Predicting long-term outcomes of graft survival

[pelagia]

Hope this is not a cross-post:

http://www.medpagetoday.com/Nephrology/KidneyTransplantation/12549

Living-Donor Kidney Transplant Nomograms Predict Long-Term Outcomes

By Crystal Phend, Staff Writer, MedPage Today
Published: January 22, 2009
Reviewed by Zalman S. Agus, MD; Emeritus Professor
University of Pennsylvania School of Medicine.

CLEVELAND, Jan. 22 -- A tool to calculate long-term outcomes with living-donor kidney transplants may aid in choosing among potential donors, researchers said.

Nomograms developed from the United Network for Organ Sharing registry predicted kidney function at one year and graft survival at five years with generally good accuracy, David Goldfarb, M.D., of the Cleveland Clinic, and colleagues reported in the March issue of the Journal of Urology.

Since 2001, the use of living donors for kidney transplants has exceeded deceased-donor procedures. This shift creates choices for patients and physicians, the researchers said.

"A transplant candidate may now have several potential living donors," they said, "and clinicians are asked to identify which donor would yield the most optimal post-transplant graft function and long-term outcome."

Whereas the many factors that contribute to deceased-donor graft survival center on quality of the organ before and after cold ischemia, living-donor selection relies more on determination of nephron mass and immunological, recipient, and procurement factors.

Since no single factor sufficiently predicts outcomes, the researchers developed nomograms to reconcile the chance of success based on multiple variables.

They used data from 20,085 living-donor renal transplant cases included in the United Network for Organ Sharing registry for 2000 to 2003.

The first nomogram predicted one-year estimated glomerular filtration rate based on patient and donor data available before transplantation including demographic and immunological factors, immunosuppressive therapy, and organ procurement technique.

This algorithm worked best when predicting estimated glomerular filtration rate values between 50 and 70 ml per minute per 1.73 m2.

Although the overall r-square value of 0.13 suggested a modest predictive ability, the researchers noted that no other tools are available. "This initial prototype will require refinement to enhance its predictive capability."

A second nomogram predicted five-year graft survival using the same set of pretransplantation variables with good accuracy. Its concordance index of 0.71 was comparable to those of widely used and validated nomograms to predict kidney cancer and sarcoma outcomes (0.74 and 0.77, respectively), the researchers said.

A third nomogram also predicted five-year graft survival but incorporated additional patient data from the first six months after transplantation regarding delayed graft function, any treated rejection episodes, and the six-month estimated glomerular filtration rate.

This dynamic nomogram performed even better with a concordance index of 0.78.

The investigators noted that prior experience with nomograms for graft survival hasn't always shown good clinical correlation in unique smaller populations.

However, "nomograms have been shown to outperform clinicians in predicting oncological outcomes and may be of benefit in certain decision-making settings," they said.

Not only can these tools reconcile the multitude of outcome-related parameters and allow physicians to better counsel patients, but objective prognostic information can improve individualization of post-transplant care, Dr. Goldfarb's group added.

"For example, closer follow-up, targeted immunosuppressive tailoring, or more aggressive treatment of modifiable risk factors can be implemented for patients at greater risk for suboptimal graft function or survival," they wrote.

They noted several caveats regarding use of the nomograms.

"Care is needed when drawing generalizations from predictive tools based on large registry data applied to unique smaller populations," they said.

They also noted that drawing lines and adding points on the nomogram figures can be cumbersome, so Internet software, currently in development, will be welcome. Finally, they noted, "a theoretical concern is the potential for abuse of the nomograms when they are used to select potential donors because recipients may be encouraged to shop around for the best possible donor." "Ultimately transplant physicians should retain clinical judgment with the help of these nomograms to counsel their patients," the researchers concluded, "because there are other factors such as patient compliance which can impact outcomes but are difficult to characterize."

The study was supported by a contract with the Health Resources and Services Administration.
The researchers reported no conflicts of interest.

Primary source: Journal of Urology
Source reference:
Tiyong HY, et al "Nomograms for predicting graft function and survival in living donor kidney transplantation based on the UNOS Registry" J Urol 2009; 181: 1248-1255.


 

 
 
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[pelagia]

the actual article is at this link:

http://www.jurology.com/article/S0022-5347(08)03012-7/fulltext

I've posted one of the nomograms below (a nomogram is a graphical depiction of numerical data).  If you had a transplant from a living donor more than 6 months ago, you can use this nomogram to predict your five year graft survival probability.  But, please remember that this is just a statistical prediction. 

Here's the figure caption.

Figure 3. A, nomogram predicting 5-year graft survival based on information at before transplant and 6 months after transplant. Instructions: first row (Points) is point assignment for each variable. Rows 2 to 22 represent variables included in model. For each donor-recipient pair each variable is assigned point value (uppermost scale, points). Vertical line is made between appropriate variable value and points line. Assigned points for all variables are summed and total is found in row 23 (Total Points). Once total is located vertical line is made between total points and final row 24 (5-Year Graft Survival Probability). W, white. B, black. O, other. D, diabetes. G, glomerulonephritis. R, re-transplant. B, calibration curve for internal validation. Diagonal line represents performance of ideal nomogram in which predicted outcome corresponds perfectly with actual ones. Line with vertical boxes represents performance of constructed nomogram. Vertical boxes indicate 95% confidence intervals based on bootstrapping analysis. Concordance index of this nomogram was 0.784.