Table 4 Causal contrast of interest and methods used to address different biases
From: Implementation of the trial emulation approach in medical research: a scoping review
Index | Study | The estimand of interest | The measurement scale of the outcome(s) | The effect size measure used to quantify the causal contrast of interest | The statistical method used for analysing the primary outcome(s) | The statistical method used to adjust for baseline confounders | The statistical method used to account for time-varying confounders | The approach used to address immortal-time bias | The statistical method used to account for potential selection bias due to loss to follow-up |
|---|---|---|---|---|---|---|---|---|---|
1a (cohort analysis) | Dickerman et al. [24] | ITT PP (treatment regimen) | Time-to-event | HR RD | Pooled logistic regression | Outcome regression on the confounders | IPTW | Participants assigned to treatment groups at start of follow-up based on their data available at that time | IPCW |
1b (case–control analysis) | Dickerman et al. [24] | ITT PP (treatment regimen) | Time-to-event | OR | Pooled logistic regression | Outcome regression on the confounders | IPTW | Cases and controls were sampled from the assembled cohort | IPCW |
2 | García-Albéniz et al. [25] | ITT (point treatment) | Time-to-event | RD | Pooled logistic regression | Outcome regression on the confounders | N.A. | Sequential trial emulations approach | Could not be determined |
3a (the addition of fluorouracil in stage II colorectal cancer) | Petito et al. [26] | PP (point treatment) | Time-to-event | HR RD | Pooled logistic regression | 1. Cloning approach + IPCW 2. Outcome regression on the confounders | N.A. | Cloning approach + IPCW | Could not be determined |
3b (the use of erlotinib in advanced pancreatic adenocarcinoma) | Petito et al. [26] | PP (point treatment) | Time-to-event | HR RD | Pooled logistic regression | 1. Cloning approach + IPCW 2. Outcome regression on the confounders | N.A. | Cloning approach + IPCW | Could not be determined |
4 | Dickerman et al. [4] | ITT PP (treatment regimen) | Time-to-event | HR SD | Pooled logistic regression | Outcome regression on the confounders | IPTW | Sequential trial emulations approach | IPCW |
5 | Dickerman et al. [27] | PP (treatment regimen) | Time-to-event | RR RD | PGF | PGF | PGF | Participants assigned to treatment groups at start of follow-up based on their data available at that time | PGF |
6a (single treatment versus no treatment) | Danaei et al. [28] | ITT PP (treatment regimen) | Time-to-event | HR SD | Pooled logistic regression | Outcome regression on the confounders | IPTW | Sequential trial emulations approach | Could not be determined |
6b (joint treatment versus no treatment) | Danaei et al. [28] | ITT PP (treatment regimen) | Time-to-event | HR SD | Pooled logistic regression | Outcome regression on the confounders | IPTW | Sequential trial emulations approach | Could not be determined |
6c (head-to-head comparison of two treatments) | Danaei et al. [28] | ITT PP (treatment regimen) | Time-to-event | HR SD | Pooled logistic regression | Outcome regression on the confounders | IPTW | Sequential trial emulations approach | Could not be determined |
7 | Zhang et al. [29] | PP (treatment regimen) | Time-to-event | RR RD | PGF | PGF | PGF | Participants assigned to treatment groups at start of follow-up based on their data available at that time | PGF |
8 | Atkinson et al. [30] | PP (point treatment) | Time-to-event | HR | Pooled logistic regression | 1. Cloning approach + IPCW 2. Outcome regression on the confounders | N.A. | Cloning approach + IPCW | Could not be determined |
9 | Rojas‑Saunero et al. [31] | PP (treatment regimen) | Time-to-event | RR RD | PGF | PGF | PGF | Participants assigned to treatment groups at start of follow-up based on their data available at that time | PGF |
10 | Maringe et al. [14] | PP (point treatment) | Time-to-event | SD | Kaplan–Meier estimator | Cloning approach + IPCW | N.A. | Cloning approach + IPCW | CCA |
11 | Gilbert et al. [32] | PP (treatment regimen) | Time-to-event | HR | Pooled logistic regression | Outcome regression on the confounders | IPTW | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
12 | Caniglia et al. [33] | PPa (point treatment) | Binary | OR | Logistic regression | IPTW | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
13 | Althunian et al. [34] | ITT PP (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Outcome regression on the confounders | Could not be determined | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
14 | Shaefi et al. [35] | ITTa (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Outcome regression on the confounders | N.A. | Sequential trial emulations approach | Could not be determined |
15a (index trial emulation) | Bacic et al. [36] | ITTa (point treatment) | Time-to-event | HR | Cox proportional hazards model | IPTW | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
15b (high risk trial emulation) | Bacic et al. [36] | ITTa (point treatment) | Time-to-event | HR | Cox proportional hazards model | IPTW | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
16 | Rossides et al. [37] | ITT (treatment regimen) | Binary | RR RD | TMLE | TMLE | N.A. | Sequential trial emulations approach | TMLE |
17 | Xie et al. [38] | ITT PP (treatment regimen) | Time-to-event | HR | 1. Cox proportional hazards model (ITT) 2. Pooled logistic regression (PP) | 1. GPS (ITT) 2. IPTW (PP) | IPTW | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
