Download My two cents on sample space - the importance of exclusion criteria

Are ACE inhibitors protective in
non-DM renal disease?
Analysis of a Major Study
Luka Pocivavsek
Outline
1. Brief background of relevant Renin Angiotensin System
(RAS) physiology
2. Presentation of major findings in a paper addressing effect of
ACE inhibitors in non-diabetic renal disease patients with similar
blood pressure control in both arms
3. Discussion of difficulty and risks of extrapolating tightly
controlled studies to a general population (an example of the
dangers of the reductionist approach in complex non-linear
dynamics)
Defining Kidney Disease/Renal Insufficiency
RIFLE classification for progression of
renal insufficiency:
Bellomo et al. Critical Care, Aug 2004, Vol 8, No 4. (consensus paper)
Protein in the urine has also
been classically linked as an
indicator of kidney damage
and malfunction
(nephropathy):
http://www.unckidneycenter.org
Renin Angiotensin System (RAS) physiology - I
Renin Angiotensin System (RAS) physiology - II
ANGII - key regulator of renal equilibrium and renal FEEDBACK loops
Renin Angiotensin System (RAS) physiology - IV
Key to appreciate that
ANG-I is a substrate for
many peripheral
enzymes.
ANG-II has many non-renal effects, some such as
cardiac remodeling are understood, however
many peripheral tissue effects underappreciated,
but being explored by physiologists.
http://www.mc.uky.edu
Paper: Lancet 1997; 349; 1857-63.
cited 902 times!
Background premise (taken as paradigm): ACE
inhibitors have greater reno-protective effects than other
anti-HTN medications in diabetic nephropathy.
Study Question: are ACE inhibitors reno-protective in
non-diabetic nephropathy in addition to their anti-HTN
effects?
Study Type: prospective double-blinded randomized trial,
i.e. gold standard, with several hundred participants
(decently powered - random events take on robust
Gaussian distributions around 500 events).
Study population demographics: male heavy, hypertensive, w/ baseline renal insufficiency
Exclusion Criteria: insulin dependent DM, coronary
artery disease (NSTEMI/STEMI in last 6 months), tx w/
corticosteroids, immunosuppressive drugs, or
NSAIDS, uncontrolled blood pressure (diastolic >115
or systolic >220), evidence or suspicion of
renovascular disease (~35% of CHF patients have
RVD), obstructive uropathy (BPH), cancer, liver
disease, chronic cough (asthma, COPD).
VERY BROAD EXCLUSION CRITERIA
Many patients who we might place or think or placing
on ACE inhibitors for renal disease as diagnosed by
protein urea are patients who have cardiac and
pulmonary disease and have a very large probability of
using NSAIDS especially aspirin since cardiac patients
are placed on aspirin as a prophylactic.
As clinicians we need to keep in mind the often very
narrow sample space that studies probe. An excellent
study, such as this one, does not mean its conclusions
are broadly applicable.
Placebo vs. study groups: tight BP control in both
Question posed by this study is very well
formulated: does treatment with ACE
inhibitors independent of tight blood
pressure control make a difference in the
progression of kidney disease.
1.
2.
3.
Non-ACE inhibitor or ARB anti-HTN
drugs were used to keep diastolic BP
of all study participants under 90 mm
Hg.
The PLACEBO arm received only
non-ACE/ARB medication and a
sugar pill, the STUDY ARM received
ramipril 2.5-5 mg initially and then
was titrated up until goal BP reached.
The placebo participants received
higher doses of the alternative
medications to keep BP within study
goals.
27 month follow up with diet
monitoring and GFR measurements
every 3 months (iohexol clearance)
Study Findings: ramipril slows rate of GFR decrease compared to placebo
Data shows that decrease in urine protein
levels in ramipril group after one month
(little change in protein levels after one
month of ACEi use in placebo no change
over study time) correlate with a slower
decrease in GFR at long time point (figure
shows 6 month GFR levels)
Correlation clearly there but data too scattered for
any extrapolation. Linear fit highly misleading and of
little significance. R2 likely no more than 0.5
Kidney Survival: Ramipril decrease likelihood of developing ESRD in 2 years
Combined endpoints:
1. Doubling of serum
creatinine (avg.
