Prediction of the Pathologic Gleason Score to Inform a Personalized Management Program for Prostate Cancer

Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) Magnetic Resonance Imaging Scoring to Predict Clinical Outcomes in Active Surveillance for Grade Group 1 Prostate Cancer

OBJECTIVE

To determine whether radiological change on serial multiparametric magnetic resonance imaging scored using the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) Scoring system predicts grade reclassification (GR) at surveillance biopsy in men on active surveillance (AS) with Grade Group 1 (GG1) prostate cancer (PCa).

METHODS

We retrospectively reviewed records of 255 men with low-risk PCa on AS with magnetic resonance imaging (MRI)-informed diagnostic and confirmatory biopsies and studied the subset who had surveillance biopsies (n = 163) within 6months of an interval MRI.

RESULTS

We studied 309 PRECISE scores in 255 men. 14% demonstrated radiological progression (PRECISE 4-5) on interval MRI performed within 24months, compared to 34% of those whose interval MRI was performed at a >3-year interval (P = .002). 28% (46/163) of men undergoing surveillance biopsy experienced GR to ≥ GG2 PCa. There was no significant increase in the rate of GR with increasing PRECISE score (PRECISE 1-2: 24%, PRECISE 3: 23%, PRECISE 4-5: 38%; P = .11). There was a significant increase in the rate of GR with increasing PI-RADS score (P < .05). On multivariable analysis, a PI-RADS score of 4-5 was significantly associated with GR compared to men who had a highest PI-RADS ≤3 (OR=1.98 [95% CI: 1.45-3.09, P = .01]).

CONCLUSION

In a low-risk AS cohort with limited follow-up, a patient's highest PI-RADS rather than their PRECISE score on interval MRI was predictive of GR on surveillance biopsy.

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.

CRISPR screening reveals gleason score and castration resistance related oncodriver ring finger protein 19 A (RNF19A) in prostate cancer

Prostate cancer (PCa) is one of the most lethal causes of cancer-related death in male. It is characterized by chromosomal instability and disturbed signaling transduction. E3 ubiquitin ligases are well-recognized as mediators leading to genomic alterations and malignant phenotypes. There is a lack of systematic study on novel oncodrivers with genomic and clinical significance in PCa. In this study we used clustered regularly interspaced short palindromic repeats (CRISPR) system to screen 656 E3 ubiquitin ligases as oncodrivers or tumor repressors in PCa cells. We identified 51 significantly changed genes, and conducted genomic and clinical analysis on these genes. It was found that the Ring Finger Protein 19 A (RNF19A) was a novel oncodriver in PCa. RNF19A was frequently amplified and highly expressed in PCa and other cancer types. Clinically, higher RNF19A expression correlated with advanced Gleason Score and predicted castration resistance. Mechanistically, transcriptomics, quantitative and ubiquitination proteomic analysis showed that RNF19A ubiquitylated Thyroid Hormone Receptor Interactor 13 (TRIP13) and was transcriptionally activated by androgen receptor (AR) and Hypoxia Inducible Factor 1 Subunit Alpha (HIF1A). This study uncovers the genomic and clinical significance of a oncodriver RNF19A in PCa. The results of this study indicate that targeting AR/HIF1A-RNF19A-TRIP13 signaling axis could be an alternative option for PCa diagnosis and therapy.

Personalised biopsy schedules based on risk of Gleason upgrading for patients with low-risk prostate cancer on active surveillance

OBJECTIVE

To develop a model and methodology for predicting the risk of Gleason upgrading in patients with prostate cancer on active surveillance (AS) and using the predicted risks to create risk-based personalised biopsy schedules as an alternative to one-size-fits-all schedules (e.g. annually). Furthermore, to assist patients and doctors in making shared decisions on biopsy schedules, by providing them quantitative estimates of the burden and benefit of opting for personalised vs any other schedule in AS. Lastly, to externally validate our model and implement it along with personalised schedules in a ready to use web-application.

