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Improved accuracy when screening for human growth disorders by likelihood ratios

Stef van Buuren1

  • 1TNO Quality of Life, P.O. Box 2215, 2301 CE Leiden, The Netherlands. Stef.vanBuuren@tno.nl

Statistics in Medicine
|August 22, 2007
PubMed

Insights

Likelihood ratio (LR) rules outperform standard deviation score (SDS) rules for identifying growth disorders. LR provides a more accurate assessment of disease probability in children compared to SDS screening.

Area of Science:

  • Pediatrics
  • Medical Statistics
  • Genetics

Background:

  • Standard deviation score (SDS) is commonly used for screening growth-related problems.
  • Current referral rules based on SDS are not optimal for differentiating reference from diseased populations.
  • The likelihood ratio (LR) and log-likelihood ratio (LLR) offer a theoretically superior approach when disease-specific growth standards are known.

Purpose of the Study:

  • To compare the diagnostic accuracy of likelihood ratio (LR) rules versus standard deviation score (SDS) rules for screening growth disorders.
  • To evaluate the effectiveness of LR and SDS in distinguishing between a reference population and a diseased population.

Main Methods:

  • Applied LR and SDS referral rules to longitudinal growth data from birth to 10 years.
  • Compared Turner syndrome patient data against a healthy reference group.
  • Calculated receiver operating characteristic (ROC) curves to assess test performance.

Main Results:

  • LR rules demonstrated superior sensitivity and specificity compared to SDS rules.
  • Empirical data confirmed theoretical predictions regarding the power of LR tests.
  • LLR rules were identified as uniformly the most powerful statistical test for this purpose.

Conclusions:

  • Likelihood ratio (LR) is the optimal measure for two-group comparative studies in growth assessment.
  • LR can be readily calculated for individual measurements, providing an absolute probability of disease.
  • LR offers a statistically robust and decision-theoretically sound method for diagnosing growth-related conditions.

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