Predictive Value of Serum Creatinine for Renal Allograft Loss
Predictive Value of Serum Creatinine for Renal Allograft Loss
Both medical care and pharmaceutical development have led to an increase in expected graft and patient survival for patients who undergo renal transplantation. From a research perspective, it has become increasingly difficult to study the efficacy of new therapies using traditional 'hard' endpoints. In reaction to this dilemma, the transplant community has sought a surrogate endpoint. A natural candidate for a surrogate marker for graft loss that has been proposed is renal function (serum creatinine or calculated GFR levels).
Using data from the USRDS, we conducted a retrospective evaluation of transplant data from 1988 to 1999 to quantify the predictive value of renal function for the outcomes of graft loss, death-censored graft loss, and patient death.
Renal function along with the change in renal function demonstrated a high relative risk for ultimate graft survival and graft loss (odds ratio = 2.2 for an increase of 1 mg/dL). However, the predictive value as measured by the area under the receiver operating characteristic curve (AUC) for this criteria was poor (0.627). These findings held true for the slope of creatinine and formulations of GFR.
While renal function is a strong risk factor and highly correlated with graft failure, the utility of renal function as a predictive tool for graft loss is limited.
The treatment and care for patients with kidney transplantation in the past decade has steadily improved. Both medical care and pharmaceutical development have led to a steady increase in expected graft and patient survival for patients who undergo this procedure. In addition, acute rejection rates continue to decrease annually. From a research and novel therapy development perspective this has led to a diminished ability to study the efficacy of treatments within a relatively short time period. If these traditional endpoints are the only acceptable assessment of novel therapies, ever increasing periods of study time and patient numbers will be needed to confirm the efficacy of these newer treatments or strategies. This may lead to prolonged evaluation of ineffective treatments, or, in a similar fashion, delayed acceptance of beneficial treatment modalities. Furthermore, pharmaceutical development costs may increase to the point that the possibility to study new drugs becomes increasingly limited. As a result, there has been a concerted effort among the transplant community to attain a diagnostic that may serve as a surrogate for eventual graft loss. A surrogate endpoint for graft loss could allow for more rapid evaluation of drug therapies, transplant techniques, and patient care protocols. A natural candidate for this surrogate endpoint that has been considered in recent literature is renal function. Creatinine levels at 1-year post transplant and changes in creatinine levels have been shown to demonstrate a strong association between poor renal function and declining renal function, respectively, with worse graft and patient survival.
While there is no disagreement concerning the strong correlation of renal function and renal transplant outcomes, caution is advised in extrapolating this correlation as predictive of the endpoint to which it serves as a surrogate. In establishing highly associated diagnostics as predictive entities, further steps of validation are required. Additionally from a statistical point of view, the interpretation of correlated values as possessing cause and effect relationships, particularly in retrospective analyses, is problematic. This point can be particularly important when counseling patients and in the decision of new clinical trials. While it may be natural to pursue assessing correlated variables as to their prediction potential, different statistical procedures must be conducted to evaluate the efficacy of variables to serve this purpose. In order to determine whether renal function can adequately serve as a predictor, and to add information regarding the acceptability of renal function as a surrogate (or substitute) endpoint for graft loss, we conducted an analysis attempting to quantify the predictive properties of renal function for graft loss from data available in the USRDS database.
Both medical care and pharmaceutical development have led to an increase in expected graft and patient survival for patients who undergo renal transplantation. From a research perspective, it has become increasingly difficult to study the efficacy of new therapies using traditional 'hard' endpoints. In reaction to this dilemma, the transplant community has sought a surrogate endpoint. A natural candidate for a surrogate marker for graft loss that has been proposed is renal function (serum creatinine or calculated GFR levels).
Using data from the USRDS, we conducted a retrospective evaluation of transplant data from 1988 to 1999 to quantify the predictive value of renal function for the outcomes of graft loss, death-censored graft loss, and patient death.
Renal function along with the change in renal function demonstrated a high relative risk for ultimate graft survival and graft loss (odds ratio = 2.2 for an increase of 1 mg/dL). However, the predictive value as measured by the area under the receiver operating characteristic curve (AUC) for this criteria was poor (0.627). These findings held true for the slope of creatinine and formulations of GFR.
While renal function is a strong risk factor and highly correlated with graft failure, the utility of renal function as a predictive tool for graft loss is limited.
The treatment and care for patients with kidney transplantation in the past decade has steadily improved. Both medical care and pharmaceutical development have led to a steady increase in expected graft and patient survival for patients who undergo this procedure. In addition, acute rejection rates continue to decrease annually. From a research and novel therapy development perspective this has led to a diminished ability to study the efficacy of treatments within a relatively short time period. If these traditional endpoints are the only acceptable assessment of novel therapies, ever increasing periods of study time and patient numbers will be needed to confirm the efficacy of these newer treatments or strategies. This may lead to prolonged evaluation of ineffective treatments, or, in a similar fashion, delayed acceptance of beneficial treatment modalities. Furthermore, pharmaceutical development costs may increase to the point that the possibility to study new drugs becomes increasingly limited. As a result, there has been a concerted effort among the transplant community to attain a diagnostic that may serve as a surrogate for eventual graft loss. A surrogate endpoint for graft loss could allow for more rapid evaluation of drug therapies, transplant techniques, and patient care protocols. A natural candidate for this surrogate endpoint that has been considered in recent literature is renal function. Creatinine levels at 1-year post transplant and changes in creatinine levels have been shown to demonstrate a strong association between poor renal function and declining renal function, respectively, with worse graft and patient survival.
While there is no disagreement concerning the strong correlation of renal function and renal transplant outcomes, caution is advised in extrapolating this correlation as predictive of the endpoint to which it serves as a surrogate. In establishing highly associated diagnostics as predictive entities, further steps of validation are required. Additionally from a statistical point of view, the interpretation of correlated values as possessing cause and effect relationships, particularly in retrospective analyses, is problematic. This point can be particularly important when counseling patients and in the decision of new clinical trials. While it may be natural to pursue assessing correlated variables as to their prediction potential, different statistical procedures must be conducted to evaluate the efficacy of variables to serve this purpose. In order to determine whether renal function can adequately serve as a predictor, and to add information regarding the acceptability of renal function as a surrogate (or substitute) endpoint for graft loss, we conducted an analysis attempting to quantify the predictive properties of renal function for graft loss from data available in the USRDS database.
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