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Table 1 Cox proportional hazards regression models

From: Accounting for individual differences and timing of events: estimating the effect of treatment on criminal convictions in heroin users

  Univariate regression models Multiple regression model 1
Variable Hazard ratio (95% CI) p-value Hazard ratio (95% CI) p-value
OMT 0.40 (0.35,0.45) <0.001 0.79 (0.72,0.87) <0.001
Female gender 0.48 (0.40,0.57) <0.001 0.75 (0.66,0.85) 0.001
Age [10 years] 0.60 (0.54,0.67) <0.001 0.79 (0.73,0.85) <0.001
>27 criminal days prior to OMT application 4.83 (4.19,5.55) <0.001 1.50 (1.35,1.66) <0.001
Criminal conviction while on waiting list 6.65 (5.70,7.76) <0.001 2.84 (2.47,3.25) <0.001
>1 OMT period 1.74 (1.33, 2.28) <0.001 1.43 (1.20,1.70) <0.001
Criminal conviction last 30 days 93.9 (87.1, 101.2) <0.001 45.2 (40.4, 50.5) <0.001
  1. Cox proportional hazards regression models with day of criminal conviction as a recurrent event outcome and opoid maintenance treatment (OMT) a time-dependent explanatory variable. Results should be interpreted with care as the multiple model failed the assumption of proportional hazards.