Are we clear on the Concept?Empirical and normative concerns

Benjamin Hippen, M.D.Carolinas Medical Center

Charlotte, NC

Overview

• Why are we talking about this?• Empirical concerns KDPI and EPTS• Normative (ethical) concerns with

the Concept• Alternatives

Overview

• The Concept document is only the most recent iteration of a long-standing project

• KPSAM -> KARS -> LYFT -> KAS• Now: KDPI (or KDRI) and EPTS• None of these models have been prospectively

validated.• The empirical limitations of the previous

models persist in the current one.

Risk factor versus Prognostic tool

• Risk factor– Diabetes is a risk factor for renal failure

• Prognostic tool– A risk factor which sharply distinguishes between a

group that does and does not have an outcome

• Not all risk factors are good prognostic tools.– Lots of folks with diabetes do not have renal failure– Diabetes is a poor prognostic tool for predicting renal

failure

Ware NEJM 355:2615

A risk factor is a good prognostic tool if the risk factor(s) clearly separate the unaffected group from the affected group.

A risk factor which does not do this will either have low sensitivity (shifting lineTo the right), or will increase sensitivity at the expense of a higher false positive rate (shifting line to the left).

BMJ 1999;319:1562-5

Empirical Concerns (1)• C-statistic – Measure of a Prognostic Test• Not a measure of “goodness of fit”– 0.5 = no better than chance for a binary outcome– 1.0 = Perfect prediction model

• LYFT– Waitlist survival – 0.6– Patient survival – 0.68– Graft survival – 0.57

• EPTS “…did not provide substantially greater predictive power…” than LYFT.

Empirical Concerns (2)• C-statistic for KDPI– C-statistic across all quartiles = 0.62– C-statistic between middle quartiles – 0.5– C-statistic between lowest/highest – 0.78

• “KDRI is more useful for distinguishing more extreme categories of graft failure risk and of less utility for distinguishing donors from the middle ranges.” (Rao Transplantation 88:235)

• But, the relevant distinction is to reliably/reproducibly differentiate the top 20% from the other 80% of kidneys.

Past projections, actual outcomes

Meier-Kriesche AJT 4:1289

Bottom line

• High frequency of mistriage (30-40%)– Incorrectly identifying kidneys and candidates as

conferring favorable survival or vice versa

• No guarantee that mistriages will be randomly distributed– Some groups may be mistriaged more often

• Frequent mistriage = a failure of the allocation system to do what it purports to do.

Normative Concerns (1)

• We know who is predicted to “win.”• But which groups will lose? • How many will lose?– Models of death on the waiting list– Should “life years gained” be offset by life years lost

for want of a transplant?

• Why not a comparative intent to treat analysis?– ITT would count additional deaths on the waiting list

Add in proportion of list and new incident patients

Data from OPTN.org

Hippen NEJM 364:1285

Normative Concerns (2)• Younger candidates disproportionately receive more

kidneys from living donors.– 18-34: 53% of removals for transplant from LD– 35-49: 41%– 50-64: 33%– 65+ : 28%

• Disproportionally disincentivising LD among the young may reduce total rates of living donation.

• Why suppose the young are randomly distributed across DSAs? The < 20% may look quite different across DSAs and across individual centers.

• Why won’t transplant centers aggressively advertise their favorable “< 20%” demographics? Why shouldn’t they?

A Kidney that Looks Like You?(But Doc, I’m pretty sick!)

Frei AJT 8: 50Not a simulation

More kidneys

• Why would centers with conservative risk tolerance currently suddenly change their institutional minds?– 79% one year graft survival, not censored for

death– More kidneys + worse outcomes versus fewer

kidneys and better outcomes

• Does “risk adjustment” help patients, or just help transplant centers and OPOs?

Whose kidneys are they, anyway?• Not the OPO• Not the Transplant Center• Not the Transplant Surgeon/Nephrologist• These kidneys are a public resource• Individual candidates should be allowed to

choose, in consultation with their physician, their own level of risk tolerance.

• Additional risk and foreclosure of benefit from a public resource should not be foisted on the older and the sicker by fiat.

Alternatives• Better, prospectively validated risk models for education

purposes = More money from HRSA, and a novel approach from SRTR

• Be a doctor– Tailor advice to individual candidates in the evaluation– Informed consent– Counsel candidates in real time when they come up for an offer– Moral obligations are sometimes inefficient

• Come to terms with the fact that tinkering with allocation will never address the supply/demand disparity in a meaningful way.

• More living donors, and more creative ways of procuring and distributing organs from living donors.

Thank you!