Kidney Transplantation in the Elderly: A Decision Analysis : Journal of the American Society of Nephrology

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Epidemiology and Outcomes

Kidney Transplantation in the Elderly

A Decision Analysis

Jassal, Sarbjit V.*,¶; Krahn, Murray D.†,‡,¶; Naglie, Gary†,§,¶,#; Zaltzman, Jeffrey S.*,¶; Roscoe, Janet M.*,¶; Cole, Edward H.*,¶; Redelmeier, Donald A.§,¶

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Journal of the American Society of Nephrology 14(1):p 187-196, January 2003. | DOI: 10.1097/01.ASN.0000042166.70351.57
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Transplantation is infrequently offered to older persons. Fewer than 5% of those aged ≥ 65 yr begun on dialysis therapy will receive a transplant (1,2). For those selected, the survival rate is favorable (3,4). Case control studies show a survival advantage for transplantation over dialysis, even for those aged over 60 yr of age (2,5), yet kidney transplantation remains controversial for older patients because of the ethical issues surrounding the allocation of scarce organs and the scientific doubts about the efficacy and cost-effectiveness of transplantation in this age group. Many clinicians view dialysis as a stable strategy with an acceptable survival and few short-term risks. In contrast, transplantation, though associated with longer life expectancy and better quality of life, is viewed as having significant risks of short-term morbidity and mortality. The purpose of this study was to use decision analytic modeling to quantify clinical and economic tradeoffs for an older patient considering transplantation.

Materials and Methods

Treatment Population

The study examined a theoretical cohort of nondiabetic patients aged 65 yr or more who were stable on dialysis at the time of the decision. Patients were assumed to be medically fit for transplantation and were excluded if they had ongoing malignancy, active cardiovascular disease, or a chronic infective condition. Additional models were constructed for patients who were known to be diabetic at the time of being placed on the waiting list for transplantation and for those with known cardiovascular disease.

Treatment Options

The two treatment strategies were transplantation and continued dialysis. Dialysis was defined as thrice weekly in-center hemodialysis, as this is the most common treatment modality used. Similarly, we assumed that patients who opted for transplantation would be transplanted with a cadaveric graft, in accordance with common practice in North America. Although immunosuppression regimens differ widely, we assumed that routine therapy included cyclosporin, prednisone, and mycophenolate mofetil (MMF) with substitution or addition of antilymphocyte products or tacrolimus as necessary. Patients who received a graft could return to the dialysis health state but were assumed not to undergo transplantation twice.

Treatment Outcomes

The major clinical events associated with transplantation and with dialysis were summarized using a Markov model programmed in Decision Maker, version 7.0 (6). This technique involves identifying clinically important events and defining them as health “states.” A theoretical cohort of patients cycles from one health state to another, in cycles set at 3 mo, until the time of death.

The model assumed that all patients remained on dialysis until the time of transplantation or, if not transplanted, until death (Figure 1). The model contained six health states: dialysis; transplant; acute rejection (AR); transplant-related complication; AR plus transplant-related complication; and death. The dialysis and transplantation health states include all aspects of health and costs associated with long-term chronic care. Specific dialysis-related complications were not modeled, as the theoretical cohort of patients were considered suitable for transplantation surgery and were therefore assumed to be at low risk for complications. Patients in the dialysis strategy were at zero risk of transplant-related complications.

Figure 1. :
Schematic diagram of model used. Patients could enter one of two treatment arms (shaded) and cycle, every 3 mo, through one of the many health states represented by the circles. Death was considered an absorbing health state (i.e., was a terminal event). Patients who were transplanted could transiently pass through the health states representing a complication, acute rejection, or both rejection and complication, or could lose their transplant and return permanently to the dialysis health state. Patients in either the transplant health state or the dialysis health state could circle continuously through these health states until the time of death. AR, acute rejection; complic, complication.

A small proportion of transplanted patients entered the death health state at the time of transplantation surgery, reflecting perioperative mortality. Those who survived the perioperative period were at risk of developing one or more episodes of AR, transplant-related complication, or a combination of AR and complication. In addition, within each cycle, transplant patients were at risk of sudden death or the resumption of dialysis because of graft loss.

