Generalizability of evidence-based assessment recommendations for pediatric bipolar disorder.

Abstract

Bipolar disorder is frequently clinically diagnosed in youths who do not actually satisfy DSM-IV criteria, yet cases that would satisfy full DSM-IV criteria are often undetected clinically. Evidence-based assessment methods that incorporate Bayesian reasoning have demonstrated improved diagnostic accuracy, and consistency; however, their clinical utility is largely unexplored. The present study examines the effectiveness of promising evidence-based decision-making compared to the clinical gold standard. Participants were 562 youth, ages 5-17 and predominantly African American, drawn from a community mental health clinic. Research diagnoses combined semi-structured interview with youths’ psychiatric, developmental, and family mental health histories. Independent Bayesian estimates relied on published risk estimates from other samples discriminated bipolar diagnoses, Area Under Curve=.75, p<.00005. The Bayes and confidence ratings correlated rs =.30. Agreement about an evidence-based assessment intervention “threshold model” (wait/assess/treat) had K=.24, p<.05. No potential moderators of agreement between the Bayesian estimates and confidence ratings, including type of bipolar illness, were significant. Bayesian risk estimates were highly correlated with logistic regression estimates using optimal sample weights, r=.81, p<.0005. Clinical and Bayesian approaches agree in terms of overall concordance and deciding next clinical action, even when Bayesian predictions are based on published estimates from clinically and demographically different samples. Evidence-based assessment methods may be useful in settings that cannot routinely employ gold standard assessments, and they may help decrease rates of overdiagnosis while promoting earlier identification of true cases.

Diagnostic Profiles and Clinical Characteristics of Youth Referred to a Pediatric Mood Disorders Clinic

“…These findings underscore the importance of using semi-structured interviews, such as the K-SADS, with a collaborative consensus team approach (26, 27). The process of conducting a full diagnostic assessment ensures that the clinician goes through each Axis I module, and systematically considers the DSM-IV-TR criteria for each disorder.…”

The International Society for Bipolar Disorders Task Force report on pediatric bipolar disorder: Knowledge to date and directions for future research

“…However, they can change the probability of a PBD diagnosis within an evidence-based medicine or Bayesian decision-making framework 111,112 and substantially improve the accuracy of clinical interpretation and agreement about next clinical action. 102,112 Some checklists have also shown sensitivity to treatment effects in masked randomized controlled trials (RCTs), with effect sizes equal to those based on direct interview of the youth and primary caregiver. 113,114 Checklists can improve diagnostic decision making in a range of clinical settings, as well as measuring treatment response.…”

Comparing the Diagnostic Accuracy of Five Instruments for Detecting Posttraumatic Stress Disorder in Youth

“…When clinicians do not know the base rate at their clinics, they can use a reported base rate at similar settings or start with a quantification of their clinical judgment. Using these methods produces large improvements in the accuracy and consistency of clinical interpretations (Jenkins et al, 2011), and increases agreement about the next clinical action that is indicated, even when the initial estimate is not accurate (Jenkins, Youngstrom, Youngstrom, Feeny, & Findling, 2012). …”