Estimating the risks and benefits of active surveillance protocols for prostate cancer: a microsimulation study

Exploring the relation of active surveillance schedules and prostate cancer mortality

BACKGROUND

Active surveillance (AS), where treatment is deferred until cancer progression is detected by a biopsy, is acknowledged as a way to reduce overtreatment in prostate cancer. However, a consensus on the frequency of taking biopsies while in AS is lacking. In former studies to optimize biopsy schedules, the delay in progression detection was taken as an evaluation indicator and believed to be associated with the long-term outcome, prostate cancer mortality. Nevertheless, this relation was never investigated in empirical data. Here, we use simulated data from a microsimulation model to fill this knowledge gap.

METHODS

In this study, the established MIcrosimulation SCreening Analysis model was extended with functionality to simulate the AS procedures. The biopsy sensitivity in the model was calibrated on the Canary Prostate Cancer Active Surveillance Study (PASS) data, and four (tri-yearly, bi-yearly, PASS, and yearly) AS programs were simulated. The relation between detection delay and prostate cancer mortality was investigated by Cox models.

RESULTS

The biopsy sensitivity of progression detection was found to be 50%. The Cox models show a positive relation between a longer detection delay and a higher risk of prostate cancer death. A 2-year delay resulted in a prostate cancer death risk of 2.46%-2.69% 5 years after progression detection and a 10-year risk of 5.75%-5.91%. A 4-year delay led to an approximately 8% greater 5-year risk and an approximately 25% greater 10-year risk.

CONCLUSION

The detection delay is confirmed as a surrogate for prostate cancer mortality. A cut-off for a "safe" detection delay could not be identified.

The EU-TOPIA evaluation tool: An online modelling-based tool for informing breast, cervical, and colorectal cancer screening decisions in Europe

Background

Aiming to support European countries in improving their breast, cervical, and colorectal cancer (CRC) screening programmes, the EU-TOPIA consortium has developed an online user-friendly tool (the EU-TOPIA evaluation tool; https://miscan.eu-topia.org) based on the Microsimulation Screening Analysis (MISCAN) model.

Methods

We designed an online platform that allows stakeholders to use their country-specific data (demographic, epidemiological, and cancer screening information) to quantify future harms and benefits of different cancer screening scenarios in their country. Current cancer screening programmes and impacts of potential changes in screening protocols (such as extending target ages or increasing screening attendance) can be simulated. Results are scaled to the country-specific population. To illustrate the tool, we used the tool to simulate two different CRC screening scenarios in the Netherlands: biennial fecal immunochemical testing (FIT) in ages 55–75 and colonoscopy every ten years in ages 55–75. Data from the Dutch screening programme was used to inform both scenarios.

Results

A total of 482,700 CRC cases and 178,000 CRC deaths were estimated in the Netherlands with FIT screening (for individuals aged 40–100 years, 2018–2050), with 47.3 million FITs performed (1.92 million positives of which 1.64 million adhered to diagnostic colonoscopy). With colonoscopy screening, CRC incidence and mortality were, respectively, up to 17% and 14% lower than in the current FIT screening programme, requiring, however, a colonoscopy demand that was 7-fold higher.

Conclusions

Our study presents an essential online tool for stakeholders and medical societies to quantify estimates of benefits and harms of early cancer detection in Europe.

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.

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.

Evaluating Parameter Uncertainty in a Simulation Model of Cancer Using Emulators

Background. Microsimulation models have been extensively used in the field of cancer modeling. However, there is substantial uncertainty regarding estimates from these models, for example, overdiagnosis in prostate cancer. This is usually not thoroughly examined due to the high computational effort required. Objective. To quantify uncertainty in model outcomes due to uncertainty in model parameters, using a computationally efficient emulator (Gaussian process regression) instead of the model. Methods. We use a microsimulation model of prostate cancer (microsimulation screening analysis [MISCAN]) to simulate individual life histories. We analyze the effect of parametric uncertainty on overdiagnosis with probabilistic sensitivity analyses (ProbSAs). To minimize the number of MISCAN runs needed for ProbSAs, we emulate MISCAN, using data pairs of parameter values and outcomes to fit a Gaussian process regression model. We evaluate to what extent the emulator accurately reproduces MISCAN by computing its prediction error. Results. Using an emulator instead of MISCAN, we may reduce the computation time necessary to run a ProbSA by more than 85%. The average relative prediction error of the emulator for overdiagnosis equaled 1.7%. We predicted that 42% of screen-detected men are overdiagnosed, with an associated empirical confidence interval between 38% and 48%. Sensitivity analyses show that the accuracy of the emulator is sensitive to which model parameters are included in the training runs. Conclusions. For a computationally expensive simulation model with a large number of parameters, we show it is possible to conduct a ProbSA, within a reasonable computation time, by using a Gaussian process regression emulator instead of the original simulation model.

A Tool for Shared Decision Making on Referral for Prostate Biopsy in the Primary Care Setting: Integrating Risks of Cancer with Life Expectancy

Prostate cancer (PCa) testing involves a complex individually based decision making process. It should consider competing risks from other comorbidities when estimating a survival benefit from the early detection of clinically significant (cs)PCa. We aimed to develop a prediction tool that provides concrete advice for the general practitioner (GP) on whether to refer a man for further assessment. We hereto combined the probability of detecting csPCa and the potential overall survival benefit from early detection and treatment. The PCa detection probabilities were derived from 3616 men enrolled in the Dutch arm of the European Randomized Study of Screening for Prostate Cancer (ERSPC). Survival estimates were derived from 19,834 men from the Surveillance, Epidemiology, and End Results (SEER) registry, ERSPC, and Dutch life tables. Treatment benefit was estimated from the Prostate Cancer Intervention versus Observation Trial (PIVOT, n = 731). The prediction of csPCa detection was based on prostate-specific antigen (PSA), age, %freePSA, and digital rectal examination (DRE). The life expectancy (LE) for patients with PCa receiving no treatment was adjusted for age and Charlson comorbidity index. A negative impact on LE and treatment benefit was found with higher age and more comorbidity. The proposed integrated approach may support triage at GP practices, as PCa is a heterogeneous disease in predominantly elderly men.

