7 Results

7.1 Demographic and Baseline Data

7.1.1 Donor information

↓42

As expected, according to the definition of the groups the mean donor age was highest in the ESP group: 70.2 ± 4.3 years (range 65-93). Donor age in Control 1 (old to any) was comparable with the ESP group at 69.8 ± 4.2 years (range 65-87), while Control 2 (any to old) was lower at 45.1 ± 15.9 years (range 0,5-86). The distribution of the donor age is displayed in Table 6.

↓43

Table 6: Distribution of donor age

 

age < 50

50 < = age < 65

65 < = age < 70

age > = 70

ESP

0 (0%)

0 (0%)

725 (51.6%)

680 (48.4%)

Control 1

0 (0%)

0 (0%)

255 (57.2%)

191 (42.8%)

Control 2

950 (56.3%)

628 (37.2%)

46 (2.7%)

63 (3.7%)

Interestingly, there were significantly more female donors in the ESP group (54.2%) compared to Control 2 (41.6%). Donor serum creatinine was comparable in all groups (mean ESP: 90.1± 50.1; Control 1: 93.8± 43.0; Control 2: 92.14±57.0). Given the considerably lower age in Control 2, this suggests an approximately 30% higher GFR for Control 2. Mean donor body weight was also comparable in all three groups (ESP: 76.6± 11.3; Control 1: 77.4± 12.0; Control 2: 75.29±16.24). UW was the most commonly used preservation solution in all groups (62.2%) followed by HTK/Bretschneider (34.4%). In Control 2 UW was even more commonly used (66.9%) while HTK/Bretschneider was used slightly more often in the ESP group (38.9%).

The incidence of diabetes and hypertension recorded in the medical history of the donor was highest in the ESP group as indicated in the Table 7 below.

↓44

Table 7: Donor: diabetes and hypertension

 

ESP

Control 1

Control 2

Diabetes mellitus

107 (16.9%)

20 (13.8%)

41 (6.2%)

Hypertension

776 (61%)

206 (55.2%)

410 (27%)

With 75.6% the most common cause of death for donors in all groups was natural death. In the Control group 2 (any to old) the percentage of traumatic cause of death was almost twice as high as in both the ESP and the Control 1 (Table 8).

Table 8: Donor: cause of death

 

ESP

Control 1

Control 2

Total

a. traumatic

218 (15.5%)

74 (16.6%)

499 (29.6%)

775 (22.6%)

b. natural

1177 (83.7%)

368 (82.5%)

1141 (67.6%)

2594 (75.6%)

c. other

11 (0.8%)

4 (0.9%)

47 (2.8%)

62 (1.8%)

7.1.2 Recipient information

↓45

The mean recipient age at time of transplantation was highest in the ESP group at 67.7 ± 2.7 years (range 65-81). Mean age in Control 1 (old to any) was 57 ± 11.1 years (range 19-81) , and in Control 2 (any to old) was as expected according to the definition 63.6 ± 1.43 years (range 60-65). The distribution of the recipient age in defined categories is displayed in Table 9.

Table 9: Age of recipient at time of transplant in categories

 

age < 50

50 < = age < 65

65 < = age < 70

age > = 70

ESP

0 (0%)

0 (0%)

1135 (80.7%)

271 (19.3%)

Control 1

108 (24.2%)

220 (49.3%)

93 (20.9%)

25 (5.6%)

Control 2

0 (0%)

1687 (100%)

0 (0%)

0 (0%)

Once again, there was a difference in gender distribution with significantly more male recipients in the ESP group (64,8%) compared to Control 2 (60%). Mean body weight of the recipient was comparable in all three groups (ESP: 73,5± 13,5; Control 1: 73,1± 14,9; Control 2: 72,9±14,5)

↓46

The primary cause for ESRD is recorded in Table 10 with no apparent differences between the groups.

Table 10: End-stage renal disease of the recipient (categorized)

 

ESP

Control 1

Control 2

Total

a. glomerular disease

366 (26.3%)

149 (34%)

447 (27.1%)

926 (27.4%)

b. interstitial disease (infectious/toxic)

203 (14.6%)

58 (13.2%)

214 (13%)

471 (14%)

c. polycystic / hereditary

203 (14.6%)

66 (15.1%)

341 (20.6%)

587 (17.4%)

d. vascular disease

117 (8.4%)

23 (5.3%)

116 (7%)

249 (7.4%)

e. diabetic nephropathy

131 (9.4%)

40 (9.1%)

147 (8.9%)

309 (9.2%)

f. systemic disease

22 (1.6%)

7 (1.6%)

27 (1.6%)

54 (1.6%)

g. unknown / others

349 (25.1%)

95 (21.7%)

360 (21.8%)

779 (23.1%)

The incidence of diabetes and hypertension reported in the medical history of the recipient was comparable in the three groups as shown in the table below. This information is not part of the Eurotransplant database and thus was only available for the datasets that have been updated.

