breast cancer recurrence and obesity - ysc2015 - robinson

Medicine, Nursing and Health Sciences

Moderate/severe obesity is associated with recurrence after breast cancer: A “real life” example of survival analysis

Penny Robinson, Robin Bell, Susan DavisBBioMed Sc (Hons), M Biostat, GCAPWomen’s Health Research Program, SPHPM, Monash University

YSC 2015 Conference, 5 – 6 February 2015

Acknowledgements and Funding BUPA study coordinator: Maria La China,

Marijana Lijovic

Pam Fradkin, Jo Bradbury (design of questionnaires)

Study Advisory Group:Dr Jacquie Chirgwin, A/Prof John Collins, Prof Graham Giles, Mr Peter Gregory, Mr Stewart Hart, Miss Suzanne Neil and Mrs Avis McPhee.

No conflict of interest

BUPA Health Foundation Novartis Australia L.E.W. Carty Trust Connie and Craig Kimberley NHMRC (Grant no. 219279 and 490938) Jack and Robert Smorgon Families

Foundation Roy Morgan Research. Victorian Cancer Agency Research

Fellowship (Robin Bell) NHMRC (Prof Davis NHMRC Prinicipal

Research Fellow)

5–6 February 2015Moderate/severe obesity is associated BC recurrence 2

Background There are factors that increase the risk of getting breast cancer (BC). There are also factors that affect the outcome after a diagnosis of BC.

Improvements in treatment Survival after BC is improving.(More women surviving longer after BC.)

– 5 year survival (2006 - 2010) was 89%.– Nodes negative: survival 96.5%– Nodes positive: survival 80.2%.

AIHW 2012. BC in Australia. Cancer series no 71.


http://www.cancer.gov/



Moderate/severe obesity is associated BC recurrence 4

Important terminology

Active disease definition (an “event”):– Recurrence in the same breast.– Metastatic disease (BC spread elsewhere in the body).– Cancer involving the other breast (spread or new BC).– The initial BC (reported in EQ) doesn’t count.

Stage 1 definition:– Small cancer (<2 cm) confined to the breast– No lymph node involvement

Types of surgery:– Lumpectomy: removal of cancerous lump– Mastectomy: removal of entire breast

5–6 February 2015

http://healthsciencedegree.info/stages-of-breast-cancer-1-4/



Research question Does moderate-severe obesity (BMI 30 to <40 kg/m2)

contribute to BC recurrence and mortality?

Population of interest:– Women whose cancer was hormone receptor positive (HR +) and

human epidermal growth factor receptor (HER2) negative.


Fat cells Fat/obese

Insulin resistance

Estrogen

HR+ Estrogen +/-Progesterone

Insulin levels

Recurrence / Death

Endocrine therapy

Body Mass Index (BMI)

Used World Health Organisation (WHO) BMI classification.


BMI classification category BMI range n (%) Comments

Underweight < 18.5 kg/m2 14 (1.2%) Excluded

Normal weight 18.5 to < 25 kg/m2 528 (44.0%) Reference

Overweight 25 to < 30 kg/m2 374 (31.2%)

Moderate-severe obesity 30 to < 40 kg/m2 253 (21.1%)

Morbid obesity ≥ 40 kg/m2 30 (2.5%) Excluded

Methods - Recruitment BUPA Health Foundation Health and Wellbeing after BC study.

Recruited < 1 year after initial invasive breast cancer diagnosis.Recruitment from June 2004 to December 2006.“Enrolment questionnaire” (EQ).

Followed up annually for 5 years.“Follow-up questionnaire” (FQ1 to FQ5)

Recruitment mainly (78%) through the Victorian Cancer Registry (VCR).

Representative of all Victorian women with BC.

Lijovic M et al. BMC Cancer 2008;8:126–30

Cohort design use survival analysis for research question


Methods – Data collected Enrolment questionnaire (EQ)

– Demographics (including age, BMI)– Initial & subsequent treatment

• Surgery• Radiotherapy• Chemotherapy• Oophorectomy

– Use of OAET

Follow-up questionnaires (FQ1 to FQ5)– Any active disease

• Location, Date• Check against change in treatment

Victorian Cancer Registry (VCR)– Oestrogen / Progesterone

receptor status– Tumour diameter– Number of nodes taken,

positive– Stage of disease

– Monthly death checks


Survival analysis is about events

We are interested in two types of events.

1. First report of active disease (recurrence, cancer spread or new BC)

2. Death due to BC.

We want to know:

Woman experience event (active disease / death due to BC) – Y / N

When?

Survival analysis answers this.


Calculating dates of events

Date of BC diagnosis = entry into survival analysis.

