WEO CRCSC EWG ‘FIT for Screening’ Barcelona, 23 October 2015

Slide set no. 2 Stephen Halloran

1

England Bowel Cancer Screening

Programme FIT Pilot

Prof Stephen P. Halloran

Acknowledgements • Prof Sue Moss • Chris Mathews • BCSP Southern Hub • BCSP Midlands & NW Hubs

Presentation messages - 15 min

1. Model for future pilots ‘within programme’ – easy to replicate with minimise disruption

2. Monitoring analytical performance across sites 4 instruments & 2 sites

1. FIT system designed to maximise uptake – Emphasis on ‘hard to reach’ groups

2. Exploiting Quantitative FIT – Implications & opportunities

0

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0 100 200 300 400 500 600 700 800 90010001100

OC

Se

nso

r Dia

na

anal

yse

r re

sult

s n

gHb

/mL

Mean OC Sensor Diana result ngHb/mL

April 2014 FIT Pilot

Bowel Cancer Screening in England

July 2006

2010

2010

2010

2013

17 million gFOBt analysed > 300,000 positives

> 306,000 colonoscopies Found

23,000 cancers 73,000 advanced adenomas

0

10

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30

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60

70

80

Gender Area deprivation%

Up

take

50%55%60%65%70%

IT

Info.

Finan

ce Tr

ain

ing

– Minimal impact upon BCSP

– Cut-off 20ug /g (?positivity >6.5%)

– FIT in place of guaiac FOBT

– 1 in 28 invitations will be FIT

– 40,000 FIT tests (single kit)

– Effectively randomised

2014 FIT Pilot FIT

FIT

FIT and NHS Bowel Cancer Screening

in England

WEO CRCSC EWG ‘FIT for Screening’ Barcelona, 23 October 2015

Slide set no. 2 Stephen Halloran

2

Both Hubs • Population 27.8 m • gFOBT Kits = 1,126,087 • FIT Kits = 40,930

Southern Hub Less Deprivation • Population 14.7 m • gFOBT Kits = 588,317 • FIT Kits = 21,641

Midlands & North West Hub More Deprivation • Population 13.1 m • gFOBT Kits = 537,770

• FIT Kits = 19,289

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0 100 200 300 400 500 600 700 800 900 1000 1100

OC

Sen

sor

Dia

na

anal

yser

res

ult

s n

gHb

/mL

Mean OC Sensor Diana result ngHb/mL

Diana 1 Wren SH result

Diana 2 Lark SH result

Diana1 Blackbird M&NWH Result

Diana 2 Robin M&NWH result

y=x

Line of best fit y=0.997x + 0.1122

FIT Pilot QA data – 4 Analysers on 2 sites 5 batches of 30 samples in both Hubs

April – October 2014

150 - Samples 5 - Batches 4 - Analysers 2 - Sites 7 - Months

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1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73

% R

etu

rne

d w

ith

+ve

re

sult

s

Period Sent to result (days)

Period in days – kit sent to final result (subjects with +ve result)

BCS01

BCS01

BCS02

BCS02

All Episodes – Uptake

50% 55% 60% 65% 70%

Mid & NW

Southern

Both

FIT

gFOBt

50% 55% 60% 65% 70%

Mid & NW

Southern

Both

FIT

gFOBt

7.0%

7.1% Increase

7.3%

290,000 More screened each year

0 – 5 previous screening invitations

Incident Episode – Uptake

82% 84% 86% 88% 90% 92%

Mid & NW

Southern

Both

FIT

gFOBt

82% 84% 86% 88% 90% 92%

Mid & NW

Southern

Both

FIT

gFOBt

4.2% Increase

4.1%

4.3%

1 – 5 previous participation episodes

First Episode – Uptake

40% 45% 50% 55% 60% 65%

Mid & NW

Southern

Both

FIT

gFOBt

40% 45% 50% 55% 60% 65%

Mid & NW

Southern

Both

FIT

gFOBt

10.9% Increase

9.7%

12.2%

1st invitation (60 year olds)