↓47

Table 11: Pre-existing diabetes and cardiovascular disease in the recipient

 

ESP

Control 1

Control 2

Total

NA

Diabetes mellitus

250 (23.8%)

46 (17.3%)

210 (20.4%)

492 (21.6%)

1155 (33.7%)

Cardiovascular disease

310 (29.6%)

73 (27%)

299 (28.9%)

657 (28.8%)

1149 (33.5%)

An analysis of the time on the waiting and of cold ischemia time list is presented in 7.2.2 and 7.2.3, as this pertains to the primary objectives of the study.

In order to reduce immunological risk, only non-immunized (panel-reactive antibody (PRA) <5%) recipients should be transplanted within the ESP. In our ESP analysis population 22 out of 1405 patients (1.6%) were highly sensitized, the remaining 98.4% complied with the ESP rule. In both of the Control groups the number of highly sensitized patients was significantly higher at approximately 10% (p<0.001).

↓48

Table 12: PRA at transplantation >5%

 

PRA < 5%

PRA > = 5%

Total

p-value

ESP

1383 (98.4%)

22 (1.6%)

1405 (100%)

-

Control 1

402 (90.5%)

42 (9.5%)

444 (100%)

< 0.0001

Control 2

1512 (89.9%)

170 (10.1%)

1682 (100%)

< 0.0001

7.1.3 Matching

In order to allow for local allocation of organs and to keep the cold ischemia times short the ESP allows ABO compatible transplantation disregarding human leukocyte antigen (HLA) matching. In contrast to this ETKAS allocates organs to identical blood group recipients only and tries to minimize HLA mismatch.

As a result, 86.4% of ESP patients compared with 94.4% of patients in Control 1 and 96.1% of patients in Control 2 had the identical blood group as their donor (p< 0.001 for both Controls versus ESP) and the mean (HLA)-mismatch was significantly higher in the ESP group than in both of the Controls (Table 13).

↓49

Table 13 Number of HLA-(A; -B, and –DR) mismatches

 

n

min

Q1

med

mean

Q3

max

SD

p-value

ESP

1406

0.00

3.00

4.00

4.20

5.00

6.00

1.09

 

Control 1

446

0.00

2.00

3.00

2.79

4.00

6.00

1.48

< 0.0001

Control 2

1687

0.00

1.00

2.00

2.04

3.00

6.00

1.44

< 0.0001

The distribution of the number of mismatches is illustrated in the figure below:

Figure 9: Distribution of number of mismatches

↓50

Consequently, the number of class I (HLA-A&B) and class II (HLA-DR) HLA-mismatches was significantly higher for the ESP group as well. 99.7% of ESP patients had at least 1 class I and 92.9% at least 1 class II mismatch. Details are given in Tables 14 and 15.

Table 14: Number of class I HLA mismatches (HLA-A&B)

 

0

1

2

3

4

Total

p-value

ESP

4 (0.3%)

86 (6.2%)

365 (26.1%)

608 (43.5%)

335 (24%)

1398 (100%)

-

Control 1

57 (12.8%)

87 (19.5%)

156 (35%)

116 (26%)

30 (6.7%)

446 (100%)

< 0.0001

Control 2

443 (26.3%)

408 (24.2%)

560 (33.2%)

230 (13.6%)

46 (2.7%)

1687 (100%)

< 0.0001

Table 15: Number of class II HLA mismatches (HLA-DR)

 

0

1

2

Total

p- value

ESP

99 (7.1%)

712 (50.9%)

587 (42%)

1398 (100%)

-

Control 1

128 (28.7%)

260 (58.3%)

58 (13%)

446 (100%)

< 0.0001

Control 2

762 (45.2%)

811 (48.1%)

114 (6.8%)

1687 (100%)

< 0.0001

7.1.4 Immunosuppressive regimen

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Induction therapy with either polyclonal or monoclonal antibodies was more frequently administered in ESP Patients than in the two other groups. 20.8% of ESP patients received polyclonal induction therapy compared to 12.9% in Control1 and 12.2% in Control 2 (p< 0.001). Monoclonal induction therapy was reported in 34.9% of ESP patients and 29.6% of patients in Control 1 (p=ns) but only in 22.4% of Control2 (p< 0.0001).

Significantly more patients in the ESP group as compared to both Controls received MMF (ESP: 84.5%; Control 1: 78%, p=0,003; Control 2: 78.7%, p<0.0001). Significantly less patients in the ESP group as compared to both Controls received CsA (ESP: 63.1%; Control 1: 71.8%, p=0.002; Control 2: 76.2%, p<0.0001). 99.2% of all patients received corticosteroids with no significant differences between the groups. Triple therapy containing a calcineurin inhibitor was given to 81.1% of all patients as initial maintenance immunosuppression with no big differences in the groups and a similar decline at 6 and 12 months (57% still on triple therapy). Less than 10% of patients received a CNI free regimen initially or up to 12 month.

