Lymph-Vascular Space Invasion
(LVSI) in Uterine Corpus Cancer
What is its Prognostic Significance in the
Absence of Lymph Node Metastases?
SHELBY ADDISON NEAL, MD
MENTORS:
WILLIAM T. CREASMAN, MD
WHITNEY S. GRAYBILL, MD, MS
BACKGROUND
 Uterine corpus cancer is
the most common
gynecologic malignancy
 Surgery is curative in
~80% of cases
 Adjuvant therapy is
appropriate for some
patients
Rubin and Farber. 1999. Pathology, 3rd edition.
BACKGROUND
Type I (65%)
Type II (35%)
Estrogen state
Exogenous
estrogen
No association
Habitus
Obese
Non-obese
Background
endometrium
Hyperplastic
Atrophic
Histology
Endometrioid
Clear cell, serous ,
anaplastic, MMT
Tumor grade
1-2
3
Myometrial
invasion
69% superficial
66% deep
Lymph node mets
9%
28%
Progesterone
sensitivity
80%
42%
5 year survival
86%
59%
BACKGROUND
 Lymph node mets are associated with decreased survival
 Lymph-vascular space invasion (LVSI) is an independent
risk factor for lymph node metastases1
OR 6.34, CI 3.45-11.66, P<0.0001
 PPV 33.6%

 The presence of LVSI in patients with unstaged
endometrial cancer may indicate the need for
lymphadenectomy or adjuvant therapy2
 Little data is available regarding LVSI as a prognostic
factor in the absence of lymph node metastases
1. Guntupalli et al. 2012. Gynecologic Oncology.
2. Cohn et al. 2002. Gynecologic Oncology.
OBJECTIVE
To determine if there is a difference in recurrencefree survival (RFS) or overall survival (OS) between
subjects who have LVSI and subjects who do not
have LVSI in the setting of negative lymph nodes
HYPOTHESIS
In the setting of negative lymph nodes, there is no
survival difference between subjects who have LVSI
and subjects who do not have LVSI.
STUDY DESIGN
 Retrospective chart review of women treated for
uterine corpus cancer at MUSC from 1987 to 2012
 Data obtained from charts included the following:
Demographic data
 Health history
 Surgical pathology
 Post-operative clinical course

SELECTION OF SUBJECTS
+ LVSI
n=37
- LVSI
n=245
Negative nodes
n=359
Total number of
subjects in database
n=884
Positive nodes
n=68
[EXCLUDED]
Incompletely staged
n=457
[EXCLUDED]
LVSI unknown
n=58
[EXCLUDED]
Stage IV disease
n=19
[EXCLUDED]
METHODS
 Simple regression analysis for the following
covariates with recurrence-free and overall survival:
• Age
• Race
• BMI
• Parity
• Co-morbidities
• Histology
• Stage
• Grade
• Lesion size
• Depth of invasion
• Number of nodes
• Adjuvant therapy
 Multiple regression analysis incorporating
significant covariates
METHODS
 Model C-index
Measures concordance between predicted and actual survival for
each subject
 Higher C-index = more accurate model
 C-index calculated for 2 different models:
 Main model
 Model excluding LVSI

 Competing risks analysis
Distinguishes between disease-related outcomes and death due to
other causes
 Outcome of interest = time to recurrence
 Competing risk = death due to other causes

