Transcript Presentation - MD Anderson Cancer Center

Visceral adiposity and clinical outcomes in
postmenopausal women with operable
breast cancer.
Does body shape matter?
Shalini Dalal, M.D.
Associate Professor
Department of Palliative Care and Rehab Medicine
U.T. MD Anderson Cancer Center, Houston TX
10th October 2014
Overview
Obesity definitions
 National obesity trends
 General vs Abdominal obesity
 Obesity and cancer
 Breast cancer retrospective study

Obesity

Definition
◦ an abnormal or excessive fat accumulation in adipose tissue, to the
extent that health is impaired

Body mass index (BMI): kg/m2
◦ For adults aged 20 years or older,
 Overweight : BMI 25.0to 29.9
 Obesity :
BMI ≥30.0





Obesity may be divided into
grade 1: BMI, 30 to <35
grade 2: BMI, 35 to <40)
grade 3 BMI ≥40
BMI does not discriminate between fat and lean mass, nor does
it address body fat distribution
 Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: executive summary: Expert
Panel on the Identification, Evaluation, and Treatment of Overweight in Adults. Am J Clin Nutr. 1998
 WHO Expert Committee on Physical Status. Physical Status:The Use and Interpretation of Anthropometry. Geneva, Switzerland:
World Health Organization; 1995
Obesity prevalence in the US

NHANES (National Health and Nutrition Examination Survey):
program of NCHS, CDC & Prevention
◦ tracks trends in the prevalence of obesity by collecting data on height and
weight measurements.
◦ Cross-sectional survey of nationally representative sample of the US
population. Initially started in 1960
◦ Since 1999 data released in 2-year cycles:

2011-2012*
◦ Overweight/obese (BMI≥25)
 Overall 69%; males 71.6%, females 66.5%
◦ Obese (BMI≥30)
 Overall 34.9%; Males 33.7%, females 36.5 %
*Ogden et al. Prevalence of Childhood and Adult Obesity in the United States, 2011-2012.
JAMA. 2014
Trends in the prevalence of obesity among adults aged 20
years and over, by sex: United States 1960-2012
All
Men
Women
35
33.4
33.3
30
30.9
31.3
27.5
27.8
25.4
25
20
13.4
14.5
15
1976-1980
20.2
1971-1974
15
33.2
32.9
35.3
35.1
33.3
31.1
35.5
34.3
35.8
35.7
35.5
32.2
36.5
35.1
33.7
23.2
10
5
• No significant change from 2003-2004 to
2011-2012,
• Except women ≥ 60 years
• Obesity increased from 31.5% to more
than 38%.
2011-2012
2009-2010
2007-2008
2005-2006
2003-2004
Years
2001-2002
1999-2000
1988-1994
0
1960-1962
Percentage
40
General and Abdominal obesity
• Fat is principally deposited in two compartments;
subcutaneously and viscerally
• Dr Jean Vague in 1947, first to draw attention to different
patterns of fat distribution:
• Android obesity: upper-body, male-type fat (visceral)
• Gynoid obesity: lower-body, female-type fat
(subcutaneous)
.
Body shape and obesity
Where the weight is deposited might be as important a
consideration as overall weight gain.
• Visceral fat more metabolically active and has multiple endocrine,
metabolic and immunological functions
• Shown to be central to the pathogenesis of the MetSyn, a proinflammatory, pro-coagulant state associated with insulin resistance
•
•
•
MetSyn: include abdominal obesity, dyslipidemia, elevated fasting plasma glucose and
hypertension
↑ Visceral fat accumulation associated
Type 2 diabetes mellitus
Dyslipidemia
Cancer

Hypertension
CAD
more strongly associated
than BMI alone
The importance of fat location in terms of dysmetabolism risk is evident as
an ↑ ratio of visceral fat area to subcutaneous fat area has been shown to
be strongly related to disorders of glucose and lipid metabolism in obese
subjects
Galic S,. Adipose tissue as an endocrine organ. Mol Cell Endocrinol 2010
Alberti KG. Metabolic syndrome – A Consensus Statement from the International Diabetes Federation. Diabet Med 2006
Fujioka S Contributionof intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism in human
obesity. Metabolism 1987
Waist circumference (WC) & waist-to-hip ratio
(WHR)



Simple anthropometric measure of abdominal obesity, fat
distribution
WC: visceral fat; WHR: visceral to subcutaneous fat distribution
Both WC and WHR are independent predictors of mortality.
◦ may be more precise than BMI in assessing obesity-related health burden,
including mortality, risk of type 2 diabetes and cardiovascular disease.

