We recently held a webinar with Dr. Navdeep Tangri, the Canadian nephrologist and medical researcher who developed the Kidney Failure Risk Equation for accurately predicting the risk of progression to renal failure in patients with chronic kidney disease (CKD). Below is an excerpt from his presentation.
Navdeep Tangri, MD, PhD, FRCP(C)
I’m really delighted to spend the next few minutes talking to you about my work on the Kidney Failure Risk Equation, and how I think it really transforms care for CKD by taking it out of the eGFR-based care paradigm and moving it into a risk-based paradigm, actually treating people according to their risk of kidney failure — which is the event we’re all trying to prevent, — rather than treating them based on what their kidney function is today.
So, why do we need to predict the progression of CKD? Well, I think the progression of CKD is important to predict because we need to provide early and appropriate nephrology care. So, let me break that down into two separate points. Early nephrology care is important for those patients with CKD stages 1, 2, and 3, who are going to progress. They may look like their kidney function is OK right now, but they’re just at such high risk of progression that they need care early to really delay their progression rate and to put them on the best cardiovascular and renal preventative medications.
Appropriate nephrology care is appropriately conservative care, and that care is for people with stages 3, 4, and 5, as well as 1 and 2, who are actually at very low risk of progression, or in the case of 4 and 5, very high risk of competing events. So, these patients actually need more conservative care, less aggressive drug treatment, because some of them are actually at higher risk of side effects as well. So, that balance between early and appropriate care requires them to look beyond eGFR.
“Appropriate nephrology care is appropriately conservative care.”
The other reason why we need risk prediction is to provide prognostic information to the patient and provider. I think sometimes we underestimate the ability or the comfort delivered by accurate prognostic information. So, for example, there was a study done by my colleagues at Tufts University which asked patients, “If you could know your risk of a disease — a disease that has no cure at all — would you still want to know a timeframe? Would you still want to know your risk? And would you be willing to pay for it?” And, in fact, most patients indicated that they would have a real willingness to pay, even if there was no treatment, because it helps them plan their life. So, in a case like CKD, where there is effective treatment, where we can actually change the trajectory of the disease, where we can actually make different treatment decisions, that prognostic information is almost invaluable — certainly for the patient, as well as the provider.
As a clinical trialist and an epidemiologist, I think knowing information about who is going to progress is very useful for pharmaceutical companies as they enroll patients for trials, to help them project their kidney failure events in their trials well in advance, right in the beginning, using baseline data.
For large dialysis organizations, such as Fresenius, DaVita, and DCI, it helps them know which patients from their CKD clinics are likely to progress to need dialysis, so they can accurately plan for dialysis spots in those units. If you imagine a rural community where theres a nephrologist whos looking after several hundred patients with CKD, and there are only five or six chairs in that station, we could probably tell them how many new starts theyll have in two, four, five years. That kind of information can be really helpful in planning.
So, those are just some of the reasons why it’s really important to know who’s going to progress, and who’s not going to progress.
See Dr. Tangri’s entire presentation here: Revolutionizing Renal Care with Predictive Analytics for CKD.