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  #1  
Old 11-27-2015
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Default Question help

A clinical trial was conducted to evaluate the effect of metoprolol, a selective beta blocker, on overall and cardiovascular mortallities in patients with chronic heart failure. The patients with chronic heart failure were randomly assigned to receive metoprolol or placebo, and were followed for a period of 3 years. The purpose of RANDOMIZATION is to control?

A. Confounding
B. Selection bias
C. Observer's bias
D. Ascertainment bias
E. Effect modification

Please explain your answer

I would select B but I read here in this forum that the answer is confounding bias.
As far as I have read, we do meta analysis and other Methods to reduce confounding bias.
Thanks in advance
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  #2  
Old 11-27-2015
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Default Its complicated

Randomization means random selection from the population AND random assignment to either treatment or control group . In the context of this question it probably means random assignment , that reduces confounding bias

Reduce selection bias--> Totally random selection from the ENTIRE population ( not health clubs , hospitals , caucasians , etc etc )

Reduce confounding --> After you randomly selected these people , assign them randomly to either control/treatment , OR even better match their characteristics so you totally eliminated confounding OR do a meta-analysis / compilation of the relevant studies
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  #3  
Old 11-27-2015
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Yea that has broadened my understanding of RANDOMIZATION. Thanks :-)
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  #4  
Old 11-27-2015
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Also, can we say that stratified analysis is another way to reduce confounding BIAS??
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  #5  
Old 11-27-2015
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I dont exactly know what you mean by stratified analysis , if you mean Stratify by severity , that is a tactic that is used to reduce Late-Look bias (e.g patients with more severe disease are now dead so you only look at the milder cases , giving you the impression that the disease is not really severe at all ) , which is a ''subtype'' of selection bias
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  #6  
Old 11-28-2015
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stratified analysis: i read in a uworld question

e.g. we do a study to evaluate relation between alcohol intake and bladder cancer
relationship between bladder cancer and alcohol intake shows a RR >1, and p value <0.05 (which makes the study statistically significant)
Next step, the same population is divided in two groups smokers and non smokers;
now again the relative risk is calculated between Alcohol intake and Bladder cancer separately in two groups, which gives RR close to 1 in Both groups (smokers and Non smokers) and p values >0.05 which tells us that small variation of RR from null value (i.e.1) is due to chance alone

Separating two groups on base of smokers and non smokers (smoking here serves as a confounding variable linked both with alcohol and bladder cancer) is called stratified analysis

what i have not understood is, is stratified analysis included under methods to control counfounding bias or something else?

Last edited by 193818; 11-28-2015 at 06:12 AM. Reason: typo
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  #7  
Old 11-28-2015
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In this case , yes , you eliminated one confounding bias . The question must say which is the basis of the stratification , so you can extrapolate what kind of bias they want to reduce
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