NHLB Institute clinical guidelines recommend that clinicians assess WC
•
Yusuf et al.. Obesity and the risk of myocardial infarction in 27,000 participants from 52countries: a
case-control study. Lancet 2005
Folsom et al. Associations of general and abdominal obesity with multiple health outcomes in older
women:the Iowa Women ’s Health Study. Arch Intern Med 2000
Ashwell et al. Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health
risks of obesity and how its use could simplify the international public health message on obesity. Int J
Food Sci Nutr 2005;
Pischon et al. General and abdominal adiposity and risk of death in Europe. N Engl J Med 2008;
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•
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National prevalence of abdominal
obesity
RESEARCH LETTER JAMA September 2014
Trends in Mean Waist Circumference and Abdominal Obesity Among
US Adults, 1999-2012

Methods: Data from seven 2-year cycles of the NHANES
starting with 1999-2000 and concluding with 2011-2012.
◦ Response rates 69.5% to 79.6%.
Waist circumference measured just above the iliac crest
 Abdominal obesity defined as a WC > 102 cm in men and > 88
cm in women.

Ford ES, Maynard LM, Li C.Trends in Mean Waist Circumference and Abdominal Obesity Among
US Adults, 1999-2012. JAMA. 2014
Results


N=32 816 men and \women >/=20 yrs.
mean waist circumference
◦ ↑ progressively and significantly to 98.5 cm in 2011-2012 from 95.5 cm in 19992000

Significant increases occurred in men, women, non-Hispanic whites,
non-Hispanic blacks, and Mexican Americans.

Particularly large increases between the first and last surveys were
observed
◦ non-Hispanic white women aged 40 to 49 years (6.6 cm)
◦ non-Hispanic black men aged 30 to 39 years (8.1 cm)
◦ Mexican American men aged 20 to 29 years (8.7 cm),
◦ Mexican American women aged 70 years or older (11.2 cm),
◦ non-Hispanic black women aged 30 to 39 years (11.6 cm).
Trends in the prevalence of Abdominal obesity among adults: United
States 1999-2012
Overall
men
women
70
61.3
60
Percentage
50
55.4
46.4
57.1
48.4
40
30
20
10
37.1
39.1
52.1
42.5
58.2
51.6
44.8
61.6
62.3
52.8
52.7
43.4
43
64.7
54.2
43.5
from 2003 to 2012, significant increases in mean WC
• among all adults (P = .02 for linear trend),
• women (P ≤ .01 for linear trend),
• non-Hispanic blacks (P = .02 for linear trend),
• Mexican Americans (P = .01 for linear trend).
0
1999-2000 2001-2002 2003-2004 2005-2006 2007-2008 2009-2010 2011-2012
Years
Conclusion
The prevalence of obesity as measured by
BMI remains high, but has plateaued since
2003-2004
 In contrast prevalence of abdominal obesity
as measured by WC is still increasing.

Robust link between obesity and cancer

↑ Cancer risk:
◦ esophagus, pancreas, colorectal, breast (postmenopausal), endometrium,
kidney
◦ relative risk estimates of 1.1–1.66 per 5 kg/m2 incremental increase in BMI

↑ Cancer-related mortality
◦ 14% of all deaths from cancer in men and 20% in women.
Animal models energy restriction decreases spontaneous tumor
occurrence
 Wt loss following bariatric surgery associated with reduction in
cancer incidence

•
•
•
•
•
Renéhan, et al. Body-mass index and incidence of cancer: A systematic review and meta-analysis of prospective
observational studies. Lancet 2008
Calle, EE et al. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. Adults. NEJM
2003;
Dirx et al. Energy restriction and the risk of spontaneous mammary tumors in mice: A meta-analysis. Int J Cancer 2003
Mai et al.. Calorie restriction and diet composition modulate spontaneous intestinal tumorigenesis in Apc(Min) mice
through different mechanisms. Cancer Res 2003
Sjostrom et al. Effects of bariatric surgery on cancer incidence in obese patients in Sweden (Swedish obese subjects study):
A prospective, controlled intervention trial. Lancet Oncol 2009
Mechanisms underlying obesity and tumorigenesis
Doyle et al. Obesity-related cancers; Visceral obesity, metabolic syndrome, insulin resistance
and cancer. Proceedings of the Nutrition Society (2012),
Obesity and breast cancer



