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A Vigilante in Statistical Badlands

By ANISH KOKA, MD

Something didn’t seem right to epidemiologist Eric Weinhandl when he glanced at an article published in the venerated Journal of the American Medical Association (JAMA) on a crisp fall evening in Minnesota. Eric is a smart guy – a native Minnesotan and a math major who fell in love with clinical quantitative database-driven research because he happened to work with a nephrologist early in his training. After finishing his doctorate in epidemiology, he cut his teeth working with the Chronic Disease Research Group, a division of the Hennepin Healthcare Research Institute that has held The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) contract for the United States Renal Data System Coordinating Center.  The research group Eric worked for from 2004-2015 essentially organized the data generated from almost every dialysis patient in the United States.  He didn’t just work with the data as an end-user, he helped maintain the largest, and most important database on chronic kidney disease in the United States. 

For all these reasons this particular study published in JAMA that sought to examine the association between dialysis facility ownership and access to kidney transplantation piqued Eric’s interest.  The provocative hypothesis is that for-profit dialysis centers are financially motivated to keep patients hooked to dialysis machines rather than refer them for kidney transplantation.  A number of observational trials have tracked better outcomes in not-for-profit settings, so the theory wasn’t implausible, but mulling over the results more carefully, Eric noticed how large the effect sizes reported in the paper were. Specifically,  the hazard ratios for for-profit vs. non-profit were 0.36 for being put on a waiting list, 0.5 for receiving a living donor kidney transplant, 0.44 for receiving a deceased donor kidney transplant.  This roughly translates to patients being one-half to one-third as likely to get referred for and ultimately receiving a transplant.  These are incredible numbers when you consider it can be major news when a study reports a hazard ratio of 0.9.  Part of the reason one doesn’t usually see hazard ratios that are this large is because that signals an effect size that’s so obvious to the naked eye that it doesn’t require a trial. There’s a reason there are no trials on the utility of cauterizing an artery to stop bleeding during surgery. 

But it really wasn’t the hazard ratios that first struck his eye.  What stuck out were the reported event rates in the study. 1.9 million incident end-stage kidney disease patients in 17 years made sense. The exclusion of 90,000 patients who were wait-listed or received a kidney transplant before ever getting on dialysis, and 250,000 patients for not having any dialysis facility information left ~1.5 million patients for the primary analysis.  The original paper listed 121,000 first wait-list events, 23,000 living donor transplants and ~50,000 deceased donor transplants.  But the United Network for Organ Sharing (UNOS), an organization that manages the US organ transplantation system, reported 280,000 transplants during the same period. 

The paper somehow was missing almost 210,000 transplants.

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