Are ACE inhibitors protective in non-DM renal disease?

Luka Pocivavsek

Analysis of a Major Study

Outline

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)

1. Brief background of relevant Renin Angiotensin System (RAS) physiology

Defining Kidney Disease/Renal Insufficiency

Bellomo et al. Critical Care, Aug 2004, Vol 8, No 4. (consensus paper)

RIFLE classification for progression ofrenal insufficiency:

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

http://www.mc.uky.edu

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.

Paper:

cited 902 times!

Lancet 1997; 349; 1857-63.

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. Non-ACE inhibitor or ARB anti-HTN drugs were used to keep diastolic BP of all study participants under 90 mm Hg.

2. 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.

3. 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. 2.14.2)

or2. 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:

N - population sizet - timer - Malthusian parameter determining rate and direction of population growthK - 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.

Lots of predators/disease, little food.

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

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)):

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

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