Epidemiological data links obesity (BMI) to higher risk for the
development of post-menopausal breast cancer
Following diagnosis, higher BMI is also associated with higher risks
of recurrence and death.
Litton et al JCO 2008
◦ high BMI associated with a decreased pCR to NC, which in part may explain the
poorer outcomes observed in obese breast cancer patients.
•
•
•
•
•
•
•
•
•
Petrelli et al. Body mass index, height, and postmenopausal breast cancer mortality in a prospective cohort of US women. Cancer
causes & control : CCC. 2002.
Morimoto et al. Obesity, body size, and risk of postmenopausal breast cancer: the Women's Health Initiative (United States). Cancer
causes & control : CCC. Oct 2002;
Whiteman et al. Body mass and mortality after breast cancer diagnosis. Cancer Epidemiol Biomarkers Prev. Aug 2005;.
Majed et al.. Is obesity an independent prognosis factor in woman breast cancer? Breast Cancer Res Treat. Sep 2008;
Hahn et al. Factors associated with advanced disease stage at diagnosis in a population-based study of patients with newly
diagnosed breast cancer. Am J Epidemiol. 2007;
Berclaz et al. Body mass index as a prognostic feature in operable breast cancer: the International Breast Cancer Study Group
experience. Ann Oncol. Jun 2004
Tao et al. . Association of overweight with breast cancer survival. Am J Epidemiol. 2006;
Loi et al. Obesity and outcomes in premenopausal and postmenopausal breast cancer. Cancer Epidemiol Biomarkers Prev. Jul 2005
Litton et al. Relationship between obesity and pathologic response to neoadjuvant chemotherapy among women with operable
breast cancer. J Clin Oncol. 2008
Studies of central obesity and breast
cancer

Confined to epidemiological studies to define breast
cancer risk.
◦ In majority of these studies, WC and/or WHR, were positively associated
with increased breast cancer risk
• Connolly BS, Barnett C,Vogt KN, Li T, Stone J, Boyd NF. A meta-analysis of published literature on
waist-to-hip ratio and risk of breast cancer. Nutrition and cancer. 2002
• Harvie M, Hooper L, Howell AH. Central obesity and breast cancer risk: a systematic review. Obesity
reviews : an official journal of the International Association for the Study of Obesity. Aug 2003
• Stoll BA. Upper abdominal obesity, insulin resistance and breast cancer risk. Int J Obes Relat Metab
Disord. Jun 2002
Gold standard techniques to quantify
body fat compartments
•
•
•
•
•
•
•

CT or MRI

Several studies using above suggest higher Visceral fat to be
associated with immune and metabolic dysfunction and
promotes tumorigenesis.
Fujioka S, Contribution of intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism in human obesity.
Metabolism. Jan 1987;
Pou et al.Visceral and subcutaneous adipose tissue volumes are cross-sectionally related to markers of inflammation and
oxidative stress: the Framingham Heart Study. Circulation. 2007;
Pouliot et al.Visceral obesity in men. Associations with glucose tolerance, plasma insulin, and lipoprotein levels. Diabetes. 1992;
Ohki et al.Visceral fat accumulation is an independent risk factor for hepatocellular carcinoma recurrence after curative
treatment in patients with suspected NASH. Gut. 2009
Takahashi, et al. Association of visceral fat accumulation and plasma adiponectin with rectal dysplastic aberrant crypt foci in a
clinical population. Cancer science. 2009
Akiyama T,Yoneda M, Inamori M, et al.Visceral obesity and the risk of Barrett's esophagus in Japanese patients with nonAllott, et al. MMP9 expression in oesophageal adenocarcinoma is upregulated with visceral obesity and is associated with poor
tumour differentiation. Molecular carcinogenesis. 2013
Association between visceral
adiposity, BMI and Clinical Outcomes
in Postmenopausal Women with
Operable Breast Cancer
2014 ASCO Annual Meeting
The Collaborative Team

Shalini Dalal1, David Hui1, Sai-ching J2.Yeung, Gary
B. Chisholm3, Ijeoma Stephanie Ihenacho1, Richard
Ogunti4, Maxine De la Cruz1, Marieberta Vidal1,
Deepak Bedi4, Rony Dev1, Eduardo Bruera1, and
Jennifer Litton5
1 Palliative
Care and Rehab Medicine
2 Emergency Medicine
3 Biostatistics
4 Diagnostic Imaging
5 Breast Medical Oncology
Study hypothesis and objectives

High BMI shown to negatively impact breast cancer outcomes in some but
not all studies.

