Tailoring Intensity of Active Surveillance for Low-Risk Prostate Cancer Based on Individualized Prediction of Risk Stability

Has Active Surveillance for Prostate Cancer Become Safer? Lessons Learned from a Global Clinical Registry

BACKGROUND AND OBJECTIVE

Active surveillance (AS) has evolved into a widely applied treatment strategy for many men around the world with low-risk prostate cancer (or in selected cases intermediate-risk disease). Here, we report on the safety and acceptability of AS, and treatment outcomes for low- and intermediate-risk tumours over time in 14 623 men with follow-up of over 6 yr.

METHODS

Clinical data from 26 999 men on AS from 25 cohorts in 15 countries have been collected in an international database from 2000 onwards.

KEY FINDINGS AND LIMITATIONS

Across our predefined four time periods of 4 yr each (covering the period 2000-2016), there was no significant change in overall survival (OS). However, metastasis-free survival (MFS) rates have improved since the second period and were excellent (>99%). Treatment-free survival rates for earlier periods showed a slightly more rapid shift to radical treatment. Over time, there was a constant proportion of 5% of men for whom anxiety was registered as the reason for treatment alteration. There was, however, also a subset of 10-15% in whom treatment was changed, for which no apparent reason was available. In a subset of men (10-15%), tumour progression was the trigger for treatment. In men who opted for radical treatment, surgery was the most common treatment modality. In those men who underwent radical treatment, 90% were free from biochemical recurrence at 5 yr after treatment.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Our study confirms that AS was a safe management option over the full duration in this large multicentre cohort with long-term follow-up, given the 84.1% OS and 99.4% MFS at 10 yr. The probability of treatment at 10 yr was 20% in men with initial low-risk tumours and 31% in men with intermediate-risk tumours. New diagnostic modalities may improve the acceptability of follow-up using individual risk assessments, while safely broadening the use of AS in higher-risk tumours.

PATIENT SUMMARY

Active surveillance (AS) has evolved into a widely applied treatment strategy for many men with prostate cancer around the world. In this report, we show the long-term safety of following AS for men with low- and intermediate-risk prostate cancer. Our study confirms AS as a safe management option for low- and intermediate-risk prostate cancer. New diagnostic modalities may improve the acceptability of follow-up using individual risk assessments, while safely broadening the use of AS in higher-risk tumours.

Use of Decipher Prostate Biopsy Test in Patients with Favorable-risk Disease Undergoing Conservative Management or Radical Prostatectomy in the Surveillance, Epidemiology, and End Results Registry

BACKGROUND AND OBJECTIVE

The extent of prostate cancer found on biopsy, as well as prostate cancer grade and genomic tests, can affect clinical decision-making. The impact of these factors on the initial management approach and subsequent patient outcomes for men with favorable-grade prostate cancer has not yet been determined on a population level. Our objective was to explore the association of Decipher 22-gene genomic classifier (GC) biopsy testing on the initial use of conservative management versus radical prostatectomy (RP) and to determine the independent effect of GC scores on RP pathologic outcomes.

METHODS

A total of 87 140 patients diagnosed with grade group 1 and 2 prostate cancer between 2016 and 2018 from the Surveillance, Epidemiology, and End Results registry data were linked to GC testing results (2576 tested and 84 564 untested with a GC). The primary endpoints of interest were receipt of conservative management or RP, pathologic upgrading (pathologic grade group 3-5), upstaging (pathologic ≥T3b), and adverse pathologic features (pathologic upgrading, upstaging, or lymph node invasion). Multivariable logistic regressions quantified the association of variables with outcomes of interest.

KEY FINDINGS AND LIMITATIONS

GC tested patients were more likely to have grade group 2 on biopsy (51% vs 46%, p < 0.001) and lower prostate-specific antigen (6.1 vs 6.3, p = 0.016). Conservative management increased from 37% to 39% and from 22% to 24% during 2016-2018 for the GC tested and untested populations, respectively. GC testing was significantly associated with increased odds of conservative management (odds ratio [OR] 2.1, 95% confidence interval [CI] 1.9-2.4, p < 0.001). The distribution of biopsy GC risk was as follows: 45% low risk, 30% intermediate risk, and 25% high risk. In adjusted analyses, higher GC (per 0.1 increment) scores (OR 1.24, 95% CI 1.17-1.31, p < 0.001) and percent positive cores (1.07, 95% CI 1.02-1.12, p = 0.009) were significantly associated with the receipt of RP. A higher GC score was significantly associated with all adverse outcomes (pathologic upgrading [OR 1.29, 95% CI 1.12-1.49, p < 0.001], upstaging [OR 1.31, 95% CI 1.05-1.62, p = 0.020], and adverse pathology [OR 1.27, 95% CI 1.12-1.45, p < 0.001]). Limitations include observational biases associated with the retrospective study design.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Men who underwent GC testing were more likely to undergo conservative management. GC testing at biopsy is prognostic of adverse pathologic outcomes in a large population-based registry.

PATIENT SUMMARY

In this population analysis of men with favorable-risk prostate cancer, those who underwent genomic testing at biopsy were more likely to undergo conservative management. Of men who initially underwent radical prostatectomy, higher genomic risk but not tumor volume was associated with adverse pathologic outcomes. The use of genomic testing at prostate biopsy improves risk stratification and may better inform treatment decisions than the use of tumor volume alone.

Long-Term Outcomes in Patients Using Protocol-Directed Active Surveillance for Prostate Cancer

Importance

Outcomes from protocol-directed active surveillance for favorable-risk prostate cancers are needed to support decision-making.

Objective

To characterize the long-term oncological outcomes of patients receiving active surveillance in a multicenter, protocol-directed cohort.

Design, Setting, and Participants

The Canary Prostate Active Surveillance Study (PASS) is a prospective cohort study initiated in 2008. A cohort of 2155 men with favorable-risk prostate cancer and no prior treatment were enrolled at 10 North American centers through August 2022.

Exposure

Active surveillance for prostate cancer.

