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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