Visceral fat is considered more pathogenic than subcutaneous fat, and
systemic inflammation and dysmetabolism associated with may contribute
to the negative impact of obesity on breast cancer outcomes.

To our knowledge no study to date have examined the relationship
between CT determined adiposity parameters and clinical outcomes in
postmenopausal women with breast cancer

Objective:
◦ To examine the association between visceral adiposity as measured
by gold standard technique on clinical outcomes
 pCR
 recurrence-free interval (RFI)
 overall survival (OS)
Methods
Retrospective study approved by the IRB
 Consecutive female patients with invasive breast
cancer diagnosed between years 2001-2012
 Inclusion criteria

◦ Postmenopausal status
◦ primary invasive ductal or lobular non-inflammatory breast
cancer
◦ Clinical Stage I-III
◦ received neo-adjuvant chemotherapy (NC) followed by
definitive surgery within 1 year of NC initiation
◦ had abdominal CT images within 8 weeks of NC initiation
Data collected
Baseline factors
Demographics: age & race
 Tumor related factors:

◦ ER, PR, & HER-2 neu status, Clinical stage, nuclear grade, presence of lymphovascular invasion

Type of NC treatment
◦ anthracycline, taxol or both based regimen

BMI :
◦ Normal category (BMI 18.5 to <25 kg/m2), overweight (BMI 25 to 29.9 kg/m2), obese class (B
30 to 34.9 kg/m2), and severely obese (BMI ≥ 35 kg/m2),
 Visceral adiposity assessment:.
Clinical outcomes:
 Lymph node (LN) status at surgery:
◦ number of LNs positive: negative, 1-3 LNs, 4-9 LNs, ≥ 10 LNs

Pathologic complete response [pCR]
◦ from surgical biopsy; defined as no residual invasive carcinoma in breast or axillary lymph nod
Residual DCIS not included in the pCR group

Survival times: from date of NC initiation
◦ Relapse-free [RFS]: date of recurrence (local/distant) or last followup
◦ Overall survival [OS]: date of death or last followup
◦ Disease-specific [DSS]: if death occurred in setting of distant recurrence
CT Adiposity measurements
CT scans obtained within 8 weeks of NC initiation
 L3 chosen as landmark.
 The average of 2 consecutive crossectional images used to
obtain visceral and subcutaneous fat areas (VFA and SFA,
respectively) in cm2.
 The VFA:SFA ratio (VSR) was used as a metric of regional fat
distribution
 Median cut-off values used


Validated software: NIH Image J
version 1.47 http://imagej.nih.gov/ij
Statistical analysis:
Univariate and multivariate logistic regression models
to predict pCR were run to compute odds ratio and
corresponding 95% confidence intervals (CI).
 Cox proportional hazards regression methods used to
model RFS, DSS and OS outcomes as function of
adiposity measures and other relevant clinical factors.

◦ adiposity parameters (VFA, SFA,VSR, BMI)
◦ and key outcomes (pCR, RFS, DSS & OS),
All reported p values are two-sided, and p< 0.05 was
considered statistically significant
Results: Baseline characteristics


N= 1227 postmenopausal women with breast cancer
Median age 58 years (range 29 to 82 years)
◦ 63% White, 17% Black, 15% Hispanic, 5% Other

BMI category:
◦ normal BMI=24% (n=293)
 includes 11 pts who were underweight (BMI range 16 to 18).
◦ Overweight= 32% (n=386)
◦ Obese = 24% (n=286)
◦ Severely obese= 20% (n=252)

Median CT- Adiposity values:
◦ VFA=109 cm2
◦ SFA=240 cm2
◦ VSR=0.41
Results: Baseline tumor characteristics, N=1227
Characteristics
Baseline TNM Stage
Nuclear Grade
Lymphovascular invasion
ER Status
PR Status
HER-2 Neu Status
NC Regimen included
I
II
III
1
2
3
Positive
Negative
Positive
Negative
Positive
Negative
Positive
Negative
Anthracycline & Taxol
Taxol based
Anthracycline based
N
%
32
736
459
52
382
786
272
951
753
474
526
694
329
898
1073
73
81
3
60
37
4
31
64
22
78
61
39
43
57
27
73
87
6
7
Correlation between BMI and adiposity
measures.
r=0.70
r=0.20
r=0.84