Main Outcomes and Measures

Cumulative incidence of biopsy grade reclassification, treatment, metastasis, prostate cancer mortality, overall mortality, and recurrence after treatment in patients treated after the first or subsequent surveillance biopsies.

Results

Among 2155 patients with localized prostate cancer, the median follow-up was 7.2 years, median age was 63 years, 83% were White, 7% were Black, 90% were diagnosed with grade group 1 cancer, and median prostate-specific antigen (PSA) was 5.2 ng/mL. Ten years after diagnosis, the incidence of biopsy grade reclassification and treatment were 43% (95% CI, 40%-45%) and 49% (95% CI, 47%-52%), respectively. There were 425 and 396 patients treated after confirmatory or subsequent surveillance biopsies (median of 1.5 and 4.6 years after diagnosis, respectively) and the 5-year rates of recurrence were 11% (95% CI, 7%-15%) and 8% (95% CI, 5%-11%), respectively. Progression to metastatic cancer occurred in 21 participants and there were 3 prostate cancer-related deaths. The estimated rates of metastasis or prostate cancer-specific mortality at 10 years after diagnosis were 1.4% (95% CI, 0.7%-2%) and 0.1% (95% CI, 0%-0.4%), respectively; overall mortality in the same time period was 5.1% (95% CI, 3.8%-6.4%).

Conclusions and Relevance

In this study, 10 years after diagnosis, 49% of men remained free of progression or treatment, less than 2% developed metastatic disease, and less than 1% died of their disease. Later progression and treatment during surveillance were not associated with worse outcomes. These results demonstrate active surveillance as an effective management strategy for patients diagnosed with favorable-risk prostate cancer.

The Prostate Cancer Active Lifestyle Study (PALS): A randomized controlled trial of diet and exercise in overweight and obese men on active surveillance

BACKGROUND

Active surveillance (AS) is increasingly used to monitor patients with lower risk prostate cancer (PCa). The Prostate Cancer Active Lifestyle Study (PALS) was a randomized controlled trial to determine whether weight loss improves obesity biomarkers on the causal pathway to progression in patients with PCa on AS.

METHODS

Overweight/obese men (body mass index >25 kg/m2) diagnosed with PCa who elected AS were recruited. The intervention was a 6-month, individually delivered, structured diet and exercise program adapted from the Diabetes Prevention Program with a 7% weight loss goal from baseline. Control participants attended one session reviewing the US Dietary and Physical Activity Guidelines. The primary outcome was change in glucose regulation from baseline to the end of the 6-month intervention, which was measured by fasting plasma glucose, C-peptide, insulin, insulin-like growth factor 1, insulin-like growth factor binding protein-3, adiponectin, and homeostatic model assessment for insulin resistance.

RESULTS

Among 117 men who were randomized, 100 completed the trial. The mean percentage weight loss was 7.1% and 1.8% in the intervention and control arms, respectively (adjusted between-group mean difference, -6.0 kg; 95% confidence interval, -8.0, -4.0). Mean percentage changes from baseline for insulin, C-peptide, and homeostatic model assessment for insulin resistance in the intervention arm were -23%, -16%, and -25%, respectively, compared with +6.9%, +7.5%, and +6.4%, respectively, in the control arm (all p for intervention effects ≤ .003). No significant between-arm differences were detected for the other biomarkers.

CONCLUSIONS

Overweight/obese men with PCa undergoing AS who participated in a lifestyle-based weight loss intervention successfully met weight loss goals with this reproducible lifestyle intervention and experienced improvements in glucose-regulation biomarkers associated with PCa progression.

Can a nomogram predict apical prostate cancer pathology upgrade from fusion biopsy to final pathology? A multicenter study

BACKGROUND

This study evaluates the efficacy of a nomogram for predicting the pathology upgrade of apical prostate cancer (PCa).

METHODS

A total of 754 eligible patients were diagnosed with apical PCa through combined systematic and magnetic resonance imaging (MRI)-targeted prostate biopsy followed by radical prostatectomy (RP) were retrospectively identified from two hospitals (training: 754, internal validation: 182, internal-external validation: 148). A nomogram for the identification of apical tumors in high-risk pathology upgrades through comparing the results of biopsy and RP was established incorporating statistically significant risk factors based on univariable and multivariable logistic regression. The nomogram's performance was assessed via the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA).

RESULTS

Univariable and multivariable analysis identified age, targeted biopsy, number of targeted cores, TNM stage, and the prostate imaging-reporting and data system score as significant predictors of apical tumor pathological progression. Our nomogram, based on these variables, demonstrated ROC curves for pathology upgrade with values of 0.883 (95% CI, 0.847-0.929), 0.865 (95% CI, 0.790-0.945), and 0.840 (95% CI, 0.742-0.904) for the training, internal validation and internal-external validation cohorts respectively. Calibration curves showed good consistency between the predicted and actual outcomes. The validation groups also showed great generalizability with the calibration curves. DCA results also demonstrated excellent performance for our nomogram with positive benefit across a threshold probability range of 0-0.9 for the training and internal validation group, and 0-0.6 for the internal-external validation group.

CONCLUSION

The nomogram, integrating clinical, radiological, and pathological data, effectively predicts the risk of pathology upgrade in apical PCa tumors. It holds significant potential to guide clinicians in optimizing the surgical management of these patients.

A prospective cohort of men with localized prostate cancer on active surveillance protocol in Hong Kong, China: what did we learn?

This study aimed to report the outcomes of active surveillance (AS) in the management of low-risk prostate cancer (PCa). It recruited 87 men who were prospectively followed up according to the Prostate Cancer Research International Active Surveillance (PRIAS) protocol with local adaptation at SH Ho Urology Centre, Prince of Wales Hospital, Hong Kong, China. We investigated the predictors of disease progression and found that baseline prostate-specific antigen density (PSAD) and the presence of the highest Prostate Imaging-Reporting and Data System (PI-RADS) score 5 lesion on magnetic resonance imaging (MRI) are significantly correlated with disease progression. Moreover, men with PSAD >0.2 ng ml -2 or PI-RADS 4 or 5 lesions had significantly worse upgrading-free survival compared to those with PSAD ≤0.2 ng ml -2 and PI-RADS 2 or 3 lesions. The study concludes that AS is a safe and effective management strategy for selected patients to defer radical treatment and that most disease progression can be detected after the first repeated biopsy. The combination of PSAD >0.2 ng ml -2 and PI-RADS 4 or 5 lesions may serve as a useful predictor of early disease progression and provide a guide to optimize follow-up protocols for men in different risk groups.

