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Patient Preference and Comprehensive Cohort Designs

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Title: Patient Preference and Comprehensive Cohort Designs


1
Patient Preference and Comprehensive Cohort
Designs
2
Background
  • Patients often have a preference for treatment.
    Patients with strong preferences for usual care
    often do not get into a trial because
    randomisation does not guarantee that they will
    get what they want.
  • Patients who do get into a trial with strong
    preferences for the novel treatment can bias
    results.

3
Strong preferences
  • When a treatment is ONLY available within a trial
    context patients who want the treatment may
    decide to consent to randomisation with the hope
    they may get the treatment.
  • This can lead to the following problems
  • Demoralisation
  • High drop out
  • BIAS

4
Effect of Preferences
  • Patients may refuse to fill in follow-up
    questionnaires due to resentful demoralisation,
    which can lead to bias.
  • Patients who DO get what they want may
    exaggerate the effectiveness of their treatment
    again this MAY lead to bias.

5
Quality of Life and Preference
  • Preferences are particularly a problem when
    quality of life is a major outcome as this is
    more susceptible than objective measures of
    outcome (e.g death).

6
Patient Preference Trial A solution
  • One approach to the issue of preferences is to
    undertake a patient preference trial.
  • Only patients indifferent to which treatment
    they receive are randomised.
  • Trial also known as Brewin-Bradley or
    Comprehensive Cohort Design.

7
Patient Flow in Preference Trial
8
Preference Example
  • A trial of two methods of abortion medical
    termination (mifepristone) vs surgical
    aspiration.
  • Some women had strong preferences and therefore
    were allowed their treatment choice.

9
Abortion Trial
Heshaw BMJ 1993307714-7.
10
Data from Abortion Study
  • The extra benefits of the preference study showed
    that clinically there was no difference.
  • HOWEVER, women with a preference should be
    allowed their choice women who were indifferent
    with late gestation would find surgical abortion
    more acceptable.

11
Comprehensive Cohort
  • In a comprehensive cohort study, Porthouse looked
    at the fracture rates among women who took part
    in a fracture prevention trial compared with
    those who were either ineligible or would not
    participate.

12
Comprehensive Cohort Design
Source Porthouse MSc thesis and QJM 200497569.
13
Results
  • Those taking part had significantly lower risk of
    fracture compared with similar, eligible, women
    refusing to take part.
  • Recruitment to fracture prevention trials selects
    individuals who are at lower risk than those for
    whom the treatments will eventually be used.

14
Problems with Preference Design
  • Because preference arms are not formed by
    randomisation they WILL be exposed to selection
    bias.
  • This makes the comparisons of these arms
    hazardous.

15
Patient Flow in Preference Trial
16
Preference Recruitment
  • Trial recruitment is unaffected by the inclusion
    of preference arms EXCEPT for the extra resources
    needed to follow-up the preference arms.
  • Cooper et al. undertook a RCT of the preference
    design and found no advantage to it.

Cooper et al. Br J Obs Gynae 19971041367-73.
17
An Alternative?
  • One approach to preserve the benefits of
    randomisation is to undertake a fully randomised
    preference trial.
  • ALL patients would be randomised irrespective of
    their preferences and preference would be used in
    the analysis.

Torgerson et al. 19961194-7.
18
Example
  • York Back Pain trial randomised 187 people with
    low back pain to an exercise programme or control
    (benign neglect?).
  • Before randomisation patients were asked their
    preferences.
  • 63 expressed a preference for the new treatment
    37 had no preference.

19
Backpain Preference Trial
Klaber Moffett et al. BMJ 1999319279-83.
20
Back Pain Trial
  • In the back pain trial we were able to show that
    the intervention was just as effective among
    patients who were indifferent to having the
    exercise therapy compared with those who were
    really keen.

21
Antenatal Care
  • In a trial of increased visits to women for
    antenatal care it was found that women with a
    strong preference for the alternative were much
    more dissatisfied with treatment.

22
Antenatal Trial Dissatisfaction with Treatment
Clement et al. 1998 BMJ 31778
23
The most interesting example
  • SPRINTER is a RCT of treatments for neckpain.
  • Two treatments a Brief Intervention (1-2
    sessions with a physio using CBT) vs usual care
    (5 sessions).
  • BEFORE randomisation we asked patients their
    treatment preference.

24
SPRINTER Preferences
  • In SPRINTER preferences were mixed
  • 53 did not have a preference
  • 16 wanted brief intervention
  • 31 wanted usual care.
  • ALL patients were randomised IRRESPECTIVE of
    their preference.

25
Patient Flow and 12 month Results - SPRINTER
Overall 12 month improvement -0.840
Overall 12 month improvement -2.825
26
SPRINTER Results
27
SPRINTER interpretation
  • Had we not asked for preferences we would have
    concluded usual care is best for all.
  • BUT we can now say that BI is best for those who
    want that treatment (also much cheaper) and UC
    should be reserved for those who want it or
    indifferent patients.

28
Where now preference?
  • In MY view if there is likely to be a problem
    with preferences we should elicit these at the
    start of the trial and include them in the
    analysis.
  • Patient preference trials of the Brewin-Bradley
    design are fraught with analytical problems
    selection bias.

29
Doctor Preference
  • As well as patients one could use doctor
    preferences to allocate treatment.
  • In a RCT of orthopaedic surgery vs orthopaedic
    medicine patients were only randomised if GP was
    indifferent to the specialist needed.
  • Patients with a named consultant were included
    and followed.

Leigh-Brown et al. 2001 Health Bulletin
59198-210.
30
Doctor Preference
  • In the OMENS trial Leigh-Brown et al found that
    outcome did not seem to be affected by physician
    preference.
  • Outcomes were similar across groups with
    orthopaedic medicine being more cost effective.

31
Summary
  • Patient preferences CAN affect outcome.
  • Elicitation of preferences when this is an issue
    BEFORE randomisation can be important.
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