Scatter plot matrix:
CT-Adiposity measures and pCR to NC

Median time from chemotherapy to surgery
◦ = 182 days (range 39 to 334 days).

pCR achieved
◦ ~20% (n=249) pts

In univariate modeling
◦ significant associations between achievement of pCR and
VFA and VS ratio (for both categoric and continuous), but
not with SFA or BMI.
◦ also significantly associated with age, race, baseline clinical
stage, nuclear grade, lymphovascular status, hormone
receptor status, and the type of NC treatment.
Odds of pCR:Adjusted Logistic Regression Model
Variable
Comparison
Age
Odds Ratio
95% C.I.
P
0.99
0.25 to 1.01
0.25
Black vs. White
0.79
0.51 to 1.23
0.30
Hispanic vs. White
1.64
1.06 to 2.51
0.03
Other vs. White
0.81
0.10 to 4.65
0.58
TNM Stage
Stage III vs. I & II
0.67
0.47 to 0.95
0.02
Nuclear Grade
3 vs. 1 & 2
2.34
1.52 to 3.61
< 0.0001
LV invasion
Positive vs. Negative
0.36
0.21 to 0.58
< 0.0001
ER Status
Positive vs. Negative
0.47
0.32 to 0.69
< 0.0001
PR Status
Positive vs. Negative
0.50
0.32 to 0.77
0.002
HER-2 Neu Status
Positive vs. Negative
2.76
1.98 to 3.83
< 0.0001
Taxane vs. Both
0.46
0.21 to 0.99
0.049
Anthracycline vs. Both
0.52
0.22 to 1.21
0.128
SFA
>median vs. ≤ median
1.69
1.18 to 2.42
0.004
VFA
>median vs. ≤ median
0.51
0.36 to 0.73
< 0.0001
Race
NC Regimen
Survival outcomes.

Median survival times for RFS, DSS, and
OS was not attained in the follow-up of this
study.

Recurrent disease: 209 (17%) pts;
◦ majority (n=195) had distant recurrences.