2.14.2)
or
2. Developing ESRD
and beginning dialysis
Treatment with ACE inhibitor reduced the probability of study patients either
doubling their creatinine (via RIFLE classification developing renal failure b/c
sCr  4.0 mg/dl) or having to start dialysis 2/2 ESRD.
Authors conclusions:
1. Agree - study convincingly showed statistically significant decrease in GFR loss and
thus development of renal failure and ESKD.
2. Disagree - study reported no increase in certain adverse effects (death, CV events)
with ramipril however the safety of the drug was no explicitly explored and safety was
not one of the controlled for end-parameters. There is no statistically significant proof
provided that giving the ACE has or does not have adverse effects which were not
studied and which in the end would be useful in making a clinical decision of whether to
use this medication.
3. Interesting - this point is very fascinating but mostly of physiological academic
interest and of little clinical value. Animal models have shown that ACE inhibitors have a
direct effect on the fenestrations formed by renal podocytes in addition to their control of
renal vascular tone.
Would I use this drug in a patient?
Only if I had a patient that exactly fit the exclusion criteria of the patient
population studied in this study!
Exclusion Criteria: insulin dependent DM, coronary artery disease
(NSTEMI/STEMI in last 6 months), tx w/ corticosteroids, immunosuppressive
drugs, or NSAIDS, uncontrolled blood pressure (diastolic >115 or systolic >220),
evidence or suspicion of renovascular disease (~35% of CHF patients have
RVD), obstructive uropathy (BPH), cancer, liver disease, chronic cough
(asthma, COPD).
Likelihood of having a random patient without any of the above exclusion
criteria which encompass a huge subset of patients with renal insufficiency and
likely proteinurea is low. Furthermore, risk of ACE inhibitors causing acute renal
failure (one of the end-points in this study) increases in patient populations that
have CHF or use NSAIDS.
Yet this extremely well cited and thus assumingly well read study in its
concluding paragraph and introductory summary DOES NOT advertise the
exclusion criteria - - why and what does this mean in general?
My two cents on sample space - the importance of exclusion criteria
Natural processes such as physiological feedback loops (BP control, RAS,
insulin release), population growth models (e.g. logisitc), and others are well
modeled by coupled differential equations.
Simplest example: population growth modeled effectively by Logistic equation
derived in 1845 by Pierre Verhulst:
Lots of predators/disease, little food.
N - population size
t - time
r - Malthusian parameter determining
rate and direction of population growth
K - maximum sustainable population
or carrying capacity
r and K set the sample space of the
model: if r > 0 population will grow
but if r < 0 population will decay.
Few predators, little disease, plenty of food.
understanding population dynamics
under only one r gives a snapshot of
population dynamics - r can be
determined by solving initial value
problem and it defines the sample
space probed
My two cents on sample space - the importance of exclusion criteria
This demonstrates a fundamental mathematical principle about systems governed
by ODEs or PDEs (which all biological processes are even though we do not yet
know the set of equations that drive most of them but many we do - diffusion
(capillaries), convective flow (blood and air flow), logistic type models (hormone
levels)):
The number of solutions tends to infinity and any solution is only
unique given proper initial value conditions or boundary conditions
 mathematicians (especially at UC) prove existence of general
solutions but we are interested in specific solutions.
Relevance to medical studies which probe response of given physiological feedback loops:
• specific solutions appearing as differences in a given study are practically guaranteed if
the study is designed narrowly enough, meaning there exclusion criteria define initial and
boundary values tightly: sample and solution space probed is small therefore
mathematically the problem is well posed and solvable.
• generallizability of the solution however is in no way guaranteed. In other words, given a
new set of boundary and initial conditions, we can try to use our prior solution however in
no way are we guaranteed it solves the equation. General solutions are extremely rare
and exists for few problems in nature.
• take home message about studies: generalizing beyond specific population
studied in the study is meaningless given that any physiological response of the
human body is governed by non-linear PDEs with undefined general solutions.
Ann. Int. Med. 2001; 135; 73-87.
Exclusion Criteria:
Complex systems and dynamics
Renin Angiotensin System (RAS) physiology - II
RAS in Volume/Sodium Homeostasis