A Classification Tree Analysis of Selection for Discretionary Treatment

Joe Feinglass*, Paul R. Yarnold, Walter J. Mccarthy, Gary J. Martin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


OBJECTIVES. To study treatment bias in observational outcomes research, the authors present a nonlinear classification tree model of clinical and psychosocial factors influencing selection for interventional management (lower extremity bypass surgery or angioplasty) for patients with intermittent claudication. METHODS. The study sample includes 532 patients with mild to moderate lower extremity vascular disease, without prior peripheral revascularization procedures or symptoms of disease progression. All patients were enrolled in a prospective outcomes study at the time of an initial referral visit for claudication to one of the 16 Chicago-area vascular surgery offices or clinics in 1993-95. The influence of baseline sociodemographic, clinical, and patient self-reported health status data on subsequent treatment is analyzed. Study variables were derived from lower extremity blood flow records and patient questionnaires. Follow-up home health visits were used to ascertain the frequency of lower extremity revasculariztion procedures within 6 months of study enrollment. Hierarchically optimal classification tree analysis (CTA) was used to obtain a nonlinear model of treatment selection. The model retains attributes with the highest sensitivity at each node based on cutpoints that maximize classification accuracy. Experimentwise Type I error is ensured at P < 0.05 by the Bonferroni method and jackknife validity analysis is used to assess model stability. RESULTS. Seventy-one of 532 patients (13.3%) underwent interventional procedures within 6 months. Ten patient attributes were used in the CTA model, which had an overall classification accuracy of 89.5% (67.6% sensitive and 92.9% specific), achieving 57.7% of the theoretical possible improvement in classification accuracy beyond chance. Eleven model prediction endpoints reflected a 33-fold difference in odds of undergoing lower extremity revasculariztion. CONCLUSIONS. Initial ankle-brachial index (100%), leg symptom status over the previous six months (89%), self-reported community walking distance (74%) and prior willingness to undergo a lower extremity hospital procedure (39%) were used to classify most patients in the sample. These attributes are critical control variables for a valid observational study of treatment effectiveness.

Original languageEnglish (US)
Pages (from-to)740-747
Number of pages8
JournalMedical care
Issue number5
StatePublished - May 1998


  • Claudication
  • Peripheral angioplasty
  • Peripheral bypass surgery
  • Peripheral vascular disease

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health


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