Table 1.
Description of the Cox models used in the approaches under consideration.
| Approach | Stratified | Time-dependent covariate history | Weight adjusted |
|---|---|---|---|
| TD-Cox | No | Full | No |
| MSCM | No | Full | Yes, IPTC# |
| Sequential Cox‡ | Yes | Up to the new baseline† | Yes, IPC§ |
| Modified Sequential Cox‡ | Yes | New baseline and afterwards†† | Yes, IPC§ |
TD-Cox, Cox model with time-dependent exposure; MSCM, Marginal structural Cox model; IPT, Inverse probability of treatment; IPC, Inverse probability of censoring; IPTC, Inverse probability of treatment and censoring.
For the sequential Cox approach, covariate values are collected at three time points for each mini-trial: at baseline, at the interval of treatment start and at the previous interval (the lagged value): L̃m = (L0, Lm−1, Lm). Here, time-fixed covariates collected at the original baseline (i.e., L0) are included in the analysis.
For the modified sequential Cox approach, the time-dependent covariate values are collected at the new baseline and then at subsequent intervals (i.e., L⃗m = (Lm, Lm+1, …, LK)). Time-fixed covariates collected at the original baseline (i.e., L0) are also included in the analysis.
Robust (sandwich) estimate is used to obtain SEs.
Pooled logistic regression is used to estimate the IPTC weights.
Aalen’s additive regression model is used to estimate the IPCW.