A summary of IS regimen administered in the three groups and changes in the first year is given below:

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Table 16: Triple therapy (MMF/AZA + CsA/Tacro + Steroids): Summary

 

ESP

Control 1

Control 2

Triple therapy

NA

Initial

1011 (79.9%)

317 (80.5%)

943 (82.4%)

2197 (81.1%)

723 (21.1%)

Month 6

587 (69.2%)

171 (75.7%)

636 (66.6%)

1349 (68.5%)

1462 (42.6%)

Month 12

471 (59.1%)

132 (61.4%)

493 (54.1%)

1066 (57%)

1562 (45.5%)

Table 17: CNI-free therapy (no CsA and no Tacro): Summary

 

ESP

Control 1

Control 2

CNI-free

NA

Initial

169 (13.3%)

27 (6.8%)

44 (3.7%)

236 (8.6%)

683 (19.9%)

Month 6

82 (9.4%)

13 (5.6%)

49 (5%)

140 (6.9%)

1413 (41.2%)

Month 12

84 (10.3%)

16 (7.1%)

82 (8.7%)

178 (9.3%)

1507 (43.9%)

7.2 Endpoints related to primary objectives

7.2.1 Increased availability of elderly donors

Prior to ESP, 10% of all used donor kidneys were retrieved from donors over 65 years of age. Since the implementation of the ESP in 1999, this proportion has increased to 14.5% (Figure 10 and Table 18).

↓53

Figure 10 and Table 18: The number of post mortem donors used for renal transplantation, stratified for donor’s age

7.2.2 Waiting time

The median time on the waitlist (time between first dialysis and transplantation) for the ESP group versus Control 1 (old to any) was comparable (3.6 years and 3.8 years, respectively) but significantly shorter than for Control 2 (any to old; 4.6 years; p<0.0001)

Table 19: Waiting time on the transplantation list

 

n

min

Q1

med

mean

Q3

max

SD

NA

p-value

ESP

1406

0.16

2.34

3.55

3.89

5.36

13.05

2.01

88

 

Control 1

446

0.25

2.34

3.79

4.21

5.90

14.99

2.47

68

0.126

Control 2

1687

0.12

2.71

4.64

4.93

6.96

13.80

2.65

256

<0.0001

↓54

In the first year analysis set all three groups had a comparable median time on the waitlist of 3.94 years for ESP; 3.61 for Control 1 (old to any) and 3.89 for Control 2 (any to old).

7.2.3 Cold ischemia time

97% of the organs in the ESP program were, as expected, allocated locally or regionally, as compared to only half of the organs transplanted via ETKAS.

Table 20: Allocation mode of donor organs

 

Abroad

Home country

Local/Regional

ESP

2 (0.1%)

44 (3.1%)

1360 (96.7%)

Control 1

84 (18.9%)

143 (32.1%)

218 (49%)

Control 2

335 (19.9%)

492 (29.2%)

860 (51%)

↓55

The cold ischemia time in the ESP group was significantly shorter with a mean of 11.9 ±5.2 hours compared with over 17 hours in both Control groups (Control 1: 17.8 ± 6.8; Control 2: 17.5 ± 6.4; p<0.001) (Figure 11). 26% of organs transplanted in the ESP had cold ischemic times below 8 hours (Table 21).

Looking at the first year analysis set, cold ischemia times for ESP patients still were significantly shorter compared to both of the controls, but generally all three groups had longer cold ischemia times (ESP: 13.01 ± 5.7; Control 1: 19.4 ± 6.9; Control 2: 18.8 ± 6.4).

Figure 11: Cold ischemia time

↓56

Table 21: Cold ischemia time below 8 hours, 8-12 and more than 12 hours

 

0-8 h

8-12 h

> 12 h

Total

NA

p-value

ESP

350 (25.7%)

426 (31.2%)

588 (43.1%)

1364 (100%)

42 (3%)

-

Control 1

26 (6.2%)

53 (12.7%)

338 (81.1%)

417 (100%)

29 (6.5%)

<0.0001

Control 2

81 (5%)

223 (13.8%)

1316 (81.2%)

1620 (100%)

67 (4%)

<0.0001

Tot. patients

452 (13.7%)

690 (20.9%)

2156 (65.4%)

3298 (100%)

133 (3.9%)

 

7.2.4 Outcome

Actual patient survival according to Kaplan-Meier is shown in Figure 12. The ESP (old to old) group had the lowest 5 year patient survival rates with 60% compared to 71% and 74% for Control 1(old to any) and 2 (any to old) respectively. The log rank test for differences between the groups was significant for both comparison EPS vs. Control 1 (p = 0.0488) as well as for EPS vs. Control 2 (p < 0.0001).

