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Pre- and post-diagnostic lifestyle factors and mortality in - PPT Presentation

Mona Jeffreys School of Social and Community Medicine Breast cancer Most common cancer in women in UK Affects approximately 50000 women in UK each year 851 of patients survive for five years or more diagnosed 20052009 ID: 617984

intake survival adjusted cancer survival intake cancer adjusted alcohol effect 001 age breast 000 disease week menopausal extent status

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Slide1

Pre- and post-diagnostic lifestyle factors and mortality in women with breast cancer

Mona Jeffreys

School of Social and Community MedicineSlide2

Breast cancer

Most common cancer in women in UK

Affects approximately 50,000 women in UK each year

85.1% of patients survive for five years or more (diagnosed 2005-2009)Slide3

Breast cancer incidence

http://www.cancerresearchuk.org/cancer-info/cancerstats/types/breast/incidenceSlide4

(Un)modifiable risk factors

Age

BRCA genes (family history)

Breast density

Benign breast disease

Birthweight

, growth, heightSlide5

Modifiable risk factors

Reproductive factors

Nulliparity

/ late age at first birth, early menarche, late menopause

, breastfeeding

Exogenous oestrogens (

OC, HRT)

Shiftwork

Diet

Saturated fat,

phyto

-oestrogens, fibre

Lifestyle

Body weight, alcohol, physical activity, smokingSlide6

Breast cancer survival

http://www.cancerresearchuk.org/cancer-info/cancerstats/types/breast/survival

/Slide7

Relative survival

Survival “adjusted for” background mortality (excess mortality “due” to cancer)

Avoids need for cause of death

Observed : expected survival ratio

Compares “observed” survival in the cancer population to “expected” survival in general populationSlide8

Relative survival (cont’d)

Life-table methods (census)

May not be valid when “observed” and “expected” groups have a different underlying expected mortality

Compare ethnic groups

Cohort study with low response rateSlide9

Lifestyle determinants of survivalSlide10

Lifestyle determinants of survival

Good evidence of lower survival in overweight womenSlide11

Obesity and all cause mortality

Protani

, BCRT 2010Slide12

Obesity and breast-cancer specific mortality

Protani

, BCRT 2010Slide13

But is it all confounding?

Women’s Intervention Nutrition Study

RCT of 2437 women, aged 43-79

Early stage breast cancer

Intervention: dietary fat reduction

Associated weight loss (2kg difference at 3 years)

Lower recurrence in intervention group (9.8%

vs

12.4%, HR

0.76 (95% CI = 0.60 to 0.98

)Slide14

But is it all confounding?

Women’s Healthy Eating and Living

RCT of 3088 women, aged 18-70

Early stage breast cancer

Intervention: High F&V,

fibre

and low fat 

No change in body weight or energy intake

No difference in breast cancer events (HR

0.96, CI: 0.80 to 1.14)

or mortality (HR

0.91; CI: 0.72 to 1.15) 

Interaction with PA: reduced mortality in women with high F&V and high PA, irrespective of obesity (HR

0.56; CI

:

0.31 to 0.98

)Slide15

Physical activity and breast cancer outcomes

Patterson 2010, h

ttp://dx.doi.org/10.1016/j.maturitas.2010.01.004Slide16

Diet and breast cancer outcomes

Patterson 2010, h

ttp://dx.doi.org/10.1016/j.maturitas.2010.01.004Slide17

Diet and breast cancer outcomes (cont’d)

Patterson 2010, h

ttp://dx.doi.org/10.1016/j.maturitas.2010.01.004Slide18

New Zealand Breast Cancer Study

Nationwide multi-ethnic, age- and ethnicity-matched population-based case-control study

Over-sampling of Māori and Pacific womenSlide19

Methods

Cases identified from Cancer Registry

April 2006 to April 2007

M

ā

ori

and Pacific cases to April 2008

Controls from Electoral Roll

General

M

ā

ori

Additional methods for Pacific controls

GP and community-basedSlide20

Response rates (cases)

1,799 cases

302 (81%) Māori,

70 (46%) Pacific,

1,427 (78%) non-Māori /non-PacificSlide21

Exposures

BMI and WHR

Smoking

Alcohol

Physical activity

Diet

Servings of F&V, meat (red/white), fish, milk, cream, cheeseSlide22

Timing of exposure

Lifetime

“In the last year, on average...”

