Are the baseline chances of survival comparable between the candidates for kidney transplantation who actually receive a graft and those who never get one?

Alberto Vianello1,, Michela Spinello3, Giuseppe Palminteri2, Anna Brunello2, Gilberto Calconi2 and Maria-Cristina Maresca2

1 Division of Nephrology, Feltre General Hospital, 2 Treviso Transplant Center, Treviso General Hospital and 3 University of Padova School of Nephrology, Italy



   Abstract
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. The superiority of kidney transplantation over dialysis for patient survival often is assessed by comparing the survival rate of candidates who get a graft to that of those on the waiting list who do not. This study tries to ascertain if the two groups are comparable in terms of their chances of surviving.

Methods. Of the 187 non-diabetic patients who entered our waiting list during 1998 and 1999 for first cadaveric kidney transplants, 81 received a graft and 106 did not. We compared the two groups for factors which could affect survival and that were present at the moment of acceptance on the list. As one of those factors was the clinical score quantifying health status, as given by the transplant team and rated from 1 (high risk) to 4 (very good), we assessed its reliability by evaluating the survival of the patients we transplanted between 1988 and 1996, grouped according to that score.

Results. Transplanted patients had been immunized less frequently (2 vs 13%; P=0.02), had a lower dialytic age (16.9±2.1 vs 22.9±2.1 months; P<0.05), and better clinical scores (2.9±0.1 vs 2.6±0.1; P<0.05). The two groups did not differ in age, gender, or the presence of single specific diseases. Logistic regression analysis confirmed the results of univariate analysis. The clinical score was a very strong predictor of patient survival, as the survival of patients transplanted from 1988 to 1996 progressively improved with better scores (P<0.0001).

Conclusions. Transplanted patients actually differ from non-transplanted candidates with respect to various factors potentially affecting survival. The difference is highly relevant clinically, yet it is not easily detected when considering mainly the presence or absence of specific diseases. A global quantitative clinical parameter based on a thorough medical evaluation is required to identify differences.

Keywords: cadaveric kidneys; dialysis; immunization; patient survival; renal transplantation; waiting lists



   Introduction
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
It has repeatedly been demonstrated that uraemic patients who undergo cadaveric kidney transplantation survive longer than patients on the kidney graft waiting list who never receive a graft [15]. This has prompted the suggestion that cadaveric kidney transplantation prolongs the survival of those who receive it [5,6].

This suggestion rests, however, on the assumption that the basal chance of survival of patients who receive a transplant is comparable with that of those on the cadaveric kidney graft waiting list who never received a graft. Although apparently sound, this assumption, on deeper analysis, appears to have several faults. In fact, patients who never receive a transplant despite being on the kidney transplant waiting list differ in many aspects from the other group; they are more likely to have been immunized, they have been reported to be older [4,7], and differences in gender and race have been reported as well [7], not to mention possible socioeconomic differences [8]. Hence, it is reasonable to suspect that the survival potential of the two groups may actually differ.

The aim of our study was to evaluate specifically whether waiting-list patients who never received a transplant and those who actually were transplanted were comparable with regard to factors likely to affect patient survival.



   Subjects and methods
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 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Between January 1, 1998 and December 31, 1999, 187 non-diabetic patients were accepted to the waiting list at our centre for a first cadaveric kidney graft. A detailed review of the clinical records of these patients was undertaken. For this purpose, chronic liver disease was defined as a 2-fold increase of ALT lasting 6 months or longer. Heart disease was defined as a history of myocardial infarction, coronary surgery or angioplasty, or the use of inotropic agents, anti-arrhythmics or nitrates. Peripheral vascular disease was defined as intermittent claudication or absence of peripheral pulses, and confirmation of clinical diagnosis by arteriograms or Doppler ultrasound findings. Hypertension was defined as the use of anti-hypertensive therapy. Tumours and tuberculosis were imputed on the basis of previous hospital discharge diagnoses.

The form for enrolment on the waiting list of our organization (North Italian Transplant, NITp) also required that at the moment of acceptance to the list, a global evaluation be made of the health status of the patient and the predictable outcome of the transplant (nephrologic evaluation). Accordingly, patients were classified into one of the following four categories: high-risk candidates, fair candidates, good candidates, and very good candidates. In our centre, these categories are given scores (clinical score) of 1, 2, 3, and 4, with the lowest score corresponding to the high risk and the highest to the very good candidate.

