THE "NEW" PROSTATE CANCER INFOLINK

A while ago now we first discussed research being done by Eric Feuer and others on what was initially being called the Cancer Survival Query System or CSQS. The goal was to develop a relatively simple, nomogram-based system that would allow doctors and their patients to predict risk of death from cancer as opposed to risk of death from other causes, which could be individualized based on a variety of factors that included things as diverse as the patient’s age, race, diagnosis, treatment, and other co-morbid conditions.

Such a system would help men to understand whether their risk of dying from prostate cancer specifically was actually increasing their risk of death from all causes or whether, even though they had been diagnosed with prostate cancer, their risk of death from all causes was unlikely to be affected by a diagnosis of prostate cancer. Such knowledge would, potentially, be of great value in helping a man to decide whether he could just monitor a low- or intermediate-risk form of prostate cancer or whether he really needed to get it treated.

There has now been significant progress in this research field, and last November there were three relevant papers published in the Journal of the National Cancer Institute Monograph series:

• A paper by Feuer et al., entitled “The Surveillance, Epidemiology, and End Results Cancer Survival Calculator SEER*CSC: validation in a managed care setting”
• A paper by Rabin et al., entitled “Health-care utilization by prognosis profile in a managed care setting: using the Surveillance, Epidemiology and End Results Cancer Survival Calculator SEER*CSC”
• A paper by Howlader et al., entitled “Providing clinicians and patients with actual prognosis: cancer in the context of competing causes of death”

In all three papers, prostate cancer and the ability to project risk of prostate cancer-specific mortality was specifically addressed. However, the methodologies used by the SEER*CSC team were different to those used by Howlander et al. Also, all three papers are complex because of the nature of the way the projections are constructed, and it won’t be possible, here, to get into all of the details. However, the authors have been kind enough to provide your sitemaster with full text copies of all three of these papers.

Let’s deal first with the paper by Feuer et al.

What Feuer and his colleagues set out to do was to validate a refined model of the original CSQS — now known as the SEER*CSC or the SEER Cancer Survival Calculator.  This calculator allows us to make a variety of predications about a specific patient and then compare them to one another. The predictions include all of the following:

• A man’s “physiological” or “health status-adjusted” age or HSAA (as compared to his calendar age) taking account of his co-morbid conditions other than his cancer (e.g., whether he has had things like a prior heart attack or ongoing liver disease)
• The probability that a man with a calendar age of 66 to 94 years and diagnosed with prostate cancer will die from his cancer, or from other causes, or still be alive at
  • 1 year after his diagnosis
  • 5 years after his diagnosis
  • 10 years after his diagnosis

Using this SEER*CSC model and data from prostate cancer patients diagnosed between 2001 and 2008 in the Kaiser Permanente Colorado managed care system, Feuer et al. were then able to demonstrate that their model actually predicted the above-mentioned risks with a relatively high degree of accuracy.

Specifically, they give the example of a married, 69-year-old, African American male, aged 69 at diagnosis with prostate cancer. He has two co-morbid conditions (cerebrovascular disease and renal disease). His HSAA is evaluated as 82 years (as compared to his calendar age of 69 years). His life expectancy without his prostate cancer is estimated at 7 years. However, he has high-risk prostate cancer and is treated by radical prostatectomy. After the surgery, he is confirmed to have a Gleason score of 8 to 10 and a pathological stage of pT2-3N1M0. Taking all of these data into account, the SEER*CSC calulator projects the following:

• At 1 year post-diagnosis
  • 2 percent of men like this will likely have died of their prostate cancer
  • 9 percent of men like this will likely have died of other causes
  • 89 percent of men like this will still be alive
• At 5 years post-diagnosis
  • 9 percent of men like this will likely have died of their prostate cancer
  • 41 percent of men like this will likely have died of other causes
  • 50 percent of men like this will still be alive
• At 10 years post-diagnosis
  • 18 percent of men like this will likely have died of their prostate cancer
  • 65 percent of men like this will likely have died of other causes
  • 17 percent of men like this will still be alive

Their model does not work so well in men who are younger than 65 years of age, and so the model is probably going to need some refinement before it could be used reliably in the prognosis of men diagnosed with prostate cancer in their 50s and early 60s.

