Overdiagnosis of breast cancer after 14

years of mammography screening

Per-Henrik Zahl Norwegian Institute of Public Health

January 31, 2013

Overview

1. What is overdiagnosis?

2. Why are 30-year old RCTs inappropriate to estimate the level of

overdiagnosis?

3. What is rate and life time risk?

4. How is the magnitude of cancer overdiagnosis calculated?

5. What is the underlying incidence increase?

6. What is the decline after age 69 and how do we adjust?

7. Comparison with Kalager et al

8. All DCIS are overdiagnoses when calculating overdiagnosis

9. Life time risk of being overdiagnosed and prevalent overdiagosed

patients

10. The dilution method

1. What is overdiagnosis?

“Overdiagnosis is detection of a disease that in the

absence of screening would not have been diagnosed

in the patient's lifetime.” Etzioni et al. J Natl Cancer Inst 2002

Overdiagnosis can be explained by:

The detection of tumors

i) that grow very slowly, or

ii) spontaneously would regress

Overdiagnosed

2. Why are 30-years old RCTs inappropriate

when estimating the level of overdiagnosis?

2.A Underestimation in the old trials

The Cochrane review reported 30 percent

overdiagnosis when screening with old type

mammography

But screening was going on also in the control

groups:

- CNBSS-2: Physical examination in the control group

- Malmö trial: DCIS rates in the control group were about 20 per 100 000

(and 40 in the screening arm) suggesting extensive screening in the

control group

Gøtzsche, Nielsen. Cochrane Review 2011

2.B There is a disease reservoir of DCIS

Prevalence of DCIS by number of slides per breast

Number of slides

per breast

Bartlow et al, 1987 9 0

Kramer et al, 1973 40 4.3

Nielsen et al, 1984 95 14.3

Nielsen et al, 1987 275 39

Prevalence of

DCIS

* Miller et al (CBCSS-2), CMAJ 1992

** Evaluering av prøveprosjektet,1999-2000

*** Skaane et al, Radiology 2013

Detection rates have increased because of: double view, computer assisted

reading, ultrasound, MR and 3D mammography without any decline in the

rate of interval cancer.

2.C Detection rate at screening has increased dramatically

0

1

2

3

4

5

6

7

8

9

10

Canada 1981-85 * Norway 1996-99 ** Norway 2011 ***

Detection rate at screening

Rate first year after a screening

Rate per 1000

3. What is rate and life time risk?

Rate = number of incident cancers/

100,000 individuals / year

0

50

100

150

200

250

300

350

Rate

1991 2010

Sum of rates over all ages = life time risk

Zahl, Strand, Mæhlen. BMJ 2004

4. How is the magnitude of overdiagnosis calculated?

0,0

100,0

200,0

300,0

400,0

500,0

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

Year

Rate

30-49 70-84

Curves show 1% and 2% annual underlying incidence increase

5. An underlying incidence increase?

Rates in Sweden, women aged 50-74 years

Zahl et al. Lancet Oncol 2011.

An increasing use of HRT?

Kalager et al. Ann Intern Med 2012.

Fra 1990 til 2010 vokste befolkningen med 33 % i aldersgruppen 50-69 år

Breast cancers / 100 000 women

5. What is the decline after age 69?

Boer et al. Lancet 1994

Age 50-69 years: 25% observed increase

In theory: about 35% expected decline in age group 70-79 years

A B

Zahl, Mæhlen. Tidsskriftet 2012

Age 50-69: observed over 50% increase

Age 70-79: almost no decline

A B

Invasive breast cancer incidence in Fife, Scotland

Vaidya. BMJ 2004; 339: b2587 (rapid responses)

250/100,000 ∙ 80,000 ∙ 7% = 14 less cancers after end of screening

Period 25-44 50-69 70-74 75+

1991-5 43 178 250 281

2005 46 285 234 282

2009 44 275 232 260

Age-specific rates of cancer

About 56% increase in the age group 50-69

About 7% reduction in the age group 70-74

178/100,000 ∙ 532,000 ∙ 56% = 530 more cancers when screening

Adjusting for earlier diagnosis

• Expected number of cancers: 945

• Observed 530 more cancers than expected when screening

• Observed 14 less after age 69

Zahl, Mæhlen. Tidsskriftet 2012

This is adjustment for

earlier diagnosis

• 1948/2,337,000 = 83 per 100,000

• Zahl et al 2004: 450/430,000 = 105 per 100,000

• Zahl et al 2012: 500/532,000 = 94 per 100,000

7. Comparison with Kalager et al

8. All DCIS are overdiagnosed when

calculating overdiagnosis

1. All DCIS that regress are overdiagnosed by definition

2. If some DCIS progress, for example 150, then we

would expect 945 - 150 = 795 breast cancers

The absolute differences between numerator and

denominator are 816 in both cases

• USA: 114/100,000 women over 40

• Norway: 800/1,177,000 = 68/100,000 women over

40

67% more overdiagnosis in USA than in Norway

9. Life time risk of being overdiagnosed

“How many percent of women will be overdiagnosed

during their life-time”?

• There are 100 overdiagnosed cancers/100,000 women

• There are 50 overdiagnosed DCIS/100,000 women

(100/100,000+ 50/100,000) ∙ 20 years = 3 %

Prevalent overdiagnosed patients: 800 ∙ 5 = 4000

Dilution of the magnitude of overdiagnosis

occurs when including all incident cancers in a

10-15 year follow up after screening was

terminated.

10.“The dilution method”

50 69 79 years

1473

945

356

370

Screening cohort:

Control cohort:

Suppose the rate is 232 for the age group 70-

74 (and 250 for the age group 75-79) who have

undergone previous screening and 250 if no

screening has occured, then

By using rates instead of cancer cases, cancers in the age group 70-79

years have larger weights than cancers in the age group 50-69 and this is

making the dilution effect stronger than if we only add cancers after age 69.

Figure 1. The black curve is the conditional IRR of the cumulative breast cancer incidence rate for a

cohort screened from age 50 to 69 to an un-screened cohort and then followed-op to age 90. The red

curve is the conditional IRR for the same cohorts, but here we assume that both cohorts are screened

from age 70 to 90.

1

1,1

1,2

1,3

1,4

1,5

1,6

55 60 65 70 75 80 85 90

Screening 50-69

Screening 50-89

Conditional IRR/overdiagnosis

The Marmot Report

• “…the Panel thinks that the best estimate of

overdiagnosis for a population invited to be

screened is roughly 11%, defined as the excess

incidence in the screening population as proportion

of the long-term expected incidence.”

– It is 11% of something that is not defined

– Why not apply the same dilution method to the mortality

reduction to make estimates comparable; i.e. (20%

mortality reduction)/5?

The Marmot Report. Lancet 2012

Conclusion

1. 30-35 years old RCTs underestimate overdiagnosis

2. The level of overdiagnosis of invasive breast cancer is 50%

• Or at least 95 overdiagnosed cancers for every 100,000 women invited

to screening

• In addition there are 50 overdiagnosed DCIS for every 100,000 women

invited to screening

• Each year there are at least 800 overdiagnosed breast cancer and

DCIS and because they are treated in 5 years, we get at least 4000

more patients who need to be treated in hospitals

• Life time risk of being overdiagnosed is at least 3%

3. These numbers are adjusted for earlier diagnoses (long lead times) and

they are minimum estimates

4. The dilution method cannot be interpreted as any of the numbers above –

conditional IRR is has very little meaning for women, I think

Slutt