Prospective comparison of restriction spectrum imaging and non-invasive biomarkers to predict upgrading on active surveillance prostate biopsy

BACKGROUND

Protocol-based active surveillance (AS) biopsies have led to poor compliance. To move to risk-based protocols, more accurate imaging biomarkers are needed to predict upgrading on AS prostate biopsy. We compared restriction spectrum imaging (RSI-MRI) generated signal maps as a biomarker to other available non-invasive biomarkers to predict upgrading or reclassification on an AS biopsy.

METHODS

We prospectively enrolled men on prostate cancer AS undergoing repeat biopsy from January 2016 to June 2019 to obtain an MRI and biomarkers to predict upgrading. Subjects underwent a prostate multiparametric MRI and a short duration, diffusion-weighted enhanced MRI called RSI to generate a restricted signal map along with evaluation of 30 biomarkers (14 clinico-epidemiologic features, 9 molecular biomarkers, and 7 radiologic-associated features). Our primary outcome was upgrading or reclassification on subsequent AS prostate biopsy. Statistical analysis included operating characteristic improvement using AUROC and AUPRC.

RESULTS

The individual biomarker with the highest area under the receiver operator characteristic curve (AUC) was RSI-MRI (AUC = 0.84; 95% CI: 0.71-0.96). The best non-imaging biomarker was prostate volume-corrected Prostate Health Index density (PHI, AUC = 0.68; 95% CI: 0.53-0.82). Non-imaging biomarkers had a negligible effect on predicting upgrading at the next biopsy but did improve predictions of overall time to progression in AS.

CONCLUSIONS

RSI-MRI, PIRADS, and PHI could improve the predictive ability to detect upgrading in AS. The strongest predictor of clinically significant prostate cancer on AS biopsy was RSI-MRI signal output.

Constructing time-invariant dynamic surveillance rules for optimal monitoring schedules

Dynamic surveillance rules (DSRs) are sequential surveillance decision rules informing monitoring schedules in clinical practice, which can adapt over time according to a patient's evolving characteristics. In many clinical applications, it is desirable to identify and implement optimal time-invariant DSRs, where the parameters indexing the decision rules are shared across different decision points. We propose a new criterion for DSRs that accounts for benefit-cost tradeoff during the course of disease surveillance. We develop two methods to estimate the time-invariant DSRs optimizing the proposed criterion, and establish asymptotic properties for the estimated parameters of biomarkers indexing the DSRs. The first approach estimates the optimal decision rules for each individual at every stage via regression modeling, and then estimates the time-invariant DSRs via a classification procedure with the estimated time-varying decision rules as the response. The second approach proceeds by optimizing a relaxation of the empirical objective, where a surrogate function is utilized to facilitate computation. Extensive simulation studies are conducted to demonstrate the superior performances of the proposed methods. The methods are further applied to the Canary Prostate Active Surveillance Study (PASS).

Zone-specific computer-aided diagnosis system aimed at characterizing ISUP ≥ 2 prostate cancers on multiparametric magnetic resonance images: evaluation in a cohort of patients on active surveillance

PURPOSE

To assess a region-of-interest-based computer-assisted diagnosis system (CAD) in characterizing aggressive prostate cancer on magnetic resonance imaging (MRI) from patients under active surveillance (AS).

METHODS

A prospective biopsy database was retrospectively searched for patients under AS who underwent MRI and subsequent biopsy at our institution. MRI lesions targeted at baseline biopsy were retrospectively delineated to calculate the CAD score that was compared to the Prostate Imaging-Reporting and Data System (PI-RADS) version 2 score assigned at baseline biopsy.

RESULTS

186 patients were selected. At baseline biopsy, 51 and 15 patients had International Society of Urological Pathology (ISUP) grade ≥ 2 and ≥ 3 cancer respectively. The CAD score had significantly higher specificity for ISUP ≥ 2 cancers (60% [95% confidence interval (CI): 51-68]) than the PI-RADS score (≥ 3 dichotomization: 24% [CI: 17-33], p = 0.0003; ≥ 4 dichotomization: 32% [CI: 24-40], p = 0.0003). It had significantly lower sensitivity than the PI-RADS ≥ 3 dichotomization (85% [CI: 74-92] versus 98% [CI: 91-100], p = 0.015) but not than the PI-RADS ≥ 4 dichotomization (94% [CI:85-98], p = 0.104). Combining CAD findings and PSA density could have avoided 47/184 (26%) baseline biopsies, while missing 3/51 (6%) ISUP 2 and no ISUP ≥ 3 cancers. Patients with baseline negative CAD findings and PSAd < 0.15 ng/mL2 who stayed on AS after baseline biopsy had a 9% (4/44) risk of being diagnosed with ISUP ≥ 2 cancer during a median follow-up of 41 months, as opposed to 24% (18/74) for the others.

CONCLUSION

The CAD could help define AS patients with low risk of aggressive cancer at baseline assessment and during subsequent follow-up.

Aggressive Prostate Cancer in Patients Treated with Active Surveillance

Active surveillance has emerged as a promising approach for managing low-risk and favorable intermediate-risk prostate cancer (PC), with the aim of minimizing overtreatment and maintaining the quality of life. However, concerns remain about identifying "aggressive prostate cancer" within the active surveillance cohort, which refers to cancers with a higher potential for progression. Previous studies are predictors of aggressive PC during active surveillance. To address this, a personalized risk-based follow-up approach that integrates clinical data, biomarkers, and genetic factors using risk calculators was proposed. This approach enables an efficient risk assessment and the early detection of disease progression, minimizes unnecessary interventions, and improves patient management and outcomes. As active surveillance indications expand, the importance of identifying aggressive PC through a personalized risk-based follow-up is expected to increase.

