More PACE trial data released

EQ_index is EuroQol-5D-3L (EQ_index in dataset).
The questionnaire asks about 5 items of health (Mobility, Pain/discomfort, Self-care, Anxiety/depression, Usual activities) scored on 3 levels (score 1, 2, 3) + a VAS of current health state (scored 0-100). EQ asks about your health today. The questionnaire used in PACE has also added a question about comparing how you feel now with 1 year ago.
The data in the dataset is the summary index score, and not the health state score (which replicates the individual item scores - eg 12132). The summary index score is normally used for cost-utility analyses. Euroqol summary index scores [in this dataset] appear to be <1.0 (although some are negative) - each country requires its own method of calculation based on age and sex.


I was hoping for the 5 dimensions which is really what the EQ5d scale is. The single value is then a country interpretation a while ago there was a paper pointing out that some treatments are only worthwhile in some countries but not others as the utility function applied to the different scores is country specific and dependent on how healthy people in the country feel about potential disabilities. If i remember correctly the utility function is computed from a regression over question answers which leads to different residual errors in different areas,

I assume it would be interesting to understand the different dimensions and also how they map to value in different countries,
 
CSRI summary(ish):

We are asking you the following questions because we would like to know the cost of your illness both to you, those looking after you and to society in general.

1. In the last 6 months, what face-to-face consultations have you had with these practitioners? (Number of contacts in last 6 months: CFS/ME related or Other reasons; Average duration of contact)
GP; Neurologist; Psychiatrist; Other doctor 1 (e.g. cardiologist); Other doctor 2 (e.g. dentist); Practice nurse; Pharmacist (for advice); Psychologist/therapist (other than in the PACE trial); Physiotherapist (other than in the PACE trial); Social worker; Community mental health worker; Acupuncturist; Osteopath; Homeopath/herbalist; Occupational therapist (other than in the PACE trial); Other (please state).

2. In the last 6 months have you spent time as a hospital inpatient? No/Yes
If yes: Give details of admission (hospital, reason, dates, days).
a) How many times have you been admitted to hospital and discharged in the same day?

3. In the last 6 months how many times have you attended A&E? a) What was the reason?

4. In the last 6 months, have you had any of the following investigations or diagnostic tests? (No/Yes; number of investigations/tests)
MRI; CT/CAT scan; Ultrasound; X-ray; EEG; Blood test; Other (please describe).

5. In the last 6 months, have you received help from friends or relatives on any of the following tasks, as a consequence of your fatigue? (No/Yes – Average number of hours help per week – Who provides this care? – Do they live in your house?)
Child care; Personal care (washing, dressing etc); Help in/around the house (cooking, cleaning etc); Help outside the home (shopping, transport etc); Other.
Total hours.

6. What was your employment status immediately before your illness started?
Employed full-time and working (1); Employed full-time but ‘off-sick’ (2); Employed part-time (3); Employed part-time but ‘off-sick’ (4); Unemployed (5); Self-employed and working (6); Self-employed but 'off-sick' (7); Retired (because of age) (8); Retired (because of ill health) (9); Student (10); Student but interrupted due to illness (11); Housewife/husband (12); Other (please specify) (13).

7. How many hours per week did you work at that time (if any)?

8. What is your current employment status? (same options as Q6).

9. If you are currently working, what is your current job title (if not, go to Q11)?

10. What are your current wages/salary before tax? Please indicate if this is: Weekly; Monthly; Annually
If the participant chooses not to give an answer, please use the prompt card to show income brackets, and record the letter that corresponds to the participant’s income.

11. What benefits (if any) do you currently receive?
Options: Income support (1); Incapacity Benefit (2); Disability Living Allowance - care component (3), - mobility component (4); Disabled Person's Tax Credit (5); Severe Disablement Allowance (6); Council Tax Benefit (7); Housing Benefit (8); Jobseeker's Allowance (9); Working Tax Credit (10); Statutory Sick Pay (11); State retirement pension (12); Other (please specify) (13)

12. Do you currently receive income protection benefit (income protection or total and permanent disability)? Yes/No

13. If yes, how much annually do you receive? £----
If the participant chooses not to give an answer, please use the prompt card to show income brackets, and record the letter that corresponds to the participant’s income.

