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Table 5 Comparative interrupted time series analysis of monthly treatment success and loss to follow-up rates

From: Tuberculosis among economic migrants: a cross-sectional study of the risk of poor treatment outcomes and impact of a treatment adherence intervention among temporary residents in an urban district in Ho Chi Minh City, Viet Nam

 Treatment successLoss to follow-up
IRR┼95% CIp-valueÞIRR‡95% CIp-valueÞ
Baseline rate (β00.85[0.83, 0.87]< 0.0010.05[0.03, 0.09]< 0.001
Pre-intervention trend, control (β1)1.00[1.00, 1.00]0.6240.96[0.92, 0.99]0.024
Post-intervention step change, control (β2)1.00[0.97, 1.03]0.9712.41[0.97, 6.00]0.059
Post-intervention trend, control (β3)1.00[1.00, 1.00]0.3821.04[1.00, 1.09]0.050
Difference in baseline (β4)1.00[0.95, 1.05]0.9091.91[0.97, 3.76]0.060
Difference in pre-intervention trends (β5)1.00[1.00, 1.00]0.5411.02[0.98, 1.07]0.305
Difference in post-intervention step change (β6)1.07[1.00, 1.15]0.0410.17[0.04, 0.69]0.013
Difference in post-intervention trends (β7)1.00[1.00, 1.00]0.4350.90[0.83, 0.98]0.019
  1. Notes
  2. All patients in intervention and control districts, January 2011 to March 2017
  3. ¥The parameters were obtained for a segmented regression model with the following structure: Yt = β0 + β1Tt + β2Xt + β3XtTt + β4Z + β5ZTt + β6ZXt + β6ZXtTt;+ϵt. Here Yt is the outcome measure along time t; Tt is the monthly time counter; Xt indicates pre- and post-intervention periods, Z denotes the intervention cohort, and ZTt, ZXt, and ZXtTt are interaction terms. β0 to β3 relate to the control group as follows: β0, intercept; β1, pre-intervention trend; β2, post-intervention step change; β3, post-intervention trend. β4 to β7 represent differences between the control and intervention districts: β4, difference in baseline intercepts; β5, difference in pre-intervention trends; β6, difference in post-intervention step changes; β7, difference in post-intervention trend
  4. IRR based on log-linear Poisson regression with robust standard error estimations;
  5. IRR based on log-linear GEE Poisson regression with an autoregressive correlation structure with lag order 2;
  6. ÞWald test;