Intention to treat analysis in population based screening interventions
Dear Sir
In an excellent article on intention to treat analysis (ITT) in
randomised controlled trials, Hollis and Campbell 1 discuss the issue of
false inclusions, ie. subjects found after randomisation not to satisfy
the entry criteria. This is a particular problem in population based
screening intervention trials, where GP Prior Notification Lists (PNLs)
are often used as the basis for randomisation. In the Breast Screening
Programme, Screening Offices issue invitations from the PNLs, which list
women deemed eligible for screening. This register is constantly being
updated because of new information sent from the FHSA, GPs and other
sources, so it is inevitable that further ineligibility will be detected
after invitation. We describe two RCTs 2 3 in which information about
ineligibility only came to light after randomisation, causing subsequent
problems with analysis.
In the first RCT, investigating the effectiveness of a home visit
intervention on the uptake of breast screening 2 among Asian women, a
study population of 527 women were randomised from PNLs. Updated
information from the FHSA before invitation, found 29 women to be
ineligible: intervention group (17), control group (12). These women were
not therefore sent an invitation by the Office, were non-participants in
the screening programme and so were excluded from the analysis. During the
home visits, a further 62 women were discovered to be ineligible (34 not
resident at address, 28 returned to Asia/visitor only). These women had
been found because of the intervention and so could not be excluded from
the analysis, which was conducted on an ITT basis for 498 women.
In the second example, the effect on attendance for breast screening
was investigated according to whether the offer of a cervical smear test
was included along with the breast screening invitation (1065 vs 1066
women) 3 . After invitation the Screening Office was notified that 219
(10%) women were ineligible for breast screening (100 vs 119 in each
group), because they were either not resident at the address (183), had
died (9), been screened recently (5) or were too ill to attend (22). The
women were false inclusions resulting in a missing outcome measure. It was
assumed that these reasons for ineligibility were unrelated to the
invitation for screening ; they were evenly distributed between the two
groups. Since a main objective was to assess detriment to breast screening
uptake when invitations for cervical screening were sent in advance,
these 219 women were excluded from the analysis, because this approach
resulted in the largest difference in attendance between the groups.
These RCTs illustrate the difficulties inherent in designing
intervention trials to fit in with the organisation of large screening
programmes. Our studies add to the debate on appropriate analysis
procedures.
Yours sincerely
Dr Tanya Hoare
Dr Gill Lancaster
Authors: No competing interests.
Dr Tanya Hoare
Senior Lecturer
Dept Health Care Studies,
Manchester Metropolitan University,
Hathersage Rd,
Manchester M13 OJA
1. Hollis S & Campbell F. (1999) What is meant by intention to
treat analysis? Survey of published RCTs. BMJ 319 670-4. 11th September
2. Hoare T, Thomas C, Biggs A, Booth M, Bradley S, Friedman E.
(1994) Can the uptake of breast screening by Asian women be increased? A
randomised controlled trial of a linkworker intervention. J Pub Health Med
16 179-85
3. Lancaster G, Elton P (1992) Does the offer of cervical screening
with breast screening encourage older women to have a cervical smear test?
J Epid & Comm Health 46 523-7.
Competing interests:
No competing interests
21 September 1999
Tanya Hoare
senior lecturer, lecturer in medical statistics
Gill Lancaster
Manchester Metropolitan University, University of Liverpool
Rapid Response:
Intention to treat analysis in population based screening interventions
Dear Sir
In an excellent article on intention to treat analysis (ITT) in
randomised controlled trials, Hollis and Campbell 1 discuss the issue of
false inclusions, ie. subjects found after randomisation not to satisfy
the entry criteria. This is a particular problem in population based
screening intervention trials, where GP Prior Notification Lists (PNLs)
are often used as the basis for randomisation. In the Breast Screening
Programme, Screening Offices issue invitations from the PNLs, which list
women deemed eligible for screening. This register is constantly being
updated because of new information sent from the FHSA, GPs and other
sources, so it is inevitable that further ineligibility will be detected
after invitation. We describe two RCTs 2 3 in which information about
ineligibility only came to light after randomisation, causing subsequent
problems with analysis.
In the first RCT, investigating the effectiveness of a home visit
intervention on the uptake of breast screening 2 among Asian women, a
study population of 527 women were randomised from PNLs. Updated
information from the FHSA before invitation, found 29 women to be
ineligible: intervention group (17), control group (12). These women were
not therefore sent an invitation by the Office, were non-participants in
the screening programme and so were excluded from the analysis. During the
home visits, a further 62 women were discovered to be ineligible (34 not
resident at address, 28 returned to Asia/visitor only). These women had
been found because of the intervention and so could not be excluded from
the analysis, which was conducted on an ITT basis for 498 women.
In the second example, the effect on attendance for breast screening
was investigated according to whether the offer of a cervical smear test
was included along with the breast screening invitation (1065 vs 1066
women) 3 . After invitation the Screening Office was notified that 219
(10%) women were ineligible for breast screening (100 vs 119 in each
group), because they were either not resident at the address (183), had
died (9), been screened recently (5) or were too ill to attend (22). The
women were false inclusions resulting in a missing outcome measure. It was
assumed that these reasons for ineligibility were unrelated to the
invitation for screening ; they were evenly distributed between the two
groups. Since a main objective was to assess detriment to breast screening
uptake when invitations for cervical screening were sent in advance,
these 219 women were excluded from the analysis, because this approach
resulted in the largest difference in attendance between the groups.
These RCTs illustrate the difficulties inherent in designing
intervention trials to fit in with the organisation of large screening
programmes. Our studies add to the debate on appropriate analysis
procedures.
Yours sincerely
Dr Tanya Hoare
Dr Gill Lancaster
Authors: No competing interests.
Dr Tanya Hoare
Senior Lecturer
Dept Health Care Studies,
Manchester Metropolitan University,
Hathersage Rd,
Manchester M13 OJA
Tel: 0161-247-2533
Fax: 0161-247-6328
Email: t.hoare@mmu.ac.uk
Dr. Gill Lancaster
Lecturer in Medical Statistics
Medical Statistics Unit,
Division of Statistics and OR
Department of Mathematical Sciences,
M & O Building,
University of Liverpool
L69 3BX
Tel: 0151-794-4733
Fax: 0151-794-4754
Email: g.lancaster@liverpool.ac.uk
References:
1. Hollis S & Campbell F. (1999) What is meant by intention to
treat analysis? Survey of published RCTs. BMJ 319 670-4. 11th September
2. Hoare T, Thomas C, Biggs A, Booth M, Bradley S, Friedman E.
(1994) Can the uptake of breast screening by Asian women be increased? A
randomised controlled trial of a linkworker intervention. J Pub Health Med
16 179-85
3. Lancaster G, Elton P (1992) Does the offer of cervical screening
with breast screening encourage older women to have a cervical smear test?
J Epid & Comm Health 46 523-7.
Competing interests: No competing interests