PATIENTS AND METHODS

Repeat prostate-specific antigen (PSA) measurements, timing and results of previous biopsies, and age at baseline from the world's largest AS study, Prostate Cancer Research International Active Surveillance (PRIAS; 7813 patients, 1134 experienced upgrading). We fitted a Bayesian joint model for time-to-event and longitudinal data to this dataset. We then validated our model externally in the largest six AS cohorts of the Movember Foundation's third Global Action Plan (GAP3) database (>20 000 patients, 27 centres worldwide). Using the model predicted upgrading risks; we scheduled biopsies whenever a patient's upgrading risk was above a certain threshold. To assist patients/doctors in the choice of this threshold, and to compare the resulting personalised schedule with currently practiced schedules, along with the timing and the total number of biopsies (burden) planned, for each schedule we provided them with the time delay expected in detecting upgrading (shorter is better).

RESULTS

The cause-specific cumulative upgrading risk at the 5-year follow-up was 35% in PRIAS, and at most 50% in the GAP3 cohorts. In the PRIAS-based model, PSA velocity was a stronger predictor of upgrading (hazard ratio [HR] 2.47, 95% confidence interval [CI] 1.93-2.99) than the PSA level (HR 0.99, 95% CI 0.89-1.11). Our model had a moderate area under the receiver operating characteristic curve (0.6-0.7) in the validation cohorts. The prediction error was moderate (0.1-0.2) in theGAP3 cohorts where the impact of the PSA level and velocity on upgrading risk was similar to PRIAS, but large (0.2-0.3) otherwise. Our model required re-calibration of baseline upgrading risk in the validation cohorts. We implemented the validated models and the methodology for personalised schedules in a web-application (http://tiny.cc/biopsy).

CONCLUSIONS

We successfully developed and validated a model for predicting upgrading risk, and providing risk-based personalised biopsy decisions in AS of prostate cancer. Personalised prostate biopsies are a novel alternative to fixed one-size-fits-all schedules, which may help to reduce unnecessary prostate biopsies, while maintaining cancer control. The model and schedules made available via a web-application enable shared decision-making on biopsy schedules by comparing fixed and personalised schedules on total biopsies and expected time delay in detecting upgrading.

Evaluation of Apparent Diffusion Coefficient as a Predictor of Grade Reclassification in Men on Active Surveillance for Prostate Cancer

OBJECTIVE

To evaluate the association between apparent diffusion coefficient (ADC) on initial multiparametric MRI (mpMRI) and biopsy grade reclassification (GR) to grade group (GG) ≥2 prostate cancer (CaP) in men on active surveillance (AS) with GG 1 CaP.

METHODS

We retrospectively identified 242 AS patients with reported ADC values on their initial mpMRI. ADC value from the index lesion was assessed as an independent predictor of GR using a Cox model. To ease clinical interpretation, we used a log-rank test to establish an ADC cutoff of 1128 × 10^-6 mm²/s for Kaplan-Meier analysis.

RESULTS

Of the 242 men, 70 underwent GR following initial mpMRI, of which 26 (37%) had GR at the index lesion. There was no significant difference in the median interval between biopsies for men with and without GR (P >.9). Men with GR had significantly lower median ADC than those without GR (P = .01). In multivariable analysis adjusting for age, prostate-specific antigen density, and National Comprehensive Cancer Network risk group, a 100-unit decrease in ADC was associated with a 12% increase in the risk of GR (HR = 1.12, 95% CI: 1.01-1.22, P = .03). Two- and 4-year rates of freedom from GR were significantly lower for men with ADC <1128 × 10^-6 mm²/s vs ADC ≥1128 × 10^-6 mm²/s (62% and 42% vs 78% and 68%, respectively; P <.001).

CONCLUSION

For AS patients, lower ADC on initial mpMRI index lesion is associated with increased risk of GR to GG ≥2 CaP and would be a useful component of multivariable risk prediction tools.

Personalized Decision Making for Biopsies in Prostate Cancer Active Surveillance Programs

