MBD and Clinical Practice

Glen Chertow on MBD and clinical practice.

Starts with the high mortality of CVD in ESRD slide shown at every gatheriong of nephrologists.

MBD as a non-traditional risk factor for CVD

HEMO, 4D, Wrone on homocysteine, D-COR all RCT, All negative. [should add correction of anemia study]

45% drop out in D-COR lead to a loss of power and contributed to negative trial.

Cinacalcet approved based on its ability to get the PTH down and get patient to guidelines but we are missing the information on whether this helps patients.

Power is the probablity of detecting the treatment affect if it really exists. 90% power means that 9 out of 10 times you will detect a treatment effect if it exists.

With 3883 patients EVOLVE had 88% power to detect 20% reduction in cardiovascular disease. If the benefit is 15%, which would phenomenally important to our patients, we may not be able to detect it.

Hepatorenal syndrome Journal Club

Journal club today reviewed this article on the treatment of hepatorenal syndrome (HRS) with terlipressin. What a breath of fresh air in the field of HRS, a real randomized double blind placebo controlled trial!

Terlipressin is part of the new wave of HRS that focus on splanchnic vasoconstriction to reverse one of the initiating events in the pathologic cascade that results in HRS. I have been using the combination of octreotide and midodrine to exploit the same therapeutic target. I have had mixed results. I am not aware of any prior controlled trials of this therapeutic target.

Enrollment criteria:

  • Age ≥18
  • Liver disease
  • Doubling of serum cr to ≥2.5 mg/dL in less than 2 weeks with no responce to stopping diuretics and giving plasma expansion

Exclusion criteria

  • Obstructive nephropathy
  • Parenchymal renal disease (ATN, glomerular disease, interstitial nephritis)
  • Use of renal toxic medications
  • Shock
  • Uncontrolled bacterial infection
  • Uncorrected fluid losses
  • Liver disease due to factors which are also nephrotoxic (e.g. acetominophen)
  • Severe cardiovascular disease (investigators discretion)

Intervention: Patients were randomized to either 1 mg terlipressin q6h or matching placebo. If after 3 days the patients had not had a decrease in Cr of 30% the study drug was doubled to 2 mg q6h. The protocol recommended daily albumin infusions (100 g on day one and 25 g daily after that). The protocol prohibited concomitant use of vasocontrictors (dopamine, norepinephrine) prostaglandin, NSAIDs.

Primary end-point: percent of patiens with a serum Cr ≤1.5 on two measurements 48 hours apart without dialysis, death or recurrence of HRS.

Secondary end-points:

  1. Change in serum Cr from baseline to day 14
  2. incidence of treatment failure (Cr ≥ baseline after day 7, dialysis, death)
  3. Combined incidence of treatment success and partial response (Cr decreased by >50% but not ≤ 1.5) without diqalysis or recurrence of HRS
  4. Survival [Yay!] at 60 days (though they did not show the results)
  5. Transplant-free survival at 60 days (though they did not show the results)
  6. Survival at 180 days
  7. Transplant-free survival at 180 days

Results:

They randomized 112 patients from 35 centers.
More patients in the terlipressin group had a Cr > 7, though the average creatinine was 3.96 in the experimental group and 3.85 in the control group.

The Table 1 did not have p values to allow you to compare differences between the two groups.

The primary outcomes were summarized in Table 2:
The primary outcome is the first line “Treatment success at day 14” and unfortunately they “Missed it by that much” with a p value of 0.093. The next line is HRS reversal which according to the article is the traditional definition of response to therapy in prior investigations of HRS. It is interesting that if the authors had used this “traditional” end-point we would be dancing in the streets about a positive therapy but since they selected a more stringent criteria of response (under pressure from the FDA?) they have a negative trial. The power analysis they provided states they predicted a 50% response rate for terlipressin and a 5% response for the placebo. They actually found a 25% response for terlipressin and 12.5% for placebo. So one cold look at this as an underpowered study because they did not meet the effectiveness they estimated in the power analysis.

The authors then provide an intriguing figure which shows that the patients who recovered in the placebo group, all recovered very early while the recoveries in the terlipressin group occurred through the period the drug was administered.
I believe the point was to show proof of efficacy, implying that the early spontaneous recoveries in the placebo group were due to misdiagnosis or lack of serious disease while the recovery of patients in the terlipressin’s group increased with increasing duration of therapy. I find this fairly compelling.

One of the secondary outcomes was survival (Yay!). There was no difference in survival between the two groups.

Though I love investigators that have the cojones to look at survival, it is a little strange in HRS because the renal failure is secondary to another life threatening primary illness, liver failure. Even if the therapy is perfectly effective at reversing the renal failure, the long-term survival is dependent on getting a liver transplant or spontaneous recovery of the liver disease. One might argue that curing the renal failure would extend the life of the patient making a transplant more likely but since renal failure is a large component of the MELD score, curing the renal failure actually pushes patients down the list for a liver transplant. So in my mind, the lack of a survival benefit in the treatment of HRS is not nearly as damaging as it normally is.

