Modeling the life expectancy benefits of active surveillance
Posted Dec 01 2010 12:00am
An article in today’s issue of the Journal of the American Medical Association, and the accompanying editorial in the same issue, are getting a lot of media attention despite the fact that the article is “only” a mathematical analysis of the possible quality of life benefits of active surveillance in low-risk patients compared to active intervention.
The article by Hayes et al. reports the results of a sophisticated attempt to assess the quality-adjusted life expectancy (QALE) of hypothetical groups (“cohorts”) of 65-year-old men newlydiagnosed with clinically localized, low-risk prostatecancer (defined by a PSA level <10 ng/ml, a clinical stageof T2a disease or less, and a Gleason score of 6 or less). Let us be quite clear … These are not “real” patients. They are hypothetical patients.
What Hayes and her colleagues have done is to use data from a variety of sources to construct a model of the way that their hypothetical cohorts of patients might reasonably be expected to respond, over time, to a variety of management strategies, specifically including active surveillance, radical prostatectomy, intensity modulated radiation therapy, and brachytherapy.
Here are their basic results, which are given in terms of quality-adjusted life expectancy (QALE), which is measured in quality-adjusted life-years (QALYs):
For the active surveillance cohort, QALE = 11.07 QALYs.
For the brachytherapy cohort, QALE = 10.57 QALYs.
For the intensity-modulated radiation therapy cohort, QALE = 10.51 QALYs.
For the radicalprostatectomy cohort, QALE = 10.23 QALYs.
In other words, based on the model constructed by Hayes and her colleagues, active surveillance offers the best long-term outcome compared to any form of active intervention for these hypothetical patient cohorts.
This is not a mathematical model that can not be applied specifically to an individual patient.
The model is based on data that is (at least in some cases) open to question.
Many assumptions have to be made in constructing a model of this type, and those assumptions may not be accepted by others.
The personal choices and priorities of the patients have been completely ignored in constructing this model.
The precise clinical characteristics of individual patients have also been ignored in this model.
Hayes and her colleagues have done an excellent job of demonstrating the potential value of active surveillance compared to active intervention in a well-defined and increasingly common set of prostate cancer patients. Their data may be helpful in allowing clinicians to explain this potential value to newly diagnosed patients. However, Hayes and her colleagues and Thompson and Klotz, in their editorial comments on the paper by Hayes et al. , are all extremely careful to not the continuing importance of patient choice in decisions about prostate cancer treatment.
In their conclusion, Hayes et al. clearly state that, “Under a wide range of assumptions, for a 65-year-oldman, active surveillance is a reasonable approach to low-riskprostate cancer based on QALE compared with initial treatment.However, individual preferences play a central role in the decisionwhether to treat or to pursue active surveillance.”
Because of the wide media “pick-up” of this story, we have provided links to a series of other articles based specifically on the Hayes et al. study: