Table 7.

Summary of the estimated parameters from the multiple sclerosis (MS) patients’ data from British Columbia, Canada (1995–2008).

Approach	$\widehat{HR}$	$se(\widehat{HR})$	95% CI	Weights
				Average (SD)	range
TD-Cox§	1.29	0.23	0.91 – 1.82
Sequential Cox#, †	1.23	0.32	0.74 – 2.07	1.00 ( 0.01 )	0.74 – 1.63
Modified Sequential Cox*, @	1.36	0.26	0.93 – 1.99	1.00 ( 0.01 )	0.92 – 1.24
MSCM±, ‡	1.31	0.23	0.92 – 1.84	1.00 ( 0.06 )	0.37 – 1.60

TD-Cox, Cox model with time-dependent exposure.

^§Adjusts for baseline covariates L₀ (sex, EDSS score, age and disease duration), and for the time-dependent confounder L_m ‘cumulative relapses’.

^#Adjusts for L₀, A_m and L̃_m.

^†The stabilized IPCW numerator model adjusts for A_m and L₀, while the denominator model additionally adjusts for L_m and lagged values of L_m via Aalen’s additive model.

^*Adjusts for baseline covariates L₀, lagged values of A_m, the time-dependent confounder L⃗_m and lagged values of L⃗_m.

^@For the stabilized IPCWs, the numerator model adjusts for A_m and baseline variable L₀, while the denominator model adjusts for L₀, A_m, L⃗_m and lagged values of L⃗_m via Aalen’s additive regression.

^±Adjusts for the potential baseline confounders L₀.

^‡The stabilized IPTW numerator model adjusts for a restricted cubic spline of the follow-up time-index, baseline confounders L₀ and lagged values of A_m to predict future treatment status. The denominator model additionally adjusts for the current and lagged values of cumulative relapses (L_m) via the pooled logistic models.