Active Surveillance for Prostate Cancer: Past, Current, and Future Trends

In response to the rising incidence of indolent, low-risk prostate cancer (PCa) due to increased prostate-specific antigen (PSA) screening in the 1990s, active surveillance (AS) emerged as a treatment modality to combat overtreatment by delaying or avoiding unnecessary definitive treatment and its associated morbidity. AS consists of regular monitoring of PSA levels, digital rectal exams, medical imaging, and prostate biopsies, so that definitive treatment is only offered when deemed necessary. This paper provides a narrative review of the evolution of AS since its inception and an overview of its current landscape and challenges. Although AS was initially only performed in a study setting, numerous studies have provided evidence for the safety and efficacy of AS which has led guidelines to recommend it as a treatment option for patients with low-risk PCa. For intermediate-risk disease, AS appears to be a viable option for those with favourable clinical characteristics. Over the years, the inclusion criteria, follow-up schedule and triggers for definitive treatment have evolved based on the results of various large AS cohorts. Given the burdensome nature of repeat biopsies, risk-based dynamic monitoring may further reduce overtreatment by avoiding repeat biopsies in selected patients.

The impact of life expectancy on cost-effectiveness of treatment options for clinically localized prostate cancer

BACKGROUND

Life expectancy (LE) impacts effectiveness and morbidity of prostate cancer (CaP) treatment, but its impact on cost-effectiveness is unknown. We sought to evaluate the impact of LE on the cost-effectiveness of radical prostatectomy (RP), radiation therapy (RT), and active surveillance (AS) for clinically localized disease.

METHODS

We created a Markov model to calculate incremental cost-effectiveness ratios (ICERs) for RP, RT, and AS over a 20-year time horizon from a Medicare payer perspective for low- and intermediate-risk CaP. Mortality outcomes varied by tumor risk and PCCI score, a validated proxy for LE. We performed 1,000 Monte Carlo simulations with 1-way sensitivity analyses of PCCI within each tumor risk subgroup to compare cost/quality-adjusted life years (QALYs) between treatments.

RESULTS

AS dominated RP and RT for low- and intermediate-risk disease in men with LE ≤10 years (PCCI ≥7 and ≥9, respectively). However, AS failed to dominate RP and RT for men with longer LE. For men with low-risk cancer and LE>10 years (PCCI 0-6), AS had the greatest effectiveness, but failed to dominate due to higher cost relative to RP. For men with intermediate-risk cancer with LE>10 years, AS failed to dominate due to higher cost relative to RP (PCCI 0-8) and lower effectiveness relative to RT (PCCI 0-3). The range of QALYs between RP, RT, and AS varied <13% (range: 0%-12.9%) while costs varied up to 521% (range 0.5%-521%) across PCCI scores.

CONCLUSIONS

LE strongly modulates the cost of CaP treatments. This results in AS dominating RP and RT in men with LE ≤10 years. However, in men with longer LE, AS fails to dominate primarily due to its high cumulative costs, underscoring the need for risk-adjusted AS protocols.

Mechanism-Driven and Clinically Focused Development of Botanical Foods as Multitarget Anticancer Medicine: Collective Perspectives and Insights from Preclinical Studies, IND Applications and Early-Phase Clinical Trials

Cancer progression and mortality remain challenging because of current obstacles and limitations in cancer treatment. Continuous efforts are being made to explore complementary and alternative approaches to alleviate the suffering of cancer patients. Epidemiological and nutritional studies have indicated that consuming botanical foods is linked to a lower risk of cancer incidence and/or improved cancer prognosis after diagnosis. From these observations, a variety of preclinical and clinical studies have been carried out to evaluate the potential of botanical food products as anticancer medicines. Unfortunately, many investigations have been poorly designed, and encouraging preclinical results have not been translated into clinical success. Botanical products contain a wide variety of chemicals, making them more difficult to study than traditional drugs. In this review, with the consideration of the regulatory framework of the USFDA, we share our collective experiences and lessons learned from 20 years of defining anticancer foods, focusing on the critical aspects of preclinical studies that are required for an IND application, as well as the checkpoints needed for early-phase clinical trials. We recommend a developmental pipeline that is based on mechanisms and clinical considerations.

Prostate cancer risk, screening and management in patients with germline BRCA1/2 mutations

Mutations in the BRCA1 and BRCA2 tumour suppressor genes are associated with prostate cancer risk; however, optimal screening protocols for individuals with these mutations have been a subject of debate. Several prospective studies of prostate cancer incidence and screening among BRCA1/2 mutation carriers have indicated at least a twofold to fourfold increase in prostate cancer risk among carriers of BRCA2 mutations compared with the general population. Moreover, BRCA2 mutations are associated with more aggressive, high-grade disease characteristics at diagnosis, more aggressive clinical behaviour and greater prostate cancer-specific mortality. The risk for BRCA1 mutations seems to be attenuated compared with BRCA2. Prostate-specific antigen (PSA) measurement or prostate magnetic resonance imaging (MRI) alone is an imperfect indicator of clinically significant prostate cancer; therefore, BRCA1/2 mutation carriers might benefit from refined risk stratification strategies. However, the long-term impact of prostate cancer screening is unknown, and the optimal management of BRCA1/2 carriers with prostate cancer has not been defined. Whether timely localized therapy can improve overall survival in the screened population is uncertain. Long-term results of prospective studies are awaited to confirm the optimal screening strategies and benefits of prostate cancer screening among BRCA1/2 mutation carriers, and whether these approaches ultimately have a positive impact on survival and quality of life in these patients.

