our body, in a disease-free individual.

Methods

We have searched databases both manually and electronically, published in English language in Cochrane group, Google search, MEDLINE and PubMed from 2000 to 2019. We have included all the published, peer-reviewed, narrative reviews; randomized controlled trials; case-control studies; and cohort studies and excluded the abstract-only articles and duplicates. Specific words such as "etiological factors," "pathology and mutations," "signs and symptoms," "genetics and IHC marker," and "treatment outcome" were used for the search. A total of 1032 citations were taken, and only 141 citations met the inclusion criteria and were analyzed.

Results

After analyzing various articles, the etiological factors, clinical signs and symptoms, genes and the pathology involved and the commonly used blood and tissue markers were analyzed. A basic investigation strategy using immunohistochemistry markers was established.

Conclusion

The set of proposed biomarkers should be studied in future to predict genetic predisposition in disease-free individuals.

Preoperative prostate health index predicts adverse pathology and Gleason score upgrading after radical prostatectomy for prostate cancer

BACKGROUND

We aimed to explore the utility of prostate specific antigen (PSA) isoform [- 2] proPSA and its derivatives for prediction of pathological outcome after radical prostatectomy (RP).

METHODS

Preoperative blood samples were prospectively and consecutivelyanalyzed from 472 patients treated with RP for clinically localized prostate cancerat four medical centers. Measured parameters were PSA, free PSA (fPSA), fPSA/PSA ratio, [- 2] proPSA (p2PSA), p2PSA/fPSA ratio and Prostate Health Index (PHI)(p2PSA/fPSA)*√PSA]. Logistic regression models were fitted to determine the accuracy of markers for prediction of pathological Gleason score (GS) ≥7, Gleason score upgrading, extracapsular extension of the tumor (pT3) and the presence of positive surgical margin (PSM). The accuracy of predictive models was compared using area under the receiver operating curve (AUC).

RESULTS

Of 472 patients undergoing RP, 339 (72%) were found to have pathologic GS ≥ 7, out of them 178 (53%) experienced an upgrade from their preoperative GS = 6. The findings of pT3 and PSM were present in 132 (28%) and 133 (28%) cases, respectively. At univariable analysis of all the preoperative parameters, PHI was the most accurate predictor of pathological GS ≥7 (OR 1.02, 95% CI 1.01-1.03, p<0.001), GS upgrading (OR 1.02, 95% CI 1.01-1.03, p<0.003), pT3 disease (OR 1.01, 95% CI 1.00-1.02, p<0.007) and the presence of PSM (OR 1.01, 95% CI 1.00-1.02, p<0.002). Adding of PHI into the base multivariable model increased significantly the accuracy for prediction of pathological GS by 4.4% to AUC = 66.6 (p = 0.015) and GS upgrading by 5.0% to AUC = 65.9 (p = 0.025), respectively.

CONCLUSIONS

Preoperative PHI levels may contribute significantly to prediction of prostate cancer aggressiveness and expansion of the tumor detected at final pathology.

Prostate cancer management: long-term beliefs, epidemic developments in the early twenty-first century and 3PM dimensional solutions

In the early twenty-first century, societies around the world are facing the paradoxal epidemic development of PCa as a non-communicable disease. PCa is the most frequently diagnosed cancer for men in several countries such as the USA. Permanently improving diagnostics and treatments in the PCa management causes an impressive divergence between, on one hand, permanently increasing numbers of diagnosed PCa cases and, on the other hand, stable or even slightly decreasing mortality rates. Still, aspects listed below are waiting for innovate solutions in the context of predictive approaches, targeted prevention and personalisation of medical care (PPPM / 3PM).A.PCa belongs to the cancer types with the highest incidence worldwide. Corresponding economic burden is enormous. Moreover, the costs of treating PCa are currently increasing more quickly than those of any other cancer. Implementing individualised patient profiles and adapted treatment algorithms would make currently too heterogeneous landscape of PCa treatment costs more transparent providing clear "road map" for the cost saving.B.PCa is a systemic multi-factorial disease. Consequently, predictive diagnostics by liquid biopsy analysis is instrumental for the disease prediction, targeted prevention and curative treatments at early stages.C.The incidence of metastasising PCa is rapidly increasing particularly in younger populations. Exemplified by trends observed in the USA, prognosis is that the annual burden will increase by over 40% in 2025. To this end, one of the evident deficits is the reactive character of medical services currently provided to populations. Innovative screening programmes might be useful to identify persons in suboptimal health conditions before the clinical onset of metastasising PCa. Strong predisposition to systemic hypoxic conditions and ischemic lesions (e.g. characteristic for individuals with Flammer syndrome phenotype) and low-grade inflammation might be indicative for specific phenotyping and genotyping in metastasising PCa screening and disease management. Predictive liquid biopsy tests for CTC enumeration and their molecular characterisation are considered to be useful for secondary prevention of metastatic disease in PCa patients.D.Particular rapidly increasing PCa incidence rates are characteristic for adolescents and young adults aged 15-40 years. Patients with early onset prostate cancer pose unique challenges; multi-factorial risks for these trends are proposed. Consequently, multi-level diagnostics including phenotyping and multi-omics are considered to be the most appropriate tool for the risk assessment, prediction and prognosis. Accumulating evidence suggests that early onset prostate cancer is a distinct phenotype from both aetiological and clinical perspectives deserving particular attention from view point of 3P medical approaches.

