Lecture bioinformatic databases - Thursday - Pragmatic and explanatory research

26 important questions on Lecture bioinformatic databases - Thursday - Pragmatic and explanatory research

How can research be categorised?

- From explanatory to pragmatic
  • Explanatory is also called pathophysiological
  • Economic is an example of pragmatic research


- Phase 1 to phase IV
- Laboratory - patient - society
- Proof of principle - efficacy - effectiveness

What is the difference between explanatory and pragmatic research?

Explanatory = how does it work
Pragmatic = does it help the patients

What do you have to do when there is overlap between your experimental groups? (=ceteris paribus)

A larger sample size is needed to show a statistically significant difference
--> when difference (delta) is small
--> when SD is large
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Why is overlap between experimental groups bad?

Bad for internal validity
- more difficult to draw statistically significant conclusions
- can be solved by increasing sample size

What are the seven aspects of research design?

  1. Choice of comparative treatments
  2. Choice of patient groups
  3. Blinding
  4. Control group
  5. Analysis: PP, AT, ITT
  6. Outcome measures
  7. Timing of measurements

What would you compare your new treatment with to know if it helps the patient?

Pragmatic research:
Compare new policy to usual care
No checks on execution and compliance

What type of patient group would you study if you want to know how your treatment works?

Explanatory research -> internal validity

- Homogeneous population with largest effect
  • strict inclusion criteria
- eliminates alternative explanations
- reduces variation, thus increasing statistical efficiency

What type of patient group would you study if you want to know whether the treatment helps?

Pragmatic research -> external validity

- Everyday heterogeneous patients

Would you blind patients if you want to know how treatment works?

Explanatory - internal validity

- ideally double blind

Would you blind patients if you want to know if treatment helps the patient?

Pragmatic - external validity

- usually non-blinded
- in daily practice patients and doctor know treatment
- possibly measurements by blinded observer

What are disadvantages of randomization?

- Expensive and slow
  • Retrospective data cannot be randomized
  • If long follow-up is required you need to wait
- No guarantee about preventing chance findings
  • but chance can be analyzed using standard statistics
- Can be bad for external validity 

How can randomization be bad for external validity?

- informed consent needed -> selective inclusion
- more aware of the research -> influence on compliance
- more aware of the alternative -> influence on reporting
- 'contamination' -> care provider may apply elements of the experimental treatment in the control group

What is minimization (type of randomization)?

- larger probability for the assignement that makes groups more comparable

--> example: assign men with 75% probability to group with the least men

What is cluster randomization?

- used in pragmatic research
- patients are clustered = all patients from one physician, practice, region etc.

--> good for external validity (prevents contamination)
--> can be bad for internal validity
  • clusters may not be comparable (many clusters needed)
  • Inclusion criteria can differ between clusters
  • Randomization is performed before inclusion (not blinded)

WHat is the difference between PP (per-protocol) and as-treated (AT) analysis?

PP = exclusion of 'protocol violations'
AT = groups defined according to treatment, irrespective of randomization (fewer exclusions)

--> both explanatory

Are PP and AT explanatory or pragmatic?

explanatory

What is ITT analysis?

Intention to treat analysis
Evaluation according to randomization without any exclusion (includes all errors)
You want to evaluate the policy (and errors are made during policy)

-- pragmatic

Is ITT pragmatic or explanatory?

Pragmatic

Is ITT bad/good for internal and external validity?

- Better for external validity
- Mixed effect on internal validity
  • Groups remain comparable (++)
    • PP and AT mess up randomization
  • Loss of statistical efficiency (-)
  • Discrepancy between randomization and primary treatment

How would you measure disease burden?

First determine what disease burden is
- patient burden (quality of life and mortality)
- societal burden (costs)
--> costs per QALY

How to measure quality of life?
- questionnaire
- expensive and slow!
- intermediary outcome measures (BP, cholesterol etc.) --> relationship with disease burden

Timing of measurements for explanatory and pragmatic non-economic research

Explanatory = measure at the time of largest expected difference, intermediary outcome measures (short term), meten is weten -> tendency to measure a lot

Pragmatic non economic = measure at time of largest expected difference, disease burden (long term needed). Measurments bring distortion -> don't measure too much

How can utility (value for the quality of life) be measured?

- Visual analogue scale (VAS)
- Time Trade-Off (TTO)
- Standard gamble (SG)
- Questionnaires (like EQ-5D)

What is the visual analog scale (VAS)?

A line from 0 to 100% and a cross on this line equals the quality of life

What is the Standard Gamble method?

You get a choice:
- A: remaining life years blind
- B: 50% immediate death or 50% life in perfect health

--> the percentages you can differ (P and 1-P) and somewhere there is a break-even point.

Differences between VAS, TTO and SG

VAS is a cross without consequences
TTO trades quality for life years
SG trades quality for mortality

Usually, VAS < TTO < SG
--> TTO considered more valid method

What is the prefered method in the Netherlands to measure quality of life?

EQ-5D questionnaire

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