Development and External Validation of the STRATified CANcer Surveillance (STRATCANS) Multivariable Model for Predicting Progression in Men with Newly Diagnosed Prostate Cancer Starting Active Surveillance

For men with newly diagnosed prostate cancer, we aimed to develop and validate a model to predict the risk of progression on active surveillance (AS), which could inform more personalised AS strategies. In total, 883 men from 3 European centres were used for model development and internal validation, and 151 men from a fourth European centre were used for external validation. Men with Cambridge Prognostic Group (CPG) 1-2 disease at diagnosis were eligible. The endpoint was progression to the composite endpoint of CPG3 disease or worse (≥CPG3). Model performance at 4 years was evaluated through discrimination (C-index), calibration plots, and decision curve analysis. The final multivariable model incorporated prostate-specific antigen (PSA), Grade Group, magnetic resonance imaging (MRI) score (Prostate Imaging Reporting & Data System (PI-RADS) or Likert), and prostate volume. Calibration and discrimination were good in both internal validation (C-index 0.742, 95% CI 0.694-0.793) and external validation (C-index 0.845, 95% CI 0.712-0.958). In decision curve analysis, the model offered net benefit compared to a 'follow-all' strategy at risk thresholds of ≥0.08 and ≥0.04 in development and external validation, respectively. In conclusion, our model demonstrated good accuracy and clinical utility in predicting the progression on AS at 4 years post-diagnosis. Men with lower risk predictions could subsequently be offered less-intense surveillance. Further external validation in larger cohorts is now required.

Improving multiparametric MR-transrectal ultrasound guided fusion prostate biopsies with hyperpolarized 13 C pyruvate metabolic imaging: A technical development study

PURPOSE

To develop techniques and establish a workflow using hyperpolarized carbon-13 (13 C) MRI and the pyruvate-to-lactate conversion rate (kPL ) biomarker to guide MR-transrectal ultrasound fusion prostate biopsies.

METHODS

The integrated multiparametric MRI (mpMRI) exam consisted of a 1-min hyperpolarized 13 C-pyruvate EPI acquisition added to a conventional prostate mpMRI exam. Maps of kPL values were calculated, uploaded to a picture archiving and communication system and targeting platform, and displayed as color overlays on T2 -weighted anatomic images. Abdominal radiologists identified 13 C research biopsy targets based on the general recommendation of focal lesions with kPL  >0.02(s-1 ), and created a targeting report for each study. Urologists conducted transrectal ultrasound-guided MR fusion biopsies, including the standard 1 H-mpMRI targets as well as 12-14 core systematic biopsies informed by the research 13 C-kPL targets. All biopsy results were included in the final pathology report and calculated toward clinical risk.

RESULTS

This study demonstrated the safety and technical feasibility of integrating hyperpolarized 13 C metabolic targeting into routine 1 H-mpMRI and transrectal ultrasound fusion biopsy workflows, evaluated via 5 men (median age 71 years, prostate-specific antigen 8.4 ng/mL, Cancer of the Prostate Risk Assessment score 2) on active surveillance undergoing integrated scan and subsequent biopsies. No adverse event was reported. Median turnaround time was less than 3 days from scan to 13 C-kPL targeting, and scan-to-biopsy time was 2 weeks. Median number of 13 C targets was 1 (range: 1-2) per patient, measuring 1.0 cm (range: 0.6-1.9) in diameter, with a median kPL of 0.0319 s-1 (range: 0.0198-0.0410).

CONCLUSIONS

This proof-of-concept work demonstrated the safety and feasibility of integrating hyperpolarized 13 C MR biomarkers to the standard mpMRI workflow to guide MR-transrectal ultrasound fusion biopsies.

Impact of Prostate Health Index Results for Prediction of Biopsy Grade Reclassification During Active Surveillance

PURPOSE

We assessed whether Prostate Health Index results improve prediction of grade reclassification for men on active surveillance.

METHODS AND MATERIALS

We identified men in Canary Prostate Active Surveillance Study with Grade Group 1 cancer. Outcome was grade reclassification to Grade Group 2+ cancer. We considered decision rules to maximize specificity with sensitivity set at 95%. We derived rules based on clinical data (R1) vs clinical data+Prostate Health Index (R3). We considered an "or"-logic rule combining clinical score and Prostate Health Index (R4), and a "2-step" rule using clinical data followed by risk stratification based on Prostate Health Index (R2). Rules were applied to a validation set, where values of R2-R4 vs R1 for specificity and sensitivity were evaluated.

RESULTS

We included 1,532 biopsies (n = 610 discovery; n = 922 validation) among 1,142 men. Grade reclassification was seen in 27% of biopsies (23% discovery, 29% validation). Among the discovery set, at 95% sensitivity, R2 yielded highest specificity at 27% vs 17% for R1. In the validation set, R3 had best performance vs R1 with Δsensitivity = -4% and Δspecificity = +6%. There was slight improvement for R3 vs R1 for confirmatory biopsy (AUC 0.745 vs R1 0.724, ΔAUC 0.021, 95% CI 0.002-0.041) but not for subsequent biopsies (ΔAUC -0.012, 95% CI -0.031-0.006). R3 did not have better discrimination vs R1 among the biopsy cohort overall (ΔAUC 0.007, 95% CI -0.007-0.020).

CONCLUSIONS

Among active surveillance patients, using Prostate Health Index with clinical data modestly improved prediction of grade reclassification on confirmatory biopsy and did not improve prediction on subsequent biopsies.

Developing machine learning algorithms for dynamic estimation of progression during active surveillance for prostate cancer

Active Surveillance (AS) for prostate cancer is a management option that continually monitors early disease and considers intervention if progression occurs. A robust method to incorporate “live” updates of progression risk during follow-up has hitherto been lacking. To address this, we developed a deep learning-based individualised longitudinal survival model using Dynamic-DeepHit-Lite (DDHL) that learns data-driven distribution of time-to-event outcomes. Further refining outputs, we used a reinforcement learning approach (Actor-Critic) for temporal predictive clustering (AC-TPC) to discover groups with similar time-to-event outcomes to support clinical utility. We applied these methods to data from 585 men on AS with longitudinal and comprehensive follow-up (median 4.4 years). Time-dependent C-indices and Brier scores were calculated and compared to Cox regression and landmarking methods. Both Cox and DDHL models including only baseline variables showed comparable C-indices but the DDHL model performance improved with additional follow-up data. With 3 years of data collection and 3 years follow-up the DDHL model had a C-index of 0.79 (±0.11) compared to 0.70 (±0.15) for landmarking Cox and 0.67 (±0.09) for baseline Cox only. Model calibration was good across all models tested. The AC-TPC method further discovered 4 distinct outcome-related temporal clusters with distinct progression trajectories. Those in the lowest risk cluster had negligible progression risk while those in the highest cluster had a 50% risk of progression by 5 years. In summary, we report a novel machine learning approach to inform personalised follow-up during active surveillance which improves predictive power with increasing data input over time.