14. Have you had to stop or reduce work/study due to your state of ill-health? Yes/No

15a. If yes: how many days in the last 6 months have you had off work/study because of your fatigue? (days) or
15b. How many fewer hours per week have you worked because of your fatigue? (hours)

16. Do you currently receive a private medical/retirement pension? Yes/No

17. If yes, how much weekly (or monthly, or annually) do you receive?(use prompt card if participant chooses not to give an answer)

18. In the past 6 months, have you received any one-off payments from income protection or insurance schemes as a result of your health? Yes/No

19. If yes, how much weekly (or monthly, or annually) do you receive? (use prompt card if participant chooses not to give an answer)

20. Are there any benefits that you don’t receive but which are currently under negotiation or in dispute? Yes/No

21. We are interested in all spells of employment that you have had in the past six months, if any. Please give details of all jobs you have had in the past six months.
Employment 1/2/3 – Occupation; Normal hours per week worked; Date started/finished; Reason for end of employment; How many days (including part days) did you take off due to fatigue?

22. If you are unemployed/retired: Do you intend to return to work? Yes/No
How long have you been unemployed/retired? Years – months.

Other info:

Ref: Beecham J K & Knapp MRJ: Costing mental health interventions. London: Gaskell; 2001.

Measured at Baseline visit 2, 24 weeks (end of therapy), 52 weeks (trial end)
 
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Reading through the questionnaires in the Protocol again is putting me in a Very Bad Mood. So apols if I'm being a bit stroppy elsewhere on here.

It's shameful that they collected so much information on participants, and gave no thought as to how they were going to use it. Combining such complex info into simple metrics makes much of the data uninterpretable. Shocking use of participants' time and effort. Makes me so cross.
 
CSRI summary(ish):



Other info:

Ref: Beecham J K & Knapp MRJ: Costing mental health interventions. London: Gaskell; 2001.

Measured at Baseline visit 2, 24 weeks (end of therapy), 52 weeks (trial end)

They did gather a mass if information.

This trial is very odd. I don't think I'd have qualified on the walking tests (too 'well'), but if I'd been asked to fill in all these questionnaires, my mind would have shut down and I'd have put them in the recycling.
 
Reading through the questionnaires in the Protocol again is putting me in a Very Bad Mood. So apols if I'm being a bit stroppy elsewhere on here.

It's shameful that they collected so much information on participants, and gave no thought as to how they were going to use it. Combining such complex info into simple metrics makes much of the data uninterpretable. Shocking use of participants' time and effort. Makes me so cross.

Yes, understandable.
 
It's shameful that they collected so much information on participants, and gave no thought as to how they were going to use it. Combining such complex info into simple metrics makes much of the data uninterpretable. Shocking use of participants' time and effort. Makes me so cross.

Especially since they dropped accelorometers due to the load on patients.
 
Reading through the questionnaires in the Protocol again is putting me in a Very Bad Mood. So apols if I'm being a bit stroppy elsewhere on here.

It's shameful that they collected so much information on participants, and gave no thought as to how they were going to use it. Combining such complex info into simple metrics makes much of the data uninterpretable. Shocking use of participants' time and effort. Makes me so cross.
Most of the "power" of the trial came from its cost. It could have been done as is for barely 1/10 the price tag, but that would have been much less impressive. It created a sunk cost that motivated people to justify the huge expense, regardless of the fact that it wholly lacked substance or anything meaningful.

So it seems expected that they'd have wasted much of it on things they didn't even have a use for. It was busywork, an exercise in confirmation that was going to show "success" no matter what. Same for the alleged expensive training. It's a bullshit treatment with a fictitious narrative model, what training could it have even involved? There's no specific expertise required, no novel technology or anything even justifying doing any training beyond a basic information session.