Exit dates:

Date of active disease = date of event.

Completed FQ5 (no active disease): Date of FQ5 = date of censoring.

Follow-up questionnaires sent out every 1 year.

95% of women returned questionnaires within 1.2 years of previous one.– “Withdrawals” classified at the 1.2 year mark.

If death within 1.2 years of last completed questionnaire– If death from BC (no recurrence). Date of death = event.– If death not BC. Date of death = date of censoring.

If no questionnaire returned within 1.2 years (and no death in that time) withdrawal classification (active / passive withdrawal, loss to follow-up) Date of last completed questionnaire = date of censoring.


All exit dates one variable for survival analysis set-up

Flow chart describing “events” and censoring


1199 EQ

1139 FQ1

1081 FQ2

1053 FQ3

1009 FQ4

954 FQ5

60 did not complete FQ1





1121 No active disease up to FQ1

18 Active disease up to FQ1

Completed EQ









1121

1051

1013

961

89816

47

16

36

14

24

18

52

1860

6 (33%)12

26 4 (13%)

32 8 (20%)

40 8 (17%)

Died BC, n = 7

Died BC, n = 2

Died BC, n = 4

Died BC, n = 2

Died BC, n = 5

non-BC, n = 2Withdrew n = 51





Statistical analysis (Stata 12.1) Preliminary descriptive statistics

– Cross-tabs and chi-square tests (categorical variables)– Median & quartiles (continuous variables)

Survival analysis

stset BCdeathrecur_eventdate_19May2014 if(activeEQ==1), origin(time DateDiagnosis) failure(BCdeathrecur_eventtype_19May2014==22 21) scale(365.25)

– Cox proportional hazard ratio modelling• Univariable regression first.• Manual stepwise regression done.• Obesity “forced in” first.• Obesity + Stage 1 had the highest log-likelihood chi-square

value, so that was the next model, etc.– Kaplan-Meier survival curves

• By “BMI category”, adjusting for other factors in the final Cox regression model.


Results – Descriptive statistics 1155 included in analysis.

Age at diagnosis 58.4 ± 11.6 years. (57.49% were 50 – 69 yrs.)

71.08% (n=821) had a lumpectomy; 28.57% (n=330) had a mastectomy.

600 (51.95%) had Stage 1 disease, 517 (44.76%) were beyond Stage 1.

Majority (88.66%, n=1024) received OAET by FQ1.

Many had radiotherapy (75%, n = 867) or chemotherapy (41%, n = 476).

Median follow-up time: 5.6 years.

98 events (event rate 8.48%) – 78 active disease, 20 deaths from BC.


Cox regression (n = 1155) 98 events (event rate 8.48%)

Univariable Cox regression Multivariable Cox Regression

HR (95% CI) p-value HR (95% CI) p-value

Body Mass Index

≥ 18.5 - < 25 (Normal) 1.00 1.00

≥ 25 - < 30 (Overweight) 1.35 (0.83 to 2.18) 0.226 1.00

≥ 30 - < 40 (Obese) 2.05 (1.27 to 3.33) 0.003 1.71 (1.12 to 2.62) 0.014

Mastectomy surgery at EQ 2.80 (1.88 to 4.17) <0.001 3.28 (1.98 to 5.44) <0.001

HRT at diagnosis 0.87 (0.48 to 1.55) 0.632

Beyond Stage 1 at diagnosis 3.30 (2.10 to 5.17) <0.001 2.87 (1.73 to 4.75) <0.001

On OAET by FQ1 0.52 (0.30 to 0.88) 0.015 0.26 (0.14 to 0.46) <0.001

Radiotherapy by FQ1 0.81 (0.52 to 1.26) 0.355 2.12 (1.24 to 3.63) 0.006

Chemotherapy by FQ1 2.34 (1.56 to 3.51) <0.001


Cox regression – Stage 1 only26 events (event rate 4.3%), n = 600

Univariable Cox regression Multivariable Cox Regression

HR (95% CI) p-value HR (95% CI) p-value

Body Mass Index

≥ 18.5 - < 25 (Normal) 1.00 1.00

≥ 25 - < 30 (Overweight) 1.05 (0.37 to 2.94) 0.930 1.00

≥ 30 - < 40 (Obese) 3.28 (1.36 to 7.91) 0.008 3.23 (1.48 to 7.03) 0.003

Mastectomy surgery at EQ 1.94 (0.81 to 4.61) 0.135

HRT at diagnosis 0.72 (0.22 to 2.39) 0.588

On OAET by FQ1 0.41 (0.17 to 0.99) 0.047 0.41 (0.17 to 0.98) 0.046

Radiotherapy by FQ1 0.45 (0.20 to 1.02) 0.055

Chemotherapy by FQ1 1.39 (0.53 to 3.69) 0.506


Final model survival curve, by obesity – adjusted for other factors in the model.


