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Table 10 Univariable and multivariable binary logistic regression analysis of predictors of drug related problems

From: Assessment of drug therapy problems among patients with cervical cancer at Kenyatta National Hospital, Kenya

Variable Univariable analysis   Multivariable analysis  
  COR (95% CI) P value AOR (95% CI) P value
Age (years)
 29–39 1   1  
 40–50 2.6(0.14–46.21) 0.525 3.4(0.13–241) 0.263
  ≥ 51 1.6(0.15–17.76) 0.689 2.3(0.14–59.22) 0.489
Education
 Illiterate 1   1  
 Literate 1.9(0.18–18.81) 0.599 2.5(0.12–48.81) 0.541
Income (USD)
  < 100 1   1  
 100–200 0.9(0.09–9.47) 0.938 1.2(0.12–13.52) 0.855
 200–500 0.2(0.01–2.08) 0.162 0.1(0.00–1.13) 0.061
Marital status
 Single 1   1  
 Married 0.8(0.08–7.23) 0.803 0.9(0.14–5.80) 0.927
Occupation
 Unemployed 1   1  
 Employed 0.1(0.01–1.48) 0.096 0.1(0.01–1.41) 1.423
Co-morbidity
 No 1   1  
 Yes 1.0(0.16–6.56) 0.982 0.8(0.11–5.11) 0.767
Number of medications
  < 5 1   1  
  ≥ 5 2.6(0.41–16.53) 0.321 2.5(0.32–21.61) 0.399
Stage of cervical cancer
 Early stage 1   1  
 Advanced stage 9.9 (1.45–67.58) 0.019* 15.4 (1.3–185.87) 0.031*
  1. COR Crude odds ratio, AOR Adjusted odds ratio, 95% CI 95% confidence interval, *Statistically significant: P value ≤0.05