The whole point was to spend money so decisions could be justified as "we spent a lot of money confirming that so you're going to use it".
 
I'm sure @sTeamTraen has done a fine job - but can I just check what the procedure was for merging the files, and what the common variables were - just so I don't go making any assumptions about the data that I shouldn't be making... ?

I don't want to put a dampener on this, but I have a nasty feeling about these assumptions... Can anyone confirm? I'm unable to replicate the secondary outcome summary stats.
 
I don't want to put a dampener on this, but I have a nasty feeling about these assumptions... Can anyone confirm? I'm unable to replicate the secondary outcome summary stats.

How off were you? If they were adjusting for variables we don't have (age, sex, etc) couldn't there be very minor differences without it being much of a problem?
 
I'm sure @sTeamTraen has done a fine job - but can I just check what the procedure was for merging the files, and what the common variables were - just so I don't go making any assumptions about the data that I shouldn't be making... ?

There were no common variables. :eek::eek::eek::eek::eek::eek:

All I was able to do was merge the columns, on the assumption that the participant order was the same in each case. I added a fictitious participant ID number, so that if anyone sorts the file for some reason they will be able to unsort it again, but that's it. We either have to trust that the records are in the same order for every file, or go back to the researchers and ask them to provide some way to be sure about this.
 
All I was able to do was merge the columns, on the assumption that the participant order was the same in each case.

Could we look at something like missing data to check if they line up, for example if all of the 52 week scores are missing from the first set there should be a reasonably high likelihood that the 52 week scores would also be missing from the second set. Giving it a quick glance over that doesn't seem to be the case.
 
We either have to trust that the records are in the same order for every file, or go back to the researchers and ask them to provide some way to be sure about this.

Without confirmation, it is not safe to trust that the records are in the same order for every file. Without knowing which groups the data were in, they are pretty much useless, apart from providing a summary of the entire cohort.
 
I have found some time to start building some code this evening. I reproduced some of the values from Table 3, where we have fatigue and physical functioning scores at baseline and 52 weeks. (Table 3 has these two side by side, but I don't have room on the page, so they are one above the other here).

The moderately encouraging news is that all of the means, SDs, and Ns seem to match the table in the article. That suggests that we have the correct treatment arm for each participant, at least for the four variables in question (but I think that these arrived on a single spreadsheet, so that would be expected).

The less encouraging news is that the mean difference values don't match the published table. The differences are small for the difference between the "active" treatment and SMC, but quite a lot larger for the difference between the "active" treatment and APT.

Now of course this could be because of how I calculated the mean differences, but the only way I can see to do that is to take the difference in the means. If it was just the CI where the discrepancy was occurring then I would assume I was using a different method from the one used by the authors to calculate the standard error, but for the means I don't know.

Edit: Does this board have a "code" mode, to preserve the spacing of a piece of text? I had this table nicely formatted, but then all the spaces got eaten.

Fatigue
TX APT CBT GET SMC
Baseline 28.5 (4.0) n=159 27.7 (3.7) n=161 28.2 (3.8) n=160 28.3 (3.6) n=160
52 weeks 23.1 (7.3) n=153 20.3 (8.0) n=148 20.6 (7.5) n=154 23.8 (6.6) n=152
MdiffSMC -0.7 (-2.2,0.9) -3.6 (-5.2,-1.9) -3.3 (-4.8,-1.7)
MdiffAPT -2.9 (-4.6,-1.2) -2.6 (-4.2,-0.9)

Phys.function
TX APT CBT GET SMC
Baseline 37.2 (16.9) n=159 39.0 (15.3) n=161 36.7 (15.4) n=160 39.2 (15.4) n=160
52 weeks 45.9 (24.9) n=153 58.2 (24.1) n=148 57.7 (26.5) n=154 50.8 (24.7) n=152
MdiffSMC -4.9 (-10.4,0.7) 7.4 (1.8,12.9) 6.9 (1.2,12.7)
MdiffAPT 12.2 (6.7,17.8) 11.8 (6.0,17.5)
 
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