Probabilities were set so that the risk of developing acute rejection was maximal in the first few months, falling exponentially to less than 2% per year by 2 yr. The occurrence of either AR or a complication was assumed to increase the risk of death and the risk of graft loss. Although complications may arise for a variety of clinical reasons, transplant-related complications were grouped as one health state for the purposes of the model. As complications are more common after acute rejection, the overall rate of complications was maximal in the first 2 yr and then fell to a baseline level thereafter.

Four assumptions about mortality were made: perioperative mortality was the same for all patients; mortality related to dialysis was assumed to be constant over time; mortality risk was increased in transplant patients in the presence of either AR or a complication; and the hazard of death was assumed to be additive when a patient had both acute rejection and a complication.

Diabetic patients were considered to be at increased risk of postoperative complications, cardiovascular disease, and death when compared with nondiabetic patients. Drug-induced diabetes was considered as a separate complication in a small proportion of those who received a transplant. We assumed that drug-induced diabetes was life-long, occurred at the time of transplantation, and brought with it the risks of increased mortality and complications described for patients with long-standing diabetes.

Wait-Listed Times

The base case assumed that there was a 2-yr delay between the decision to proceed with transplant and harvesting a suitable organ. In practice, however, patients can either proceed with transplantation with an organ from a live donor or be wait-listed for a cadaveric transplant (3,4). Therefore, subsequent analyses with a wait-time of 0 and 4 yr were also performed. Patients with zero wait-time were assumed to have had a living donor organ and therefore incurred extra costs of organ acquisition. During the wait-listing period, the costs, probabilities, and utilities were those of dialysis patients plus additional costs of the transplant work-up. Thus, the overall benefits and risks of transplantation included those from the time spent on the waiting list as well as those incurred after transplantation. Death while waiting for a suitable organ was also anticipated in a proportion of patients.

Long-Term Outcomes

As patients with end-stage renal failure were expected to be dialysis-dependent for life, the time horizon used for the analysis was the lifetime of the patient. The outcome was measured as life expectancy, both with and without quality-adjustment. Cost-effectiveness was estimated as the incremental cost incurred for each additional quality-adjusted life year (QALY).

Data Sources

Probability values were derived from the literature following a formal MEDLINE search for studies published between 1991 and 2000. When no single study reported the exact probability of an event, an estimate was obtained by combining data from several sources. When multiple studies reported different probability estimates, the studies that most closely represented the population of interest were chosen (e.g., those that focused on an over 65-yr-old population with first cadaveric graft). If multiple studies were relevant, a mean value was calculated and used as the baseline estimate. Data from multiple studies were used to estimate a clinically plausible range for each variable that was used in sensitivity analyses (Table 1).

Table 1:
Baseline probability and utility values (with clinically plausible range)

Life Expectancy for Transplant Patients

Mortality data for dialysis and transplant patients were taken from the United States Renal Data Systems (USRDS). Estimates of transplant and dialysis mortality were validated against published data and that from the Canadian Organ Replacement Register (CORR) (3,7).

We estimated mortality rates in transplant recipients by summing the age-standardized mortality rate (ASR) for the general population and the disease-specific mortality rate for transplantation (810):


We calculated the transplant-specific mortality rate by subtracting the ASR for 65-yr-olds from the overall mortality rate reported by the USRDS for 65-yr-old renal transplant recipients. Thus, the predicted overall mortality rate for each age included both an age-specific general mortality rate and an age-independent transplant mortality rate.

Life Expectancy for Dialysis Patients

Dialysis mortality was estimated from the USRDS mortality rate of wait-listed dialysis patients (11). Patients had been selected as being suitable for transplantation, screened, and then placed on the waiting list. The disease-specific mortality rate for dialysis patients who were otherwise suitable for transplantation was calculated by subtracting the age-specific mortality rate for 65-yr-olds in the general population from the overall mortality rate of wait-listed dialysis patients aged 65 to 70 yr old (8,9,11).

