Postcards from Beyond The Zero
This is a statistical walk through the odds I've faced in my battle with
metastatic renal cell cancer and how those odds have changed with time and
circumstances. To understand the background, read
my complete story. I hope this inspires you to see that even the most
terrible prognosis and odds can be overcome. I also intend it to illustrate
some of the considerations involved in interpreting survival curves.
I was diagnosed with widely metastatic kidney cancer only
one month after surgery for a huge, but seemingly localized tumor. I found the
survival curve to the right in a review article my own doctor had written. This
curve shows survival of patients with what I had, who either relapsed within
six months of surgery (like me), or who had metastasis at diagnosis. It applied
The curve is approximately constant risk. Constant risk
means that the chance of dying does not change over time. Constant risk curves
have a constant half life, which is the time it takes for half the
remaining patients to die. Living longer brings no relief, the risk is always
the same. For my curve, the half life (and therefore also median survival) is
only about four months. The chance of surviving one year is only about 12%. At
four and one half years, the curve reaches the zero.
Taken at face value, this is a statistical nightmare, a
stark portrait of the odds against terminal cancer. There is no hint of even
the slightest possibility of a cure or way out. Only a relentless descent to
death. But this superficial appearance was not the reality. Escape was
Caveats: The data was old, and strongly reflects the
fact that at that time there was no standard effective treatment. But that was
still true at the time of my diagnosis. This curve is also based on a fairly
small number of patients and cannot exclude a tiny fraction of truly long term
survivors. While the chance of surviving 5 years is surely very small, I don't
believe it is actually zero!
I changed my odds and got off the curve above by entering a
clinical trial of a then experimental drug called Interleukin-2. Here is a long
term survival curve for 255 patients given high dose IL-2 (I had Interferon
with the IL-2, but this is as close as I can find).
Notice that this curve, while still very rough, has 20%
survivors at four and a half years (instead of zero percent in the previous
curve) and maybe 15% survivors at 10 to 11 years. There is a small but real
chance here! Best of all it flattens out towards the end, suggesting that a few
may actually be cured.
When I started my treatment, IL-2 was still in development.
So since it took more than a decade to accumulate enough follow-up to make this
curve, I didn't have it to look at when I had to make my decision. What I had
instead were hints that IL-2 might improve the curve - hints in the form
of a report in the literature of dramatic responses that were continuing after
two or three years (To see just exactly what I was looking at, see my article,
The Hint). Given the survival with standard
treatment, that was more than enough for me. Seeing the first curve with its
message of doom turned out to be a positive because only in comparison to that
dreadful curve could I have known that a mere hint was worth pursuing with
everything I had.
Caveats: Unlike the first curve, this curve is not
limited to treatment of patients who relapsed within 6 months of diagnosis, so
the inclusion of patients who had a somewhat better prognosis to begin with may
represent part of the improvement. More generally, there is considerable
uncertainty any time you compare survival curves from completely different
trials or groups. There can easily be a difference between the groups which,
rather than the difference in treatment, accounts for a difference in
survival. Ideally, survival curves are best compared when they are from a
randomized trial where bias due to group difference is eliminated by the trial
design. But in the real world, decisions often have to be made with less than
ideal data. In this case the fraction of really long term survivors is still
better from what could reaonably be expected with metastatic renal cancer with
earlier treatments, so while the curve I changed to may not be exactly what I
present here, I surely did change my odds for the better by taking IL-2.
I could have responded... or not responded. I had control
over my choice of treatment, but not over whether it worked. I was fortunate in
that I did respond. Once that happened, the odds changed again, and again
dramatically for the better! Here is a curve for patients who responded to high
dose IL-2. Notice that nearly 40% are still in remission over a decade later.
Had I not responded, my odds would have changed for the worse and probably
would not be much better than they were when I started.
Caveats: Note that this curve charts response
duration rather than actual survival. Since patients survive at least some time
after relapse, and since it takes at least some time to get into remission, an
actual survival curve would look at least slightly better than this.
There is a classic statistical trap in comparing responders to
non-responders (or to all patients treated) because those who respond may have been
those who were healthier to begin with and who would have lived longer anyway.
So it may not be the case that the patients really benefited from treatment,
even if they achieve a temporary shrinkage of their tumors, as is often the
case with chemotherapy (My treatment was immunotherapy). I do not think that
this is the case here because many of the responses that did occur were long
term, and because without treatment, long term survival for this disease is
Once I got into remission, I resumed my life hoping I would
be one of those whose responses lasted. As time passed I got to see more and
more data which showed, as these curves do, that the longer I stayed in
remission, the greater the chance I was going to stay there! As you can see
from the previous two curves, the risk of relapse or death is highest during
the first 30 months and then decreases substantially. So the mere passage of
time improved my odds as I moved past the initial high risk 30 months to a
substantially flatter area of the curve.
Since there have been no relapses after 85 months, for
survivors who are out at least that far, the curve is flat at 100%. In fact, as
I write this in September 2001, I am off the end of the curve in remission at
142 months, So my curve is now flat at 100%! (If you don't actually see a curve
here, it's the line at the very top!)
Caveats: That 100% is based on a small number of
patients, so just as I don't believe the first curve really guaranteed death, I
also don't believe this one guarantees life, though things are looking very,
very good. Finally, because I am "off the curve," I am extrapolating a little
in time to claim 100%. But despite these caveats, the difference between the
curve I am on now and the one on which I started my journey is not in doubt. It
This CancerGuide Page By
Steve Dunn. © Steve Dunn
Page Created: 2001,
Last Updated: March 14, 2002