Modeling the clinical assessment of men with suspected obstructed voiding using Bayes' Theorem.

Jennifer Caffarel, Clive Griffiths, Robert Pickard, Wendy Robson, Michael Drinnan

Research output: Contribution to journalArticlepeer-review


Pressure-flow studies (PFS) are the only reliable way to diagnose bladder outlet obstruction (BOO) in men with lower urinary tract symptoms (LUTS). However, in routine clinical practice, BOO is usually inferred by any of a number of tests (symptoms, flow rate, prostate size…). Bayes' Theorem provides a mathematical method, which may be similar to the process used by clinicians, for combining the results of multiple tests to reach a diagnosis. We have applied Bayes' Theorem to the results of several tests known weakly to predict BOO in men with LUTS to assess if they improve the diagnostic accuracy of a flow rate test which alone is known to predict obstruction moderately well.

We applied Bayes' Theorem to data from 50 patients using Qmax alone and with the inclusion of additional variables (IPSS, PSA, and residual urine), to establish individual probabilities of BOO. The chi-squared statistic (with trend) was used to compare the relative diagnostic values, against the BOO index calculated from the results of subsequent PFS.

The diagnostic value of Qmax alone (chi-squared = 9.2, P = 0.002), was superior than that for the Bayesian model using the combination of tests available (chi-squared = 4.9, P = 0.026).

Although in our sample relevant additional tests do not improve the diagnostic power of Qmax as a predictor of BOO, we believe the Bayesian approach is conceptually suited to modeling clinical decision making but may be better tested for a more clinically relevant outcome such as treatment response.
Original languageEnglish
Pages (from-to)797-801
Number of pages5
JournalNeurourology and Urodynamics
Issue number8
Early online date28 May 2008
Publication statusPublished - 1 Nov 2008
Externally publishedYes


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