NephMadness: Sweet 16 – Proximal Tubule Region

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Proximal Tubule Region: S-one Segment Group Finalists:

(1) HEMO Trial vs (5) ALLHAT Trial

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The HEMO versus TREAT round of 32 match-up was interesting because both of these trials crushed long-standing dogma that had been established through observational data. Nephrology, through the USRDS and DOPPS, has a wealth of retrospective data and relies on it to form most of it’s evidence base, so it is frightening when we see observational data fall in well designed randomized controlled trials.

HEMO is one of the definitive studies that anchors dialysis. Before HEMO doctors would battle patients to stretch out every inkling of low molecular weight clearance they could. Countless hours were spent convincing patients to stay an extra 5 minutes, battling with accesses to increase the blood flow an extra few ml per minute. All in the service of additional Kt/V. This was based on acres of observational data and Gotch and Sargent’s reinterpretation of the original NCDS study.

Observational data from multiple cohorts, various countries and with differing statistical methods all had shown improved survival with increased urea clearance:

  • PJ Held et al: Mortality risk was lower by 7% (P = 0.001) with each 0.1 higher level of delivered Kt/V
  • FK Port et al  the RR (for mortality) was 17%, 17%, and 19% lower per 5% higher URR category among groups with small, medium, and large BMI
  • T Shinzato et al The analysis indicated that important death risk predictors were: (i) advanced age, (ii) occurrence of diabetes mellitus, (iii) male sex, (iv) Kt/V lower than 1.8
  • RA Wolf et al. Mortality was less among larger patients and those receiving greater eKt/V

It was this culture that HEMO completely overturned. The finding that a significant and achievable increase in dialysis dose within the context of three days a week, daytime schedule made no observational difference broke the paradigm. The discovery that low molecular weight clearance is not the answer has subsequently been reinforced in the world of peritoneal dialysis with the Ademex study and in the realm of ARF with the ATN trial. A fair assessment of the first decade of the 21st century in dialysis was the repeated debunking of the primacy of small molecule clearance and its ties to mortality and morbidity. And this change began with HEMO.

The TREAT trial walks the same path as HEMO, with one critical difference. From the introduction of epoetin in 1988 until 1998, no one had published randomized controlled data on whether epoetin decreased mortality or hospitalizations. Epo had been approved because of its ability to reduce transfusions. Subsequently people began to theorize that avoiding renal anemia could have other benefits, primarily on reducing cardiovascular disease based on observational data:

  • IC Macdougall et al. Long-term cardiorespiratory effects of amelioration of renal anemia by erythropoietin. (I interviewed Iain Macdougall for eAJKD last year)
  • G Cannella et al. Reversal of left ventricular hypertrophy following recombinant human erythropoietin treatment of anemic dialysed uremic patients.
  • C Zehnder et al. Influence of long-term amelioration of anemia and blood pressure control on left ventricular hypertrophy in hemodialyzed patients.
  • JS Silberberg et al. Impact of left ventricular hypertrophy on survival in end-stage renal disease.

Beserab’s Normalization of Hematocrit study in 1998 showed that not to be the case in dialysis, and more concerning than the lack of benefit was the increased risk of death or MI with increased target hematocrit (RR 1.3; 95% CI, 0.9 to 1.9, yes not quite significant but the study was stopped early, I suspect had it been allowed to proceed it would have shown harm). But this risk did not usher in a HEMO-like change in thinking. This may in part be due to confounders identified by the authors. They pointed to decreased Kt/V and increased iron as possible culprits in the study and exonerated the dose of epoetin (data not shown) and achieved hemoglobin.

Following Beserab, the interest in EPO moved upstream from dialysis to CKD. CHOIR and CREATE dropped in the same issue of the NEJM in 2006, both were RCTs of epoetin with a low and a near normal hemoglobin target for pre-dialysis CKD patients. And both showed no effect and areas of concern:

  • Trend to increased mortality and CHF in CHOIR (P=0.07)
  • Shorter time to dialysis in CREATE P=0.03

It was into this milieu that TREAT dropped. It is the only placebo controlled trial of ESA with mortality and hospitalizations as its primary end-point. Read that sentence again. Thirty years of Epo and ESA research and only one serious, placebo controlled trial with an end-point of death or hospitalization. This, along with its large size is why TREAT is so important.

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TREAT was much larger than all of the previous anemia studies and made a compelling case against treating anemia in pre-dialysis CKD.

The primary difference between the impact of TREAT and HEMO was that by the time TREAT was published there had already been three negative RCTs and this result was expected. HEMO dropped in a world that was fully unprepared to cope with this new view of low molecular weight clearance.

This surprise is why HEMO trumped TREAT.

IDEAL Trial

IDEAL is the study that shouldn’t be. People are familiar with lead time bias, this has been a major issue in the debates over PSA for prostate cancer screening and mammograms for breast cancer screening. Use of these technologies allows earlier diagnosis of the targeted illness, and the patients who are diagnosed with these techniques reliably live longer than patients that are eventually diagnosed without the screening test. While on the surface this looks like a win for the screening test it may just mean that patients destined to die of their disease are merely diagnosed earlier in the course of disease and even if there is no benefit to early diagnosis will appear to live longer after diagnosis due to the early diagnosis.