Figure 12 : Kaplan-Meier Analysis of patient survival for ESP patients (old to old) versus Control 1 (old to any) and Control 2 (any to old)

↓57

An important remark regarding Control 1 is that the survival curve is very flat from the third year on, when it clearly diverges from the ESP curve. In particular, no deaths are reported after 4.85 years post transplantation. Chance (no deaths in a small population at risk) and/or underreporting of late death cases are probably the largest contributors to the described flattening

When patients in Control 2 were analyzed separately for donor age < 60 (Control 2 d< 60, n=1100) and 60 years of age (Control 2 d ≥ 60, n=275), the Kaplan-Meier survival shows a clear spilt of the two subpopulations, and no statistically significant differences between ESP and Control 2 d ≥ 60 were found. 5-year patient survival for the ESP group of 60% now compared to 67% for Control 2 d ≥ 60 and 76% for Control 2 d < 60 (Figure 13).

Figure 13 Kaplan-Meier Analysis of patient survival for ESP patients (old to old) versus Control 2 stratified by donor age < and ≥ 60 years.

↓58

After 5 years, patient and graft survival (= uncensored graft survival) was 47% for the ESP group compared to 51 and 64%, respectively, for Control 1 and Control 2. Figure 14 shows the probability of graft survival for the ESP (old to old) group compared to Control 1 (old to any) and Control 2 (any to old). The log rank test for differences between the groups was not significant for the comparison EPS vs. Control 1 (p = 0.6248) but highly significant for the comparison EPS vs. Control 2 (p < 0.0001).

Figure 14: Kaplan-Meier Analysis of patient and graft survival for ESP patients (old to old) versus Control 1 (old to any) and Control 2 (any to old)

The Kaplan Meier curve for the sub analysis of patients in Control 2 with donor age < 60 (Control 2 d< 60) and 60 years of age (Control 2 d ≥ 60) revealed the same spilt for the uncensored graft survival as for the patient survival. 1 and 5-year patient and graft survival for the ESP group of 75 and 47% now compared to 74 and 53% for Control 2 d ≥ 60 (p= 0,38) and 85 and 67% for Control 2 d < 60 (Figure 15).

↓59

Figure 15 Kaplan-Meier Analysis of patient and graft survival for ESP patients (old to old) versus Control 2 stratified by donor age < and ≥ 60 years.

Figure 16 depicts the probability of graft survival when losses of graft as a result of the patient death were censored. Graft survival rates censored for death with function at 5 years were 67% for ESP (old to old) and Control 1 (old to any) compared to 81% for Control 2 (any to old). The log rank test showed no significant differences for the comparison EPS vs. Control 1 (p = 0.5519) but highly significant for the comparison EPS vs. Control 2 (p < 0.0001).

Figure 16: Kaplan-Meier Analysis death censored graft survival for ESP patients (old to old) versus Control 1 (old to any) and Control 2 (any to old)

↓60

Overall, death with functioning graft occurred in 76,6% of patients with no significant differences between the three groups (ESP: 75.3%; Control 1: 74.6%; Control 2: 77.4%; p=ns). The most common reason for graft loss in all groups was rejection (overall 30.9%). Patients in Control 1 lost more grafts due to rejection (42.4%) as compared to ESP (29.5) or Control 2 (28.8%), but the numbers are relatively small. Details can be found in the table below:

Table 22: Reason for graft loss

 

ESP

Control 1

Control 2

Total

a. rejection

94 (29.5%)

42 (42.4%)

64 (28.8%)

188 (30.9%)

b. recurrent disease

3 (0.9%)

0 (0%)

3 (1.4%)

6 (1%)

c. technical / vascular

42 (13.2%)

9 (9.1%)

27 (12.2%)

75 (12.3%)

d. infection

37 (11.6%)

7 (7.1%)

22 (9.9%)

62 (10.2%)

e. non-function (primary)

47 (14.7%)

19 (19.2%)

33 (14.9%)

94 (15.5%)

f. other /unknown

96 (30.1%)

22 (22.2%)

73 (32.9%)

183 (30.1%)

Total

319 (100%)

99 (100%)

222 (100%)

608 (100%)

Almost 60% of all patients that died, did so due to infectious or cardiovascular event. Interestingly, death due to cardiovascular events occurred slightly less often in the ESP group (22.9%) compared with Control 1 (32.4%) and 2 (32.5%)(Table 23).

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Table 23: Cause of death

 

ESP

Control 1

Control 2

Total

a. cardiovascular

67 (22.9%)

23 (32.4%)

75 (32.5%)

156 (27.2%)

b. infectious

90 (30.7%)

21 (29.6%)

69 (29.9%)

174 (30.3%)

c. malignant

27 (9.2%)

3 (4.2%)

19 (8.2%)

49 (8.5%)

d. others (defined)

50 (17.1%)

13 (18.3%)

38 (16.5%)

97 (16.9%)

e. unknown / not determined

59 (20.1%)

11 (15.5%)

30 (13%)

98 (17.1%)

Total

293 (100%)

71 (100%)

231 (100%)

574 (100%)

7.3 Endpoints related to Secondary Objective

7.3.1 Graft function

A direct primary functioning kidney graft was obtained for 63% of ESP patients compared with 55.5% of Control 1 (p= 0.009) and 63.8% of Control 2 patients (p=ns). Delayed graft function was seen in 29.7%; 36.2% and 30.9% of the ESP, Control 1 and Control 2 transplants, respectively (ESP vs. Control 1 p= 0.047; ESP vs. Control 2 p= ns), and kidneys suffered permanent non-functioning in 7.3%, 8.3.% and 5.0% of patients in each group, respectively (Figure 17) .

