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(

n

= 2191) compared with men included in our cohort. No

differences were observed in age, preoperative PSA, clinical

stage, biopsy grade group, number of cores taken, number of

lymph nodes removed, proportion of patients with positive

lymph nodes, and number of positive lymph nodes (all

p

0.07). After multiple imputation, the use of a 7% cutoff of

the novel nomogram was associated with 75% ePLND

spared and 3.2% LNIs missed.

4.

Discussion

Nodal staging is crucial to identify patients with localized

PCa at a higher risk of adverse oncologic outcomes and plan

their optimal management

[1–4]

. Available imaging mo-

dalities are associated with suboptimal performance

characteristics

[5]

. Therefore, an anatomically defined

ePLND still represents the gold standard for the detection

of nodal metastases

[6,7] .

Given the potential morbidity

associated with this procedure

[8,9] ,

an ePLND should be

considered only in men with an increased risk of LNI

[6,7]

. The EAU–ESTRO–SIOG and the NCCN guidelines

recommend the use of the Briganti and MSKCC nomograms,

respectively, to identify individuals at a higher risk of LNI

who should be considered for an ePLND

[6,7,10–13] .

Al-

though these models are associated with very good

performance characteristics, they are missing potential

important information such as the extent of cancer

involvement within the cores. Moreover, they do not take

into account for grading heterogeneity among different

cores. For example, a patient with two cores of Gleason

grade group 3 and four cores of grade group 1 PCa out of

12 cores is assigned a 50% positive cores of grade group

3 disease (highest grade within the biopsy), which is not the

case. This may lead to an overestimation of the risk of LNI

[15]

. We hypothesized that the availability of detailed

biopsy reports that also account for PCa heterogeneity

might improve our ability to identify patients at a higher

risk of LNI who should be considered for an ePLND. To test

our hypothesis, we developed a novel tool predicting LNI in

contemporary patients treated with RP and ePLND, with

detailed biopsy information available after centralized

biopsy specimens’ review.

Distinct facets of our results deserve attention. First, our

results show that detailed biopsy characteristics such as the

maximumpercentage of single core involvement and tumor

length in cores with the highest- and lower-grade diseases

represent predictors of LNI at univariable analyses. These

observations confirm the association between variables

that can be considered as a proxy of pathologic tumor

volume and the risk of adverse pathologic findings

[23,24]

. Nonetheless, inclusion of these covariates into

multivariable models predicting LNI did not improve their

accuracy compared with a base model including PSA,

clinical stage, biopsy grade group, percentage of cores with

highest-grade PCa, and percentage of cores with lower-

grade PCa. Therefore, in the absence of detailed biopsy data,

the use of a prediction tool based on these covariates is not

warranted, where the base model depicted excellent

calibration characteristics and was associated with an

improvement in clinical risk prediction against threshold

probabilities 20%.

Second, we demonstrated that the adoption of a 7% cutoff

would result into sparing approximately 70% of ePLNDs at

the cost of missing only 1.5% of LNIs. The use of an arbitrary

cutoff to select patients who should receive nodal staging

implies the acceptance of the possibility of missing LNI in a

certain proportion of individuals below that cutoff. For

example, the threshold recommended by the EAU–ESTRO–

SIOG guidelines is 5% according to the previous Briganti

nomogram. The adoption of this cutoff in the original cohort

was associated with 65% of ePLNDs spared and 1.5% of

patients with LNIs missed

[10] .

With the novel nomogram,

the use of a 7% cutoff would increase the number of patients

in whom an ePLND (and its morbidity) could be avoided,

missing exactly the same proportion of LNIs. Therefore, a

cutoff of 7% can be considered to reduce the number of

ePLNDs performed without missing additional node-posi-

tive patients as compared with the previous Briganti

nomogram

[10]

.

Third, we compared the performance characteristics of

the novel model with the Briganti and MSKCC nomograms.

Our tool achieved higher predictive accuracy and net

benefit at DCA

[10,11,13] .

Moreover, the adoption of a 7%

cutoff calculated with our novel nomogram was associated

with a lower proportion of LNIs missed and a similar

percentage of ePLNDs spared as compared with the Briganti

nomogram, which is currently recommended by the EAU–

ESTRO–SIOG guidelines

[6] .

The use of a 7% cutoff with our

novel nomogram was associated with a higher number of

ePLNDs spared without an increase in the percentage of

LNIs missed when compared with the MSKCC nomogram,

which is recommended by the NCCN guidelines

[7]

. The

better performance characteristics associated with the use

of our novel nomogram might be related to the inclusion of

detailed data on PCa grading. In particular, while the

previous nomograms include information on the percent-

age of positive cores regardless of the presence of cores with

different grading, we were able to demonstrate that the

percentage of cores with the highest- and lower-grade

diseases has different prognostic implications. Availability

of detailed biopsy information would result into improved

predictive accuracy and reduce overestimation of the risk of

LNI associated with the adoption of previous models. For

example, the calculated risk of LNI in a patient with

preoperative PSA 4 ng/ml, T1c, Gleason grade group

3 disease in one core, and grade group 1 PCa in five out

of 16 cores would be higher than 5% according to the

Briganti nomogram, and this patient should be considered

for an ePLND according to the EAU–ESTRO–SIOG guidelines.

However, using the novel nomogram, this patient would

have a risk of LNI lower than 5% and an ePLND could be

spared.

From a clinical standpoint, our model improves our

ability to identify patients at a higher risk of LNI, and its

implementation in the clinical practice would reduce the

number of ePLNDs performed without compromising the

identification of LNI. While an ePLND should be considered

in virtually all patients with high-risk characteristics

[6]

,

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