The second paper, by Rabin et al., used the SEER*CSC with somewhat different intent — to see how patient prognosis might influence patterns of health service utilization, again in cohort of patients enrolled in the Kaiser Permanente Colorado managed care system.

Looking specifically at the findings for the cohort of 1,102 prostate cancer patients — all diagnosed between 2001 and 2008, Rabin et al. found that:

• Their average age was 67 ± 8.8 years.
• They were followed for an average (mean) of 71 ± 35.2 months.
• 259/1,102 (24 percent) died within the study period (of any cause)
• 908/1,102 (82 percent) were diagnosed with AJCC Stage I disease.
• 100/1,102 (9 percent) were diagnosed with AJCC Stage IV disease.
• The SEER*CSC projected that
  • 53 percent of these men would probably die of causes other than prostate cancer within 5 years of diagnosis (Group A).
  • 40 percent of these men had a roughly equal probability of dying from their cancer or from other causes within 5 years (Group B).
  • 22 percent were significantly more likely to die of their cancer within 5 years (Group C).

However, what was really interesting was the following:

• The men in Groups A, B, and C all had similar rates of urology visits within the first year after diagnosis (about 11 or 12 visits per 1,000 person-days).
• The men in Group C (as one might expect) had far more medical oncology visits (9.1 per 1,000 person-days) within the first year post-diagnosis than the men in Groups A and B.
• Primary care visits in the first year post-diagnosis varied much less from group to group, with
  • 8.8 visits per 1,000 person-days for men in Group A
  • 6.4 visits per 1,000 person-days for men in Group B
  • 9.5 visits per 1,000 person-days for men in Group C
• Primary care visits varied very little from year to year for men in all three groups.

Exactly why there was little significant difference or change in primary care health resource utilization after diagnosis with prostate cancer is unclear — although this could have something to do with good coordination of care between primary care physicians and specialists within the Kaiser Permanente system.

The last paper, by Howlader et al., used a somewhat different system to evaluate risk of dying of prostate cancer from risk of dying of other causes, based on the competing effects of age, co-morbidities, and cancer stage at diagnosis. As the authors of this article are careful to observe, their model is much less individualized than the SEER*CSC model. However, it does provide us with a good deal of clarity, for prostate cancer, about the relative risk of prostate cancer-specific mortality in different groups of patients categorized by the competing characteristics defined above.

This is best indicated in Figure 3 of the paper, which shows the very high risk for prostate cancer-specific mortality within 5 years among men initially diagnosed with metastatic prostate cancer (regardless of age or co-morbidities) as compared to the risk for prostate cancer-specific mortality within 5 years for men diagnosed with earlier (localized or regional) stages of the disease. We hope that we will be forgiven for reproducing this figure below.

As yet, as far as we have been able to ascertain, the SEER*CSC nomogram system is not publicly available for use by either physicians or their patients. However, we are optimistic that, after some further refinement, it may become available — for physicians at least (and ideally for patients too) in the not too distant future. We see this tool as having great potential value in helping the newly diagnosed to gain greater insight, specifically for prostate cancer, into the relative risks of expectant management as opposed to immediate active treatment — most especially for older men with low-risk disease who are at major risk for over-treatment.

Editorial comment: The “New” Prostate Cancer InfoLink thanks Dr. Borsika Rabin and Dr. Nadia Howlader for providing us with the full texts of the three articles referred to in this commentary.

Filed under: Diagnosis, Living with Prostate Cancer, Management, Risk, Treatment | Tagged: age, calandar, cancer, Co-morbidity, mortality, other, physiological, risk |