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Summary Environmental Policy (1st Master Biomed - EHS) $7.50   Add to cart

Summary

Summary Environmental Policy (1st Master Biomed - EHS)

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A summary of the lessons of Environmental Policy given by professor Nawrot. Mostly written in English with a bit of Dutch.

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  • January 22, 2021
  • 38
  • 2019/2020
  • Summary
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Environmental Policy
Meta analyse
Review articles

Review

Author: has the freedom to choose the article to write about

Concern: less objective than systematic review

Systematic review

Very clearly (methodological) write what you did during the search process of an
article

Gather all possible literature about the subject  write how you worked  put all
the information in research tables + mention why you didn’t take certain articles in
account

(Nauwkeurig alle literatuur verzamelen over onderwerp  beschrijven hoe te werk
werd gegaan  alle informatie in onderzoekstabellen zetten + zeggen waarom
bepaalde artikels niet meegenomen werden)

Rigorous review of specific clinical question

‘Systematic’ literature search

Explicit regarding information provided

Steps

Clearly formulated question

Identify literature (is there enough literature?)

Select studies that are valid

Describe quality of selected studies

May use forest plot to summarize studies

Identify potential bias with funnel plot (ex. publication bias: study gets
negative results  doesn’t get published as often  keep in mind that the
true results can differ because of this)

Meta-analysis

Gives a clearer picture (multiple studies  better view on results)

Systematic review

Quantitative pooling of data

Statistical technique for combining individual effects of a number of studies addressing the
same question to produce a summary effect

, Studies with more accurate prediction (smaller CI)  more weight in end result  not an
average because some studies carry more weight

Weighting factor: 1/(standard error)2

Systematic review: flowchart

Justify why you used or didn’t use certain studies

Flowchart can be used

Use of search terms: ‘myocardial infarction’ and ‘trigger’

538 studies found

Only 17 studies used

Reasons?  review article, double published paper, not a specific trigger,
not the right study by reading the abstract

New search to find other articles with new keywords: ‘myocardial infarction’ and
‘case-crossover’ or ‘time-series’

20 studies found

Total: 37 studies used in analysis

What is a meta-analysis?

Focus on mean effects and differences between studies

Determines effect on individuals

Quantification of individual responses as a standard deviation

Subject characteristics are known (age, gender)

Problem: quality of the studies is important

Forest plot

, Bottom one: mean

Heterogeneity

Clinical heterogeneity

Clinical differences in studies with respect to patients, interventions and outcomes

Methodological heterogeneity

Other methods used

Statistical heterogeneity

Individual trials may seem to measure same outcome, but have results that are not
consistent

test for heterogeneity:

‘null hypothesis’ – difference due to chance

p value

Lots of heterogeneity: hard to summarize studies

Examples of statistical heterogeneity:




2 studies: verbetering van bv medicatie

2 studies: geen verbetering

 Heeft geen zin om meta analyse van te doen

Kijken of bv populatie verschilt of andere verklaringen waarom sommige studies wel
verbetering vinden en andere niet

Extreem: geen overlap tussen studies

, Minder sterke heterogeniteit  alle studies gaan in dezelfde richting

Maar toch: beter om alle individuele studies te bekijken en te poolen om te zien
waar het verschil aan ligt

Think about these things:

Was it a good idea to combine the studies?

Is there too much clinical heterogeneity to make sense?

Do the forest plots look consistent?

Do statistical tests suggest that heterogeneity is a problem?

Estimating a common effect

Pooled results: provide a more precise estimate

Type of weighted average

Sample size: important when calculating weight

Event rate

Precision: 95% CI




Test for heterogeneity  p > 0.2  not significant  acceptable

, Sensitivity analysis

For sources of heterogeneity

To see how many studies it takes to change the result

Exclude studies one by one  calculate estimate again  notice which study modifies the
estimate the most

Publication bias

Positive results

More likely to be published

Rapidly published

In English

Cited

Literature may be selective and biased

Biased interpretation of trial results

Solution

Since 2005: clinical trial registration mandatory

Requires specific information about patient population, intervention and outcomes

Eerst informatie registreren voor het onderzoek uitgevoerd wordt  zo kunnen
resultaten en bijgevolg publicaties niet achtergehouden worden die een ongewenst
resultaat uitkomen

Funnel plots

Detect bias in studies

Results of the studies are plotted against the sample size




Odds ratio: estimate

Vormt vorm als er geen publicatie bias is

Onderste bollen: kleine studies  meer variatie

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