1
Nutrition in Health & Disease
HC1: Introduction
Clinical Nutrition: nutritional care for individual patients or patient groups.
Changes in nutritional requirements due to illness, treatment, malnutrition.
● Physiology, metabolism.
● Body composition.
● What is the most optimal nutrition for this patient?
Exam: open ended questions
HC2: Rules and Regulations in (Clinical nutrition) research
Writing a research proposal:
Background: broad context:
Start with writing broad, working to specific.
Background: Clinical relevance:
Consequences of muscle wasting: (observational studies)
↑ More severe toxicity of treatment.
↓ Reduced functional status.
↓ Reduces quality of life (QoL).
↓ Reduced survival.
, 2
● Clinical outcomes may be improved by interventions aiming at preserving muscle
mass.
● For inducing muscle protein anabolism, a sufficient protein intake, next to an
adequate physical activity, is of critical importance.
Background: Known/unknown:
● Dietary advice has a beneficial effect on body weight after one year.
● Gastrointestinal tract, non-small cell lung cancers or mesothelioma.
● Beneficial effect of PN on BMI, BCM, QoL, chemotherapy toxicity, survival.
○ No control group.
No clear guidelines for nutritional support.
Background: Scientific relevance
Research question/ aim:
Use PICO.
What's next, when you have a research question? Start with searching for a budget to move
on with your research proposal and fund your study.
Budget:
● ! Salary (researcher, research assistant, dietitian, date manager, statistician).
● Equipment (depending on measurements).
● Laboratory costs.
● Education (courses, conferences etc.).
● Office equipment (computer, paper, pencils etc.).
● Travel costs of participants.
To do before you can start:
1. Write protocol.
2. Present protocol to department(s) involved.
3. Prepare protocol and other files for Scientific Research Committee.
4. Prepare protocol and other files for the Medical Research Ethical Committee (MREC/
Dutch: METC).
5. Prepare logistics.
Useful website: ccmo: https://english.ccmo.nl/investigators/standard-research-file
Study population:
Inclusion criteria & exclusion criteria.
, 3
Study design:
- Randomized controlled trial?
- Blinding; single blind? double blind?
- Cohort study?
Make a Study Flowchart.
Intervention:
When RCT:
1. Arm A (intervention)
2. Arm B (control)
Study endpoints:
What is your primary outcome?
Sample size:
Why calculation?
n = too small → false negative conclusion.
n = too large → intervention effective: too many subjects have missed out on this
intervention.
→ intervention ineffective: too many have been exposed to this
ineffective intervention.
- Population too small?
- Budget.
- Sample represents the population you want to study.
What information do you need?
Desired power of the study (1 - ß)
How certain do you want to be of preventing a type II error?
80% - accepting a chance of 20% of failing to detect an effect that is indeed present in the
population (false negative).
Desired significance level (α)
How certain do you want to be of preventing a type I error?
, 4
5% accepting a chance of 0.05 to detect an effect in your study that is not present in the
whole population (false positive).
Desired test direction
One or two sided?
2-sided: treatment A better than treatment B // treatment B better than treatment A.
Type I error (α) - the probability of falsely rejecting H0.
Type II error (ß) - the probability of falsely accepting H0.
Clinically relevant (or expected) difference (v)
Which difference or which effect are you trying to find?
From literature.
Expected variance/ standard deviation (σ)
How much variation is expected in subjects belonging to the same study group?
From pilot data or literature.
Attrition rate
Anticipate on the number of included subjects who will not be available for the study
analysis.
Expected drop-out/ withdrawal from previous studies.
E.g. if 10% drop-out is expected: divided number needed by 0.9.
Differences in means
● Differences in body weight change between groups.
● Difference in survival time between groups.
Differences in proportions
● Difference in proportions (%) 1 year survival between groups.
● Difference in proportions (%) with a certain weight loss between groups.
Primary endpoint
What is your primary outcome measurement, and how many patients do you need?