Background. Low-risk prostate cancer patients enrolled in active surveillance programs commonly undergo biopsies for examination of cancer progression. Biopsies are conducted as per a fixed and frequent schedule (e.g., annual biopsies). Since biopsies are burdensome, patients do not always comply with the schedule, which increases the risk of delayed detection of cancer progression. Objective. Our aim is to better balance the number of biopsies (burden) and the delay in detection of cancer progression (less is beneficial) by personalizing the decision of conducting biopsies. Data Sources. We used patient data of the world’s largest active surveillance program (Prostate Cancer Research International Active Surveillance; PRIAS). It enrolled 5270 patients, had 866 cancer progressions, and an average of 9 prostate-specific antigen (PSA) and 5 digital rectal examination (DRE) measurements per patient. Methods. Using joint models for time-to-event and longitudinal data, we model the historical DRE and PSA measurements and biopsy results of a patient at each follow-up visit. This results in a visit and patient-specific cumulative risk of cancer progression. If this risk is above a certain threshold, we schedule a biopsy. We compare this personalized approach with the currently practiced biopsy schedules via an extensive and realistic simulation study, based on a replica of the patients from the PRIAS program. Results. The personalized approach saved a median of 6 biopsies (median: 4, interquartile range [IQR]: 2–5) compared with the annual schedule (median: 10, IQR: 3–10). However, the delay in detection of progression (years) is similar for the personalized (median: 0.7, IQR: 0.3–1.0) and the annual schedule (median: 0.5, IQR: 0.3–0.8). Conclusions. We conclude that personalized schedules provide substantially better balance in the number of biopsies per detected progression for men with low-risk prostate cancer.

Challenges and Opportunities for Using Big Health Care Data to Advance Medical Science and Public Health

Methodological advancements in epidemiology, biostatistics, and data science have strengthened the research world's ability to use data captured from electronic health records (EHRs) to address pressing medical questions, but gaps remain. We describe methods investments that are needed to curate EHR data toward research quality and to integrate complementary data sources when EHR data alone are insufficient for research goals. We highlight new methods and directions for improving the integrity of medical evidence generated from pragmatic trials, observational studies, and predictive modeling. We also discuss needed methods contributions to further ease data sharing across multisite EHR data networks. Throughout, we identify opportunities for training and for bolstering collaboration among subject matter experts, methodologists, practicing clinicians, and health system leaders to help ensure that methods problems are identified and resulting advances are translated into mainstream research practice more quickly.

ESTIMATING AND COMPARING CANCER PROGRESSION RISKS UNDER VARYING SURVEILLANCE PROTOCOLS

Outcomes after cancer diagnosis and treatment are often observed at discrete times via doctor-patient encounters or specialized diagnostic examinations. Despite their ubiquity as endpoints in cancer studies, such outcomes pose challenges for analysis. In particular, comparisons between studies or patient populations with different surveillance schema may be confounded by differences in visit frequencies. We present a statistical framework based on multistate and hidden Markov models that represents events on a continuous time scale given data with discrete observation times. To demonstrate this framework, we consider the problem of comparing risks of prostate cancer progression across multiple active surveillance cohorts with different surveillance frequencies. We show that the different surveillance schedules partially explain observed differences in the progression risks between cohorts. Our application permits the conclusion that differences in underlying cancer progression risks across cohorts persist after accounting for different surveillance frequencies.

Clinical Evaluation of an Individualized Risk Prediction Tool for Men on Active Surveillance for Prostate Cancer

OBJECTIVE

To determine whether providing individualized predictions of health outcomes to men on active surveillance (AS) alleviates cancer-related anxiety and improves risk understanding.

MATERIALS AND METHODS

We consecutively recruited men from our large, institutional AS program before (n = 36) and after (n = 31) implementation of a risk prediction tool. Men in both groups were surveyed before and after their regular visits to assess their perceived cancer control, biopsy-specific anxiety, and burden from cancer-related information. We compared pre-/post-visit differences between men who were and were not shown the tool using two-sample t-tests. Satisfaction with and understanding of the predictions were elicited from men in the intervention period.

RESULTS

Men reported a relatively high level of cancer control at baseline. Men who were not shown the tool saw a 6.3 point increase (scaled from 0 to 100) in their perceived cancer control from before to after their visit whereas men who were shown the tool saw a 12.8 point increase, indicating a statistically significant difference between groups (p = .04). Biopsy-specific anxiety and burden from cancer information were not significantly different between groups. Men were satisfied with the tool and demonstrated moderate understanding.

CONCLUSION

Providing individualized predictions to men on AS helps them better understand their cancer risk and should be considered at other clinical sites.