Major Complications

The probability of acute rejection was taken from USRDS data and reported rejection rates with MMF treatment (12,13). Additional studies were used to derive the clinically plausible range (1,1422). Infection rates were estimated from data specifically relating to older patients and from that relating to the large immunosuppressive trials (12,23,24). Other studies were used to establish the clinically plausible range of values (12,15,17,2527). The relative risk of developing a complication after therapy for acute rejection was estimated by calculating the mean rate reported in six studies that examined the effects of two or more antirejection drug regimens and reported complication rates (2833). The probability of graft loss was derived directly from USRDS graft survival rates in >65-yr-old patients (4,34). The increased risk of graft loss or death after acute rejection was estimated from one series that reported the reasons for and exact numbers of grafts lost in an elderly cohort of patients (14). The increased risk of death after a complication was estimated on the basis of the assumption that the risk of death after a complication was higher than after acute rejection. The clinically plausible range of values was calculated using data from those studies used to estimate the clinical risk of a complication (12,15,17,2527). The risk of drug-induced diabetes was estimated by calculating the mean rate reported in several studies (25,3546).

Utility Estimates

Utility estimates were derived from the literature. A MEDLINE search revealed seven studies reporting the utility of dialysis or transplantation using the time tradeoff or the standard gamble methods (4753). One study was clearly superior to others because of its long-term prospective design (it followed dialysis patients through until the time of transplantation) and the specific inclusion of older patients (51). Time tradeoff values reported for patients aged 60 yr or more were used as the baseline estimates. The utility associated with a good transplant (i.e., no dysfunction or comorbidity) and a bad transplant (i.e., multiple problems requiring admission and changes in therapy) were also reported. These, together with information from other reports, were used to determine the clinically plausible range (Table 1) (4753). No data were available on the disutility associated with an episode of rejection, posttransplant complications, or hospitalization for transplant surgery. The analysis assumed a utility of zero for the whole period of hospitalization associated with rejection episodes, complications, or the initial surgery. The duration of hospitalization was estimated from USRDS data on hospitalization and from the Toronto hospital administrative database for the years 1996/7.

Economic Assumptions and Data

The perspective taken was that of the third-party payer. Costs were estimated from published data (35,51,5468). Where appropriate, costs were converted to 1999 US dollars by using the median 1999 exchange rate and the Bureau of Labor Statistics Consumer Price Index (69,70). Health outcomes and costs were discounted at 3% per year (71).

We used Medicare data to estimate the annual cost of both transplantation and dialysis (4,72). Although more accurate cost estimates are available for individual strategies, none of these studies utilize the same methods to derive costs for both transplantation and dialysis. We acknowledge that current reimbursement levels for dialysis may underestimate the true costs of providing this service and would introduce a bias favoring dialysis. However, we believe that using comparably costing methodology for transplantation and dialysis is essential in estimating marginal costs across strategies and that introducing a bias against transplantation was acceptable. Estimates for the annual cost of dialysis, transplant surgery, and transplantation follow-up were $50,829, $62,217, and $9,792, respectively.

Newer immunosuppressive medications, including MMF and tacrolimus, are more commonly used now than in the period from which the cost estimates were drawn. Therefore, the cost of transplant follow-up was increased by an estimated $6027 per year, to include the costs of additional, optional treatment with MMF (65,68). The cost of transplant work-up, transplant surgery, and graft failure were also estimated from Medicare data (4,72).

No data were available from Medicare for the costs of acute rejection or transplant-related complications. One study, comparing the costs associated with different immunosuppressive regimens, reported the cost of all complications (by type of complication) and both inpatient and outpatient rejection (60). These were used to estimate costs associated with acute rejection and complications. The clinically plausible range of costs was estimated from all published data available (4,51,5860,6265,7376) (Table 1).


Transplant survival was modeled to within 0.2% of that reported by the USRDS (4). The modeled transplant survival rates were compared with Canadian data taken from the CORR database (5-yr mortality rate: 34.57%, 34.50%, and 32.00% for model, USRDS, and CORR data, respectively).


Both cadaveric and living donor transplantation increased life expectancy (LE) and quality-adjusted LE (QALE) for patients of all ages and comorbidity subgroups (Tables 2 and 3). A 65-yr-old patient without comorbidity gained 1.2 yr of life and approximately 1.1 QALY with transplantation. Gains in LE and QALE were smaller for patients with diabetes and cardiovascular disease. No age threshold was observed (Table 3). Otherwise, healthy patients continued to gain QALY with transplantation even at the age of 80 yr.