- How
- When
- Who
Nutrition in Health & Disease
HC1: Introduction
Clinical Nutrition: nutritional care for individual patients or patient groups.
Changes in nutritional requirements due to illness, treatment, malnutrition.
● Physiology, metabolism.
● Body composition.
● What is the most optimal nutrition for this patient?
Exam: open ended questions
HC2: Rules and Regulations in (Clinical nutrition) research
Writing a research proposal:
Background: broad context:
Start with writing broad, working to specific.
Background: Clinical relevance:
Consequences of muscle wasting: (observational studies)
↑ More severe toxicity of treatment.
↓ Reduced functional status.
↓ Reduces quality of life (QoL).
↓ Reduced survival.
, 2
● Clinical outcomes may be improved by interventions aiming at preserving muscle
mass.
● For inducing muscle protein anabolism, a sufficient protein intake, next to an
adequate physical activity, is of critical importance.
Background: Known/unknown:
● Dietary advice has a beneficial effect on body weight after one year.
● Gastrointestinal tract, non-small cell lung cancers or mesothelioma.
● Beneficial effect of PN on BMI, BCM, QoL, chemotherapy toxicity, survival.
○ No control group.
No clear guidelines for nutritional support.
Background: Scientific relevance
Research question/ aim:
Use PICO.
What's next, when you have a research question? Start with searching for a budget to move
on with your research proposal and fund your study.
Budget:
● ! Salary (researcher, research assistant, dietitian, date manager, statistician).
● Equipment (depending on measurements).
● Laboratory costs.
● Education (courses, conferences etc.).
● Office equipment (computer, paper, pencils etc.).
● Travel costs of participants.
To do before you can start:
1. Write protocol.
2. Present protocol to department(s) involved.
3. Prepare protocol and other files for Scientific Research Committee.
4. Prepare protocol and other files for the Medical Research Ethical Committee (MREC/
Dutch: METC).
5. Prepare logistics.
Useful website: ccmo: https://english.ccmo.nl/investigators/standard-research-file
Study population:
Inclusion criteria & exclusion criteria.
, 3
Study design:
- Randomized controlled trial?
- Blinding; single blind? double blind?
- Cohort study?
Make a Study Flowchart.
Intervention:
When RCT:
1. Arm A (intervention)
2. Arm B (control)
Study endpoints:
What is your primary outcome?
Sample size:
Why calculation?
n = too small → false negative conclusion.
n = too large → intervention effective: too many subjects have missed out on this
intervention.
→ intervention ineffective: too many have been exposed to this
ineffective intervention.
- Population too small?
- Budget.
- Sample represents the population you want to study.
What information do you need?
Desired power of the study (1 - ß)
How certain do you want to be of preventing a type II error?
80% - accepting a chance of 20% of failing to detect an effect that is indeed present in the
population (false negative).
Desired significance level (α)
How certain do you want to be of preventing a type I error?
, 4
5% accepting a chance of 0.05 to detect an effect in your study that is not present in the
whole population (false positive).
Desired test direction
One or two sided?
2-sided: treatment A better than treatment B // treatment B better than treatment A.
Type I error (α) - the probability of falsely rejecting H0.
Type II error (ß) - the probability of falsely accepting H0.
Clinically relevant (or expected) difference (v)
Which difference or which effect are you trying to find?
From literature.
Expected variance/ standard deviation (σ)
How much variation is expected in subjects belonging to the same study group?
From pilot data or literature.
Attrition rate
Anticipate on the number of included subjects who will not be available for the study
analysis.
Expected drop-out/ withdrawal from previous studies.
E.g. if 10% drop-out is expected: divided number needed by 0.9.
Differences in means
● Differences in body weight change between groups.
● Difference in survival time between groups.
Differences in proportions
● Difference in proportions (%) 1 year survival between groups.
● Difference in proportions (%) with a certain weight loss between groups.
Primary endpoint
What is your primary outcome measurement, and how many patients do you need?
- How
- When
- Who
