Deceased Donor Organ Quality: Balancing Organ Utilization, Patient Outcomes & Regulatory Risk

deceased donor organ quality

Deceased Donor Organ Quality: Balancing Organ Utilization, Patient Outcomes & Regulatory Risk

By: Krista Lentine, MD, Ph.D.

In December 2016, the SRTR privately released new Program Specific Reports (PSRs).1 The SRTR and their advisory bodies have dramatically adjusted the statistical models used to predict graft failures and deaths. Features of the new kidney transplant risk adjustment equations include complex statistical adjustments (linear base rates with 6 splines) to characterize the risk of deceased donor organ quality, as measured by Kidney Donor Profile Index (KDPI), a remapping of Kidney Donor Risk Index onto a cumulative percentage risk scale. These equations attempt to adjust for the marked differences in donor and recipient characteristics between programs. What does this more complicated modeling of organ quality risk mean for transplant centers?

In the era of public reporting, a common response by transplant programs facing or fearing regulatory performance evaluations is to adopt more conservative transplant candidate acceptance and organ selection. KDPI appears to be an exponential driver of discards, such that the discard rate of recovered high KDPI kidneys is >50%.2 Recently, Schold et al examined SRTR data for 315,000 kidney transplant candidates and demonstrated a striking increase in the frequency of waitlist removals at centers with higher numbers of performance evaluations.3 These removal practices were associated with a decline in transplant rates, driven by lower rates of deceased donor transplantation – so access appears to suffer.

While clearly impacting organ utilization and transplant access, the question becomes, “Does conservative behavior protect centers from regulatory sanctions?” Based on SRTR data for the June 2015 cohort, Snyder et al found that while there was a clear relationship between KPDI and increased risk of graft failure and recipient death, this correlation disappeared after applying the SRTR risk adjustment models.4 In other words, there was no relationship between a program’s use of high-KDPI kidneys and poor performance evaluations after risk adjustment. In the new models, the risk captured by KDRI is characterized with even greater granularity. Furthermore, no center was flagged based solely on poor outcomes for high risk organs.

Unfortunately, the inference that centers should be more aggressive in their use of high KDPI organs as a straightforward solution to the discard problem is, in fact, not so clear cut. While having predictive value, KDPI as may incorrectly forecast post-transplant outcomes. The C-statistic for KDPI has been quantified as ~0.6, indicating a substantial portion of unexplained variation. The reasons for unexplained risk include a strong reliance on donor age which may be associated with wide variation in kidney function. Terminal serum creatinine elevated by acute kidney injury may underestimate organ quality. The risk of donor hepatitis C seropositivity may also be lowered in the era of new antiviral therapies. Unmeasured factors commonly used in clinical practice to evaluate organ quality, such as percentage fibrosis on biopsy and pulsatile perfusion parameters, are not included in KDRI. They are also difficult to standardize due to variation, such as biopsy sampling and interpretation by pathologists with varying experience under time pressure.

The “revised” Kidney Allocation System was designed to address some of these issues by offering the KPDI>85 kidneys through a separate allocation system. However, this binary distinction (above or below 85) allows organs of varying quality to be offered under essentially the same allocation system. Under this system acceptance of organs with high KPDIs may not substantially reduce the time a given candidate must wait for “better offer” to offset the clear risk of earlier graft failure. Further, even with improved capture of the risk of graft failure and death to mitigate the impact on center outcome evaluation, these organs have been associated with more post-transplant complications (including the need for dialysis) which increase costs and length of stay. As there is no payment adjustment for this risk, higher risk transplantation may not be financially viable for some centers.

What approaches may appropriately motivate use of organs that are currently discarded, but could benefit some patients over dialysis? Proposed strategies include true fast-tracking of allocation of high KDPI organs, including preferential access for centers that routinely use these organs and achieve good outcomes.5 Tiered payer reimbursement to account for higher expected complication costs has also been recommended.

The UNOS Collaborative Innovation and Improvement Network (COIIN) project was recently launched as a HRSA-sponsored collaborative learning initiative designed to examine risk acceptance behavior, alternative monitoring, and practice improvement rough a direct coaching model.6 The planned 3-year project enrolled a cohort of 19 diverse transplant programs – while ultimately the program may guide best practices, more time is needed to impact broader care.

For now, transplant centers must maintain real-time vigilance of program performance and an ability to assess individual case risk, considering measured and unmeasured factors. While transplant risk prediction is still an imperfect science, decision analytics have suggested the “break even” times for patient-level survival benefits from acceptance of higher risk organs compared to waiting on dialysis.7 Such models can be used to guide surgeon decision-making and patient counseling. Critically, ongoing awareness of observed and expected adverse outcomes in current and upcoming regulatory cohorts is necessary for centers to make informed decisions, such as when accepting the uncertainty of a higher risk organ can be acceptable for their patients without compromising the performance rating of their program.


References

  1. Scientific Registry of Transplant Recipients (SRTR). Program-specific statistics on organ transplants. http://www.srtr.org/reports-tools/program-specific-reports/.
  2. Stewart D. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons. 2013;13 (S5): 123-124.
  3. Schold JD, Buccini LD, Poggio ED, Flechner SM, Goldfarb DA. Association of Candidate Removals From the Kidney Transplant Waiting List and Center Performance Oversight. American journal of transplantation 2016;16(4): 1276-1284.
  4. Snyder JJ, Salkowski N, Wey A, et al. Effects of High-Risk Kidneys on Scientific Registry of Transplant Recipients Program Quality Reports. American journal of transplantation. 2016;16(9): 2646-2653.
  5. Reese PP, Harhay MN, Abt PL, Levine MH, Halpern SD. New Solutions to Reduce Discard of Kidneys Donated for Transplantation. J Am Soc Nephrol. 2016;27(4): 973-980.
  6. COIIN project studying effective practices at model hospitals, OPOs. UNOS Newsroom, April 24, 2016. https://optn.transplant.hrsa.gov/news/coiin-project-studying-effective-practices-at-model-hospitals-opos/.
  7. Massie AB, Luo X, Chow EK, Alejo JL, Desai NM, Segev DL. Survival benefit of primary deceased donor transplantation with high-KDPI kidneys. American journal of transplantation. 2014;14(10): 2310-2316.
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