Active surveillance in favorable intermediate risk prostate cancer: outstanding questions and controversies

PURPOSE OF REVIEW

Active surveillance has become the preferred management strategy for patients with low risk prostate cancer, but it is unclear if active surveillance can be safely extended to favorable intermediate risk (FIR) prostate cancer patients. Furthermore, defining a favorable intermediate risk prostate cancer population safe for active surveillance remains elusive due to paucity of high-level data in this population. This article serves to review relevant data, particularly the safety of active surveillance in grade group 2 patients, and what tools are available to aid in selecting a favorable subset of intermediate risk patients.

RECENT FINDINGS

Active surveillance studies with long-term data appear to report worsened survival outcomes in intermediate risk patients when compared to those undergoing definitive treatment, but there exists a subset of intermediate risk patients with nearly equivalent outcomes to low risk patients on active surveillance. Tools such as percentage and total length of Gleason pattern 4, tumor volume, prostate specific antigen density, magnetic resonance imaging, and genomic modifiers may help to select a favorable subset of intermediate risk prostate cancer appropriate for active surveillance.

SUMMARY

Active surveillance is a viable strategy in select patients with low volume group grade 2 (GG2) prostate cancer. Prospective and retrospective data in the FIR population appear to be mostly favorable in regards to survival outcomes, but there exists some heterogeneity with respect to long-term outcomes in this patient population.

Impact of Decipher Biopsy testing on clinical outcomes in localized prostate cancer in a prospective statewide collaborative

BACKGROUND

Decipher Biopsy is a commercially available gene expression classifier used in risk stratification of newly diagnosed prostate cancer (PCa). Currently, there are no prospective data evaluating its clinical utility. We seek to assess the clinical utility of Decipher Biopsy in localized PCa patients.

METHODS

A multi-institutional study of 855 men who underwent Decipher Biopsy testing between February 2015 and October 2019. All patients were tracked through the prospective Michigan Urological Surgery Improvement Collaborative and linked to the Decipher Genomics Resource Information Database (GRID^®; NCT02609269). Patient matching was performed by an independent third-party (ArborMetrix Inc.) using two or more unique identifiers. Cumulative incidence curves for time to treatment (TTT) and time to failure (TTF) were constructed using Kaplan-Meier estimates. Multivariable Cox proportional hazard models were used to evaluate the independent association of high-risk Decipher scores with the conversion from AS to radical therapy and treatment failure (biochemical failure or receipt of salvage therapy).

RESULTS AND LIMITATIONS

Eight hundred fifty-five patients underwent Decipher Biopsy testing during the study period. Of the 855 men, 264 proceeded to AS (31%), and 454 (53%) received radical therapy. In men electing AS, after adjusting for NCCN risk group, age, PSA, prostate volume, body mass index, and percent positive cores, a high-risk Decipher score was independently associated with shorter TTT (HR 2.51, 95% CI 1.52-4.13 p < 0.001). Similarly, in patients that underwent radical therapy, a high-risk Decipher score was independently associated with TTF (HR 2.98, 95% CI 1.22-7.29, p = 0.01) on multivariable analysis. Follow-up time was a limitation.

CONCLUSION

In a prospective statewide registry, high-risk Decipher Biopsy score was strongly and independently associated with conversion from AS to definitive treatment and treatment failure. These real-world data support the clinical utility of Decipher Biopsy. An ongoing phase 3 randomized trial (NCT04396808) will provide level 1 evidence of the clinical impact of Decipher biopsy testing.

A machine learning approach to predict progression on active surveillance for prostate cancer

PURPOSE

Robust prediction of progression on active surveillance (AS) for prostate cancer can allow for risk-adapted protocols. To date, models predicting progression on AS have invariably used traditional statistical approaches. We sought to evaluate whether a machine learning (ML) approach could improve prediction of progression on AS.

PATIENTS AND METHODS

We performed a retrospective cohort study of patients diagnosed with very-low or low-risk prostate cancer between 1997 and 2016 and managed with AS at our institution. In the training set, we trained a traditional logistic regression (T-LR) classifier, and alternate ML classifiers (support vector machine, random forest, a fully connected artificial neural network, and ML-LR) to predict grade-progression. We evaluated model performance in the test set. The primary performance metric was the F1 score.

RESULTS

Our cohort included 790 patients. With a median follow-up of 6.29 years, 234 developed grade-progression. In descending order, the F1 scores were: support vector machine 0.586 (95% CI 0.579 - 0.591), ML-LR 0.522 (95% CI 0.513 - 0.526), artificial neural network 0.392 (95% CI 0.379 - 0.396), random forest 0.376 (95% CI 0.364 - 0.380), and T-LR 0.182 (95% CI 0.151 - 0.185). All alternate ML models had a significantly higher F1 score than the T-LR model (all p <0.001).

CONCLUSION

In our study, ML methods significantly outperformed T-LR in predicting progression on AS for prostate cancer. While our specific models require further validation, we anticipate that a ML approach will help produce robust prediction models that will facilitate individualized risk-stratification in prostate cancer AS.

Genetic Factors Associated with Prostate Cancer Conversion from Active Surveillance to Treatment

Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for prostate cancer, many men on AS eventually convert to active treatment. PC is one of the most heritable cancers, and genetic factors that predispose to aggressive tumors may help distinguish men who are more likely to discontinue AS. To investigate this, we undertook a multi-institutional genome-wide association study (GWAS) of 5,222 PC patients and 1,139 other patients from replication cohorts, all of whom initially elected AS and were followed over time for the potential outcome of conversion from AS to active treatment. In the GWAS we detected 18 variants associated with conversion, 15 of which were not previously associated with PC risk. With a transcriptome-wide association study (TWAS), we found two genes associated with conversion (MAST3, p = 6.9×10-7 and GAB2, p = 2.0×10-6). Moreover, increasing values of a previously validated 269-variant genetic risk score (GRS) for PC was positively associated with conversion (e.g., comparing the highest to the two middle deciles gave a hazard ratio [HR] = 1.13; 95% Confidence Interval [CI]= 0.94-1.36); whereas, decreasing values of a 36-variant GRS for prostate-specific antigen (PSA) levels were positively associated with conversion (e.g., comparing the lowest to the two middle deciles gave a HR = 1.25; 95% CI, 1.04-1.50). These results suggest that germline genetics may help inform and individualize the decision of AS-or the intensity of monitoring on AS-versus treatment for the initial management of patients with low-risk PC.