A comparison of prostate health index, total PSA, %free PSA, and proPSA in a contemporary US population-The MiCheck-01 prospective trial

BACKGROUND

Increasing numbers of patients are presenting with aggressive prostate cancer (CaP); therefore, there exists a need to optimally identify these patients pre-biopsy.

OBJECTIVES

To compare the accuracy of total prostate specific antigen (PSA), %free PSA, and prostate health index (PHI) to differentiate between patients without CaP, with non-aggressive (Gleason 3 + 3, non-AgCaP) and with aggressive (Gleason ≥ 3 + 4, AgCaP) in a contemporary US population.

DESIGN, SETTINGS, AND PARTICIPANTS

Serum samples were collected from 332 US patients scheduled for biopsy due to an elevated age-adjusted PSA. Site and Central biopsy pathologic assessment were performed.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Testing of PSA, free PSA, proPSA, and PHI was performed along with central pathology review. Test performance using logistic regression analysis for differentiating CaP from non-CaP as well as non-AgCaP from AgCaP was evaluated.

RESULTS AND LIMITATIONS

Central pathology review resulted in 32 upgrades including 14 Gleason 3 + 3 scores being upgraded to AgCaP with final distribution of 148 no-CaP, 64 non-AgCaP, and 120 AgCaP patients. Receiver operator curve (ROC) analysis of the different tests showed that PHI performed best at differentiating CaP from no-CaP subjects (area under the receiver operator curve 0.79). In contrast, the different tests were essentially equivalent in differentiating AgCaP vs. non-AgCaP.

CONCLUSIONS

In this recent US study of prebiopsy patients we observed a high proportion of AgCaP patients consistent with previous studies in contemporary US populations. Central Gleason review is recommended for multi-institutional studies comparing biomarkers. PHI was superior to PSA, free PSA, %free PSA, and proPSA in detecting CaP in this population but was not superior at differentiating AgCaP from non-AgCaP.

[Clinical value of serum isoform [-2] proprostate-specific antigen and its derivatives in predicting aggressive prostate cancer]

OBJECTIVE

To explore the clinical value of serum isoform [-2] proprostate-specific antigen (p2PSA) and its derivatives %p2PSA and prostate health index (PHI) in predicting aggressive prostate cancer (PCa).

METHODS

The pre-operation serum and basic clinical data of 322 patients with PCa (including 143 patients diagnosed with PCa by transrectal ultrasound-guided prostate biopsy and 179 patients undergoing radical prostatectomy) in Peking University First Hospital were collected from August 2015 to May 2018. Serum total prostate-specific antigen (tPSA), free prostate antigen (fPSA) and fPSA/tPSA (f/t) and the p2PSA level of all these patients were measured on automatic immune analyzers DxI800, and then %p2PSA and PHI were calculated. The prostate pathologic result was considered as the gold standard to evaluate the Gleason score of the patients with PCa. Receiver operator curves (ROC) were used to assess the ability of p2PSA, %p2PSA and PHI to predict aggressive PCa (pathologic Gleason score≥7) compared with those traditional markers tPSA, fPSA and f/t.

