The JH-AS cohort included data on 769 cases with a median follow-up time of 2.7 years (range from 4 days to 15.0 years). Among these cases, PSA grew by 3.1% per year on average with a standard error of 0.5%. 253 patients initiated treatment by the time of analysis and another 66 had progressed but had not yet initiated treatment (and so are censored). The median time to treatment among those treated was 5.9 years; the failure rate in the last year of observation (0.10) was used for extrapolation beyond the last observed treatment time. presents the results of the model for GS progression by the time of treatment. A longer time to treatment and older age were associated with a greater chance of biopsy upgrade while on AS. PSA and the annual change in PSA from diagnosis to treatment were not significantly associated with biopsy upgrading, and excluding the PSA covariates did not materially change our projections. The majority of upgrades (86%) were to GS 7.
Logistic regression model of biopsy upgrading for active surveillance patients who were diagnosed after 1995 and underwent treatment (n=237).
The T-stage ≤ T2a CaPSURE cohort for analysis of recurrence under delayed RP includes data on 3,470 men diagnosed after January 1994 and treated with RP, of whom 385 (11.1%) recurred after RP. The average age at diagnosis was 60.8 (range 39–80) years, and the median follow-up time was 3.6 years (range from 5 days to 15.3 years). The cumulative incidence of recurrence was 10.1% at 5 years and 11.1% at 10 years. The Weibull regression model used to extrapolate beyond the follow-up period had a median time to recurrence of 68.2 years. The low-risk CaPSURE cohort for analysis of recurrence under immediate RP includes data on 2,150 (62.0%) men, of whom 163 (7.6%) recurred after RP. The average age at diagnosis was 60.2 (range 39–79) years, and the median follow-up time was 3.7 years (range from 7 days to 15.3 years). The cumulative incidence of recurrence was 6.8% at 5 years and 7.6% at 10 years. The Weibull regression model used to extrapolate beyond the follow-up period had a median time to recurrence of 86.1 years. summarizes the characteristics of the T-stage ≤ T2a CaPSURE cohort and low-risk CaPSURE cohort. presents the Cox model results for recurrence following immediate and delayed RP.
Characteristics of T-stage ≤ T2a and low-risk (T-stage ≤ T2a, Gleason score ≤ 6, and PSA level ≤ 10 ng/mL) CaPSURE patients diagnosed after 1994.
Table 4 Cox proportional hazards regression model for recurrence following immediate and delayed RP based on CaPSURE data and for prostate cancer death based on T-stage ≤ T2a JH-PCM data. The immediate RP model was fit to 2,150 cases with low-risk disease (more ...)
The JH-PCM cohort includes 1,745 men, of whom 963 (55.2%) received RP after January 1994 and had T-stage ≤ T2a. The average age at diagnosis was 58.7 (range 39–74) years. 63 (6.5%) men died of prostate cancer and the cumulative incidence of PCM was 3.4% at 5 years and 5.9% at 10 years after recurrence. The Weibull regression model used to extrapolate beyond the follow-up period had a median time to PC death of 122.4 years. summarizes the JH-PCM data, and % presents the results of our model of PCM. shows the strong association between time to recurrence and PCM, with each additional year of recurrence-free survival reducing the risk of PCM following recurrence by 35%.
Characteristics of T-stage T2a JH-PCM data diagnosed after 1994 (n=963).
Our distributions of age and PSA at diagnosis were based on low-risk cases diagnosed after 2004 in SEER (mean age 60.6; mean PSA 4.9 ng/mL). The model projected that 63.7% of cases on JH-AS would progress to treatment before they died of other causes. The projected 20-year cumulative incidence of PCM was 2.78% under AS and 1.64% under immediate RP. The reduced incidence of PCM under immediate RP amounted to an average of 1.8 months of life saved per case (). Compared to men initially treated with RP, men on AS had on average 6.4 more years of life free from treatment and its side effects.
Comparison of outcomes of following active surveillance or immediate radical prostatectomy. Outcomes are based on 1 million simulated patients.
As a sensitivity analysis of the intensity of surveillance, we modified the simulated time to treatment on AS by a hazard ratio of 0.5 to lengthen the interval from diagnosis to treatment. Our goal was to approximate a less intensive surveillance regimen; the hazard ratio of 0.5 was motivated by the published time to treatment on the Toronto AS study (7
), which reported 84%, 72%, and 62% remaining on surveillance at 2, 5, and 10 years respectively versus 81%, 56% and 34% respectively in the JH-AS cohort. Under this setting, the model projected that about 54.8% patients would progress to treatment within their lifetimes (versus 63.7% projected for the JH-AS cohort), and the corresponding 20-year PCM would increase from 2.78% to 2.82%.
As a second sensitivity analysis, we altered the assumed fraction upgrading to GS ≥ 8 while on AS. In our baseline model, projections of post-treatment survival assume that 14% of upgraded cases are treated with GS ≥ 8, based on the observed grade distribution at treatment in the JH-AS cohort. In our sensitivity analysis, we changed this fraction to 25% and, as a consequence, projected that 20-year PCM would increase from 2.75% to 3.04%.
Our third sensitivity analysis relaxed the correlation between the time to treatment under AS and the time to recurrence following surgery. Under baseline assumptions, the Spearman correlation was 0.94. We projected that 20-year PCM under AS would decrease to 2.38% with a correlation of 0.5 and to 1.69% with no correlation, resulting in a more comparable survival outcome relative to immediate RP. When we only correlate times in these phases for cases on AS who were treated due to biopsy upgrading (Spearman correlation 0.94), we projected that 20-year PCM under AS would decrease to 2.08%.
All sensitivity analyses produced only modest differences in cumulative PCM under AS, and supported our projections that AS would have minimal impact on life expectancy for low-risk prostate cancer cases.