Within 1 year

After 1 year

Number (%)

1,237 (71.5%)

492 (28.5%)

Median

7.9 months

22.3 months

Range

4 to 12 months

12 to 39 monthsSlide23

Ascertainment of outcome

Linked to death register

Covers all of New Zealand

Requires ethical approval

Censored at 28/02/2009

Not valid for Pacific women

Going home to die”

Informed of date of death but not cause

All cause mortalitySlide24

Statistical methods

Kaplan Meier curves

Log rank tests

Cox regression

Followed from time of diagnosis to dead / censoring

Adjusted for age at diagnosis, menopausal status, interview method, extent of disease at diagnosis (stage)Slide25

Basic results

Māori

nMnP

Total

302

1,427

Deaths

21 (7.0%)

109 (7.6%)

Follow-up (years)

2.92 (1.1 to

3.9 yrs)

3.29 (11

mths

to 3.9 yrs)

Median age

54.3 (47.0 to 62.8)

57.9 (49.1 to 67.6)

Interviewed after 1 year

152 (50%)

340 (24%)Slide26

Follow-up by ethnicity

Log rank test

P=0.56Slide27

Effect of BMI on survival

Log rank test

P=0.21Slide28

Effect of BMI on survival

BMI (kg/m

2

)

<25

25 to 30

>=30

Adjusted*

1.00

0.79 (0.50 to 1.24)

0.73 (0.44 to 1.21)

Pre-diagnostic

1.00

0.86 (0.52 to 1.44)

0.87 (0.49 to 1.54)

Post-diagnostic

1.00

0.49 (0.15 to 1.56)

0.39 (0.14 to 1.13)

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of diseaseSlide29

Effect of WHR on survival

Log rank test

P=0.085Slide30

Effect of WHR on survival

Waist – hip ratio

Tertile

1

Tertile

2

Tertile

3

Adjusted*

1.00

1.20 (0.74

to 1.97)

1.35 (0.82 to 2.22)

Pre-diagnostic

1.00

1.13 (0.65 to 1.95)

1.48 (0.86 to 2.56)

Post-diagnostic

1.00

1.74 (0.53 to 5.73)

1.13 (0.32 to 4.06)

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of diseaseSlide31

Effect of alcohol on survivalSlide32

Effect of alcohol on survival

Newcomb, JCO 2013Slide33

Effect of alcohol on survival

Newcomb, JCO 2013Slide34

Measurement of alcohol

How often did you have a drink containing alcohol? (frequency)

How many drinks containing alcohol did you have on a typical day when you are drinking? (amount)Slide35

Alcohol frequency and amount

Alcohol frequency

Never

<=1/

mth

Up to 1/wk

2-3/wk

4+/wk

Alcohol amount

None

334

0

0

0

0

1-2 drinks

0

354

221

209

257

3-4

drinks

0

20

50

62

61

5-6 drinks

0

16

15

17

17

7-9 drinks

0

10

3

3

8

10 or

more

0

8

8

9

3

Nil

,

slight

,

moderate

,

heavy

Used “slight” as the reference groupSlide36

Effect of alcohol on survival

Log rank test

P=0.14Slide37

Effect of alcohol on survival: overall

Alcohol intake

None

Slight

Moderate

Heavy

Adjusted*

0.95 (0.57 to 1.58)

1.00

0.93 (0.58 to 1.49)

1.96 (0.98 to 3.94)

Pre-diagnostic

0.79 (0.43 to 1.49)

1.00

0.94 (0.56 to 1.57)

1.39 (0.57 to 3.34)

Post-diagnostic

1.61 (0.64 to 4.06)

1.00

0.57 (0.12 to 2.73)

4.82 (1.43 to 16.29)

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of diseaseSlide38

Effect of alcohol on survival: frequency

Alcohol intake (frequency)

Never

≤1/

mth

Up to 1/wk

2+/wk

Adjusted*

1.08

(0.61 to 1.90)

1.00

1.49

(0.82 to 2.72)

1.18

(0.70 to 1.98)

Adjusted**

1.19

(0.66 to 2.16)

1.00

1.63

(0.86 to 3.09)

1.26

(0.73 to 2.19)

Pre-diagnostic**

0.82

(0.41 to 1.64)

1.00

1.05

(0.50 to 2.21)

0.95

(0.52 to 1.71)

Post-diagnostic**

4.88

(1.22 to 19.61)

1.00

8.25

(1.93 to 35.22)

3.80

(0.82 to 17.63)

Merged categories 2-3 per week and 4+ per week

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of disease

** Also adjusted for alcohol amountSlide39

Effect of alcohol on survival: amount

Alcohol intake (drinks per day)

None

1-2

3-4

5-6

7+

Adjusted*

0.98

(0.61 to 1.58)

1.00

0.97

(0.48 to 1.97)

1.33

(0.48 to 3.74)

2.36

(0.79 to 7.07)

Adjusted**

1.19

(0.66 to 2.15)

1.00

0.93

(0.45 to 1.90)

1.36

(0.49 to 3.83)

2.39

(0.80 to 7.18)

Pre-diagnostic**

0.83

(0.41 to 1.66)

1.00

1.06

(0.49 to 2.30)

0.94

(0.22 to 3.93)

1.87

(0.40 to 8.80)

Post-diagnostic**

4.53

(1.15 to 17.80)

1.00

0.54

(0.07 to 4.33)

2.85

(0.56 to 14.53)

3.41

(0.54 to 21.30)

Merged categories 7-9 and 10+ drinks per day

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of disease

** Also adjusted for alcohol frequencySlide40

Smoking

Have you ever smoked, now or in the past?

Are you a current smoker?