RESULTS

Among these patients, the p2PSA, %p2PSA and PHI median levels were significantly higher in patients with pathologic Gleason score≥7 than those with Gleason score<7 (p2PSA: 30.22 ng/L vs. 18.33 ng/L; %p2PSA: 2.50 vs. 1.27; PHI: 91.81 vs. 35.44; all P<0.01). The area under curve (AUC) of %p2PSA and PHI (0.770, 0.760) in predicting Gleason score≥7 were higher than those of the traditional indicators tPSA, fPSA and f/t (AUC were 0.648, 0.536 and 0.693, respectively). Among those patients diagnosed with PCa by transrectal ultrasound-guided prostate biopsy, the AUC of %p2PSA and PHI (AUC were 0.808 and 0.801, respectively) in predicting Gleason score≥7 were higher than those of the traditional indicators tPSA, fPSA and f/t (AUC were 0.729, 0.655 and 0.665 respectively). Among those patients undergoing radical prostatectomy, PHI and %p2PSA also had the trend of higher predictive value than those of the traditional indicators. The AUC of %p2PSA and PHI were 0.798 and 0.744, respectively while the AUC of tPSA, fPSA and f/t were 0.625, 0.507 and 0.697, respectively.

CONCLUSION

Compared with traditional markers tPSA, fPSA and f/t, %p2PSA and PHI had much higher predictive value for aggressive PCa, which may help clinicians to evaluate the therapeutic regime and make more appropriate management plan for the patients.

Beyond PSA: The Role of Prostate Health Index (phi)

Background: Widespread use of prostate specific antigen (PSA) in screening procedures allowed early identification of an increasing number of prostate cancers (PCas), mainly including indolent cancer. Availability of different therapeutic strategies which have a very different impact on the patient’s quality of life suggested a strong need for tools able to identify clinically significant cancer at diagnosis. Multi-parametric magnetic resonance showed very good performance in pre-biopsy diagnosis. However, it is an expensive tool and requires an experienced radiologist. In this context, a simple blood-based test is worth investigating. In this context, researchers focused their attention on the development of a laboratory test able to minimize overdiagnosis without losing the identification of aggressive tumors. Results: Recent literature data on PCa biomarkers revealed a clear tendency towards the use of panels of biomarkers or a combination of biomarkers and clinical variables. Phi, the 4Kscore, and Stockholm3 as circulating biomarkers and the Mi-prostate score, Exo DX Prostate, and Select MD-X as urinary biomarker-based tests have been developed. In this scenario, phi is worthy of attention as a noninvasive test significantly associated with aggressive PCa. Conclusions: Literature data showed that phi had good diagnostic performance to identify clinically significant (cs) PCa, suggesting that it could be a useful tool for personalized treatment decision-making. In this review, phi potentialities, limitations, and comparisons with other blood- and urinary-based tests were explored.

Abdominal aortic aneurysm in prostate cancer patients: the "road map" from incidental detection to advanced predictive, preventive, and personalized approach utilizing common follow-up for both pathologies

Abdominal aortic aneurysm (AAA) is often a hidden pathological process showing no clinical symptoms. Genetic burden, smoking, male gender, age > 65 years, and white race have been identified as the main risk factors. A regular screening program has been introduced but is, as yet, unclear and is not performed in most countries. Prostate cancer is the most frequent male malignant disease in Western countries. Prostate cancer is a disease of older age with a median primary diagnosis of over 60 years. In recent years, advanced imaging methods have been established as important diagnostic tools in prostate cancer diagnostics. The incidental detection of AAA during diagnostic imaging performed due to prostate cancer diagnosis could reveal some asymptomatic aneurysms. Using our experience, the incidental detection of AAA during ¹⁸F-fluoromethylcholine PET/CT imaging, performed due to the staging, follow-up, and restaging of the prostate cancer, was reworked into a regular tool of secondary prevention within the framework of personalized medicine strategies. Experience with this type of AAA detection is demonstrated by a cohort of 500 patients who underwent ¹⁸F-fluorometylcholine PET/CT examination due to the staging or restaging of prostate cancer. A total of 28 aneurysms were detected (26 aneurysms < 50 mm, 2 aneurysms > 50 mm). In 2 cases (diameter < 50 mm), serious complications were found (penetrating aortic ulcer). The detection and monitoring of AAA in patients undergoing ¹⁸F-fluorometylcholine PET/CT due to the prostate cancer offers the possibility of a secondary prevention of AAA, patient stratification, and common follow-up for both pathologies.