La situation face à l'activité et à l'emploi deux ans...

La situation face à l'activité et à l'emploi deux ans après un diagnostic de cancer

Alain Paraponaris, Luis Sagaon-Teyssier, Aurélia Tison

Contact: [email protected]

Research funded by: National Cancer Institute (INCa) and Cancer Research Association (ARC), Programme Cancer: maintien dans l’emploi et retour au travail

Fondation MGEN pour la Santé Publique Jeudi 9 octobre 2014, 14.00-15h30

Salle Plein Ciel

Introduction Cancer, a model for chronicisation of illnesses and treatments?

Cancer, a key-public health issue in France

358,000 new cases

150,000 deaths

800,000 persons in treatment

2 million cancer survivors

Major advances in cancer treatments

Survival rates and quality-of-life (QoL) improve

Half of adult cancer survivors < 65 years [de Boer et al, JAMA, 2009]

In France (2005), mean age (male/female) at diagnosis: 67/64 years [INCa, 2010]

New opportunities to participate to the labor force

Return to work/job tenure, component of cancer survivors QoL

Cancer, transitory or permanent shock on occupational status? Cancer survivors are more likely to be unemployed

Rate of job tenure after cancer diagnosis

From 24% (3 months) to 75% (5 years)

Varies with clinical (cancer site, treatment), demographic (gender, age), but also

social (occupational status, educational level, SES) characteristics

[Bradley et al, JHE, 2005; Bradley et al, Psycho-Onco, 2002; de Boer et al, JAMA, 2009]

Impact of cancer on job tenure depends on Productivity loss (limitations in functional/psychological abilities)

Adjustment of workstation and general working conditions

[van der Wouden et al, J Occup Med, 1992]

Social representations (discrimination, stigma, self-esteem)

[Rothstein et al, Oncology, 1995; Paraponaris et al, Health Policy, 2011]

Introduction

Cancer, transitory or permanent shock on occupational status?

What usually matters Possible confounding effects between SES, cancer prognosis and treatment

after-effects In France, gender inequalities in job tenure due to individual characteristics (age, marital

status) rather than clinical characteristics of cancer and its treatment

[Marino et al, JCO, 2013]

Deleterious impact of cancer and usual events in the job market to be disentangled

In what way does cancer induce job insecurity?

Most often, employment to employment transitions only considered

Non-employment transitions (unemployed, retired, other non-working) neglected

[Joutard et al, Ann. Eco. Stat., 2012]

Introduction

2012 French cancer survey (French National Cancer Institute) Sample of 4,349 French cancer survivors two years after cancer

diagnosis in 2010

Representative of the French population aged 20-85 years insured by the three main Health Insurance schemes

Salaried Farmers Self-employed

Sub-sample of 2,508 cancer survivors aged 57 years and less when diagnosed in 2010

12 cancer locations Breast, prostate, thyroid, melanoma (good prognosis) Bowel, aero-digestive tract, bladder, kidney, non-Hodgkin lymphoma, uterus and cervix

(intermediate prognosis) Lung (bad prognosis)

Cancer survivors in long-term sick leave for 2 years excluded

>90% of the French population (special schemes excluded)

Data and method

2012 French cancer survey (French National Cancer Institute) Random stratified sampling with unequal sampling probabilities

(rare cancers overrepresented)

Sample made representative of the reference population after: Weighting according to age, Health Insurance Scheme and cancer location Adjusting for non-response bias

Male (+), Age (+), SES (-), Cancer location: breast (-), lung (+), prostate (+), aerodigestive tract (+), non-Hodgkin lymphoma (-), worsening of cancer (+)

Response rate (AAPOR): 44% (4,349/9,885) Melanoma: 33% / non-Hodgkin lymphoma: 52%

Data Healthcare consumption (Health Insurance)

inpatient and outpatient care

CATI (survivors) postal questionnaire for some survivors with lung or aerodigestive tract cancer

Clinical data (medical staff) Tumor characteristics (tumor size and grade, TNM,…) Treatment (surgery, chemotherapy, radiotherapy, hormonotherapy,…) Support (psychological,…)

Data and method

Data and method Are cancer survivors comparable to the general population?

