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Nutrition in Health and DiseaseLecture 1 - Introduction
Clinical nutrition: nutritional care for individual patients or patient groups Changes in
nutritional requirement due to illness, treatment, malnutrition
- Physiology, metabolism
- Body composition
- What is the most optimal nutrition for this patient’
Lecture 2 – Rules and Regulations
Nutritional status
▪ Self-reported weight loss at presentation: 34-72% 1,2 ▪ Low muscle mass: 39-57% 3
▪ Further loss of muscle mass during treatment
With cancer:
• Impaired digestion and absorption
• Increased metabolic activity
• Chemotherapeutic toxicity >> decreased nutritional intake
• Physical activity has shown to be decreased during treatment
• accelerate loss of muscle mass 4,5
• muscular deconditioning 6
Consequences of muscle wasting: (observational studies)
1. More severe toxicity of treatment
2. Reduced functional status
3. Reduced quality of life (QoL)
4. Reduced survival
Clinical relevance:
- 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
1. Broad context + clinical / social relevance
2. What is already known about this topic Scientific relevance GAP
3. Research question / aim
4. (Hypothesis)
5. Study design→Research proposal
BUDGET
▪ Salary (researcher, research assistant, dietitian, data manager, statistician)
▪ Equipment (depending on measurements)
▪ Laboratory costs
▪ Education (courses, conferences etc)
▪ Office equipment (computer, paper, pencils etc)
▪ Travel costs of participants
, - Study population: inclusion and exclusion criteria.
- Study design: RCT > I vs usual care/other I/placebo
- Primary endpoint: “first effect would be on body weight or muscle mass (before
effect on treatment toxicity/quality of life/survival would be expected)
SAMPLE SIZE CALCULATION
Twisk ‘Inleiding in de Toegepaste Biostatistiek’
n = number of participants in intervention or control group
α = 0.05 (significance)
β = 80% (power)
σ = variance (from literature)
ν = difference in outcome (clinically relevant)
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 exposed to this ineffective intervention
,What information do you need:
1. 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)
2. Desired significance level (α)
- How certain do you want to be of preventing a type I error?
- 5% - accepting a chance of 0.05 to detect an effect in your study that is not
present in the whole population (false positive)
3. Desired test direction
- One or two sided? 2-sided is: treatment A better than treatment B // treatment
B better than treatment A
4. Clinically relevant (or expected) difference (v)
- Which difference or which effect are you trying to find?
- from literature
5. Expected variance / standard deviation (σ)
- How much variation is expected in subjects belonging to the same study
group?
- from pilot data or literature
6. 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: divide number needed by 0.9
7. Differences in means, eg:
- difference in body weight change between groups
- difference in survival time between groups
8. Differences in proportions, eg:
- difference in proportions (%) with a certain weight loss between groups
- difference in proportions (%) 1 year survival between groups
Improvement in overall survival would be most important! Sample size calculation:
▪ v = difference in outcome → Median survival time = 20 months. Improvement of 2 months
(standard for new medicins) = 20 vs 22 months
▪ α = 0.05 (significance) ▪ β = 80% (power)
First effect would be on body weight or muscle mass (before effect on treatment toxicity /
quality of life / survival would be expected). Effect on muscle mass measured on CT scan.
Type I error: false negative; the probability of falsely rejecting H0
Type II error: false positive; the probability of falsely accepting H0
, WMO: wet medisch-wetenschappelijk onderzoek met mensen Research is subject to the
WMO if the following criteria are met:
1. It concerns medical scientific research and
2. participants are subject to procedures or are required to follow rules of behavior
a. infringement of the subject's physical and/or psychological integrity
b. subject himself/herself must be physically involved in the research
Declaration of Helsinki → Good Clinical Practice (GCP)
Goals GCP and Declaration of Helsinki: Protection of humans (ethical principles, protection
of personal information, safety procedures etc). Standard for quality of research (reliable,
reproducible etc)
1. Doctors must prioritize patients' well-being.
2. Research must aim to understand diseases and improve treatments.
3. Ethical standards protect human research subjects.
4. Individual rights come before research goals.
5. Research should minimize harm to the environment.
6. Only qualified individuals can conduct research on humans.
- Informed Consent → Participation must be voluntary and informed. Subjects must be
informed about the study's aims, risks, and benefits.
- Use of Placebo → Placebos should be used when scientifically necessary and
ethical.
- All research involving humans must be publicly registered. Researchers must publish
all research results.
- In desperate cases, doctors may use unproven interventions with informed consent,
followed by research to evaluate them.
Participants Must Be Actively Involved:
If your research involves actions that affect a person's physical or mental integrity, it's subject
to WMO. Simple tasks like one-time urine samples might not need WMO review, but
longer-term urine collection likely does. Randomizing participants in a study doesn't
automatically trigger WMO. It depends on whether the actions or rules imposed by
randomization affect participants' physical or mental integrity.
MONITORING BOARD (Goals: guarding safety of patients and quality of research)
▪ Check of progress of study
▪ Quality check in random test of recruited patients: > Informed consent;
> In- and exclusion criteria;
> Source data verification;
> Protocol violations;
> Check of Serious Adverse Events
Why more and more rules, laws, directives? Why monitoring?
- Unethical medical experiments in minorities → Prisoners, prostitutes, orphans,
homosexuals, etc
- Fraude – falsification
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