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Specific guide to this web site for:


 1.  Medical School
      Educators 
      in Statistics


 2.  Medical Students

 3.  Science media writers

 4.  High School & College
     Statistic Teachers


   Misadventures:


1. Harvard led MI study

2. JACC study 

   (J. of Amer. Coll.
   Cardio.)


3. NEJM cath study

4. Amer. J. of Cardio.
    review of literature

5.
ALLHAT
    controversy
 

6.
Oat bran study

7.
Pregnancy & Alcohol

8.
Are Geminis really
   
different?
      
9. Columbia 'Miracle' Study  
                                                 

Additional Topics:

Celebrex

Limitations of Meta-Analyses

Large Randomized Clinical Trials

Tale of Two Large
Trials

Advocate meta-analyses

Network meta-analyses






 

 

 


Web Site Entry for Medical Students  

 

Your feedback is welcome.
email@improvingmedicalstatistics.com

Medical studies from the perspective of a medical student:

There is an overwhelming amount of information coming your way. Simply reading the conclusions in the abstract of a study represents an accomplishment.

There may come a time, though, when a particular major clinical trial directly affects your chosen field of medicine in a substantial fashion. That will be the time that you may want to critically review a trial in detail. This web site contains examples of medical studies with significant problems in statistics or properly formulated conclusions.

The goal of this web site is to encourage a discerning eye towards medical studies.  Many studies are quite well done. Unfortunately, a number of medical trials come up with conclusions that will not withstand the passage of time.

 

WEB SITE TOPICS OF POTENTIAL INTEREST FOR MEDICAL STUDENTS:

1.  A suboptimal study regarding the effects of oat bran (a soluble fiber):
Death of the oat bran fad.  (Murdered by a poorly conceived study.)

2. Lessons from an unusual saga of possible fraud in the literature   The Columbia ' Miracle' Study

3. The pregnancy and alcohol section is a bit of an eye opener in regards to the foundations of some of our general health recommendations.  The foundations of some of these recommendations may not be as secure as usually assumed. This area of the website discusses some of the strengths and limitations of epidemiologic research.   
Pregnancy and alcohol, what do some of the studies really suggest?

4. Can a meta-analysis be biased?
   
  You decide in 30 seconds download    (pdf files)
       Limitations of Meta-analysis: overview:   download

5.  Are Geminis really different?   Inappropriate subgroup analysis is a recurring temptation in the medical literature. The Hazards of Subgroup Analysis 

6.  List of questions to consider regarding the reliability of a clinical trial.  

 

7.  Large randomized clinical trials and meta-analyses will define the guidelines for care in your future field of medical practice. The following topics may help in understanding of some of the issues involved in these type of studies.

Limitations of Meta-Analyses
    Often a meta-analysis is thought of as the final word concerning a medical topic. A meta-analysis can be performed in an optimal fashion or quite poorly. This web site looks at this issue from a perspective that may not be readily available from other sources.

A Tale of Two Large Trials  
    A very well done large randomized trial is compared to a poorly interpreted large clinical trial. Both these trials have and will affect clinical practice guidelines.

The Very Large Randomized Clinical Trials (Strengths and  Limitations)
   
Appropriately, clinical practice guidelines are being driven and defined by large randomized trials.  However, not all large randomized clinical trials have conclusions which are valid. In addition, the degree to which the specific trial protocol can be generalized and to what specific patient populations are two issues that always need to be defined.

    Good luck in your clinical careers. You will see some of the truths of clinical practice taught today overturned by subsequent, more definitive clinical studies. Well constructed, conservatively interpreted studies will reduce the number of clinical u-turns clinicians will need to make in the future.  Demand nothing less.


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