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

Impact of genomic testing on urologists' treatment preference in favorable risk prostate cancer: A randomized trial

INTRODUCTION

The Oncotype Dx Genomic Prostate Score (GPS) is a 17-gene relative expression assay that predicts adverse pathology at prostatectomy. We conducted a novel randomized controlled trial to assess the impact of GPS on urologist's treatment preference for favorable risk prostate cancer (PCa): active surveillance versus active treatment (i.e., prostatectomy/radiation). This is a secondary endpoint from the ENACT trial which recruited from three Chicago hospitals from 2016 to 2019.

METHODS

Ten urologists along with men with very low to favorable-intermediate risk PCa were included in the study. Participants were randomly assigned to standardized counseling with or without GPS assay. The main outcome was urologists' preference for active treatment at Visit 2 by study arm (GPS versus Control). Multivariable best-fit binary logistic regressions were constructed to identify factors independently associated with urologists' treatment preference.

RESULTS

Two hundred men (70% Black) were randomly assigned to either the Control (96) or GPS arm (104). At Visit 2, urologists' preference for prostatectomy/radiation almost doubled in the GPS arm to 29.3% (29) compared to 14.1% (13) in the Control arm (p = 0.01). Randomization to the GPS arm, intermediate NCCN risk level, and lower patient health literacy were predictors for urologists' preference for active treatment.

DISCUSSION

Limitations included sample size and number of urologists. In this study, we found that GPS testing reduced urologists' likelihood to prefer active surveillance.

CONCLUSIONS

These findings demonstrate how obtaining prognostic biomarkers that predict negative outcomes before treatment decision-making might influence urologists' preference for recommending aggressive therapy in men eligible for active surveillance.

The value of time-dependent risk predictions in a screening context - a comprehensive simulation analysis validated on German cancer registry data

Background

Risk-prediction tools allow classifying individuals into risk groups based on risk thresholds. Such risk categorization is often used to inform screening schemes by offering screening only to individuals at increased risk of harmful events. Adding information concerning an individual’s risk development over time would allow assessing not just who to screen but also when to screen. This paper illustrates the value of personalised, time-dependent risk predictions to optimize risk-based screening schemes.

Methods

In a simulation analysis, two different time-dependent risk-based screening approaches are compared to another risk-based, but time-independent approach regarding their impact on screening efficiency. For this purpose, 81 scenarios featuring 5000 patients with five consecutive annual risk estimations for a hypothetical disease D are simulated, using different parameters to model disease progression and risk distribution. This simulation analysis is validated using a real-world clinical case study based on German breast cancer patients and the INFLUENCE-nomogram for locoregional breast cancer recurrence.

Results

If individual risk estimations were used to personalise screening for a disease D aiming at detecting a 90% of curable cases, more than 20% of screening examinations could be avoided relative to a conventional uninformed approach, depending on the simulated scenario. Whereas an individual but time-independent approach is associated with acceptable saving potentials in case of a relatively homogenous risk distribution, the time-dependent approaches are superior when the complexity of a scenario increases. With slowly progressing diseases, risk-accumulation over time needs to be considered to achieve the highest screening efficiency on population level, for rapidly progressing diseases, an interval-specific approach is superior. The possible benefits of time-dependent risk-based screening were confirmed in the real-world clinical case study.

Conclusions

Appropriate approaches to use time-dependent risk predictions may considerably enhance screening efficiency on individual and population level. Therefore, predicting risk development over time should be supported by future prediction tools and be incorporated in decision algorithms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01718-2.

Risk of progression following a negative biopsy in prostate cancer active surveillance

BACKGROUND

Currently, follow-up protocols are applied equally to men on active surveillance (AS) for prostate cancer (PCa) regardless of findings at their initial follow-up biopsy. To determine whether less intensive follow-up is suitable following negative biopsy findings, we assessed the risk of converting to active treatment, any subsequent upgrading, volume progression (>33% positive cores), and serious upgrading (grade group >2) for negative compared with positive findings on initial follow-up biopsy.

METHODS

13,161 men from 24 centres participating in the Global Action Plan Active Surveillance Prostate Cancer [GAP3] consortium database, with baseline grade group ≤2, PSA ≤ 20 ng/mL, cT-stage 1-2, diagnosed after 1995, and ≥1 follow-up biopsy, were included in this study. Risk of converting to treatment was assessed using multivariable mixed-effects survival regression. Odds of volume progression, any upgrading and serious upgrading were assessed using mix-effects binary logistic regression for men with ≥2 surveillance biopsies.

RESULTS

27% of the cohort (n = 3590) had no evidence of PCa at their initial biopsy. Over 50% of subsequent biopsies in this group were also negative. A negative initial biopsy was associated with lower risk of conversion (adjusted hazard ratio: 0.45; 95% confidence interval [CI]: 0.42-0.49), subsequent upgrading (adjusted odds ratio [OR]: 0.52; 95%CI: 0.45-0.62) and serious upgrading (OR: 0.74; 95%CI: 0.59-92). Radiological progression was not assessed due to limited imaging data.

CONCLUSION

Despite heterogeneity in follow-up schedules, findings from this global study indicated reduced risk of converting to treatment, volume progression, any upgrading and serious upgrading among men whose initial biopsy findings were negative compared with positive. Given the low risk of progression and high likelihood of further negative biopsy findings, consideration should be given to decreasing follow-up intensity for this group to reduce unnecessary invasive biopsies.

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.

