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Simple nomograms to calculate sample size in diagnostic studies
  1. S Carley1,
  2. S Dosman2,
  3. S R Jones3,
  4. M Harrison4
  1. 1Manchester Royal Infirmary, Manchester, UK
  2. 2Cambridge, UK
  3. 3Hope Hospital, Salford, Manchester, UK
  4. 4North Staffordshire Hospital, UK
  1. Correspondence to:
 Dr S Carley
 Manchester Royal Infirmary, Manchester M13 9WL, UK;


Objectives: To produce an easily understood and accessible tool for use by researchers in diagnostic studies. Diagnostic studies should have sample size calculations performed, but in practice, they are performed infrequently. This may be due to a reluctance on the part of researchers to use mathematical formulae.

Methods: Using a spreadsheet, we derived nomograms for calculating the number of patients required to determine the precision of a test’s sensitivity or specificity.

Results: The nomograms could be easily used to determine the sensitivity and specificity of a test.

Conclusions: In addition to being easy to use, the nomogram allows deduction of a missing parameter (number of patients, confidence intervals, prevalence, or sensitivity/specificity) if the other three are known. The nomogram can also be used retrospectively by the reader of published research as a rough estimating tool for sample size calculations.

  • diagnosis
  • nomogram
  • power
  • sample size
  • sensitivity

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  • Competing interests: none declared

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