Age, Gleason score, PSA indicate risk for prostate cancer overdiagnosis

Issue: March 25, 2014

A nomogram created to predict individualized risk for prostate cancer overdiagnosis showed risk varied significantly based on age, Gleason score and PSA at the time of diagnosis, according to study results.

Perspective from Donald L. Trump, MD, FACP

Researchers assessed risk for overdiagnosis — defined as a cancer detected through screening that otherwise would have been asymptomatic or clinically unapparent— using a microsimulation model of virtual life histories of men aged 50 to 84 years from 1975 to 2005.

Researchers then applied SEER prostate cancer incidence and PSA screening data to the virtual models.

Overall, the risk for overdiagnosis ranged from 2.9% to 88.1%.

Results indicated that the odds for overdiagnosis increased by 12.9% (95% CI, 12.2-13.6) for each additional year of age at the time of diagnosis.

A Gleason score of at least 7 was associated with a 19.5% (95% CI, 11.7-26.5) decrease in the risk for overdiagnosis when compared with a Gleason score of 6 or lower (P<.001).

The odds of overdiagnosis decreased by 16.6% (95% CI, 14.2-18.9) with each additional 1 ng/mL of serum PSA up to 10 ng/mL.

Researchers found age to be the most statistically significant risk.

Among men with a Gleason score of 6 or lower and PSA levels from 4 ng/mL to 4.9 ng/mL, those who were aged 50 to 54 years had an 11.6% risk for overdiagnosis, whereas those who were aged 70 to 74 years had a 59.9% risk and those who were aged 80 to 84 years had an 83.4% risk.

“Although other studies have quantified the likelihood of overdiagnosis associated with PSA screening for the US population as a whole, the results presented here are likely to be considerably more useful for screen-detected patients trying to understand the severity of their newly diagnosed prostate cancer,” the researchers wrote. “It is hoped that the resulting nomogram, tailored to individual patient characteristics known at diagnosis, will provide useful information for patients and their physicians seeking to weigh the likely harms and benefits of the treatment options available for contemporary screen-detected prostate cancers.”

In an invited commentary, Boris Freidlin, PhD, and Edward L. Korn, PhD, both of the biometric research branch of the division of cancer treatment and diagnosis at the NCI, said implications of modeling may be limited to screening practices.

“Microsimulation could be useful to expand the applicability of randomized trial results on the benefits and harms of a PSA screening regimen, including the probability of overdiagnosis,” Freidlin and Korn wrote. “However, once an individual has been screened and found to have prostate cancer, the relevant question is the outcomes of various treatments (treatment morbidity, prostate cancer symptoms and death), not the probability of an event that could have happened if the individual had not been screened.”

For more information:

Freidlin B. J Natl Cancer Inst. 2014;doi:10.1093/jnci/djt368.
Gulati R. J Natl Cancer Inst. 2014;doi:10.1093/jnci/djt367.

Disclosure: The researchers report no relevant financial disclosures.

Perspective

Donald L. Trump, MD, FACP

The goal of the development of this model is to provide information that would allow a patient and his physician to estimate whether the patient’s cancer is "incidental" or clinically relevant. The model is clearly pertinent to a major challenge in the management of patients with recently diagnosed, localized prostate cancer, and it does provide more refined estimates of risk — those that are "incidental" or "clinically important."

However, the precision of these estimates is still less than we need. For example, a man aged 65 years with a Gleason ≤6 tumor and PSA between 6 and 6.9 has, as calculated by this model, a 36.1% risk of having an "overdiagnosed" (by inference, an incidental) cancer. If that man’s PSA was between 4 and 4.9, the risk of overdiagnosis increases to 44.9% — almost a coin flip.

As Friedlin and Korn note in an accompanying editorial, an important concern is that models have limitations, and what is really needed are results of randomized trials that define the outcomes and expectations of the various therapies available, more than a calculation that estimates "the probability of an event that could have happened if the individual had not been screened." Biomarkers that more directly allow us to implement the right treatment for the individual patient are vitally needed. As one of my friends and cherished mentors, Donald S. Coffey, PhD, says: "We need to be able to tell the tigers from the pussycats."

Donald L. Trump, MD, FACP

HemOnc Today Editorial Board member

Disclosures: Trump reports no relevant financial disclosures.