DEMOGRAPHIC CHARACTERISTICS
LVSI positive
(N=37)
LVSI negative
(N=245)
P-value
Age
65 (51-84)
61 (29-93)
0.02
BMI
32.0 (20.5-44.5)
33.0 (16.9-59.4)
0.73
Variable
Race
0.17
White
23 (62%)
181 (74%)
Non-white
14 (38%)
66 (27%)
Parity
0.66
0
5 (14%)
45 (18%)
1-3
21 (57%)
142 (58%)
>3
10 (27%)
52 (21%)
Diabetes
10 (27%)
52 (21%)
0.40
Hypertension
25 (68%)
156 (64%)
0.72
Comorbidities
HISTOPATHOLOGICAL CHARACTERISTICS
Variable
LVSI positive
(N=37)
LVSI negative
(N=245)
Histology
p-value
0.03
Type I
16 (43%)
155 (62%)
Type II
21 (57%)
93 (38%)
Stage
<0.001
I
23 (62%)
211 (86%)
II
7 (19%)
23 (9%)
III
7 (19%)
11 (5%)
Grade
0.026
1
6 (16%)
73 (30%)
2
10 (27%)
90 (36%)
3
21 (57%)
82 (34%)
Lesion size
1.00
< 2cm
1 (3%)
13 (8%)
> 2 cm
21 (95%)
142 (92%)
Myom. invasion
0.0003
None
1 (3%)
52 (22%)
< 1/2
9 (25%)
92 (39%)
> 1/2
26 (72%)
92 (39%)
ASSOCIATIONS WITH
RECURRENCE-FREE SURVIVAL
Covariate
HR
95% CI
p-value
Age
1.05
1.02, 1.08
0.002
LVSI
2.78
1.52, 5.09
0.0009
White
0.34
0.20, 0.58
0.0001
Parity >3
2.51
1.07, 5.92
0.035
Stage III
6.06
3.06, 11.99
<0.0001
Grade 3
2.89
1.19, 7.04
0.019
Type II
2.10
1.20, 3.66
0.0089
MULTIPLE REGRESSION MODEL:
RECURRENCE-FREE SURVIVAL
Model 1: All covariates
Model 2: Without LVSI
HR (95% CI)
p-value
HR (95% CI)
p-value
Age
1.03 (1.00, 1.06)
0.071
1.03 (1.00, 1.06)
0.050
LVSI
1.90 (1.01, 3.58)
0.045
White
0.38 (0.21, 0.69)
0.0015
0.39 (0.21, 0.71)
0.0021
Stage = 2 (vs. 1)
1.44 (0.60, 3.44)
0.42
1.46 (0.61, 3.50)
0.39
Stage = 3 (vs. 1)
5.86 (2.76, 12.47)
<0.0001
7.01 (3.40, 14.43)
<0.0001
Type II (vs. I)
1.49 (0.79, 2.79)
0.22
1.59 (0.85, 2.97)
0.15
Model C-index
0.761
0.753
ASSOCIATIONS WITH OVERALL SURVIVAL
Covariate
HR
95% CI
p-value
Age
1.08
1.04, 1.12
<0.0001
LVSI
2.76
1.30, 5.84
0.008
White
0.27
0.14, 0.54
0.0002
Parity>3
5.27
1.55, 17.9
0.008
Stage III
4.09
1.65, 10.11
0.0023
Grade3
3.95
0.17, 13.36
0.027
Type II
2.79
1.35, 5.76
0.0056
MULTIPLE REGRESSION MODEL:
OVERALL SURVIVAL
Model 1: All covariates
Model 2: Without LVSI
HR (95% CI)
p-value
HR (95% CI)
p-value
Age
1.07 (1.03, 1.12)
0.00061
1.07 (1.03, 1.11)
0.00087
LVSI
1.88 (0.85, 4.17)
0.12
--
--
White
0.33 (0.16, 0.69)
0.0031
0.33 (0.16, 0.70)
0.0038
Stage = 2 (vs. 1)
1.71 (0.64, 4.59)
0.29
1.74 (0.64, 4.70)
0.28
Stage = 3 (vs. 1)
3.50 (1.26, 9.69)
0.016
4.56 (1.75, 11.89)
0.0019
Type II (vs. I)
1.67 (0.75, 3.74)
0.21
1.72 (0.76, 3.89)
0.20
Model C-index
0.788
0.791
COMPETING RISKS ANALYSIS
Covariate
HR
95% CI
p-value
Log(lesion size)
2.11
1.36, 3.28
0.00089
LVSI
2.46
1.21, 5.02
0.013
White
0.39
0.21, 0.71
0.0023
Stage III
8.25
3.86, 17.67
<0.0001
Grade3
2.53
1.03, 6.22
0.043
Adjuvant therapy
1.91
1.04, 3.51
0.037
Type II
2.61
1.39, 4.87
0.0027
COMPETING RISKS ANALYSIS
Solid line- LVSI; Dashed line- no LVSI
CONCLUSIONS
 There is no survival difference between uterine
cancer subjects with negative nodes who have LVSI
and those who do not
 Adjuvant therapy for patients with LVSI and
negative nodes should not be administered unless
otherwise indicated by stage, grade or histology
ACKNOWLEDGEMENTS
William Creasman, MD
Whitney Graybill, MD, MS
Elizabeth Garrett-Mayer, PhD
Gweneth Lazenby, MD
Jennifer Pierce, MD, MPH
Misty McDowell, MD
Catie Haar
Virginia McLean
Lee Bullard
Anquinette Gadson
This project was supported by the South Carolina Clinical & Translational
Research (SCTR) Institute, with an academic home at the Medical University
of South Carolina, through NIH Grant Numbers UL1 RR029882 and
UL1 TR000062.