Categorised into never, current, ex-smokersSlide41

Effect of smoking on survival

Log rank test

P=0.66Slide42

Effect of smoking on survival

Smoking

Never smoked

Ex-smokers

Current smokers

Adjusted*

1.00

1.05 (0.69 to 1.58)

1.43 (0.76

to 2.68)

Pre-diagnostic

1.00

0.94 (0.59 to 1.50)

1.36 (0.63 to 2.93)

Post-diagnostic

1.00

1.95 (0.70 to 5.41)

2.31 (0.65 to 8.28)

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of diseaseSlide43

Physical activity

Measured using

Godin

questionnaire

Frequency of mild, moderate and strenuous

Analysed in quartiles

Lowest quartile designated as “sedentary”Slide44

Effect of physical activity on survival

Log rank test

P=0.146Slide45

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of disease

Effect of physical activity on survival

Physical

activity

Active

Sedentary

Adjusted*

1.00

1.12 (0.74

to 1.69)

Pre-diagnostic

1.00

0.93 (0.57 to 1.52)

Post-diagnostic

1.00

2.03 (0.90 to 4.60)Slide46

Fruit and vegetable intake

How many servings of

vegetables

(excluding potatoes) did you usually eat each week?

How many servings of

fruit

did you usually eat each week?Slide47

Effect of

fruit and vegetable intake on survival

Fruit intake

(>14 servings per week)

Vegetable intake

(>21 servings per week)

No

Yes

No

Yes

Adjusted*

1.00

1.42 (0.96 to

2.10)

1.00

1.41 (0.91 to 2.19)

Pre-diagnostic

1.00

1.43 (0.92 to 2.22)

1.00

1.39 (0.84 to 2.29)

Post-diagnostic

1.00

1.27 (0.54 to 3.00)

1.00

1.44 (0.55 to 3.73)

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of diseaseSlide48

Summary

Suggestion of poorer survival in women who were

Had lower BMI, but higher WHR

Never and heavy alcohol drinkers

Sedentary

No clear relationship with

F&V intake

SmokingSlide49

Other dietary measures

No clear relationship with intake of

Milk

Cream

Cheese

Meat (red/white)

FishSlide50

Dairy intake and cancer survivalSlide51

Dairy intake and cancer survival

Kroenke

, JNCI 2013Slide52

Limitations of NZ study

Poor measurement of some exposures

Particularly dietary measures

What time frame are women actually reporting on?Slide53

Effect of childhood

fruit and vegetable intake on survival

Fruit intake

(days/week)

Vegetable intake

(days/week)

<=4

5+

<=4

5+

Adjusted*

1.00

1.09 (0.74 to

1.62)

1.00

0.48 (0.28 to 0.83)

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of diseaseSlide54

Effect of childhood

fruit and vegetable intake on survival

Fruit intake

(days/week)

Vegetable intake

(days/week)

<=4

5+

<=4

5+

Adjusted*

1.00

1.09 (0.74 to

1.62)

1.00

0.48 (0.28 to 0.83)

Pre-diagnostic

1.00

1.39 (0.87 to 2.19)

1.00

0.44 (0.24 to 0.82)

Post-diagnostic

1.00

0.47 (0.20 to 1.08)

1.00

0.61 (0.20 to 1.84)

* Adjusted for age, menopausal status, type of interview, ethnicity and extent of diseaseSlide55

Determinants of high F&V reporting

Fruit intake

(>14 servings per week)

Vegetable intake

(>21 servings per week)

Childhood F&V

1.86 (1.42 to 2.46)

1.65 (1.28 to 2.13)

Ever smoked

0.71 (0.57 to 0.88)

1.00 (0.79 to 1.28)

Ethnicity

0.87 (0.65 to 1.16)

0.83 (0.59 to 1.16)

Unrelated: area deprivation, childhood SEP, age, menopausal status, extent of disease Slide56

Determinants of high F&V reporting

Fruit intake

(>14 servings per week)

Vegetable intake

(>21 servings per week)

Childhood F&V

1.86 (1.42 to 2.46)

1.65 (1.28 to 2.13)

Ever smoked

0.71 (0.57 to 0.88)

1.00 (0.79 to 1.28)

Ethnicity

0.87 (0.65 to 1.16)

0.83 (0.59 to 1.16)

Interviewed after 1 year

1.15 (0.91 to 1.45)

1.50 (1.16 to 1.95)

Unrelated: area deprivation, childhood SEP, age, menopausal status, extent of disease Slide57

Limitations of NZ study

Poor measurement of some exposures

Particularly dietary measures

What time frame are women actually reporting on?

Pre- and post-diagnostic comparisons are not of the same women

Ideally have a measure of change

Survivor bias

Conditional survival

Limited statistical power for some analysesSlide58

Where next?

Re-analysis with longer follow-up

Physical activity intervention trial

acceptability of intervention and randomisation

Consider weight loss intervention

effect on lean body massSlide59

Acknowledgements

Co-PIs:

Lis

Ellison-

Loschmann

, Fiona McKenzie,

Riz

Firestone

Co-Investigators: Neil Pearce, Michelle Gray, Ate

Moala

,

Soo

Cheng

Funders:

New Zealand Lottery Grants Board

Massey University Research Fund

Health Research Council of New Zealand

Cancer Society of New Zealand