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.

Background

Active surveillance (AS) is increasingly accepted for managing low-risk prostate cancer, yet there is no consensus about implementation. This lack of consensus is due in part to uncertainty about risks for disease progression, which have not been systematically compared or integrated across AS studies with variable surveillance protocols and dropout to active treatment.

Objective

To compare risks for upgrading from a Gleason score (GS) of 6 or less to 7 or more across AS studies after accounting for differences in surveillance intervals and competing treatments and to evaluate tradeoffs of more versus less frequent biopsies.

Design

Joint statistical model of longitudinal prostate-specific antigen (PSA) levels and risks for biopsy upgrading.

Setting

Johns Hopkins University (JHU); Canary Prostate Active Surveillance Study (PASS); University of California, San Francisco (UCSF); and University of Toronto (UT) AS studies.

Patients

2576 men aged 40 to 80 years with a GS between 2 and 6 and clinical stage T1 or T2 prostate cancer enrolled between 1995 and 2014.

Measurements

PSA levels and biopsy GSs.

Results

After variable surveillance intervals and competing treatments were accounted for, estimated risks for biopsy upgrading were similar in the PASS and UT studies but higher in UCSF and lower in JHU studies. All cohorts had a delay of 3 to 5 months in detecting upgrading with biennial biopsies starting after a first confirmatory biopsy versus annual biopsies.

Limitation

The model does not account for possible misclassification of biopsy GS.

Conclusion

Men in different AS studies have different risks for biopsy upgrading after variable surveillance protocols and competing treatments are accounted for. Despite these differences, the consequences of more versus less frequent biopsies seem to be similar across cohorts. Biennial biopsies seem to be an acceptable alternative to annual biopsies.

Primary funding source

National Cancer Institute.