Sample sizes of prediction model studies in prostate cancer were rarely justified and often insufficient

OBJECTIVE

Developing clinical prediction models (CPMs) on data of sufficient sample size is critical to help minimize overfitting. Using prostate cancer as a clinical exemplar, we aimed to investigate to what extent existing CPMs adhere to recent formal sample size criteria, or historic rules of thumb of events per predictor parameter (EPP)≥10.

STUDY DESIGN AND SETTING

A systematic review to identify CPMs related to prostate cancer, which provided enough information to calculate minimum sample size. We compared the reported sample size of each CPM against the traditional 10 EPP rule of thumb and formal sample size criteria.

RESULTS

About 211 CPMs were included. Three of the studies justified the sample size used, mostly using EPP rules of thumb. Overall, 69% of the CPMs were derived on sample sizes that surpassed the traditional EPP≥10 rule of thumb, but only 48% surpassed recent formal sample size criteria. For most CPMs, the required sample size based on formal criteria was higher than the sample sizes to surpass 10 EPP.

CONCLUSION

Few of the CPMs included in this study justified their sample size, with most justifications being based on EPP. This study shows that, in real-world data sets, adhering to the classic EPP rules of thumb is insufficient to adhere to recent formal sample size criteria.

The Movember Prostate Cancer Landscape Analysis: an assessment of unmet research needs

Prostate cancer is a heterogeneous cancer with widely varying levels of morbidity and mortality. Approaches to prostate cancer screening, diagnosis, surveillance, treatment and management differ around the world. To identify the highest priority research needs across the prostate cancer biomedical research domain, Movember conducted a landscape analysis with the aim of maximizing the effect of future research investment through global collaborative efforts and partnerships. A global Landscape Analysis Committee (LAC) was established to act as an independent group of experts across urology, medical oncology, radiation oncology, radiology, pathology, translational research, health economics and patient advocacy. Men with prostate cancer and thought leaders from a variety of disciplines provided a range of key insights through a range of interviews. Insights were prioritized against predetermined criteria to understand the areas of greatest unmet need. From these efforts, 17 research needs in prostate cancer were agreed on and prioritized, and 3 received the maximum prioritization score by the LAC: first, to establish more sensitive and specific tests to improve disease screening and diagnosis; second, to develop indicators to better stratify low-risk prostate cancer for determining which men should go on active surveillance; and third, to integrate companion diagnostics into randomized clinical trials to enable prediction of treatment response. On the basis of the findings from the landscape analysis, Movember will now have an increased focus on addressing the specific research needs that have been identified, with particular investment in research efforts that reduce disease progression and lead to improved therapies for advanced prostate cancer.

The Movember global Landscape Analysis Committee (LAC) was established to act as an independent group of experts across urology, medical oncology, radiation oncology, radiology, pathology, translational research, health economics and patient advocacy to identify the highest priority research needs across the prostate cancer biomedical research domain. Findings from the landscape analysis illustrate the research priorities in prostate cancer and will enable Movember to focus on specific needs, with particular investment in research to reduce disease progression and improve therapies for advanced prostate cancer.

Adherence to Active Surveillance Protocols for Low-risk Prostate Cancer: Results of the Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance Initiative

BACKGROUND

Active surveillance (AS) enrolment criteria and follow-up schedules for low-risk prostate cancer vary between institutions. However, uncertainty remains about adherence to these protocols.

OBJECTIVE

To determine adherence to institution-specific AS inclusion criteria and follow-up schedules within the Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance (GAP3) initiative.

DESIGN, SETTING, AND PARTICIPANTS

We retrospectively assessed the data of 15 101 patients from 25 established AS cohorts worldwide between 2014 and 2016.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Adherence to individual AS inclusion criteria was rated on a five-point Likert scale ranging from poor to excellent. Nonadherence to follow-up schedules was defined as absence of repeat biopsy 1 yr after the scheduled date. Cohorts were pooled into annual and Prostate Cancer Research International: Active Surveillance (PRIAS)-based biopsy schedules, and a generalised linear mixed model was constructed to test for nonadherence.

RESULTS AND LIMITATIONS

Serum prostate-specific antigen (PSA) inclusion criteria were followed in 92%, Gleason score (GS) criteria were followed in 97%, and the number of positive biopsy cores was followed in 94% of men. Both age and tumour stage (T stage) criteria had 99% adherence overall. Pooled nonadherence rates increased over time-8%, 16%, and 34% for annual schedules and 11%, 30%, and 29% for PRIAS-based schedules at 1, 4, and 7 yr, respectively-and did not differ between biopsy schedules. A limitation is that our results do not consider the use of multiparametric magnetic resonance imaging.

CONCLUSIONS

In on-going development of evidence-based AS protocols, variable adherence to PSA and GS inclusion criteria should be considered. Repeat biopsy adherence reduces with increased duration of surveillance, independent of biopsy frequency. This emphasises the importance of risk stratification at the commencement of AS.

PATIENT SUMMARY

We studied adherence to active surveillance protocols for prostate cancer worldwide. We found that inclusion criteria were generally followed well, but adherence to repeat biopsy reduced with time. This should be considered when optimising future active surveillance protocols.

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.

Evidence-based approach to active surveillance of prostate cancer

Active surveillance is a good management option for some men with non-metastatic prostate cancer. In this review, we examine the evidence for several topics related to active surveillance. We examine: (1) which patients should be eligible for active surveillance, (2) what follow-up (monitoring) protocols should be used for men on surveillance, (3) what is the role of prostate magnetic resonance imaging (MRI) for men on surveillance, and (4) what is the prognosis for men who choose surveillance compared to radical treatment. In many instances, the evidence is evolving or lacking. In these situations, we highlight the limitations of the data.