Lead time bias took center stage in the debates that raged regarding the initiation of dialysis. Vittorio Bonomini was big proponent of early initiation of dialysis and was able to show very low mortality rates for his cohort of patients that he started on dialysis with GFRs in the mid teens. This observational data was susceptible to lead-time bias. Traynor did some of the compelling work demonstrating lead time bias in initiation data sets by tracking survival of patients not from the time they start dialysis but from the time their GFR fell below 20 mL/min. He was able to show that all of the supposed benefit of early dialysis was actually an illusion that hid the truth that early initiation of dialysis was actually harmful. In his discussion he discusses the possibility of a randomized controlled trial to analyze this:

Against this background, it may be that such a randomized, prospective trial will never be performed, placing a greater emphasis on the results of retrospective and cohort studies.

He argued that the size of the study and difficulty in randomizing patients to differing start times for dialysis might mean the study would never get done. He estimated 372 patients arm and a 5 year study. Well that is as good an introduction to the IDEAL trial as possible, a randomized controlled trial of start times for dialysis, or the study they said couldn’t be done.

The difficulty of recruiting patients was absolutely seen in this trial and it took 8 years to complete. Additionally the investigators were not able to get the separation between the groups they were targeting. Only 25% of the late start group reached the target GFR of 5-7 ml/min, with the balance starting dialysis with a GFR over 7 due to uremia or doctors discretion. To make matters worse, 18% of the early start group started dialysis with a GFR < 10 ml/min. That said, they did get some separation: early start 12 ml/min, late start 9.8 ml/min. The authors found no difference in survival with the two strategies with a trend to worse outcome with early initiation of dialysis. Lead time bias, conclusively demonstrated.

IDEAL stands for the ability to do a randomized controlled trial even in circumstances that initially appear daunting.

ALLHAT

ALLHAT faced off against the important ACCOMPLISH trial in the first round. ALLHAT is the largest hypertension trial ever conducted and was a unique combination of NIH sponsorship with industry support that may be a model for future trials in this resource constricted era. ALLHAT provided some of the first data on the prevalence of resistant hypertension. Much of the earlier data on resistant hypertension came from tertiary care centers and so suffered from selection bias. ALLHAT revealed that the prevelance of this type of high blood pressure was 15%. ALLHAT also brought to the forefront the unique effectiveness of chlorthalidone a lesson still paying dividends a decade after the study.

ALLHAT became the foundation on which many of the recommendations of JNC 7 were built.

Proximal Tubule Region: Vasa Recta Group Finalists:

(6) anti-PLA2R vs (2) APOL1

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anti-PLA2R

Anti-PLA2R is alive and well in #NephMadness. The last 2 rounds proved to be quite a contest as both suPAR and FGF23 were both knock-down drag-out matchups. The main challenge in this group is that each of these three “teams” have provided a lot of hype in the field of nephrology but as of yet have not provided a real clinical utility. Membranous nephropathy has an incidence of 1 per 100,000 persons/year. Patients diagnosed with this condition are typically placed into one of three groups in accordance to the “one third” rule. “One third” of patient will experience spontaneous remission. “One third” of patients will have persistent proteinuria with reduced by stable GFR.  Finally, “one third” will have persistent loss of GFR and progress to ESRD. Lumping patients into these categories is typically done by the degree of proteinuria and renal function as below:

  • low-risk group- normal renal function and less than 4 grams/day proteinuria over a 6-month period
  • medium-risk group- normal renal function and persistent proteinuria between 4 and 8 grams/day proteinuria over a 6-month period
  • high-risk group- worsening renal function and proteinuria greater than 8 grams/day over a 6-month period

The hype is that with the addition of a biomarker, such as anti-PLA2R, we can better identify which patients will have spontaneous remission and which should be treated aggressively. Furthermore, guiding therapy to anti-PLA2R antibodies could help in decreasing the burden of immunosuppressive medications. This will be a tough matchup as APOL1 has the potential to explain the high prevalence of ESRD in African Americans.

APOL1 

APOL1 has always had to get out of the shadow of MYH9.  Both are located on chromosome 22 and it is hard to mention one without the other. I guess you could call this region of the chromosome the tobacco road of genetic polymorphisms linked to kidney disease. As mentioned in this first round description, APOL1 was born of genetic studies that initially indicated that MYH9 was the culprit genetic lesion. The identification of MYH9 polymorphisms were initially based on single nucleotide polymorphisms (SNPs) identified using the HapMap consortium data. The HapMap consortium provided genomic data that happened to be biased towards European ancestry. Later, the 1000 genome project provided a larger and more exhaustive resource including SNPs and haplotypes of African origin. This led to two distinct sets of variants in the APOL1 gene, termed alleles ‘G1′ and ‘G2′, as the main association with end-stage renal disease in African Americans (reviewed here). Further studies confirmed that polymorphisms in APOL1 are linked to FSGS, hypertensive associated ESRD and HIVAN. A matchup between APOL1 and HIVAN was inevitable and APOL1 won in a decisive manner. An interesting finding is that 50% of HIV-infected African Americans with two APOL1 risk alleles who are not receiving antiviral therapy will develop HIVAN. The true potential of APOL1 has yet to be realized, but it has the possibility to dramatically change the face of kidney disease.

Click here to see the Loop of Henle Region.

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