Deceased: 187 (15%) deaths.
◦ Deaths were classified as caused by breast cancer
if the death occurred after distant recurrence
(n=140).
Recurrence free survival:Adjusted Cox Regression Model
Variable
Age
Race
TNM Stage
Nuclear Grade
LV invasion
ER Status
PR Status
HER-2 Neu Status
NC Regimen
pCR achieved
Number of Lymph
nodes (LN) positive
BMI category
Visceral to Subcut fat
Ratio
Comparison
OR
95% C.I.
P
Black vs. White
Hispanic vs. White
Other vs. White
Stage III vs. I & II
3 vs. 1 & 2
Positive vs. Negative
Positive vs. Negative
Positive vs. Negative
Positive vs. Negative
Taxane vs. Both
Anthracycline vs. Both
0.99
1.59
.61
1.16
1.56
1.41
1.46
0.55
0.74
0.74
1.05
0.48
0.98 to 1.01
1.12 to 2.27
0.36 to 1.04
0.59 to 2.31
1.15 to 2.12
1.00 to 1.99
1.07 to 2.00
0.38 to 0.80
.52 to 1.05
0.51 to 1.06
0.58 to 1.87
0.25 to 0.92
0.48
0.01
0.07
0.67
0.004
0.05
0.02
0.002
0.09
0.10
0.88
0.03
Positive vs. Negative
0.33
0.16 to 0.65
0.002
1-3 LN Positive vs. Negative
4-9 LN Positive vs. Negative
≥ 10 LN Positive vs. Negative
Overweight vs. Normal
Obese vs. Normal
Severely obese vs. Normal
1.82
3.32
6.00
0.80
0.72
1.03
1.18 to 2.79
2.15 to 5.11
3.67 to 9.80
0.56 to 1.18
0.47 to 1.11
0.69 to 1.56
0.007
< 0.0001
< 0.0001
0.25
0.14
0.88
>median vs. ≤ median
1.45
1.08 to 1.96
0.02
Overall survival: Adjusted Cox Regression Model
Variable
Age
Race
TNM Stage
Nuclear Grade
LV invasion
ER Status
PR Status
HER-2 Neu Status
NC Regimen included
pCR achieved
Number of Lymph
nodes (LN) positive
BMI category
Visceral to Subcut fat
Ratio
Comparison
OR
95% C.I.
P
Black vs. White
Hispanic vs. White
Other vs. White
Stage III vs. I & II
3 vs. 1 & 2
Positive vs. Negative
Positive vs. Negative
Positive vs. Negative
Positive vs. Negative
Taxane vs. Both
Anthracycline vs. Both
1.00
1.20
0.67
0.59
1.74
1.27
1.28
0.49
0.73
0.72
1.02
0.82
0.98 to 1.02
0.80 to 1.80
0.39 to 1.14
0.24 to 1.46
1.26 to 2.40
0.88 to 1.82
0.92 to 1.79
0.33 to 0.72
0.50 to 1.06
0.49 to 1.05
0.54 to 1.92
0.47 to 1.44
0.87
0.39
0.14
0.25
0.001
0.20
0.15
< 0.0001
0.10
0.09
0.95
0.48
Positive vs. Negative
0.52
0.28 to 0.96
0.04
1-3 LN Positive vs. Negative
4-9 LN Positive vs. Negative
≥ 10 LN Positive vs. Negative
Overweight vs. Normal
Obese vs. Normal
Severely obese vs. Normal
1.54
3.26
4.78
0.65
0.65
0.70
0.97 to 2.46
2.08 to 5.11
2.87 to 7.98
0.44 to 0.96
0.42 to 1.00
0.45 to 1.08
0.07
< 0.0001
< 0.0001
0.03
0.05
0.10
>median vs. ≤ median
1.80
1.31 to 2.48
< 0.0001
Disease specific survival: Adjusted Cox Regression Model
Variable
Age
Race
TNM Stage
Nuclear Grade
LV invasion
ER Status
PR Status
HER-2 Neu Status
NC Regimen included
pCR achieved
Number of Lymph
nodes (LN) positive
BMI category
Visceral to Subcut fat
Ratio
Comparison
OR
95% C.I.
P
Black vs. White
Hispanic vs. White
Other vs. White
Stage III vs. I & II
3 vs. 1 & 2
Positive vs. Negative
Positive vs. Negative
Positive vs. Negative
Positive vs. Negative
Taxane vs. Both
Anthracycline vs. Both
0.99
1.40
0.56
0.78
1.76
1.67
1.43
0.50
0.62
0.62
1.08
0.42
0.97 to 1.01
0.90 to 2.18
0.29 to 1.09
0.31 to 1.95
1.21 to 2.56
1.08 to 2.58
0.98 to 2.09
0.32 to 0.77
0.40 to 0.97
0.40 to 0.97
0.53 to 2.19
0.18 to 0.97
0.32
0.13
0.09
0.59
0.003
0.02
0.06
0.002
0.03
0.04
0.84
0.04
Positive vs. Negative
0.35
0.15 to 0.81
0.01
1-3 LN Positive vs. Negative
4-9 LN Positive vs. Negative
≥ 10 LN Positive vs. Negative
Overweight vs. Normal
Obese vs. Normal
Severely obese vs. Normal
1.75
3.66
6.35
0.73
0.63
0.82
1.02 to 3.00
2.17 to 6.20
3.51 to 11.46
0.46 to 1.17
0.37 to 1.07
0.50 to 1.35
0.04
< 0.0001
< 0.0001
0.19
0.09
0.43
>median vs. ≤ median
1.76
1.22 to 2.55
0.002
Adjusted Kaplan–Meier Estimates of Survival According
to the Visceral to Subcutaneous ratio
Overall survival
Relapse free survival
Disease specific survival
CONCLUSION

This retrospective study of postmenopausal women
with operable stage breast cancer suggests fatdepot specific dfferences in clinical outcomes.
◦ Higher visceral fat and lower subcutaneous fat were
independently associated with lower likelihood of pCR.
◦ Higher visceral to subcutaneous fat ratio predicted worse
RFS, DSS and OS.

The predisposition to accumulate fat viscerally
versus subcutaneously may be a novel prognostic
factor independent of BMI, absolute fat stores and
tumor characteristics.
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