Personalized schedules for surveillance of low-risk prostate cancer patients

Low‐risk prostate cancer patients enrolled in active surveillance (AS) programs commonly undergo biopsies on a frequent basis for examination of cancer progression. AS programs employ a fixed schedule of biopsies for all patients. Such fixed and frequent schedules may schedule unnecessary biopsies. Since biopsies are burdensome, patients do not always comply with the schedule, which increases the risk of delayed detection of cancer progression. Motivated by the world's largest AS program, Prostate Cancer Research International Active Surveillance (PRIAS), we present personalized schedules for biopsies to counter these problems. Using joint models for time‐to‐event and longitudinal data, our methods combine information from historical prostate‐specific antigen levels and repeat biopsy results of a patient, to schedule the next biopsy. We also present methods to compare personalized schedules with existing biopsy schedules.

PSMA expression: a potential ally for the pathologist in prostate cancer diagnosis

Prostate cancer (PCa) patients are risk-stratified on the basis of clinical stage and PSA level at diagnosis and the Gleason Score (GS) in prostate biopsy. However, these parameters are not completely accurate in discriminating between high- and low-risk disease, creating a need for a reliable marker to determine aggressiveness. Prostate-specific membrane antigen (PSMA) appears to fulfill this need. We analyzed 79 prostate biopsies and 28 prostatectomies to assess whether PSMA expression detected by immunohistochemistry is related to GS. PSMA expression was correlated with GS in both sample types (biopsies, P < 0.0001 and prostatectomy samples, P = 0.007). We observed lower PSMA expression in Gleason pattern 3 than Gleason pattern 4, suggesting that this biomarker could be useful to distinguish between these entities (p < 0.0001). The best cut-off value of 45% immunopositivity was determined by receiver operating characteristic (ROC) curve analysis. In Gleason pattern 3 vs. Gleason pattern 4 and 5, PSMA sensitivity was 84.1% (95% CI 76.5%-91.7%) and specificity was 95.2% (95% CI 90.6%-99.8%), with an area under the curve of 93.1 (95% CI 88.8-97.4). Our results suggest that PSMA represents a potential ally for the pathologist in the diagnostic work-up of PCa to overcome long-standing morphological classification limits.

Active surveillance: a review of risk-based, dynamic monitoring

Active surveillance (AS) is an important treatment modality aiming to reduce the overtreatment of patients with prostate cancer (PCa) who have a low risk of disease reclassification. After enrolling in AS patients are actively monitored using different diagnostic tests (e.g., prostate specific-antigen, digital rectal exams (DREs), medical imaging, and prostate biopsies). Biopsy is the most burdensome test. We aimed to review schedules for monitoring men on AS. We compare fixed versus risk based dynamic monitoring, where biopsies are scheduled during follow-up based on dynamic risk predictions. Several prediction models and scheduling techniques have been published. All proposed risk prediction models need further external validation. We conclude that risk based, dynamic monitoring is a promising new strategy to further reduce overtreatment in PCa patients.

Prognostic Significance of a Negative Confirmatory Biopsy on Reclassification Among Men on Active Surveillance

OBJECTIVE

To examine the association between absence of disease on confirmatory biopsy and risk of pathologic reclassification in men on active surveillance (AS).

MATERIALS AND METHODS

Men with grade groups 1 and 2 disease on AS between 2002 and 2015 were identified who received a confirmatory biopsy within 1 year of diagnosis and ≥3 biopsies overall. The primary outcomes were pathologic reclassification by grade (any increase in primary Gleason pattern or Gleason score) or volume (>33% of sampled cores involved or increase in the number of cores with >50% involvement). The effect of a negative confirmatory biopsy survival was evaluated using Kaplan-Meier analysis and a Cox proportional hazards modeling.

RESULTS

Out of 635 men, 224 met inclusion criteria (median follow-up: 55.8 months). A total of 111 men (49.6%) had a negative confirmatory biopsy. Decreased grade reclassification (69.7% vs 83.9%; P = .01) and volume reclassification (66.3% vs 87.4%; P = .004) was seen at 5 years for men with a negative confirmatory biopsy compared with those with a positive biopsy. On adjusted analysis, a negative confirmatory biopsy was associated with a decreased risk of grade reclassification (hazard ratio, 0.51; 95% confidence interval, 0.28-0.94; P = .03) and volume reclassification (hazard ratio, 0.32; 95% confidence interval, 0.17-0.61; P = .0006) at a median of 4.7 years.

CONCLUSION

Absence of cancer on the confirmatory biopsy is associated with a significant decrease in rate of grade and volume reclassification among men on AS. This information may be used to better counsel men on AS.