WEO CRCSC EWG ‘FIT for Screening’ Barcelona, 23 October 2015

Slide set no. 2 Stephen Halloran

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Prevalent Episode - Uptake

0% 5% 10% 15% 20% 25% 30%

Mid & NW

Southern

Both

FIT

gFOBt

0% 5% 10% 15% 20% 25% 30%

Mid & NW

Southern

Both

FIT

gFOBt

11.6% Increase

11.8%

11.3%

No previous response to 1 – 5 invitations

Age & Sex – Uptake

45% 50% 55% 60% 65% 70% 75%

All Age

60-64

65-69

70-74

All Age

60-64

65-69

70-74

Mal

eFe

mal

e

FIT

gFOBt

45% 50% 55% 60% 65% 70% 75%

All Age

60-64

65-69

70-74

All Age

60-64

65-69

70-74

Mal

eFe

mal

e

FIT

gFOBt

10.6%

Deprivation – Uptake

40%

45%

50%

55%

60%

65%

70%

75%

IMD 1 (Posh) IMD 2 IMD 3 IMD 4 IMD 5 (Poor)

gFOBt

FIT

40%

45%

50%

55%

60%

65%

70%

75%

IMD 1 (Posh) IMD 2 IMD 3 IMD 4 IMD 5 (Poor)

gFOBt

FIT

Deprivation – Uptake

40%

45%

50%

55%

60%

65%

70%

75%

IMD 1 (Posh) IMD 2 IMD 3 IMD 4 IMD 5 (Poor)

gFOBt

FIT

40%

45%

50%

55%

60%

65%

70%

75%

IMD 1 (Posh) IMD 2 IMD 3 IMD 4 IMD 5 (Poor)

Deprivation – Uptake

40%

45%

50%

55%

60%

65%

70%

75%

IMD 1 (Posh) IMD 2 IMD 3 IMD 4 IMD 5 (Poor)

gFOBt

FIT

40%

45%

50%

55%

60%

65%

70%

75%

IMD 1 (Posh) IMD 2 IMD 3 IMD 4 IMD 5 (Poor)

6.7% 6.0%

6.8%

8.0%

7.9%

% Positivity & Deprivation

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

IMD 1 (Posh) IMD 2 IMD 3 IMD 4 IMD 5 (Poor)

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

IMD 1 (Posh) IMD 2 IMD 3 IMD 4 IMD 5 (Poor)

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

IMD 1 (Posh) IMD 2 IMD 3 IMD 4 IMD 5 (Poor)

FIT Cut-off - 20 ug Hb/g Faeces

WEO CRCSC EWG ‘FIT for Screening’ Barcelona, 23 October 2015

Slide set no. 2 Stephen Halloran

4

0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0%

Mid & NW

Southern

Both

0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0%

Mid & NW

Southern

Both

0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0%

Mid & NW

Southern

Both

% Positivity & Screening Episode

First Screening Episode

Incident Episode

Prevalent Episode

FIT Cut-off - 20 ug Hb/g Faeces

Outcome at Colonoscopy

10.1%

8.3%

19.5%

17.5%

30.6%

14.0%

4.0%

FIT 20

FIT 40

FIT 100

FIT 150

FIT 180

gFOBT Cancer

High-risk Adenoma

Low-risk Adenoma

Abnormal

Normal

Intermediate-risk Adenoma ug Hb/g Faeces

Sex & FIT threshold – % Positivity

0.0%

1.0%

2.0%

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6.0%

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8.0%

9.0%

10.0%

0%

10%

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30%

40%

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60%

70%

80%

90%

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% F

IT P

osi

tivi

ty

% M

isse

d n

eo

pla

sms

rela

tive

to

th

ose

de

tect

ed

usi

ng

20

ug

/g c

ut-

off

FIT (OC-Sensor) Cut-off (ug/g)

Personal Characteristics Influence Screening Outcomes

More positive tests in…

• Male

• Elderly

• Deprived

• Screening non-compliant

FIT cut-off at a high threshold disproportionally disadvantages… • Female

• Elderly

• Screening non-compliant

FIT – An opportunity to personalise population-based screening?

Better Screening by….

…focusing on populations… and on individuals?

‘Personalising population-based screening’ – PPS

1. Intelligent use of FIT data

2. FIT & personal risk – Multivariate risk scores

3. …ready to join the ‘Personalised Medicine’ band wagon?