Table 2:
Results for a 65-yr-old patient with and without diabetes or cardiovascular disease with wait-listing times of 0 and 2 yr, respectivelya
Table 3:
Outcomes for otherwise healthy patients for different age and wait-listing periods

Economic Results

The analysis showed that transplantation improved health outcomes at an increased cost (Figure 2). Cadaveric transplantation remained favorable only in those of a relatively young age (<70 yr) without comorbidity. Diabetic patients incurred about twofold higher costs with transplantation than with dialysis because of a higher rate of complications (the additional life years gained from transplantation when aged 65 yr at the time of transplantation equaled 0.7 yr at an incremental cost/QALY of $138,660). Similar results were seen for those transplanted if they had cardiovascular disease (0.7 life-years gained at an incremental cost/QALY of $110,327 when aged 65 yr).

Figure 2. :
Results of analysis by age and comorbidity profile, showing the cost per quality-adjusted life year (QALY) if treated with transplantation compared with dialysis for patients aged 65 to 85 yr at the time of transplantation. The figure assumes a 2-yr wait-listing period. The results for populations with diabetes or cardiovascular disease are also shown. CVD, cardiovascular disease.

Effect of Increased Wait-Listing Interval

The time to transplantation was varied from 0 to 6 yr to reflect the range of possible waiting times. The results showed the survival advantage decreased considerably with increased waiting time. Transplantation, performed without delay, appeared economically attractive (incremental cost/QALY, <$30,000) for 65-yr-old patients. In patients over the age of 80 yr, the incremental cost per QALY was higher compared with those aged ≤ 65 yr, but it remained favorable when compared with the costs associated with providing life-saving dialysis care (incremental cost/QALY for transplantation, $50,000 for those aged 80 yr). Waiting list times of more than 2 yr were associated with a dramatic increase in cost-effectiveness ratios (incremental cost/QALY: $15 000, $68 000, and $193,600 for wait-listed times of 0, 2, and 4 yr, respectively). At 6.7 yr, the QALE of dialysis for a 65 yr-old equaled that of transplantation (Table 3). Transplantation remained economically attractive for a nondiabetic 65-yr-old patient only if a transplant became available within 22 mo of wait-listing.

Sensitivity Analyses

One-way sensitivity analyses were performed for all probability, utility, and mortality estimates. The model was said to be sensitive to the variable if the value at which the QALE was equal with either strategy fell within the plausible range. The results were highly sensitive to the duration of time spent on the waiting list (threshold, 6.7 yr). The threshold for the dialysis mortality rate was significantly lower than the clinically plausible range, thus minimizing the likelihood that an error in the estimate would influence the model results (threshold, 1% per year mortality rate on dialysis). The hypothesis that perioperative mortality rates would increase with age, and therefore limit usefulness of transplantation, was tested by sensitivity analysis. No threshold was found.

With regard to cost-effectiveness, the model was tested across the range of plausible values. Sensitivity analysis shows that the analysis is moderately sensitive to the utility of transplantation. The results were not sensitive to other variables (Figure 3).

Figure 3. :
Results of sensitivity analysis. Figure showing the results of the one-way sensitivity analyses. The incremental cost-effectiveness is shown for variables when tested at the extreme of the clinically plausible values. Model sensitive to variable.


Transplantation has been shown to be superior to dialysis in younger populations (7,11). This study focused on those patients aged more than 65 yr and had no upper age limit. The study has two principal findings. The first is that transplantation offers substantial gains in both LE and QALE for older patients. The benefits are shown to be higher in those receiving a transplant immediately (as with living donor transplantation), than those who are transplanted after a prolonged wait time. As wait-listed times increase, the clinical benefits of transplantation as a treatment strategy for management of the older person with end-stage renal disease decrease dramatically. These data would promote the use of living donor transplants for the older patient. The second finding is that, in comparison with other accepted medical therapies (e.g., coronary artery bypass surgery or the use of enoxaparin DVT prophylaxis), cadaveric transplantation is economically attractive for otherwise healthy patients up to age 70 yr and in the younger elderly with some comorbidity (7779).