The utility of prostate MRI within active surveillance: description of the evidence

Purpose

We present an overview of the literature regarding the use of MRI in active surveillance of prostate cancer.

Methods

Both MEDLINE^® and Cochrane Library were queried up to May 2020 for studies of men on active surveillance with MRI and later confirmatory biopsy. The terms studied were ‘prostate cancer’ as the anchor followed by two of the following: active surveillance, surveillance, active monitoring, MRI, NMR, magnetic resonance imaging,  MRI, and multiparametric MRI. Studies were excluded if pathologic reclassification (GG1 →  ≥ GG2) and PI-RADS or equivalent was not reported.

Results

Within active surveillance, baseline MRI is effective for identifying clinically significant prostate cancer and thus associated with fewer reclassification events. A positive initial MRI (≥ PI-RADS 3) with GG1 identified at biopsy has a positive predictive value (PPV) of 35–40% for reclassification by 3 years. MRI possessed a stronger negative predictive value, with a negative MRI (≤ PI-RADS 2) yielding a negative predictive value of up to 85% at 3 years. Surveillance MRI, obtained after initial biopsy, yielded a PPV of 11–65% and NPV of 85–95% for reclassification.

Conclusion

MRI is useful for initial risk stratification of prostate cancer in men on active surveillance, especially if MRI is negative when imaging is obtained during surveillance. While useful, MRI cannot replace biopsy and further research is necessary to fully integrate MRI into active surveillance.

The Impact of Body Mass Index on Freedom From Therapeutic Intervention and Quality of Life in Active Surveillance Prostate Cancer Patients

OBJECTIVE

The objective of this study was to evaluate the impact of body mass index (BMI) on overall survival, freedom from distant metastases, rates of therapeutic intervention (TI), and quality of life (QOL) in active surveillance (AS) prostate cancer patients.

MATERIALS AND METHODS

Three hundred forty consecutive, prospectively evaluated AS patients underwent a staging transperineal template-guided mapping biopsy before AS enrollment and were stratified by BMI (<25, 25 to 29.9, 30 to 34.9, and >35 kg/m2). Evaluated outcomes included overall survival, freedom from distant metastases, TI, QOL to include urinary, bowel, sexual function and depression and serial postvoid residual urine measurements. The relationship between BMI and anterior prostate cancer distribution was evaluated. Repeat biopsy was based on prostate specific antigen kinetics, abnormal digital rectal examination and patient preference.

RESULTS

Of the 340 patients, 323 (95%) were Gleason 3+3 and 17 patients (5.0%) were Gleason 3+4. The median follow-up was 5.2 years (range: 1 to 14 y). At 10 years, TI was instituted in 4.7%, 2.2%, 9.5%, and 25.0% of patients in BMI cohorts <25, 25 to 29.9, 30 to 34.9, and ≥35 (P=0.075). No patient has developed distant metastases. The median time to TI was 4.86 years. In multivariate analysis, TI was most closely predicted by prostate specific antigen density (P=0.071). At 8 years, no statistical differences in urinary function, bowel function, depression or postvoid residual were noted. However, a trend for erectile dysfunction was identified (P=0.106).

CONCLUSION

At 10 years, BMI did not statistically predict for TI, geographic distribution of prostate cancer or QOL parameters.

Reliability of Serial Prostate Magnetic Resonance Imaging to Detect Prostate Cancer Progression During Active Surveillance: A Systematic Review and Meta-analysis

CONTEXT

Although magnetic resonance imaging (MRI) is broadly implemented into active surveillance (AS) protocols, data on the reliability of serial MRI in order to help guide follow-up biopsy are inconclusive.

OBJECTIVE

To assess the diagnostic estimates of serial prostate MRI for prostate cancer (PCa) progression during AS.

EVIDENCE ACQUISITION

We systematically searched PubMed, Scopus, and Web of Science databases to select studies analyzing the association between changes on serial prostate MRI and PCa progression during AS. We included studies that provided data for MRI progression, which allowed us to calculate diagnostic estimates. We compared Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) accuracy with institution-specific definitions.

EVIDENCE SYNTHESIS

We included 15 studies with 2240 patients. Six used PRECISE criteria and nine institution-specific definitions of MRI progression. The pooled PCa progression rate, which included histological progression to Gleason grade ≥2, was 27%. The pooled sensitivity and specificity were 0.59 (95% confidence interval [CI] 0.44-0.73) and 0.75 (95% CI 0.66-0.84) respectively. There was significant heterogeneity between included studies. Depending on PCa progression prevalence, the pooled negative predictive value for serial prostate MRI ranged from 0.81 (95% CI 0.73-0.88) to 0.88 (95% CI 0.83-0.93) and the pooled positive predictive value ranged from 0.37 (95% CI 0.24-0.54) to 0.50 (95% CI 0.36-0.66). There were no significant differences in the pooled sensitivity (p = 0.37) and specificity (p = 0.74) of PRECISE and institution-specific schemes.

CONCLUSIONS

Serial MRI still should not be considered a sole factor for excluding PCa progression during AS, and changes on MRI are not accurate enough to indicate PCa progression. There was a nonsignificant trend toward improved diagnostic estimates of PRECISE recommendations. These findings highlight the need to further define the optimal triggers and timing of biopsy during AS, as well as the need for optimizing the quality, interpretation, and reporting of serial prostate MRI.

