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would benefit from consideration of preoperative systemic

therapy, adjuvant systemic therapy, or enrollment into a

clinical trial.

Interestingly, three clinicopathologic features were

prognostic of CSM and ACM: ECOG PS 1, coagulative

tumor necrosis, and sarcomatoid differentiation. This

suggests that unlike the development of distant metastases,

which appears to be largely driven by tumor biology, the

endpoints of CSM and ACM reflect not only disease biology

(as captured by adverse pathologic features) but also

patient functional status. The latter may indicate eligibility

for systemic therapy or, alternatively, cancer-related

functional decline.

Historically, LN involvement has been associated with

[9_TD$DIFF]

a

poor prognosis

[4,14,15]

. Indeed, in the original account of

the outcomes of radical nephrectomy by Robson et al in

1969, the authors reported 3-yr survival of approximately

35% for pN1M0 disease

[15] .

Perhaps more notable is that

the survival figure in that study (

[10_TD$DIFF]

Figure 1

[11_TD$DIFF]

in

[15]

) appears to

capture the underlying biology of isolated LN involvement:

the survival of patients with LN involvement parallels that

of patients with distant metastases, probably because of

progression from occult systemic disease, until the LN

survival curve plateaus, reflecting the subset of durable

survivors without occult systemic disease at the time of

surgery.

Several contemporary series have examined isolated LN

disease. Investigators from the MD Anderson center

reported on a series of 40 patients with surgically resected

pN1M0 disease, and observed that disease recurred in 70%

at a median of 4.9 mo

[17]

. An updated report on 68 patients

with longer follow-up noted 22.1% progression-free surviv-

al at a median of 43.5 mo after surgery

[16]

. Favorable

prognostic features included ECOG PS of 0 and the absence

of sarcomatoid features. In a multi-institution series of

171 patients with median follow-up of 1.3 yr, median CSS

was 1.2 yr, and the presence of systemic symptoms was the

strongest predictor of poor survival

[18] .

More recently,

Trinh and colleagues

[19]

conducted a population-based

study of 799 patients with median follow-up of only 17 mo,

reporting median OS of 28 mo and actuarial CSS of 38% at

5 yr. Adverse prognostic features included higher Fuhrman

grade, clear cell histology, advanced pT stage, and percent-

age of positive nodes. Randomized trials examining

adjuvant therapies have observed similar survival in the

setting of node-positive disease

[21,22]

. Some of the

differences in oncologic outcomes reported may be related

to differences among study populations.

RCC has been associated with predominantly hematog-

enous, rather than lymphogenous, spread

[3,23] .

For

instance, in one autopsy study that included 80 patients

with pN1 RCC, only five (6.3%) were without concurrent

distant metastatic disease

[24]

. Anatomic studies provide

several mechanisms to explain these findings. Lymphatic

drainage from the kidney is unpredictable, and direct

lymphatic drainage into the IVC and thoracic duct have both

been described

[25]

. Alternatively, hematogenous spread

may reflect tumor biology rather than anatomic consider-

ations

[26]

.

Despite these findings, there does appear to be a small

subset of patients without occult systemic disease in whom

resection of isolated LN disease is associated with durable

long-term survival. These patients are characterized by

pathologic nodal involvement (pN1) in the absence of

adverse prognostic features, as identified in this and other

studies. However, the majority of existing prediction tools

to identify patients with pN1 disease

[27–29]

utilize the

same clinicopathologic features that have been associated

with occult systemic disease and early progression, proba-

bly reflecting the association of nodal disease with systemic

disease. Alternative prediction tools are required to identify

patients with nodal metastases independent of features

associated with systemic disease

[30]

.

This retrospective study has several limitations. Most

importantly, it reflects a surgical cohort and the selection

bias inherent to surgical candidacy. In addition, LND was

performed at the surgeon’s discretion, which may intro-

duce additional selection bias. LND boundaries were not

standardized, and it is possible that more extensive LND

may be associated with different oncologic outcomes.

Moreover, variability has been reported in the assessment

of LN counts. Neither the location of positive lymph nodes

nor specific pathologic features of positive lymph nodes,

such as the presence of extranodal extension or sarco-

matoid features, was available. Furthermore, given the

rarity of isolated pN1 disease, a larger cohort may

improve the statistical power for detection of associations

between clinicopathologic features and oncologic out-

comes. Finally, assessment of pathologic features may not

be available preoperatively without renal mass biopsy.

Still, this is the largest single-institution study to examine

the topic. Accordingly, it benefits from the availability of a

comprehensive set of clinical, radiographic, and patho-

logic features, utilization of re-reviewed pathology, and

long-term follow-up.

5.

Conclusions

Isolated pN1 disease portends poor prognosis, with a 5-yr

probability of metastasis-free survival of only 16%. Never-

theless, a subset of patients experience durable long-term

survival to 10 yr after surgical resection of isolated

lymphatic metastases. Adverse prognostic features includ-

ing symptoms at presentation, radiographic IVC involve-

ment, pT4 stage, coagulative tumor necrosis, and clear cell,

collecting duct, or NOS histologic subtypes were indepen-

dently associated with the development of distant metas-

tases, and may enhance patient risk stratification and

facilitate multimodal management approaches.

Author contributions:

Boris Gershman had full access to all the data in

the study and takes responsibility for the integrity of the data and the

accuracy of the data analysis.

Study concept and design:

Gershman, Thompson, Moreira, Boorjian,

Lohse, Costello, Cheville, Leibovich.

Acquisition of data:

Lohse, Thompson, Leibovich.

Analysis and interpretation of data:

Gershman, Thompson, Moreira,

Boorjian, Lohse, Costello, Cheville, Leibovich.

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