Figure 17: Post-transplant graft function- Overview

↓62

Renal function as expressed by the serum creatinine at post-transplant week 2 was highest with a median SCr of 153 μmol/l (range 53-910) in Control 2 (any to old). The median SCr value in the ESP group of 186 μmol/l (range 53-970) was significantly higher (p < 0,0001) but still significantly lower than Control 1 (median SCr 210 μmol/l; range 64-919; p = 0,007). At six months, a median SCr of 127 μmol/l in Control 2 compared to 159 μmol/l in the ESP and 167 μmol/l in Control 1. Similar differences in graft function were maintained over time with ESP patients having higher SCr values and lower calculated GFRs compared to Control 2 (any to old) but lower SCr values and comparable calculated GFRs compared to Control 1 (old to any).(Figures 18 a and b).

Figure 18 a/b: Renal function in the three groups assessed at post-transplant week 2, month 3 and 6 and yearly thereafter a) SCr values b) Calculated Creatinine Clearance using the Cockroft-Gault Formula.

7.3.2 Acute rejection

The proportion of patients experiencing at least one rejection episode at any time post transplant in the ESP group (29.1%) was comparable with Control 1 (24.3%; p = 0.087) but significantly higher than in Control 2 (20.1%; p < 0.0001). Overall, out of all patients with at least one rejection episode, 78.7% experienced one episode, 15.9% had two episodes and only 5.5% had three episodes of rejection with no significant differences between groups. The number of biopsy proven acute rejection episodes was 19.4% in the ESP group. This is comparable to Control 1 (15.9 %; p = 0.16) but significantly higher than in Control 2 (12.4%; p < 0.0001). Most rejections in all groups occurred in the first 6 months. Less than 2% occurred between months 6 and 12 post-transplant and less than 3% late acute rejections beyond the first year were recorded.

↓63

Kaplan-Meier analysis for rejection is shown in Figure 19. The log rank test for differences between the groups was significant for both comparison EPS vs. Control 1 (p = 0.0431) as well as for EPS vs. Control 2 (p < 0.0001).

Figure 19: Kaplan-Meier estimates for rejection

7.3.3 Adverse events

This information is not captured in the ET database and was added to the data collection toll. Thus, information is limited to the completed patient population and percentages are calculated accordingly.

↓64

Occurrence of serious opportunistic infections at any time post transplant was very common and highest in ESP (51%) and Control 1 (50.4%) patients compared to 38.8% in Control 2. Overall, cardiovascular events (defined as MI, bypass grafting, stroke or amputation) and malignancies at any time post transplant were reported in 14.3% and 9.5% of all patients, again with the highest incidence in the ESP group (15.2% and 10.3 % respectively) (Table 24)

Table 24: Incidence of serious adverse events at any time after transplant

 

ESP

Control 1

Control 2

Total

NA

Infection

491 (51%)

125 (50.4%)

377 (39.8%)

959 (45.8%)

1335 (38.9%)

Cardiovascular event

147 (15.2%)

29 (11.7%)

132 (14%)

299 (14.3%)

1339 (39%)

Malignancy

100 (10.3%)

18 (7.3%)

85 (9%)

199 (9.5%)

1333 (38.9%)

7.3.4 Hospitalization and the frequency of readmission

The median number of in-hospital days for transplantation was 27 days for ESP (range 2-109) and Control 1 (range 7-136) compared to 25 days (range 1-170) for patients in Control 2 (ESP vs. Control 2: p<0.0001). ESP patient were reported to be significantly more often readmitted to hospital per year of follow up compared to both of the Controls (median number of hospital stays per year of follow up ESP: 1.01 (range 0-59); Control 1: 0.78 (range 0-28); Control 2: 0.71 (range 0-21)). The number of in-hospital days during readmissions to hospital per year of follow-up was also longest for the ESP group (Table 25)

↓65

Table 25: Days in hospital per year in follow-up [days/year]

 

n

min

Q1

med

mean

Q3

max

SD

NA

p-value

ESP

1406

0.00

4.53

11.09

29.12

30.95

559.15

51.80

641

 

Control 1

446

0.00

3.68

9.84

25.50

25.62

397.21

47.95

232

0.241

Control 2

1687

0.00

2.16

7.00

20.65

17.69

2206.40

87.64

927

<0.0001

7.3.5 Clinical condition

The clinical condition at the most recent visit was judged by the attending physician as poor for 20.1% of ESP patients compared to 12.9% of patients in Control 1 and 10.1% of patients in Control 2. Table 26 depicts an overview of the patient status in the three groups.

