[情報] Paul Meier dies at 87
Paul Meier's obituary on the Washington Post
http://www.washingtonpost.com/rw/WashingtonPost/Content/Epaper/2011-08-11/Bx7.pdf
新聞稿
Paul Meier, biostatistician and co-inventor of a famous graph, dies at 87
http://www.washingtonpost.com/local/obituaries/paul-meier-biostatistician-and-co-inventor-of-a-famous-graph-dies-at-87/2011/08/09/gIQAfHBH7I_story.html
By David Brown, Published: August 10
Paul Meier, who was among the most influential biostatisticians
of his generation and helped bring mathematical rigor to medical
research in the years after World War II, died Aug. 7 at his home
in Manhattan. He had suffered a disabling stroke about 10 years
ago and died after a series of recent strokes. He was 87.
As a biostatistician, Dr. Meier brought probability theory,
data analysis and logic to bear on problems in biology and
medicine. In the late 1950s, he co-invented the “Kaplan-Meier
estimator” as a way of depicting survival and other important
outcomes in medical experiments. It has been used in tens of
thousands of scientific studies.
In addition to introducing analytical techniques, he was an early
and successful proponent of “randomization” in clinical trials.
The idea of assigning subjects in a medical experiment to one
treatment or another solely on the basis of chance horrified many
physicians.
In developing ways to more easily figure out which treatments
worked and which ones didn’t, Dr. Meier “must already have
helped save tens of thousands of lives,” said Richard Peto,
a leading biostatistician at the University of Oxford in England.
“I and hundreds of others use his methods every week in our work.”
Dr. Meier’s claim to fame was the two-dimensional, X- and
Y-axis graph that can be found in the New England Journal
of Medicine, the Lancet and dozens of other medical journals
each week.
The Kaplan-Meier curve is a way of illustrating what happens
to a group of subjects over the course of an experiment in
which everyone starts in the same state: alive, disease-free,
unpregnant, et cetera. If the subjects receive different
“interventions” that affect health — say, half are getting
an active drug and the other half a placebo — the graph
depicts the two subgroups’ experiences as two diverging lines.
The problem that Dr. Meier and his collaborator,
Edward L. Kaplan, solved was how to calculate an outcome
— such as the chance of surviving five years after a cancer
treatment — when not everyone participates in the experiment
for the same length of time.
That problem is not uncommon, because clinical trials are
time-consuming affairs and it often takes months or years
to enroll enough volunteers.
The consequence is that a five-year study of survival after
a cancer treatment might have only 50 or 60 percent of its
subjects observed for the full five years. The rest are in for
less time. Kaplan and Dr. Meier derived a series of equations
that allows every patient’s experience — death or survival
for whatever length of time observed — to contribute to
the ultimate calculation of survival.
“It was a very, very important advance,” said Steven N. Goodman,
associate dean for clinical research at Stanford University’s
medical school and editor of the journal Clinical Trials.
“It seems so elementary now.”
Kaplan, then at the University of California Radiation Laboratory,
and Dr. Meier, then at the University of Chicago, published
their 24-page paper in the Journal of the American Statistical
Association in 1958.
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