Source: Robinson PJ, Bell RJ, Davis SD. Maturitas 79 (2014) 279 - 286.

Conclusion - Biostatistics

“Real life” survival analysis can be more complicated than examples taught in survival analysis courses.

Survival analysis can be difficult when the total number of deaths/ recurrences/ other undesirable outcomes is small.

– In our study, only 98 (8.48%) experienced an “event”– 864 (74.81%) completed FQ5– Others withdrew/died from non-BC.


Conclusion – Clinical significance

Moderate-severe obesity associated with a higher BC recurrence rate (in HR+, HER2- disease).

This result remained in women who had Stage 1 disease (good prognosis).

Obesity is a modifiable risk factor.

Further research is required to determine if reducing weight after diagnosis improves prognosis.


Questions?

Publication from this work:

Robinson PJ, Bell RJ, Davis SD. Maturitas 79 (2014) 279 - 286.

Contact:

[email protected]

Twitter: @PennyRobaus (me)

@Monash_WHRP (Women’s Health Research Program)

@Monash_SPHPM (Monash Public Health)


mailto:[email protected]

Moderate/severe obesity is associated BC recurrence 21

Additional slides for reference/information

5–6 February 2015

Types of withdrawals

Active withdrawal (AW)– Woman (or family member) advised us they were withdrawing

Passive withdrawal (PW)– Did not return a questionnaire, despite follow-up.– Not an active withdrawal,

Lost contact (LC)– Questionnaire “return to sender” (to us).– Unable to contact woman by post, home/work/mobile or

alternative contact.

Administrative error (admin)– Woman inadvertently not sent a questionnaire.


Flow chart – different withdrawals1683 EQ

1588 FQ1

1496 FQ2

1444 FQ3

1377 FQ4

1305 FQ5

56 deaths post FQ5

20Deaths prior to FQ1





19Active withdrawals





54Passive Withdrawals

38Passive withdrawals




2Lost to follow-up

1Lost to follow-up

3Lost to follow-up

2Lost to follow-up

2Lost to follow-up

1Forced withdrawal

3Forced exclusions

5 6

7 8

0 1

4 0

6 5

Total 220 deaths up to June 2013

1Admin error

1


31





48

20

29

36

Getting to stset – generating “Event date”gen BCdeathrecur_eventdate_19May2014 = .replace BCdeathrecur_eventdate_19May2014 = datedeath21May2013 if deaths21May2013==1replace BCdeathrecur_eventdate_19May2014 = datedeath21May2013 if deaths21May2013==1 & deathcause21May2013==1

replace BCdeathrecur_eventdate_19May2014 = dateFQ5 if activeFQ5==1

replace BCdeathrecur_eventdate_19May2014 = dateEQ if newAW==1replace BCdeathrecur_eventdate_19May2014 = dateFQ1 if newAW==2replace BCdeathrecur_eventdate_19May2014 = dateFQ2 if newAW==3replace BCdeathrecur_eventdate_19May2014 = dateFQ3 if newAW==4replace BCdeathrecur_eventdate_19May2014 = dateFQ4 if newAW==5

replace BCdeathrecur_eventdate_19May2014 = dateEQ if newPW==1replace BCdeathrecur_eventdate_19May2014 = dateFQ1 if newPW==2replace BCdeathrecur_eventdate_19May2014 = dateFQ2 if newPW==3replace BCdeathrecur_eventdate_19May2014 = dateFQ3 if newPW==4replace BCdeathrecur_eventdate_19May2014 = dateFQ4 if newPW==5

replace BCdeathrecur_eventdate_19May2014 = dateFQ3 if newPW==6replace BCdeathrecur_eventdate_19May2014 = dateFQ4 if newPW==7replace BCdeathrecur_eventdate_19May2014 = dateFQ1 if newPW==8

replace BCdeathrecur_eventdate_19May2014 = dateEQ if Lost_Contact_Maria=="LC 1"replace BCdeathrecur_eventdate_19May2014 = dateFQ1 if Lost_Contact_Maria=="LC 2"replace BCdeathrecur_eventdate_19May2014 = dateFQ2 if Lost_Contact_Maria=="LC 3"replace BCdeathrecur_eventdate_19May2014 = dateFQ3 if Lost_Contact_Maria=="LC 4"replace BCdeathrecur_eventdate_19May2014 = dateFQ4 if Lost_Contact_Maria=="LC 5"