PATIENT SUMMARY

Our study suggests that serial prostate magnetic resonance imaging (MRI) alone in patients on active surveillance is not accurate enough to reliably rule out or rule in prostate cancer progression. Other clinical factors and biomarkers along with serial MRI are required to safely tailor the intensity of follow-up biopsies.

Active surveillance for prostate cancer: selection criteria, guidelines, and outcomes

INTRODUCTION

Active surveillance (AS) has been widely adopted for the management of men with low-risk prostate cancer. However, there is still a lack of consensus surrounding the optimal approach for monitoring men in AS protocols. While conservative management aims to reduce the burden of invasive testing without compromising oncological safety, inadequate assessment can result in misclassification and unintended over- or undertreatment, leading to increased patient morbidity, cost, and undue risk. No universally accepted AS protocol exists, although numerous strategies have been developed in an attempt to optimize the management of clinically localized disease. Variability in selection criteria, reclassification, triggers for definitive treatment, and follow-up exists between guidelines and institutions for AS. In this review, we summarize the landscape of AS by providing an overview of the existing AS protocols, guidelines, and their published outcomes.

METHODS

A comprehensive electronic search was performed to identify representative studies and guidelines pertaining to AS selection criteria and outcomes.

CONCLUSION

While AS is a safe and increasingly utilized treatment modality for lower-risk forms of PCa, ongoing research is needed to optimize patient selection as well as surveillance protocols along with improved implementation across practices. Further, assessment of companion risk assessment tools, such as mpMRI and tissue-based biomarkers, is also needed and will require rigorous prospective study.

A review on the role of tissue-based molecular biomarkers for active surveillance

PURPOSE

Over the last decade, we have seen the emergence of tissue-based genomic prognostic markers that can be used for decision-making regarding the need for treatment. This review provides an up-to-date summary of the relevant literature surrounding these markers with a discussion of the relevant strength and limitations.

METHODS

We performed a literature search of tissue-based genomic prognostic markers and selected those that were currently available for clinical use. We selected the following markers for further review: Decipher (Decipher Bioscience), Polaris (Myriad), Genome Prostate Score (Oncotype Dx), and Promark. We selected the initial validation study for each marker along with other validation studies in independent cohorts. Furthermore, we selected available clinical utility studies or studies combining multi parametric MRI.

RESULTS

In this article, we provide an in-depth review of four commercially available biomarkers and discuss the current literature surrounding these markers, including the benefits and limitations of their use. We found that each of these markers has evidence supporting their role as an independent predictor of relevant prostate cancer endpoints, which can be helpful for clinical decision-making. However, issues related to heterogeneity and a lack of prospective randomized studies supporting their utility are limitations. Evidence appears to suggest that MRI and genomic risk assessment maybe complementary.

CONCLUSION

Although these markers can help in improved risk stratification of patients eligible for AS, more prospective studies with head to head comparison between markers are needed to elucidate the true potential of these markers in AS.

Multiple Tissue Biomarkers Independently and Additively Predict Prostate Cancer Pathology Outcomes

BACKGROUND

Distinguishing indolent from aggressive prostate cancer remains a key challenge for decision making regarding prostate cancer management. A growing number of biomarkers are now available to help address this need, but these have rarely been examined together in the same patients to determine their potentially additive value.

OBJECTIVE

To determine whether two previously validated plasma markers (transforming growth factor β1 [TGFβ1] and interleukin-6 soluble receptor [IL6-SR]) and two validated tissue scores (the Genomic Evaluators of Metastatic Prostate Cancer [GEMCaP] and cell cycle progression [CCP] scores) can improve on clinical parameters in predicting adverse pathology after prostatectomy, and how much they vary within tumors with heterogeneous Gleason grade.

DESIGN, SETTING, AND PARTICIPANTS

A case-control study was conducted among men with low-risk cancers defined by biopsy grade group (GG) 1, prostate-specific antigen (PSA) ≤10 ng/mL, and clinical stage ≤ T2 who underwent immediate prostatectomy. We collected paraffin-fixed prostatectomy tissue and presurgical plasma samples from 381 cases from the University of California, San Francisco, and 260 cases from the University of Washington.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Pathologic outcomes were minor upgrading/upstaging (GG 2 or pT3a) or major upgrading/upstaging (GG ≥ 3 or ≥ pT3b), and multinomial regression was performed to determine putative markers' ability to predict these outcomes, controlling for PSA, percent of positive biopsy cores, age, and clinical site. For upgraded tumors, a secondary analysis of the GEMCaP and CCP scores from the higher-grade tumor was also performed to evaluate for heterogeneity.

RESULTS AND LIMITATIONS

Overall, 357 men had no upgrading/upstaging event at prostatectomy, 236 had a minor event, and 67 had a major event. Neither TGFβ1 nor IL6-SR was statistically significantly associated with any upgrading/upstaging. On the contrary, both the CCP and the GEMCaP score obtained from Gleason pattern 3 tissue were directly associated with minor and major upgrading/upstaging on univariate analysis. The two scores correlated with each other, but weakly. On multinomial analysis including both scores in the model, the CCP score predicted minor upgrading/upstaging (odds ratio [OR] 1.62, 95% confidence interval [CI] 1.05-2.49) and major upgrading/upstaging (OR 2.26, 95% CI 1.05-4.90), p =  0.04), and the GEMCaP score also predicted minor upgrading/upstaging (OR 1.05, 95% CI 1.03-1.08) and major upgrading/upstaging (OR 1.07, 95% CI 1.04-1.11), p <  0.01). The other clinical parameters were not significant in this model. Among upgraded tumors including both Gleason patterns 3 and 4, both the GEMCaP and the CCP score tended to be higher from the higher-grade tumor. The main limitation was the use of virtual biopsies from prostatectomy tissue as surrogates for prostate biopsies.

CONCLUSIONS

Biomarker signatures based on analyses of both DNA and RNA significantly and independently predict adverse pathology among men with clinically low-risk prostate cancer undergoing prostatectomy.

PATIENT SUMMARY

Validated biomarker scores derived from both prostate cancer DNA and prostate cancer RNA can add independent information to help predict outcomes after prostatectomy.