No, because of differences in the occupations distribution

2%

7%

13%

24%

29%

13%

2%

10%

1%

5%

12%

19%

24%

20% 19%

0% 0%

5%

10%

15%

20%

25%

30%

Farmers Craftsmen,shopkeepers

(self-employed)

Executives,knwoledge

workers

Foremen,supervisors

Clerks,assistants

Workmen No occupation Not defined

Cancer survey (2010)

General population (2010)

82% of cancer survivors employed in 2010 (+10% compared to general population)

Differences in employment rate (population employed/population) and in unemployment rate (population unemployed/working population) potentially due to structural differences in working populations as well as to cancer

Data matched with the help of propensity score matching (PSM) Controls for observed heterogeneity

Gives a control group with a non-experimental (ex post) method Mitigates the sampling bias in measured characteristics

[Rosenbaum et al, Biometrika, 1983; Rosenbaum et al, J of Am Stat Assoc, 1984; Heckman et al, Econometrics Journal, 2009; Becker et al, Stata J., 2002]

2010-2012 French employment survey Conducted by the National Institute of Statistics and Economic Studies 22,359 individuals aged 57 years and less in 2010

Principle Logit estimation of the probability to be in the cancer survivors sample Regressors: gender, age, educational level, occupational status in 2010,

income, diploma, work contract Cancer survivors paired with the best non-cancer individuals with the same

predicted probability to be treated (nearest neighbor method, probability difference<.0001)

87% of 2,508 cancer survivors matched a control 324 individuals with no control: men (53%), employed (66%), occupation not

documented (85%)

Data and method

Results

Occ

up

atio

nal

sta

tus

in 2

01

0 Occupational status of cancer survivors in 2012 (n=2,184)

Employed Sick leave Unemployed Retired Other Total

Employed 76,8 12,0 5,8 0,5 4,8 100

Sick leave 23,8 33,3 14,3 0,0 28,6 100

Unemployed 30,2 1,4 43,9 1,4 23,0 100

Retired 0,0 0,0 0,0 93,8 6,3 100

Other 7,9 0,0 4,7 0,8 86,6 100

Total 68,7 10,8 8,2 1,3 11,0 100

Evolution in the occupational status, matched samples (2010-2012)

¾ of cancer survivors employed in 2010 still employed 2 years after

Good prognosis melanoma: 85% thyroid: 84% breast: 75% prostate: 67%

Intermediate prognosis uterus: 81% kidney: 78% cervix: 73% non-Hodgkin lymphoma: 72% bowel: 62% aero-digestive tract: 53% bladder: 52%

Bad prognosis lung: 39%

Results

Occ

up

atio

nal

sta

tus

in 2

01



Employed 76,8 12,0 5,8 0,5 4,8 100

Sick leave 23,8 33,3 14,3 0,0 28,6 100

Unemployed 30,2 1,4 43,9 1,4 23,0 100

Retired 0,0 0,0 0,0 93,8 6,3 100

Other 7,9 0,0 4,7 0,8 86,6 100

Total 68,7 10,8 8,2 1,3 11,0 100

Occ

up

atio

nal

sta

tus

in 2

01

0

Occupational status of matched general population in 2012 (n=2,184)

Employed Unemployed Retired Other Total

Employed 93,8 2,8 0,5 2,9 100

Unemployed 42,6 38,3 1,1 18,1 100

Retired 0,0 0,0 100,0 0,0 100

Other 8,6 3,7 1,2 86,4 100

Total 84,7 5,1 1,7 8,5 100


17% drop in the probability to be still employed

Compared to people with no cancer, cancer survivors employed in 2010

3% increase in the probability to become unemployed

2% increase in the probability to become inactive (and not retired: disabled)

Results

Occ

up

atio

nal

sta

tus

in 2

01



Employed 76,8 12,0 5,8 0,5 4,8 100

Sick leave 23,8 33,3 14,3 0,0 28,6 100

Unemployed 30,2 1,4 43,9 1,4 23,0 100

Retired 0,0 0,0 0,0 93,8 6,3 100

Other 7,9 0,0 4,7 0,8 86,6 100

Total 68,7 10,8 8,2 1,3 11,0 100

Occ

up

atio

nal

sta

tus

in 2

01

0

Occupational status of matched general population in 2012 (n=2,184)

