Age and disease severity predict choice of atypical neuroleptic: A signal detection approach to physicians' prescribing decisions

Jerome A. Yesavage, Jennifer Hoblyn, Javaid Sheikh, Jared R. Tinklenberg, Art Noda, Ruth O'Hara, Catherine Fenn, Martin S. Mumenthaler, Leah Friedman, Helena C. Kraemer

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Objective: We used a novel application of a signal detection technique, receiver operator characteristics (ROC), to describe factors entering a physician's decision to switch a patient from a typical high potency neuroleptic to a particular atypical, olanzapine (OLA) or risperidone (RIS). Methods: ROC analyses were performed on pharmacy records of 476 VA patients who had been treated on a high potency neuroleptic then changed to either OLA or RIS. Results: Overall 68% patients switched to OLA and 32% to RIS. The best predictor of neuroleptic choice was age at switch, with 78% of patients aged less than 55 years receiving OLA and 51% of those aged greater than or equal to 55 years receiving OLA (χ2=38.2, P<0.001). Further analysis of the former group indicated that adding the predictor of one or more inpatient days to age increased the likelihood of an OLA switch from 78% to 85% (χ2=7.3, P<0.01) while further analysis of the latter group indicated that adding the predictor of less than 10 inpatients days to age decreased the likelihood of an OLA switch from 51% to 45% (χ 2=7.0, P<0.01). Conclusions: ROC analyses have the advantage over other analyses, such as regression techniques, insofar as their "cut-points" are readily interpretable, their sequential use forms an intuitive "decision tree" and allows the potential identification of clinically relevant "subgroups". The software used in this analysis is in the public domain (http://mirecc.stanford.edu).

Original languageEnglish
Pages (from-to)535-538
Number of pages4
JournalJournal of Psychiatric Research
Volume37
Issue number6
DOIs
Publication statusPublished - Nov 2003
Externally publishedYes

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olanzapine
Antipsychotic Agents
Physicians
Risperidone
Inpatients
Decision Trees
Public Sector
Software

Keywords

  • Age
  • Neuroleptics
  • Schizophrenia
  • Signal detection

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Biological Psychiatry
  • Psychology(all)

Cite this

Age and disease severity predict choice of atypical neuroleptic : A signal detection approach to physicians' prescribing decisions. / Yesavage, Jerome A.; Hoblyn, Jennifer; Sheikh, Javaid; Tinklenberg, Jared R.; Noda, Art; O'Hara, Ruth; Fenn, Catherine; Mumenthaler, Martin S.; Friedman, Leah; Kraemer, Helena C.

In: Journal of Psychiatric Research, Vol. 37, No. 6, 11.2003, p. 535-538.

Research output: Contribution to journalArticle

Yesavage, JA, Hoblyn, J, Sheikh, J, Tinklenberg, JR, Noda, A, O'Hara, R, Fenn, C, Mumenthaler, MS, Friedman, L & Kraemer, HC 2003, 'Age and disease severity predict choice of atypical neuroleptic: A signal detection approach to physicians' prescribing decisions', Journal of Psychiatric Research, vol. 37, no. 6, pp. 535-538. https://doi.org/10.1016/S0022-3956(03)00053-0
Yesavage, Jerome A. ; Hoblyn, Jennifer ; Sheikh, Javaid ; Tinklenberg, Jared R. ; Noda, Art ; O'Hara, Ruth ; Fenn, Catherine ; Mumenthaler, Martin S. ; Friedman, Leah ; Kraemer, Helena C. / Age and disease severity predict choice of atypical neuroleptic : A signal detection approach to physicians' prescribing decisions. In: Journal of Psychiatric Research. 2003 ; Vol. 37, No. 6. pp. 535-538.
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AU - O'Hara, Ruth

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