451 476
ROC curve analysis
( Table 4, Supplementary Fig. 2)
comparing the full model with the 4Kpanel and the full
clinical model with serum PSA indicated that the 4Kpanel
significantly improved the accuracy for predicting reclassi-
fication (AUC 0.78 vs 0.74) in the initial surveillance biopsy,
with a significant incremental value in AUC of 0.04 (95% CI
0.003–0.09). In a model without prostate volume, the
incremental value in AUC was 0.07 (95% CI 0.02–0.11). The
4Kpanel did not improve prediction of reclassification in
subsequent biopsies relative to PSA (AUC 0.75 vs 0.76).
Similar findings were observed in DCA. Compared to a
clinical model with serum PSA, the model with 4Kpanel
showed a higher net benefit for the initial surveillance
biopsy, but there was no benefit for subsequent biopsies. All
models showed substantial gain in net benefit compared
with the biopsy-all and biopsy-none strategies across
Table 2 – Biopsy characteristics at each sequential surveillance biopsy after diagnosis for 558 participants in the training set
Parameter
Initial biopsy
Subsequent surveillance biopsies
First
Second
Third
Fourth
Fifth
Sixth
Seventh
Eighth
Biopsies (
n
)
319
246
108
34
20
10
3
1
CR for previous biops
y aMedian (IQR)
0.08 (0.08)
0.07 (0.17)
0.08 (0.17)
0.06 (0.12)
0.06 (0.12)
0 (0.07)
0.11 (0.06)
0 (0)
Missing,
n
(%)
0
5 (2)
5 (5)
0
0
0
0
0
Median MC
R b (IQR)
0.08 (0.08)
0.11 (0.08)
0.13 (0.15)
0.17 (0.13)
0.10 (0.17)
0.14 (0.15)
0.17 (0.08)
0.17 (0.00)
Negative biopsie
s c , n(%)
0
319 (100)
145 (59)
44 (41)
10 (29)
4 (20)
1 (10)
1 (33)
0
1
0
101 (41)
38 (35)
13 (38)
6 (30)
3 (30)
2 (67)
0
2
0
0
26 (24)
6 (18)
3 (15)
1 (10)
0
1 (100)
3
0
0
0
5 (15)
2 (10)
3 (30)
0
0
4
0
0
0
0
5 (25)
2 (20)
0
0
Median PV, cm
3
(IQR)
41.0 (26.5)
38.0 (27.0)
41.0 (27.0)
48.5 (25.0)
59.5 (36.5)
43.5 (27.8)
41.0 (19.5)
97.0 (0.0)
Biopsy GS,
n
(%)
Negative
107 (34)
95 (39)
38 (35)
11 (32)
8 (40)
6 (60)
2 (67)
0
6
152 (48)
108 (44)
48 (45)
21 (62)
10 (50)
3 (30)
1 (33)
1 (100)
7
58 (18)
42 (17)
21 (19)
2 (6)
2 (10)
1 (10)
0
0
8
1 (0)
1 (0)
1 (1)
0
0
0
0
0
9
1 (0)
0
0
0
0
0
0
0
CR = core ratio; IQR = interquartile range; MCR = maximum CR; PV = prostate volume; GS = Gleason score.
a
CR is defined as the number of biopsy cores containing cancer divided by the total number of biopsy cores in the previous biopsy.
b
MCR among all previous biopsies.
c
Number of surveillance biopsies in which no cancer was found.
Table 3 – Summary of fitted models including clinical variables + serum PSA or 4Kpanel in the training set
Variable
PSA + full clinical model
4K + full clinical model
OR (95% CI)
p
value
OR (95% CI)
p
value
Age
1.03 (1.00–1.06)
0.068
Body mass index
1.11 (1.06–1.16)
<
0.001
1.09 (1.04–1.14)
<
0.001
Positive ore ratio
>
0.2
2.19 (1.39–3.44)
0.001
2.10 (1.33–3.32)
0.001
Negative biopsies 2
0.19 (0.04–0.80)
0.023
0.19 (0.04–0.85)
0.029
Log(prostate volume)
0.31 (0.20–0.48)
<
0.001
0.47 (0.31–0.70)
<
0.001
Log(PSA)
2.11 (1.53–2.91)
<
0.001
4Kpanel
1.54 (1.31–1.81)
<
0.001
PSA = prostate-specific antigen; OR = odds ratio; CI = confidence interval.
Table 4 – Results of final regression models for reclassification
Base model
Area under the curve (95% confidence interval)
4K + clinical model
PSA + clinical model
Difference
Full clinical model
Initial biopsy
0.783 (0.691–0.871)
0.740 (0.652–0.828)
0.043 (0.003–0.086)
Subsequent biopsy
0.754 (0.657–0.838)
0.755 (0.653–0.841)
0.001 ( 0.037–0.041)
Clinical model without prostate volume
Initial biopsy
0.748 (0.654–0.840)
0.678 (0.579–0.774)
0.069 (0.016–0.114)
Subsequent biopsy
0.738 (0.633–0.825)
0.718 (0.611–0.810)
0.02 ( 0.023–0.07)
PSA = prostate-specific antigen.
Confidence intervals were calculated with bootstrap accounting for correlations among individuals.
E U R O P E A N U R O L O G Y 7 2 ( 2 0 1 7 ) 4 4 8 – 4 5 4
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