Employed Unemployed Retired Other Total

Employed 93,8 2,8 0,5 2,9 100

Unemployed 42,6 38,3 1,1 18,1 100

Retired 0,0 0,0 100,0 0,0 100

Other 8,6 3,7 1,2 86,4 100

Total 84,7 5,1 1,7 8,5 100


12% drop in the probability to get employed

5% increase in the probability to be still unemployed

5% increase in the probability to become inactive (and not retired: disabled)

Compared to people with no cancer, cancer survivors unemployed in 2010

Results

Probability not to be on sick leave

Probability to remain on sick leave

men

women

production staff

executive staff

men

women

production staff

executive staff

Months from cancer diagnosis to sick leave start Months from cancer diagnosis to sick leave start

Sick leave duration (months)

Pro

bab

ility

no

t t

o b

e o

n s

ick

leav

e

Pro

bab

ility

no

t t

o b

e o

n s

ick

leav

e

Sick leave duration (months)

Pro

bab

ility

to

rem

ain

on

sic

k le

ave

Pro

bab

ility

to

rem

ain

on

sic

k le

ave

Log-rank test, p<0.001 Log-rank test, p=0.031

Log-rank test, p=0.026 Log-rank test, p<0.001

Employment to employment transition probability, cancer survivors and non-cancer individuals (n=2,184)

Results

Gender

.77

.76

.94

Cancer

yes

no

female

male

.96

.93

.77

female

male

Employment to employment transition probability, cancer survivors and non-cancer individuals (n=2,184)

Results

Prognosis SES

.77

.84

.71

.48

.89

.94

Cancer

yes

no

Production

Executive

Production

Executive

.95

.94

good

bad

.28

.74 good

bad

Relative prognosis 5 years-expected survival rate based on cancer site and level and age

Good: > 80% Bad : 20%

SES (occupation) Executive and supervisory staff executives, knowledge workers,

foremen, supervisors Production staff

farmers, craftsmen, shopkeepers, clerks, assistants, workmen

Unemployment to employment transition probability, cancer survivors and non-cancer individuals (n=2,184)

Results

Gender

.30

.27

.43

Cancer

yes

no

female

male

.32

.45

.30

female

male

Unemployment to employment transition probability, cancer survivors and non-cancer individuals (n=2,184)

Results

Prognosis SES

.30

.49

.20

.50

.50

.43

Cancer

yes

no

Production

Executive

Production

Executive

.58

.30

good

bad

.00

.30 good

bad

Relative prognosis 5 years-expected survival rate based on cancer site and level and age

Good: > 80% Bad : 20%

SES (occupation) Executive and supervisory staff executives, knowledge workers,

foremen, supervisors Production staff

farmers, craftsmen, shopkeepers, clerks, assistants, workmen

Results Factors associated with cancer survivors’ job loss (employed in 2010, n=1,669) p-value (Khi-2 Wald test for OR: ***<0.001, **<0.01, *<0.05) LR test = 42.99 (H0 : equivalence of “production” and “supervisory “ models rejected)

% job loss Logistic regression (OR for job loss)

Variable All Production Supervisory- executive

All Production Supervisory- executive

Gender Male

Female (ref)

14.29 12.80

10.30 10.14

3.98 2.66

0.77 -1-

0.71 -1-

1.06 -1-

Age in 2010 Age

Age2

0.70***

1.004***

0.69**

1.005**

0.74

1.004

Marital status In couple

Single (ref)

11.60 17.53

8.82

13.93

1.45*

-1-

1.62*

-1-

1.04 -1-

Diploma <A-level (ref)

≥A-level

33.08 11.46

29.32 8.83

-1-

0.38***

-1-

0.38**

-1-

0.36**

Occupation Production

Supervisory-executive (ref)

18.07 6.87

1.56*

-1-

Work contract Temporary (ref)

Permanent

22.65 10.27

18.83 7.52

3.82 2.74

-1-

0.43***

-1-

0.40***

-1-

0.38*





Gender Male

Female (ref)

14.29 12.80

10.30 10.14

3.98 2.66

0.77 -1-

0.71 -1-

1.06 -1-

Age in 2010 Age

Age2

0.70***

1.004***

0.69**

1.005**

0.74

1.004


Single (ref)

