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Table 13 Univariable and multivariable binary logistic regression analysis of predictors of dosing problems

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

Variable Univariable analysis P-Value Multivariable analysis P-value
COR (95% CI) AOR (95% CI)
Age (years)
 29–39 1   1  
 40–50 1.7(0.34–8.15) 0.529 2.4(0.32–17.61) 0.412
  ≥ 51 1.5(0.32–6.39) 0.625 1.7(0.24–11.52)  
Education
 Illiterate 1   1  
 Literate 2.8(0.54–14.11) 0.221 4.2(0.60–30.01) 0.161
Marital status
 Single 1   1  
 Married 1.6(0.54–4.82) 0.386 1.2(0.42–3.71) 0.761
Co-morbidity
 No 1   1  
 Yes 0.4(0.17–1.11) 0.084 0.4(0.11–1.32) 0.125
Number of medications
  < 5 1   1  
  ≥ 5 3.2(1.15–8.73) 0.026* 3.6(1.24–11.23) 0.026*
Type of cancer
 Adenocarcinoma & Invasive anaplastic carcinoma 1   1  
 Squamous cell carcinoma 1.6(0.29–8.96) 0.586 1.5(0.32–7.43) 0.614
 Stage of cervical cancer     
 Early stage 1   1  
 Advanced stage 2.3(0.58–9.33) 0.231 3.2(0.72–13.62) 0.121
Treatment Regimen
 Cisplatin + Paclitaxel 3.7(0.9–16.5) 0.079 9.8(1.25–77.81) 0.030*
  1. COR Crude odds ratio, AOR Adjusted odds ratio, 95% CI 95% confidence interval, *Statistically significant: P value ≤0.05