Dataset Information

Identification of men with low-risk biopsy-confirmed prostate cancer as candidates for active surveillance.

ABSTRACT:

Background

A combined clinical cell-cycle risk (CCR) score that incorporates prognostic molecular and clinical information has been recently developed and validated to improve prostate cancer mortality (PCM) risk stratification over clinical features alone. As clinical features are currently used to select men for active surveillance (AS), we developed and validated a CCR score threshold to improve the identification of men with low-risk disease who are appropriate for AS.

Methods

The score threshold was selected based on the 90th percentile of CCR scores among men who might typically be considered for AS based on NCCN low/favorable-intermediate risk criteria (CCR = 0.8). The threshold was validated using 10-year PCM in an unselected, conservatively managed cohort and in the subset of the same cohort after excluding men with high-risk features. The clinical effect was evaluated in a contemporary clinical cohort.

Results

In the unselected validation cohort, men with CCR scores below the threshold had a predicted mean 10-year PCM of 2.7%, and the threshold significantly dichotomized low- and high-risk disease (P = 1.2 × 10^-5). After excluding high-risk men from the validation cohort, men with CCR scores below the threshold had a predicted mean 10-year PCM of 2.3%, and the threshold significantly dichotomized low- and high-risk disease (P = 0.020). There were no prostate cancer-specific deaths in men with CCR scores below the threshold in either analysis. The proportion of men in the clinical testing cohort identified as candidates for AS was substantially higher using the threshold (68.8%) compared to clinicopathologic features alone (42.6%), while mean 10-year predicted PCM risks remained essentially identical (1.9% vs. 2.0%, respectively).

Conclusions

The CCR score threshold appropriately dichotomized patients into low- and high-risk groups for 10-year PCM, and may enable more appropriate selection of patients for AS.

SUBMITTER: Lin DW

PROVIDER: S-EPMC8127807 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveTo 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 methodsRepeat 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).ResultsThe 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).ConclusionsWe 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.

Project description:In the United States, 192,000 men were diagnosed as having prostate cancer in 2009, the majority with low-risk, clinically localized disease. Treatment of these cancers is associated with substantial morbidity. Active surveillance is an alternative to initial treatment, but long-term outcomes and effect on quality of life have not been well characterized.To examine the quality-of-life benefits and risks of active surveillance compared with initial treatment for men with low-risk, clinically localized prostate cancer.Decision analysis using a simulation model was performed: men were treated at diagnosis with brachytherapy, intensity-modulated radiation therapy (IMRT), or radical prostatectomy or followed up by active surveillance (a strategy of close monitoring of newly diagnosed patients with serial prostate-specific antigen measurements, digital rectal examinations, and biopsies, with treatment at disease progression or patient choice). Probabilities and utilities were derived from previous studies and literature review. In the base case, the relative risk of prostate cancer-specific death for initial treatment vs active surveillance was assumed to be 0.83. Men incurred short- and long-term adverse effects of treatment.Hypothetical cohorts of 65-year-old men newly diagnosed as having clinically localized, low-risk prostate cancer (prostate-specific antigen level <10 ng/mL, stage ?T2a disease, and Gleason score ?6).Quality-adjusted life expectancy (QALE).Active surveillance was associated with the greatest QALE (11.07 quality-adjusted life-years [QALYs]), followed by brachytherapy (10.57 QALYs), IMRT (10.51 QALYs), and radical prostatectomy (10.23 QALYs). Active surveillance remained associated with the highest QALE even if the relative risk of prostate cancer-specific death for initial treatment vs active surveillance was as low as 0.6. However, the QALE gains and the optimal strategy were highly dependent on individual preferences for living under active surveillance and for having been treated.Under a wide range of assumptions, for a 65-year-old man, active surveillance is a reasonable approach to low-risk prostate cancer based on QALE compared with initial treatment. However, individual preferences play a central role in the decision whether to treat or to pursue active surveillance.

Project description:Prostate specific antigen velocity is an unreliable predictor of adverse pathology findings in patients on active surveillance for low risk prostate cancer. However, to our knowledge a new concept called prostate specific antigen velocity risk count, recently validated in a screening cohort, has not been investigated in an active surveillance cohort.We evaluated a cohort of men from 1995 to 2012 with prostate cancer on active surveillance. They had stage T1c disease, prostate specific antigen density less than 0.15 ng/ml, Gleason score 6 or less, 2 or fewer biopsy cores and 50% or less involvement of any core with cancer. The men were observed by semiannual prostate specific antigen measurements, digital rectal examinations and an annual surveillance biopsy. Treatment was recommended for biopsy reclassification. Patients with 30 months or greater of followup and 3 serial prostate specific antigen velocity measurements were used in primary analysis by logistic regression, Cox proportional hazards, Kaplan-Meier analysis and performance parameters, including the AUC of the ROC curve.Primary analysis included 275 of 668 men who met very low risk inclusion criteria, of whom 83 (30.2%) were reclassified at a median of 57.1 months. Reclassification risk increased with risk count, that is a risk count of 3 (HR 4.63, 95% CI 1.54-13.87) and 2 (HR 3.73, 95% CI 1.75-7.97) compared to zero. Results were similar for Gleason score reclassification (HR 7.45, 95% CI 1.60-34.71 and 3.96, 95% CI 1.35-11.62, respectively). On secondary analysis the negative predictive value (risk count 1 or less) was 91.5% for reclassification in the next year. Adding the prostate specific antigen velocity risk count improved the AUC in a model including baseline prostate specific antigen density (0.7423 vs 0.6818, p = 0.025) and it outperformed the addition of overall prostate specific antigen velocity (0.7423 vs 0.6960, p = 0.037).Prostate specific antigen velocity risk count may be useful for monitoring patients on active surveillance and decreasing the frequency of biopsies needed in the long term.