11.60 17.53

8.82

13.93

2.78 3.60

1.45*

-1-

1.62*

-1-

1.04 -1-


≥A-level

33.08 11.46

29.32 8.83

-1-

0.38***

-1-

0.38**

-1-

0.36**



18.07 6.87

1.56*

-1-


Permanent

22.65 10.27

18.83 7.52

3.82 2.74

-1-

0.43***

-1-

0.40***

-1-

0.38*





Gender Male

Female (ref)

14.29 12.80

10.30 10.14

3.98 2.66

0.77 -1-

0.71 -1-

1.06 -1-

Age in 2010 Age

Age2

0.70***

1.004***

0.69**

1.005**

0.74

1.004


Single (ref)

11.60 17.53

8.82

13.93

2.78 3.60

1.45*

-1-

1.62*

-1-

1.04 -1-


≥A-level

33.08 11.46

29.32 8.53

3.76 2.93

-1-

0.38***

-1-

0.38**

-1-

0.36**



18.07 6.87

1.56*

-1-


Permanent

22.65 10.27

18.83 7.52

3.82 2.74

-1-

0.43***

-1-

0.40***

-1-

0.38*

Results Factors associated with cancer survivors’ job loss (employed in 2010, n=1,669) p-value (Khi-2 Wald test for OR: ***<0.001, **<0.01, *<0.05) LR test = 42.99 (H0 : equivalence of “Production” and “supervisory “ models rejected)




Gender Male

Female (ref)

14.29 12.80

10.30 10.14

3.98 2.66

0.77 -1-

0.71 -1-

1.06 -1-

Age in 2010 Age

Age2

0.70***

1.004***

0.69**

1.005**

0.74

1.004


Single (ref)

11.60 17.53

8.82

13.93

2.78 3.60

1.45*

-1-

1.62*

-1-

1.04 -1-


≥A-level

33.08 11.46

29.32 8.53

3.76 2.93

-1-

0.38***

-1-

0.38**

-1-

0.36**



18.07 6.87

1.56*

-1-


Permanent

22.65 10.27

18.83 7.52

3.82 2.74

-1-

0.43***

-1-

0.40***

-1-

0.38*

Results % job loss Logistic regression (OR for job loss)



Firm size <10 (ref)

10-499 ≥500

16.29 14.25 6.62

13.44 11.20 4.02

2.85 3.04 2.60

-1-

1.24 0.65

-1-

1.66* 0.63

-1-

0.58 0.41

Business sector Primary/secondary (ref)

Tertiary

15.51 12.37

12.50 9.38

3.01 2.99

-1-

0.74

-1-

0.82

-1-

0.55

Workstation arrangt

no (ref) yes

21.00 5.21

16.84 3.39

4.15 1.82

-1-

0.16***

-1-

0.12***

-1-

0.28***

Workplace discrimtion no (ref)

yes

12.19 20.50

9.53

15.00

2.65 5.50

-1-

2.29***

-1-

2.08*

-1-

2.99**

5-year prognosis >80%

50-80% 20-50%

<20% (ref) Nd

11.32 14.73 18.11 34.21 14.12

8.89

12.79 13.39 21.05 9.60

2.43 1.94 4.72

13.16 4.52

0.33* 0.43 0.47 -1-

0.38*

0.57 0.73 0.65 -1-

0.46

0.10**

0.09 0.23 -1-

0.27

Factors associated with cancer survivors’ job loss (employed in 2010, n=1,669) p-value (Khi-2 Wald test for OR: ***<0.001, **<0.01, *<0.05) LR test = 42.99 (H0 : equivalence of “production” and “supervisory “ models rejected)




Chemotherapy yes

no (ref)

13.86 12.50

10.75 9.62

3.11 2.88

1.32 -1-

1.19 -1-

1.72 -1-

After-effects no (ref)

moderate Important

8.17

12.90 20.24

6.35 9.13

16.90

1.81 3.77 3.33

-1-

2.25*** 3.18***

-1-

2.32*** 4.08***

-1-

2.19 1.91

Opiates use

no (ref) yes

8.96

15.30

6.63

11.97

2.33 3.33

-1-

1.52*

-1-

1.54

-1-

1.62

Psychotropics use no (ref)

yes

12.67 29.41

9.77

23.53

2.90 5.88

-1-

2.77**

-1-

3.61*

-1-

2.23

Anxiolytics use no (ref)

yes

10.43 15.03

7.45

12.02

2.98 3.01

-1-

1.11

-1-

1.21

-1-

0.86

Hypnotics use no (ref)

yes

10.27 19.26

7.17

16.48

3.10 2.78

-1-

1.46*

-1-

1.8**

-1-

0.72

Factors associated with cancer survivors’ job loss (employed in 2010, n=1,669) p-value (Khi-2 Wald test for OR: ***<0.001, **<0.01, *<0.05) LR test = 42.99 (H0 : equivalence of “production” and “supervisory “ models rejected)