replace BCdeathrecur_eventdate_19May2014 = recurr_date if recurrFQ5==1


Getting to stset – generating “Event type”gen BCdeathrecur_eventtype_19May2014 = .replace BCdeathrecur_eventtype_19May2014 = 1 if deaths21May2013==1 Non-BC deathreplace BCdeathrecur_eventtype_19May2014 = 22 if deaths21May2013==1 & deathcause21May2013==1 BC death

replace BCdeathrecur_eventtype_19May2014 = 2 if activeFQ5==1 Complete FQ5

replace BCdeathrecur_eventtype_19May2014 = 6 if newAW==1 (active withdrawal) AW1replace BCdeathrecur_eventtype_19May2014 = 7 if newAW==2 AW2replace BCdeathrecur_eventtype_19May2014 = 8 if newAW==3 AW3replace BCdeathrecur_eventtype_19May2014 = 9 if newAW==4 AW4replace BCdeathrecur_eventtype_19May2014 = 10 if newAW==5 AW5

replace BCdeathrecur_eventtype_19May2014 = 11 if newPW==1 (passive withdrawal) PW1replace BCdeathrecur_eventtype_19May2014 = 12 if newPW==2 PW2replace BCdeathrecur_eventtype_19May2014 = 13 if newPW==3 PW3replace BCdeathrecur_eventtype_19May2014 = 14 if newPW==4 PW4replace BCdeathrecur_eventtype_19May2014 = 15 if newPW==5 PW5

replace BCdeathrecur_eventtype_19May2014 = 3 if newPW==6 Admin FQ4replace BCdeathrecur_eventtype_19May2014 = 4 if newPW==7 Admin FQ5replace BCdeathrecur_eventtype_19May2014 = 5 if newPW==8 Admin FQ2

replace BCdeathrecur_eventtype_19May2014 = 16 if Lost_Contact_Maria=="LC 1“ (lost contact) LC1replace BCdeathrecur_eventtype_19May2014 = 17 if Lost_Contact_Maria=="LC 2“ LC2replace BCdeathrecur_eventtype_19May2014 = 18 if Lost_Contact_Maria=="LC 3“ LC3replace BCdeathrecur_eventtype_19May2014 = 19 if Lost_Contact_Maria=="LC 4“ LC4replace BCdeathrecur_eventtype_19May2014 = 20 if Lost_Contact_Maria=="LC 5“ LC5

replace BCdeathrecur_eventtype_19May2014 = 21 if recurrFQ5==1 Recurrence


Survival analysis set-upstset BCdeathrecur_eventdate_19May2014 if(activeEQ==1), origin(time DateDiagnosis) failure(BCdeathrecur_eventtype_19May2014==22 21) scale(365.25)

Entry point = Date of diagnosis.

Exit date– Date of event

• Recurrence or BC death

– Date of censoring• Non-BC death• Withdrawal (AW, PW, LC or admin)• Complete FQ5

Scale = 1 year


Descriptive statistics of BC


CharacteristicPrevalence Event rate

n % n %

Body Mass Index ≥ 18.5 to < 25 528 45.71% 34 6.4%

≥ 25 to < 30 374 32.38% 32 8.6%

≥ 30 to < 40 253 21.90% 32 12.7%

Age (years) < 50 289 25.02% 30 10.4%

50 to <70 664 57.49% 54 8.1%

≥70 202 17.49% 14 6.9%

Type of surgery at EQ Mastectomy 330 28.57% 50 15.2%

Lumpectomy 821 71.08% 47 5.7%

HRT at diagnosis Yes 167 14.46% 13 7.8%

No 988 85.54% 85 8.6%

Stage at diagnosis Beyond Stage 1 517 44.76% 71 13.7%

Stage 1 600 51.95% 26 4.3%

Cancer type (51 missing) Lobular 201 17.40% 21 10.5%

Ductal 907 78.53% 73 8.0%

OAET by FQ1 Yes 1024 88.66% 82 8.0%

No 131 11.34% 16 12.2%

Radiotherapy by FQ1 Yes 867 75.06% 71 8.2%

No 288 24.94% 27 9.4%

Chemotherapy by FQ1 Yes 476 41.21% 60 12.6%

No 679 58.79% 38 5.6%

Strengths and Weaknesses of studyStudy strengths

Prospective design, cohort study with high retention rate.

Postal survey – Women from metro & country areas could participate.

Recruitment representative of BC community

Study weaknesses

Used BMI (obese/non-obese) at EQ for follow-up period.


breast cancer recurrence and obesity - ysc2015 - robinson

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