The evaluation was performed by one of the five nephrologists on the transplant team of our hospital. According to our policy, doubtful cases were discussed jointly by two to five members of the team. Although inevitably subjective, the nephrologic evaluation was based on criteria that were relatively universally accepted by members of the staff and had been applied for years by the same doctors. They depended mainly on history, laboratory data, and result of instrumental examinations available at the time of acceptance to the waiting list. Our indicative criteria for patient classification are given in Table 1Go. It must be stressed, however, that each patient was classified according to the global evaluation of his/her particular case, and not necessarily in strict accordance with those criteria. A strong suspicion of very poor compliance was a reason for a poor score. Patients were nearly always considered as high risk (score 1) if over 60 years old. As present analysis included only patients with no previous transplants, and at our centre PRA was not known at the time the candidates were evaluated and accepted to our first transplant waiting list, immunologic factors were not considered when giving the clinical scores to these patients. Clinical factors were by far the most important determinants of the ascribed scores. Surgical risk was evaluated separately, as a separate surgical score, and was not considered here.


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Table 1.  Criteria for classification of patients according to clinical score

 
We chose the starting point of our analysis, January 1988, because from that date on, graft assignment at our organization was based on an algorithm which took into account immunization, HLA matching, donor/recipient age ratio, and waiting time [9]. The clinical condition of the patients and their clinical scores were not considered in the assignment process.

The characteristics of the patients are summarized in Table 2Go.


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Table 2.  Characteristics of the 187 non-diabetic patients on our first cadaveric kidney transplant waiting list at time of acceptance to the waiting list

 
By March 15, 2000, 81 of the previously considered patients had received a kidney transplant. We compared those who received a transplant (n=81) with those who did not (n=106), taking into account the parameters listed in Table 2Go.

In the same period, 116 kidney transplants were performed at our transplant centre. We reviewed the transplant records, checking if the first candidate (with negative cross-match) received a graft or not and, if not, why he or she had been excluded. We also reviewed the data forms of each candidate. Complete data was available on 108 cases. The first candidates to transplantation with negative cross-matches were divided into three groups: those who received a transplant (n=66), those who did not because they were considered to be unsuitable candidates due to intercurrent disease at the time of being called (n=30), and those who did not due to other reasons (n=12). The three groups were compared for clinical scores.

In order to check the reliability of the clinical scores given at our centre, we analysed the survival of the 277 non-diabetic patients who received a first cadaveric kidney transplant at our centre between January 1, 1988 and December 31, 1996. The clinical scores given at the time of acceptance to our cadaveric transplant waiting list were available in 250 cases, divided as follows: score 1, 17; score 2, 49; score 3, 135; score 4, 49. The same physicians who assigned scores to the previous groups of patients also gave the scores to the patients in the present group. Patient survival was analysed without censoring at the time of graft loss. Thus, the starting point of the patient survival analysis was the date of transplantation and the end-point was March 15, 2000, or the date of death. The relative importance for a patient's survival of clinical score, age, and dialytic age was examined by both univariate and multivariate (Cox models) analyses. We could not perform a multivariate analysis of the survival of the 187 patients accepted to our centre's waiting list for cadaveric kidney transplant from 1998 to 1999 owing to the short follow-up (slightly more than 2 years) and the small number of end-points reached (only three patients died—two after having received a graft, and one while still on the waiting list).

Survival analyses were performed with survival curves and Mantel–Cox statistics, and Cox models. Groups were compared with the Levene F variability test and with either the classical Student's t-test in case of a negative Levene F-test, or otherwise with the separate variance (Welch) test, and the {chi}2-test, with Yates correction for 2x2 tables and the two-tailed Fisher's exact test when needed. Clinical scores were compared with the Mann–Whitney test. Prognostic factors for receiving a kidney graft in patients on the waiting list were identified by logistic regression analysis (with both backward and forward entrance of variables).

Data is expressed as mean±SEM (range) or as percentage, unless otherwise specified. A two-tailed value of P<0.05 was considered as significant.



   Results
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 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
The characteristics of the group of patients who received a cadaveric kidney transplant and the group that did not are presented in Table 3Go. Patients who received a kidney transplant had a significantly lower rate of immunization, significantly lower dialytic age, and significantly higher clinical scores in univariate analysis.


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Table 3.  Characteristics of patients who received or did not receive a kidney transplant

 
Logistic regression analysis confirmed the results of univariate analysis. In fact, as reported in Table 4Go, when the same variables of Table 3Go were entered in both a forward and a backward manner into logistic regression analysis, in order to differentiate patients who received a cadaveric kidney graft from those who did not, the best model (C.C. Brown, P=0.990) which predicted receiving a cadaveric kidney always was that which considered immunization (yes or no), dialytic age, and clinical score. Therefore, the probability of transplantation was higher in non-immunized patients with low dialytic age and good clinical scores.