Chemotherapy yes

no (ref)

13.86 12.50

10.75 9.62

3.11 2.88

1.32 -1-

1.19 -1-

1.72 -1-

After-effects no (ref)

moderate Important

8.17

12.90 20.24

6.35 9.13

16.90

1.81 3.77 3.33

-1-

2.25*** 3.18***

-1-

2.32*** 4.08***

-1-

2.19 1.91

Opiates use

no (ref) yes

8.96

15.30

6.63

11.97

2.33 3.33

-1-

1.52*

-1-

1.54

-1-

1.62

Psychotropics use no (ref)

yes

12.67 29.41

9.77

23.53

2.90 5.88

-1-

2.77**

-1-

3.61*

-1-

2.23

Anxiolytics use no (ref)

yes

10.43 15.03

7.45

12.02

2.98 3.01

-1-

1.11

-1-

1.21

-1-

0.86

Hypnotics use no (ref)

yes

10.27 19.26

7.17

16.48

3.10 2.78

-1-

1.46*

-1-

1.8**

-1-

0.72

Factors associated with cancer survivors’ job loss (employed in 2010, n=1,669) p-value (Khi-2 Wald test for OR: ***<0.001, **<0.01, *<0.05) LR test = 42.99 (H0 : equivalence of “Production” and “supervisory “ models rejected)

In the short run, cancer has a detrimental impact on careers No obvious gender inequalities

No systematic differences due to gender Potential differences linked to job characteristics

Strong discrepancies across occupations Ability to remain employed heavily depends on occupation Severity of cancer enhances differences within and between

occupations Job access or tenure always possible for executives and knowledge

workers two years after cancer diagnosis, even for bad prognosis cancers

Unemployment prevails for blue-collars whatever the severity of cancer

Size of the firm more likely to protect insiders (employed survivors) than to give a chance to outsiders (unemployed survivors)

Conclusion

Conclusion Limits/required refinements

Estimates conditional to survival People diagnosed with cancer in 2010 and who died between 2010 and 2012

are censored impact of cancer on careers deeper

What about sick leaves? 87% of people employed when cancer was diagnosed took benefit from one

sick leave at least Cancer survivors with no sick leave

Melanoma, thyroid, prostate No sequelae Female workers Living as a couple Diploma < A-level Production staff No workstation arrangement No workplace discrimination Temporary work contract

What about durations and employment loss/finding? 22% of people employed in 2010 lost their job (mean time: 4 months to be

compared to 7 months in general population) Among them, 30% (6.6% of people employed in 2010) found a new job (mean

time: 11 months to be compared to 5 months in general population)

Conclusion Limits/required refinements

What consequences for earnings? A drop in earnings for 3 cancer survivors out of 4

At least €296 for 1 household out of 4

Cancer survivors’ poverty rate: 21% (2010)24% (2012) (general population: 14% 14,3% )

Populations at higher risks of earnings loss Older people Bad prognosis cancers Diploma<A-level Chemotherapy Production staff No workstation arrangement Temporary work-contract Small to medium firms

How do socioeconomic inequalities in job retention evolve over time?

Comparison with 2004 Cancer Survey by DREES and INSERM Comparison with Employment Survey by INSEE News are bad

What about consequences for long-term cancer survivors? Forthcoming survey on 5 years cancer survivors (with longitudinal follow up)

La situation face à l'activité et à l'emploi

deux ans après un diagnostic de cancer

Alain Paraponaris, Luis Sagaon-Teyssier, Aurélia Tison

Contact: [email protected]

Research funded by: National Cancer Institute (INCa) and Cancer Research Association (ARC), Programme Cancer: maintien dans l’emploi et retour au travail

Fondation MGEN pour la Santé Publique Jeudi 9 octobre 2014, 14.00-15h30

Salle Plein Ciel

La situation face à l'activité et à l'emploi deux ans...

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