In older patients, our data show that transplantation compared with dialysis continues to increase LE at an advanced age, but it does so at increased cost. The data also show that for the older patient the attractiveness of transplantation is highly sensitive to the time spent waiting for the transplant. As no consensus exists for the level at which a cost-effectiveness ratio is economically attractive, the interpretation of our results may vary among readers. Azimi and Welch (80) have shown that most authorities support additional expenditures associated with cost-effectiveness ratios of ≤$61,500/QALY but that they draw different conclusions about cost-effectiveness ratios within the range $61,500 and $11,600,000/QALY. On this basis, we would suggest that transplantation is significantly more attractive for patients aged 65 yr in a center where the wait-listed time is ≤2 yr or for patients aged up to 80 yr where a living donor program exists.

In comparison with previous studies, we focused on the implications of transplantation in the older population. Although one may argue that other disease-specific and comorbidity-associated factors may influence survival with transplantation in patients over 70 yr old, we have attempted to adjust for these factors by using age-standardized mortality rates, wide sensitivity analyses, and separate analyses for populations with CV disease and diabetes. In fact, older age may be associated with benefits with respect to transplantation. For example, acute rejection appears to be reduced in older patients because of a less active immune system (1,13,81,82). Although the elderly do not appear to be at lower risk of infection or chronic graft rejection with standard immunosuppressive regimens, future regimens at modified doses may decrease complications in this age group and increase the graft survival. Dialysis vintage, gender, and race are not adjusted for in this analysis. Thus, in the case of black patients, particularly women, one may expect a higher gain from transplantation than for white patients of the same age and comorbidity profile.

Most analyses in younger patients have shown that transplantation offers prolonged survival and cost savings compared with dialysis treatment (51,59,60,62,65,73,83). Using our model, a patient aged 55 yr who was transplanted after a 2-yr period on the waiting list could expect prolongation of LE by 1.1 yr (estimated LE of 9.2 yr and 8.0 yr with transplantation and dialysis, respectively). Cost-effectiveness after a 2-yr wait for a cadaveric organ showed an incremental cost of $55,237/QALY with transplantation. In contrast to our findings, others have suggested that transplantation results in a longer LE at lower costs (51,62,73). One reason for this discrepancy is potential overestimation of costs and marginal underestimation of survival benefits in younger patients with this model, because utilities for transplantation and dialysis rates and consequences (e.g., death) of acute rejection and infections, hospitalization duration, and costs were derived from data specifically relating to patients aged ≥65 yr. Also, incremental costs per QALY increased with increased time on the waiting list, suggesting that, regardless of age, longer wait times significantly impact on the cost-benefits of transplantation.

The results of our analysis are somewhat conservative because of some assumptions made in the model. First, Medicare charges tend to underestimate the actual costs of providing dialysis care to the standards currently recommended (54,84). In addition, the costs of acute rejection or transplant-related complications reflect those cases, requiring hospitalization rather than those managed in an outpatient setting. These assumptions result in an overestimation of the costs of transplantation and an underestimation of the costs of dialysis. Second, the analysis used pessimistic utilities for the complications of transplantation, again resulting in a bias that favors dialysis. In contrast, the time costs for patients on hemodialysis, in terms of both lost leisure and productivity, are only captured within the utility value for current health thus favoring transplantation.

Renal transplantation has been controversial in older patients. From the clinician’s viewpoint, our results confirm that many older patients may benefit from renal transplantation. However, liberalizing transplant criteria may introduce problems. First, ethical arguments against the allocation of scarce cadaveric organs to older patients may still prevail. Second, advocating that older patients should be accepted for transplantation would only increase the number of potential recipients for each cadaveric organ harvested and thus further prolong the wait-list. We acknowledge that our study does not address the issues of equity or rationing and that individual healthcare providers will need to develop their policies on the basis of local availability. We do, however, advocate financing transplantation, particularly living donor transplantation, in this population.

In conclusion, renal transplantation offers significant LE gains for well-selected patients aged ≤70 yr, with the young elderly having the most economically favorable profile. Transplantation centers should consider the substantial health benefits that could accrue to the elderly in formulating equitable transplant policies. Potential benefits from transplantation would have to be evaluated within the context of local wait-listed times and the local availability of organs.

Funding in the form of a Research Fellowship to SVJ has been provided by the Ontario Government.

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