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Table 4.  Logistic regression analysis: prediction of receiving a first cadaveric kidney graft

 
The characteristics of patients according to their status of immunization are shown in Table 5Go. Compared with non-immunized patients, immunized patients were significantly older and had significantly lower clinical scores. They also had higher dialytic age and higher frequencies of hepatotropic viruses and cardiovascular disease, but the differences between the groups were not statistically significant.


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Table 5.  Characteristics of the patients according to immunization

 
The analysis of the files of the 108 cases (over 116) of cadaveric kidney grafts performed from January 1, 1988 to March 15, 2000, for which lists of cross-match-negative candidates were available, demonstrated that in 66 (61%) cross-match-negative cases first candidates received the graft, whereas in 30 cases (28%) first candidates did not receive a graft because they were temporarily excluded from transplantation because of intercurrent disease, and in 12 cases (11%) first candidates were not chosen because of non-clinical reasons (refusal by patients in five cases, time shortage preventing transplantation within 24 h of cold ischaemia in three cases, recovery of renal function in one case, excessive difference between donor and recipient age in one case, and other reasons in two cases). The clinical scores of the three groups were 2.7±0.1 (1–4) for those who were transplanted, 2.7±0.2 (1–4) for those who were not transplanted because of non-clinical reasons, and 2.5±0.2 (1–4) for those who were not transplanted due to a particular disease at the time of the call (P not significant).

The predictive value for post-transplant survival of the clinical scores allocated to patients at our centre is shown in Figure 1Go. There was a highly significant difference in patient survival between the four scores (Mantel–Cox P<0.0001), with survival progressively decreasing from the score of 4 (100% survival at 10 years) to the score of 1 (about 40% survival at 10 years). According to Cox models (Table 6Go), the best model predicting patient survival (P<0.0001) consisted of age and clinical score. On univariate analysis dialytic age also was negatively correlated with patient survival—depending largely upon the cut-off points chosen (data not shown), but its value was lost in multivariate analysis when age and clinical score also were considered. Graft loss also affected patient survival negatively, but its addition to the model consisting of age and clinical score enhanced the predictive power very little (improvement of {chi}2 P=0.12).



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Fig. 1.  Survival of non-diabetic recipients of first cadaveric kidney transplanted between January 1, 1988 and December 31, 1996, divided according to clinical scores given at the time of acceptance to the recipient waiting list. Clinical scores range from 1 (high-risk candidates) to 4 (very good candidates). The difference between groups is highly significant (Mantel–Cox P<0.0001).

 

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Table 6.  Survival analysis with Cox models: predictive factors of patient death after receiving a primary kidney graft

 
Of the 187 patients accepted to our waiting list in 1998 and 1999, three died, two of them at 5 and 10 months after transplantation, and one while still waiting for a graft. Their ages ranged between 55 and 63 years at the time of enrolment and one of them had a clinical score of 2 while the other two had scores of 3.



   Discussion
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 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Our results clearly show that, despite comparable waiting periods, candidates who received a cadaveric kidney graft at the time of admission on the waiting list differed from those who did not for at least three characteristic features: immunization, dialytic age (shorter in the group that received a graft), and clinical scores. Those who received a graft had higher scores.

Dialytic age has previously been found to be associated with reduced patient survival [10,11]. According to Table 5Go, immunization was associated with older age, which by itself affected patient survival, and with lower clinical score; the importance of the latter needs to be discussed. In fact, according to our data the clinical score appeared both as an independent factor predicting transplantation and an important parameter different between immunized and non-immunized patients.

Although necessarily subjective, the assigned clinical score is probably the best reliable measure of overall, clinically relevant health status. It is more reliable than the simple presence or absence of any single disease such as cardiovascular disease, hypertension, etc. In fact, it simultaneously takes into account the presence and severity of all diseases present in an individual, their interrelations, and their impact on health status. It must be stressed that the physicians who performed the nephrologic evaluations were unaware at that time that their evaluations might be used for the present analysis. It is worth noting also that the two groups of our subjects (those who received a graft and those who did not) did not differ in any of the single risk factors considered such as cardiovascular disease or infections. Therefore, without the clinical score, they would have been considered to be comparable (Table 3Go). The same happened when patients were divided into PRA-positive and PRA-negative recipients (Table 5Go).

The short follow-up and the very low mortality rate (actuarial survival rate of the 187 candidates: 92.91±0.04% SE at 26 months) of our subjects prevented meaningful direct analysis to be performed on the impact on patient survival of kidney transplantation or of other potentially important factors, such as the clinical score. The fact that two out of three patients died shortly after receiving a graft seems to confirm, however, previous reports that kidney transplantation does in fact increase the risk of death at least in the immediate period after surgery [3,4].

