Personalized Decision Making for Biopsies in Prostate Cancer Active Surveillance Programs

Abstract

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.

Active surveillance for prostate cancer—will the discoveries of the last 5 years change the future?

“…Finally, dynamic risk prediction techniques incorporated into active surveillance management strategies will help in finding the optimal balance between the burden of monitoring while on active surveillance and the risk of missing signs of disease progression. The first models show encouraging results and the time has come to prospectively validate this approach (19)(20)(21)(22).…”

Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study

“…We used a Bayesian joint modelling contemporary approach, 8 which is optimal for integrating longitudinal parameters recorded at any time intervals, and prognostic factors that do not vary over time. This approach has already been found to have clinical relevance in several health domains, such as oncology, 9 cardiovascular disease, 10 and hypertension. 11…”

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

“…In other words, longer delays in detecting upgrading may be acceptable after the first negative biopsy. To evaluate the potential harm of personalised schedules, we compared them with fixed schedules in a realistic and extensive simulation study [32]. We concluded that personalised schedules plan, on average, six fewer biopsies compared to annual schedule and two fewer biopsies than the PRIAS schedule in slow/non-progressing AS patients, while maintaining almost the same time delay in detecting upgrading as the PRIAS schedule.…”

“…A caveat of doing so is that reduction in the number of PSA measurements can also lead to an increase in the variance of risk estimates, and also affect the performance of personalised schedules. Although we have done a simulation study to conclude that personalised schedules may not be any more harmful than PRIAS or an annual schedule [32], with an infrequent PSA schedule, these conclusions may not hold. Hence, we do not recommend any changes in the schedule of PSA measurements from the current protocol of PSA measurements every 6 months.…”