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Saving Women's Lives Strategies for Improving Breast Cancer Detection and Diagnosis (2005) / Chapter Skim
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Appendix D: Common Weaknesses in Study Designs
Pages 322-325

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From page 322...
... The enrolled population should include individuals without the target disease of interest, such as patients with risk factors for the disease but without the disease itself, patients with different, but commonly confused conditions, and patients with other types of pathology in the same organ systems.a Failure to enroll the appropriate spectrum of patients in a study of a new diagnostic technology can lead to overestimates a For example, different breast cancer detection technologies vary in their ability to detect microcalcifications, which are not cancerous lesions but are significant breast cancer risk factors. For instance, ultrasound is highly sensitive to lesions but does a poor job of detecting microcalicifications.
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From page 323...
... This particular failure lies at the root of countless headlines announcing new breakthrough procedures or therapies that kindle excitement, but deliver only false hopes -- and leave the public wondering why there are so few breakthroughs in their own treatment. Failure to Use Appropriate Controls or Comparison Groups.
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From page 324...
... The most common sources of bias due to measurement error, however, arise in evaluation of the outcomes of patients in two arms of a study. Ascertainment of patient outcomes by an "unblinded'" investigator who knows what intervention each patient received poses a serious risk of bias.
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From page 325...
... Diagnostic and therapeutic techniques are often employed using very specific protocols or techniques that affect the effectiveness or safety of the interventions. For example, different pulse sequences can be used in magnetic resonance imaging studies and different software might base comparisons of digitized mammography images on different calculations.
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Key Terms

  • particular findings
  • study design
  • poorly described
  • technology tested
  • risk factors

  • diagnostic technology
  • percent confidence
  • statistical power
  • statistical issues
  • confidence intervals

  • outcome occurs
  • meaningful conclusions
  • study cost
  • enrolled population
  • comparative effects

  • target disease
  • detect microcalcifications
  • confused conditions
  • interpret particular
  • mammography images

  • cancerous lesions
  • confounding variable
  • patient subgroup
  • received poses
  • untreated disease

  • commonly confused
  • resonance imaging
  • described techniques
  • relative risks
  • own treatment


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