The reliability of the clinical scores assigned at our centre is an obvious problem; a potential weakness that needs to be addressed. The answer is shown in Figure 1Go. There was a highly significant correlation between patient survival and clinical score, at least after transplantation. As we were not able to perform a similar analysis on the 187 patients accepted to our cadaveric kidney waiting list, we cannot automatically assume that a similar correlation would have existed independently from transplantation, although such a conclusion seems reasonable. We can say at least that by applying the survival function consisting of clinical score and age, as identified by the Cox model in our non-diabetic recipients of first cadaveric kidney grafts, if all the 187 candidates for transplantation had been transplanted the 81 who actually were transplanted, would have enjoyed a 27% lower risk of dying than the 106 who actually were not transplanted, a difference due to their baseline clinical situations.

Therefore, we suppose that, based on clinical score, candidates who received a graft had better a chance of survival than candidates who did not.

Given that kidney graft allocation at our organization was based on an algorithm, which did not take into account the nephrologic evaluation and tended to favour candidates who had been waiting longer, our results may seem surprising. In fact it may appear sound to presume that, using an algorithm such as ours, candidates for transplantation who actually receive a graft should be absolutely comparable in terms of clinical status with those who do not, or have longer dialytic ages.

Keeping in mind that candidates for transplantation widely differ in terms of health status, we propose two hypotheses to explain our results.

The first is that even when using the algorithm, subjective selection of candidates still is possible. Thus, a centre may favour candidates in a better general health within the extremely restricted list of candidates with roughly similar scores according to the algorithm. However, our analysis of transplants performed in recent years revealed that clinically adequate first candidates with a negative cross-match were passed in only about 11% of cases. Even in those cases the reasons for not choosing the first candidates clearly were not related to health status in six cases (5.5%) (refusal of the patient and recovery of renal function), very likely not related to health status in four cases (3.7%), even if the reasons for not performing transplantation might be considered specious (excessive cold ischaemia time and excessive difference between donor and recipient age), but possibly related to health status in only two cases (1.8%). Therefore, a subjective choice of the candidates may have occurred in only 1.8–5.5% of cases. In line with the low probability of such an occurrence, the clinical scores of the candidates who did not receive the grafts due to non-clinical reasons, despite being first on the list, were comparable with those of the candidates who were transplanted.

The second, and more probable explanation of our results is health status itself—which may impair the chance of getting a graft in various ways. First, from the analysis of the reasons why the first candidates for transplantation did not receive a graft it follows that 28% of patients were considered to be temporarily unsuitable for transplantation because of an intercurrent disease. We propose that the poorer the health status of the candidate, the higher the possibility of being temporarily unfit for transplantation when called. Accordingly, the clinical scores of the candidates who were not transplanted due to transient illness were lower (although not significantly so) than those of patients who either were transplanted or were not due to non-clinical reasons. Secondly, immunization is an obvious factor, which reduces the possibility of being transplanted; we showed, however, that immunization also was associated with a poorer health status (Table 5Go), possibly because the poorer the health status, the higher the need for transfusions—which in turn may cause immunization. Thirdly, dialytic age itself is associated with a reduced patient survival and may favour the development of diseases [10], which may impair the possibility of being grafted upon a call. Finally, the poorer the health status, the higher the chance of further deterioration over time—resulting in the exclusion from the waiting list, thus limiting tenure on the waiting list, and the chance of transplantation.

Accepting the latter hypothesis implies that kidney graft allocation, independently from any deliberate intervention, is by itself a biased process, which favours healthier candidates, even within the selected group of uraemic patients accepted to the recipient waiting list.

The relatively short follow-up of our patients also should be stressed. Other factors potentially affecting patient survival such as age [4,7] have been reported to be significantly different between candidates who receive grafts and those who do not. We could not confirm the importance of age in the selection process. In fact, patients who received a graft were younger, but the difference (1 year) was clinically irrelevant and not significant. It is possible, however, that a longer follow-up might have accentuated the difference.

In conclusion, our results demonstrate that candidates who receive a kidney graft may be different from candidates who do not in terms of their chances of survival. The difference between the two groups of patients may be too subtle to be detectable by simple statistical analysis of the presence or absence of single risk factors, yet that difference seems to be clinically relevant. Any comparison of the two populations requires extreme caution, and conclusions based on that comparison may be unwarranted. We also propose that kidney graft allocation by itself is a selective process, which favours healthier candidates.



   Notes
 
Correspondence and offprint requests to: Alberto Vianello, MD, Division of Nephrology-Haemodialysis Unit, Feltre General Hospital, Via Bagnols Sur Ceze, 1, I-32032 Feltre (BL), Italy. Email: modevian{at}hotmail.com Back



   References
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

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Received for publication: 9. 9.00
Accepted in revised form: 25. 7.01





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