Table 26: Clinical condition of the patient at most recent visit as judged by attending physician

 

excellent

good

poor

Total

NA

p-value

ESP

59 (6.8%)

636 (73.1%)

175 (20.1%)

870 (100%)

536 (38.1%)

-

Control 1

24 (10.3%)

178 (76.7%)

30 (12.9%)

232 (100%)

214 (48%)

0.014

Control 2

150 (15.7%)

711 (74.2%)

97 (10.1%)

958 (100%)

729 (43.2%)

<0.0001

Total

226 (11.3%)

1477 (74%)

293 (14.7%)

1996 (100%)

1435 (41.8%)

 

7.4 Regression Models

↓66

Cox regression analysis was used to additionally evaluate the impact of baseline and treatment characteristics on patient and graft survival.

Each of the following tables summarizes the result of the multiple Cox regression models after Akaike's Information Criterion (AIC)-based backwards selection. AIC is used to compare several (nested) models.

7.4.1 Cox regression: patient survival in ESP and Control 1

The Cox regression analysis for patient survival in ESP and Control 1 revealed that significant independent risk factors of patient survival were ESP group, recipient gender, delayed graft function, donor age, graft loss and recipient diabetes and a preservation solution other than UW. Patients experiencing graft loss had a > 200% increased risk of death (RR= 3.07; p< 0.0001); patients with diabetes were 1.7 times more likely to die (RR= 1.77; p< 0.0001), and DGF increased the risk of death by 40% (RR= 1,41; p= 0.011). For each year of donor age the risk of death increases by 3.5%, male recipients have 50% higher relative risk and use of a preservation solution other than UW almost doubled the risk. The other factors listed in Table 27 are relevant as well but were not statistically significant.

↓67

Table 27: Multiple Cox regression model after AIC-based backward selection for patient survival in ESP and Control 1 (n=1148)

Risk Factor

Category

Relative Risk

lower 0.95 CL

upper 0.95 CL

p-value

ESP group

True

1.86233

1.26343

2.74513

0.0017

Recipient gender

Male

1.47955

1.08522

2.01715

0.013

Donor SCr

10 µmol/l

1.00155

0.9982

1.00491

0.37

Waiting time

Year

1.00303

0.97735

1.02939

0.82

Cold ischemia time

Hour

0.98463

0.95985

1.01004

0.23

Delayed graft function

Yes

1.41244

1.08405

1.84032

0.011

Recipient weight

kg

0.98758

0.97574

0.99958

0.042

Donor age

Year

1.03465

1.00584

1.06428

0.018

HLA mismatch Class II

Per mismatch

0.91792

0.74733

1.12746

0.41

Graft loss

True

3.06996

2.30503

4.08874

< 0,0001

Recipient Diabetes

True

1.77581

1.34293

2.34823

< 0,0001

Preservation solution

Other

1.9415

1.0973

3.43516

0.023

Preservation solution

UW

1.09727

0.83917

1.43476

0.5

7.4.2 Cox regression: patient survival in ESP and Control 2

In the same model for ESP and Control 2 recipient gender was not associated with an increased risk but the model showed one new independent risk factor compared to the ones described in 7.4.1. In this model patient survival was significantly influenced by reported cardiovascular disease. Cardiovascular disease in the medical history of the recipient increased the risk of death by almost 40% (RR= 1.39; p= 0.0067). Again, graft loss and preservation solution other than UW appeared to be strongly associated with an increased risk of death.

Table 28: Multiple Cox regression model after AIC-based backward selection for patient survival in ESP and Control 2 (n=1756)

Risk factor

Category

Relative Risk

lower 0.95 CL

upper 0.95 CL

p-value

ESP Group

True

1.79549

1.31829

2.44544

< 0,0001

Recipient gender

Male

1.26476

0.96981

1.64941

0.083

Donor SCr

10 µmol/l

1.00005

0.99999

1.00012

0.087

Waiting time

Year

0.99883

0.99677

1.0009

0.27

HLA mismatch Class I

Per mismatch

1.00799

0.89768

1.13185

0.89

Cold ischemia time

Hour

0.98989

0.96992

1.01026

0.33

Rejection

Yes

0.81561

0.63695

1.04439

0.11

Delayed graft function

Yes

1.38633

1.10238

1.74341

0.0052

Recipient Diabetes

True

1.37636

1.07104

1.76872

0.013

Recipient CV disease

True

1.39205

1.0958

1.76841

0.0067

Graft Loss

True

3.54001

2.7474

4.56129

< 0,0001

Preservation solution

Other

1.92702

1.13083

3.28381

0.016

Preservation solution

UW

1.15667

0.90997

1.47025

0.23

Recipient weight

kg

0.99975

0.99019

1.0094

0.96

↓68

Since the ESP group and the Control 2 differ significantly in both donor as well as recipient age, a model for age of donor and recipient as the only factors was created for Control 2. The model was then used to predict survival in putative patients transplanted according to the protocol used for Control 2 but with a donor and recipient age comparable to the ESP group.