Recent incidence and surgery trends for prostate cancer: Towards an attenuation of overdiagnosis and overtreatment?

Background

Screening for prostate cancer is frequent in high-income countries, including Switzerland. Notably due to overdiagnosis and overtreatment, various organisations have recently recommended against routine screening, potentially having an impact on incidence, mortality, and surgery rates. Our aim was therefore to examine whether secular trends in the incidence and mortality of prostate cancer, and in prostatectomy rates, have recently changed in Switzerland.

Methods

We conducted a population-based trend study in Switzerland from 1998 to 2012. Cases of invasive prostate cancer, deaths from prostate cancer, and prostatectomies were analysed. We calculated changes in age-standardised prostate cancer incidence rates, stratified by tumor stage (early, advanced), prostate cancer-specific mortality, and prostatectomy rates.

Results

The age-standardised incidence rate of prostate cancer increased greatly in men aged 50–69 years (absolute mean annual change +4.6/100,000, 95% CI: +2.9 to +6.2) between 1998 and 2002, and stabilised afterwards. In men aged ≥ 70 years, the incidence decreased slightly between 1998 and 2002, and more substantially since 2003. The incidence of early tumor stages increased between 1998 and 2002 only in men aged 50–69 years, and then stabilised, while the incidence of advanced stages remained stable across both age strata. The rate of prostatectomy increased markedly until 2002, more so in the 50 to 69 age range than among men aged ≥ 70 years; it leveled off after 2002 in both age strata. Trends in surgery were driven by radical prostatectomy. Since 1998, the annual age-standardised mortality rate of prostate cancer slightly declined in men aged 50–69 years (absolute mean annual change -0.1/100,000, 95% CI: -0.2 to -0.1) and ≥ 70 years (absolute mean annual change -0.5/100,000, 95% CI: -0.7 to -0.3).

Conclusions

The increases in the incidence of early stage prostate cancer and prostatectomy observed in Switzerland among men younger than 70 years have concomitantly leveled off around 2002/2003. Given the decreasing mortality, these trends may reflect recent changes in screening and clinical workup practices, with a possible attenuation of overdiagnosis and overtreatment.

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.

Comparative effectiveness of prostate cancer screening between the ages of 55 and 69 years followed by active surveillance

BACKGROUND

Because of the recent grade C draft recommendation by the US Preventive Services Task Force (USPSTF) for prostate cancer screening between the ages of 55 and 69 years, there is a need to determine whether this could be cost-effective in a US population setting.

METHODS

This study used a microsimulation model of screening and active surveillance (AS), based on data from the European Randomized Study of Screening for Prostate Cancer and the Surveillance, Epidemiology, and End Results Program, for the natural history of prostate cancer and Johns Hopkins AS cohort data to inform the probabilities of referral to treatment during AS. A cohort of 10 million men, based on US life tables, was simulated. The lifetime costs and effects of screening between the ages of 55 and 69 years with different screening frequencies and AS protocols were projected, and their cost-effectiveness was determined.

RESULTS

Quadrennial screening between the ages of 55 and 69 years (55, 59, 63, and 67 years) with AS for men with low-risk cancers (ie, those with a Gleason score of 6 or lower) and yearly biopsies or triennial biopsies resulted in an incremental cost per quality-adjusted life-year (QALY) of $51,918 or $69,380, respectively. Most policies in which screening was followed by immediate treatment were dominated. In most sensitivity analyses, this study found a policy with which the cost per QALY remained below $100,000.

CONCLUSIONS

Prostate-specific antigen-based prostate cancer screening in the United States between the ages of 55 and 69 years, as recommended by the USPSTF, may be cost-effective at a $100,000 threshold but only with a quadrennial screening frequency and with AS offered to all low-risk men. Cancer 2018;124:507-13. © 2017 American Cancer Society.

When should active surveillance for prostate cancer stop if no progression is detected?

BACKGROUND

A significant proportion of screen-detected men with prostate cancer may be overdiagnosed. Active Surveillance (AS) has emerged as a way to mitigate this problem, by delaying treatment of men, who are at low-risk until this becomes necessary. However, it is not known after how much time or biopsy rounds should patients stop AS and transition to conservative management (CM), if no progression is detected.

METHODS

We used a microsimulation model with natural history of prostate cancer based on ERSPC and SEER data. We modeled referral to treatment while in AS, based on Johns Hopkins treatment-free survival data. We projected lifetime costs and effects of AS (and radical treatment, if progression is detected) under different biopsy follow-up schedules compared to CM, where radical treatment only occurs when men would be clinically diagnosed in absence of screening.

RESULTS

For men with low-risk disease in younger age groups (55-65), AS is cost-effective for up to 7 yearly biopsy rounds. For men older than 65, even one biopsy round results in quality adjusted life years (QALYs) lost, though it may result in QALYs gained for men without previous screening. For men with intermediate-risk disease AS is cost-effective even for men in 65-75 age group.

CONCLUSIONS

The benefit of AS when compared to CM is strongly dependent on life expectancy and disease risk. Clinicians should take this into account when selecting men to AS, deciding on biopsy frequency and when to stop AS surveillance rounds and transition to CM.