My final conclusion is that though the study did nt reach scientific signifigance for its primary outcome it did demonstrate compelling evidence for positive biologic activity and since all of the alternative therapies have worse data I would use terlipressin if it was available. My guess though is this negative trial will mean that it will not be licensed and distributed in the U.S.

Teaching on the Consult Service: ARF The PICARD Study Group

The first article that was pulled from the reading sessions in NephSAP is this retrospective review of ARF by the PICARD Group.

PICARD Study

The introduction begins by setting the scene: Acute renal failure is lethal with over 50% mortality in most series. Additionally, we haven’t seen any major improvement in mortality for these patients in the last 30 years. Then they authors state that the ANP ARF trials were well designed. This is almost laughable as the ANP trials are the poster child on how not to do a clinical trial on ARF. After that they go over the fact that ARF research is hard because the patients are sick and we lack a standardized methodology for talking about the severity of illness. APACHE II scores are notoriously bad at predicting mortality in renal failure. And the storied Cleaveland clinic ARF score has not been validated outside that institution. Then the authors layout the problem they are trying to answer:

To prepare for future clinical trials in ARF, it is essential that valid, generalizable models for risk adjustment be developed, both for stratification in patient selection and for covariate adjustment in the event of imbalanced randomization.

So in order to accurately risk stratify patients and successfully balance study groups we will not be able to properly evaluate new therapies. This study group was created to do a RCT of CVVH vs IHD and hence captured lots of prospective data of patients in ARF. Only 166 of the 851 were enrolled and randomized in the trial (negative and tragic because they were unlucky with their randomization and they had a significantly higher severity of illness in the CVVH group.). This paper uses all 851 patients to look for predictors of mortality in ARF.

Enrollment criteria:

  • ARF + ICU + Nephrology consult
  • No CKD Cr > 2 or BUN > 40
  • CKD: Cr increased by 1.0
  • No prior dialysis, kidney transplant, obstructive uropathy or pre-renal azotemia

Severity of illness scores (they calculated 13 different scores besides creating their own score) were calculated on the day of nephrology consult. Using the day of consult seems arbitrary and prone to variations in local practice patterns, i.e. if the study is done in an area where early consult is the norm then presumably the patients will have less severe disease and hence have better outcomes, hence a score derived with this methodology will underestimate the mortality in a center with a culture which leans towards later consultation (and presumably sicker patients).

After excluding subjects that had missing data that prevented them from calculating the scores they were left with a cohort of 605 patients.

Half of the cohort received dialysis while in the ICU and 51.9% died in the hospital.

They created a risk score based on:

  • Age
  • Gender
  • Respiratory failure
  • Liver failure
  • Hematologic failure
  • Creatinine
  • BUN
  • Log urine output
  • Heart rate

They then showed that their new model beating the crap out of the old models with an AUC on the ROC of 0.832. The best other scoring system, SAPS2, received only a 0.766. The APACHE II had an AUC of only 0.634. (Perfect AUC is 1.0 and a worthless value is 0.5).

The biggest weakness is that the Mehta score (the eponyminous name for the score created with The PICARD Data) was able to predict outcomes well when you tested it using the data used to define the score. This is the ultimate home field advantage. Levey in the MDRD group divided their cohort into a derivation group and a validation group. This current authors did not do that.

This will be a moot point if the score is validated in a new independent study. I wonder if the ATN group did that? I bet they did, or will publish on this soon.

My fellow just answered a question I have had for years.

Part of the dogma of evaluating iron deficiency in patients with anemia is that after a transfusion the iron indices are altered. Over and over the question comes up…

How long after a transfusion do you have to wait before checking to see if the patient is iron deficient?

Well Jabri, my current fellow went to the literature and found this reference. It looks like the answer is you should be safe 48 hours after the transfusion. This surprised me, I expected the acute effects of the transfusion to persist longer than that.

Abstract from the paper:

The effect of transfusion of packed red blood cells on serum iron level, total iron-binding capacity, and transferrin saturation was studied. Samples of blood from 37 hemodynamically stable patients were obtained for analysis at various intervals following the transfusion of packed red blood cells. In 10 patients with possible iron deficiency, a significant rise in serum iron level and transferrin saturation occurred during the 24 hours following transfusion, which persisted at a marginally significant level up to 36 hours. In the remaining 27 patients, a significant rise was also noted in serum iron level and transferrin saturation results, but the rise did not persist beyond the 24 hours after transfusion. No change in total iron-binding capacity was noted in either group. These data show that the diagnosis of iron deficiency (based on a transferrin saturation of < 0.16) might be missed if iron studies are performed on patients within 24 hours following packed red blood cell transfusion. Therefore, if serum iron studies are obtained for patients suspected of having iron deficiency anemia, these studies are best done on blood samples obtained before blood transfusion.