In the model, both donor and recipient age were highly significantly associated with patient survival (p<0.001 for both factors). The relative risk of death was about 2% and 1% for each additional year of age of the recipient and the donor, respectively. No relevant interaction between the two factors appeared to be present. Figure 20 shows the probability of patient survival for Control 2 compared to the extrapolated Control 2. The higher mean donor and recipient age in the extrapolated curve explains the large survival difference.

A comparison of survival in ESP and the extrapolated Control 2 over the first 5 years post-transplantation points to a slight but systematic survival advantage for patients transplanted under the ESP (Table 29)

↓69

Figure 20: Kaplan-Meier Analysis of patient survival for Control2 versus Control 2 extrapolated to ESP parameters

Table 29: Comparison of survival in ESP group with extrapolation from Control 2

 

Year 1

Year 2

Year 3

Year 4

Year 5

ESP Group

0.86

0.81

0.75

0.67

0.60

Control 2 (extrapolated to ESP parameters)

0.82

0.76

0.69

0.65

0.58

7.4.3 Cox regression: patient & graft survival in ESP and Control 1

Patient and graft survival (uncensored graft survival) was significantly influenced by male gender of recipient (RR= 1.441; p=0.0021), delayed graft function (RR= 1.32; p= 0.0091); donor age (RR= 1.043; p = 0.0017) and diabetes of the recipient. The latter one increased the risk by 27% (RR= 1.268; p = 0.0044).

↓70

Table 30: Multiple Cox regression model after AIC-based backward selection for patient and graft survival (uncensored graft survival) in ESP and Control 1

Risk factor

Category

Relative Risk

lower 0.95 CL

upper 0.95 CL

p-value

ESP Group

True

1.24841

0.93324

1.67003

0.14

Recipient gender

Male

1.46728

1.15786

1.85938

0.0015

Donor SCr

10 µmol/l

1.00146

0.99868

1.00425

0.3

Waiting time

Year

1.00332

0.98162

1.02549

0.77

HLA mismatch Class I

Per mismatch

1.05997

0.95308

1.17886

0.28

Cold ischemia time

Hour

1.00065

0.98129

1.02039

0.95

Delayed graft function

Yes

1.31904

1.07132

1.62405

0.0091

Recipient weight

Kg

0.99358

0.98483

1.00241

0.15

Donor age

Year

1.0426

1.02021

1.06549

0.00017

Preservation solution

Other

1.41375

0.86087

2.3217

0.17

Preservation solution

UW

0.95598

0.77761

1.17525

0.67

Recipient diabetes

True

1.26891

1.00677

1.59932

0.044

7.4.4 Cox regression: patient & graft survival in ESP and Control 2

The model for patient & graft survival in ESP and Control 2 only identified three significant risk factors: The ESP group itself, male gender of the recipient and delayed graft function. Details of the increase in risk can be found in Table 30.

Table 31 Multiple Cox regression model after AIC-based backward selection for patient and graft survival (uncensored graft survival) in ESP and Control 2

Risk factor

Category

Relative Risk

lower 0.95 CL

upper 0.95 CL

p-value

ESP Group

True

1.57011

1.20818

2.04046

0.00074

Recipient gender

Male

1.47239

1.19345

1.81653

0.00031

Donor SCr

10 µmol/l

1.00016

0.99955

1.00077

0.61

Waiting time

Year

0.99835

0.99627

1.00042

0.12

HLA mismatch Class I

Per mismatch

1.08261

0.98617

1.18848

0.095

Cold ischemia time

Hour

1.002

0.9857

1.01856

0.81

Delayed graft function

Yes

1.3979

1.16293

1.68033

0.00036

Recipient weight

Kg

0.99906

0.99153

1.00665

0.81

Preservation solution

Other

1.20359

0.74619

1.94137

0.45

Preservation solution

UW

0.97696

0.80872

1.1802

0.81

7.4.5 Cox regression: graft survival (censored for death with functioning graft) in ESP and Control 1

↓71

Male recipients, cold ischemia time and donor age were the only three independent predictors of death censored graft survival in the model for ESP and Control 1. Male recipients had a 74% increased risk of graft loss (RR= 1.742; p < 0.0001). For every hour of cold ischemia time the risk of graft loss increased by 3% and for each year of donor age the risk of graft loss increased by 6% (RR= 1.058; p<0.0001).

Table 32: Multiple Cox regression model after AIC-based backward selection for graft survival (censored for DwFG) in ESP and Control 1 (n=1125)

