title: Does introduction of thresholds in decision aids benefit the patient?: Comparison between findings-based and threshold-based diagnostic decision aids.
abstract: To assess how different diagnostic decision aids perform in terms of sensitivity, specificity, and harm.
  
  
  
  Four diagnostic decision aids were compared, as applied to a simulated patient population: a findings-based algorithm following a linear or branched pathway, a serial threshold-based strategy, and a parallel threshold-based strategy. Headache in immune-compromised HIV patients in a developing country was used as an example. Diagnoses included cryptococcal meningitis, cerebral toxoplasmosis, tuberculous meningitis, bacterial meningitis, and malaria. Data were derived from literature and expert opinion. Diagnostic strategies' validity was assessed in terms of sensitivity, specificity, and harm related to mortality and morbidity. Sensitivity analyses and Monte Carlo simulation were performed.
  
  
  
  The parallel threshold-based approach led to a sensitivity of 92% and a specificity of 65%. Sensitivities of the serial threshold-based approach and the branched and linear algorithms were 47%, 47%, and 74%, respectively, and the specificities were 85%, 95%, and 96%. The parallel threshold-based approach resulted in the least harm, with the serial threshold-based approach, the branched algorithm, and the linear algorithm being associated with 1.56-, 1.44-, and 1.17-times higher harm, respectively. Findings were corroborated by sensitivity and Monte Carlo analyses.
  
  
  
  A threshold-based diagnostic approach is designed to find the optimal trade-off that minimizes expected harm, enhancing sensitivity and lowering specificity when appropriate, as in the given example of a symptom pointing to several life-threatening diseases. Findings-based algorithms, in contrast, solely consider clinical observations. A parallel workup, as opposed to a serial workup, additionally allows for all potential diseases to be reviewed, further reducing false negatives. The parallel threshold-based approach might, however, not be as good in other disease settings.
authors.affiliation: Institute of Tropical Medicine, Antwerp, Belgium (BB, EB)
authors.forename: Bettina
authors.initials: B
authors.lastname: Bisig
authors.affiliation: Institute of Tropical Medicine, Antwerp, Belgium, and Centro de Epidemiologı´a Comunitaria y Medicina Tropical, Esmeraldas, Ecuador (JM)
authors.forename: Juan
authors.initials: J
authors.lastname: Moreira
authors.affiliation: University Hospital, Antwerp, Belgium (MC)
authors.forename: Mattieu
authors.initials: M
authors.lastname: Combes
authors.affiliation: Centre Hospitalier Universitaire, Kigali, Rwanda (AA)
authors.forename: Anita
authors.initials: A
authors.lastname: Asiimwe
authors.affiliation: Centro per le Malattie Tropicali, Negrar, Verona, Italy (ZB)
authors.forename: Zeno
authors.initials: Z
authors.lastname: Bisoffi
authors.affiliation: Belgian Technical Cooperation, Laos (FH)
authors.forename: Frank
authors.initials: F
authors.lastname: Haegeman
authors.affiliation: Institute of Tropical Medicine, Antwerp, Belgium (BB, EB)
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Bottieau
authors.affiliation: Institute of Tropical Medicine, University Hospital, Antwerp, Belgium (JVDE)
authors.forename: Jef
authors.initials: J
authors.lastname: Van den Ende
mesh_terms: D003657:Decision Making; D006801:Humans; D010361:Patients