Risk factor

Category

Relative Risk

lower 0.95 CL

upper 0.95 CL

p-value

Recipient gender

Male

1.74251

1.26405

2.40209

< 0.0001

Donor SCr

10 µmol/l

1.00048

0.99656

1.00441

0.81

Waiting time

Year

1.00314

0.9653

1.04245

0.87

HLA mismatch Class I

Per mismatch

1.111

0.96797

1.27516

0.13

HLA mismatch Class II

Per mismatch

1.26872

1.02095

1.57661

0.032

Cold ischemia time

Hour

1.02769

1.00301

1.05298

0.028

Delayed graft function

Yes

1.22412

0.92653

1.61729

0.15

Recipient weight

kg

0.9971

0.98585

1.00847

0.62

Recipient CV disease

True

0.74947

0.53699

1.04604

0.09

Donor age

year

1.05888

1.02944

1.08916

< 0.0001

Preservation solution

Other

1.00475

0.46188

2.18569

0.99

Preservation solution

UW

0.90563

0.68839

1.19143

0.48

7.4.6 Cox regression: graft survival (censored for DwFG) in ESP and Control 2

Death censored graft survival in ESP and Control 2 was influenced by a number of variables including ESP group, male gender, HLA class I mismatch and delayed graft function. Interestingly, male recipient was determined as the strongest risk factor in this analysis increasing the risk of graft loss by 66% (RR= 1.659; p = 0.00066). For every mismatch in class I the risk for losing the graft increased by 15%(Table 33).

7.4.7 Cox regression: rejections in ESP and Control 1

↓72

A HLA class II mismatch conferred a 1.217 relative risk of graft rejection, and delayed graft function increased the risk of rejection by over 50% (RR= 1.524; p< 0.0001) when analyzed in the Cox regression model (Table 34).

Table 33: Multiple Cox regression model after AIC-based backward selection for graft survival (censored for DwFG) in ESP and Control 2 (n=1715)

Risk factor

Category

Relative Risk

lower 0.95 CL

upper 0.95 CL

p-value

ESP Group

True

1.47312

1.03028

2.10629

0.034

Recipient gender

Male

1.65926

1.23966

2.22089

0.00066

Donor SCr

10 µmol/l

0.9992

0.9964

1.00201

0.58

Waiting time

Year

0.9978

0.99576

0.99985

0.036

HLA mismatch Class I

Per mismatch

1.14974

1.01113

1.30736

0.033

HLA mismatch Class II

Per mismatch

1.18215

0.96455

1.44882

0.11

Cold ischemia time

Hour

1.01642

0.99435

1.03897

0.15

Delayed graft function

Yes

1.33374

1.03584

1.71731

0.026

Recipient weight

Kg

0.9976

0.98728

1.00802

0.65

Preservation solution

Other

0.54839

0.22275

1.35009

0.19

Preservation solution

UW

0.83595

0.65002

1.07506

0.16

Table 34: Multiple Cox regression model after AIC-based backward selection for graft rejection in ESP and Control 1 (n=1206)

Risk factor

Category

Relative Risk

lower 0.95 CL

upper 0.95 CL

p-value

HLA mismatch Class II

Per mismatch

1.21776

1.04323

1.42149

0.013

Donor age

Year

1.01736

0.99512

1.0401

0.13

Delayed graft function

Yes

1.5244

1.24302

1.86948

< 0,0001

Donor SCr

10 µmol/l

1.00712

1.00331

1.01094

0.00024

Cold ischemia time

Hour

0.99341

0.97568

1.01146

0.47

Preservation solution

Other

0.99507

0.97735

1.01312

0.59

Preservation solution

UW

1.46721

0.91719

2.34706

0.11

Recipient diabetes

True

1.23328

0.97774

1.55561

0.077

Anti IL-2rAB

Yes

1.14544

0.93386

1.40495

0.19

Polyclonal AB

Yes

0.81514

0.62219

1.06793

0.14

7.4.8 Cox regression: rejections in ESP and Control 2

↓73

The relative risk for developing graft rejection estimated by Cox regression increased by 13% and 26% for each HLA class I mismatch and each HLA class II mismatch respectively. In this model, delayed graft function increased the risk of rejection by almost 60% (RR= 1.568; p < 0.0001). Interestingly, use of a preservation solution other than UW also increased the relative risk by 52% and the risk for recipients with diabetes was 1.24 fold higher than for patients without diabetes. Finally, this was the only analysis that showed a reduction in risk by 27% for rejection in patients receiving polyclonal antibodies for induction (Table 35).

Table 35: Multiple Cox regression model after AIC-based backward selection for graft rejection in ESP and Control 2 (n=1823)

Risk factor

Category

Relative Risk

lower 0.95 CL

upper 0.95 CL

p-value

HLA mismatch Class I

Per mismatch

1.13222

1.04478

1.22698

0.0025

HLA mismatch Class II

Per mismatch

1.26631

1.10569

1.45026

0.00065

Delayed graft function

Yes

1.56841

1.31592

1.86935

< 0,0001

Donor SCr

10 µmol/l

1.0007

1.00025

1.00115

0.0023

Cold ischemia time

Hour

0.99079

0.97621

1.00559

0.22

Preservation solution

Other

1.52405

1.00782

2.30471

0.046

Preservation solution

UW

1.03853

0.86465

1.24737

0.69

Recipient diabetes

True

1.24178

1.01871

1.51369

0.032

Anti IL-2rAB

Yes

0.96038

0.79693

1.15737

0.67

Polyclonal AB

Yes

0.7303

0.5726

0.93141

0.011


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