18 | Caniglia et al. [39] | ITT PP (treatment regimen) | Time-to-event | RD | Pooled logistic regression | Outcome regression on the confounders | IPTW | Sequential trial emulations approach | IPCW |
19 | Caniglia et al. [40] | PP (treatment regimen) | Time-to-event | SD | Pooled logistic regression | 1. Cloning approach + IPCW 2. Outcome regression on the confounders | Cloning approach + IPCW | Cloning approach + IPCW | Could not be determined |
20a (historical comparison) | Caniglia et al. [41] | Modified ITT (treatment regimen) | Binary | RR | 1. Log-binomial regression 2. Poisson regression | 1. Adjusted for confounders at the design stage 2. Outcome regression on the confounders | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | IPCW |
20b (contemporaneous comparison) | Caniglia et al. [41] | Modified ITT (treatment regimen) | Binary | RR | 1. Log-binomial regression 2. Poisson regression | 1. Adjusted for confounders at the design stage 2. Outcome regression on the confounders | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | IPCW |
21 | Matthews et al. [42] | ITTa (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | IPTW | N.A. | Sequential trial emulations approach | Could not be determined |
22 | Schmidt et al. [43] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | 1. Propensity score matching 2. Outcome regression on the confounders | N.A. | Sequential trial emulations approach | CCA |
23 | Al-Samkari et al. [44] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | IPTW | N.A. | Sequential trial emulations approach | Could not be determined |
24a (test the effect of hypoglycemia among individuals with dementia and diabetes, with respect to subsequent serious adverse events) | Mattishent et al. [45] | PPa (point treatment) | Time-to-event | HR | Cox proportional hazards model | Outcome regression on the confounders | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | 1. CCA 2. MI |
24b (evaluate whether the effect of hypoglycemia was modified by the presence or absence of dementia) | Mattishent et al. [45] | PPa (point treatment) | Time-to-event | HR | Cox proportional hazards model | Outcome regression on the confounders | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | 1. CCA 2. MI |
25 | Lenain et al. [46] | ITT (point treatment) | Time-to-event | SD | Kaplan–Meier estimator | Matching on time-dependent propensity score | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | CCA |
26 | Yiu et al. [47] | ITT PP (treatment regimen) | Binary | RD RR | Generalized linear model | 1. Propensity score matching 2. IPTW | IPTW | Participants assigned to treatment groups at start of follow-up based on their data available at that time | 1. CCA 2. Nonresponder imputation 3. Last observation carried forward 4. IPCW 5. MI |
27 | Wanis et al. [48] | ITT (point treatment) | Time-to-evet | SD | 1. Kaplan–Meier estimator 2. Pooled logistic regression | Outcome regression on the confounders (pooled logistic regression) | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
28 | Lu et al. [49] | ITT PP (treatment regimen) | Time-to-event | HR RD | 1. Cox proportional hazards model 2. Weighted Kaplan–Meier estimator | IPTW | IPTW | Participants assigned to treatment groups at start of follow-up based on their data available at that time | IPCW |
29 | Lyu et al. [50] | PP (point treatment) | Time-to-event | HR RD | Pooled logistic regression | 1. Cloning approach + IPCW 2. Outcome regression on the confounders | N.A. | Cloning approach + IPCW | IPCW |
30 | Russell et al. [51] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | 1. Propensity score matching 2. Outcome regression on the confounders | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
31 | Takeuchi et al. [52] | ITT PP (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | IPTW | IPTW | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
32 | Abrahami et al. [53] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score methods (adjustment, stratification, fine stratification and matching) | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
33 | Secora et al. [54] | ITT (treatment regimen) | Time-to-event | HR | Time-to-event Fine and Gray regression model | 1. Outcome regression on the confounders 2. IPTW 3. Propensity score matching | N.A. | Sequential trial emulations approach | Could not be determined |
34a (comparison of partly NRTI-sparing regimens) | Young et al. [55] | ITTa (treatment regimen) | Time-to-event | HR | Bayesian Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
34b (comparison of fully NRTI-sparing regimens) | Young et al. [55] | ITTa (treatment regimen) | Time-to-event | HR | Bayesian Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
35 | Czaja et al. [56] | ITTa (treatment regimen) | Time-to-event | OR | Pooled logistic regression | IPTW | N.A. | Sequential trial emulations approach | Could not be determined |
36 | Keyhani et al. [57] | PPa (point treatment) | Time-to-event | RD | Kaplan–Meier estimator | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37a (LEADER) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37b (DECLARE) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37c (EMPA-REG) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37d (CANVAS) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37e (CARMELINA) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37f (TECOS) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37 g (SAVOR- TIMI) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37 h (CAROLINA) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37i (TRITON- TIMI) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
37j (PLATO) | Franklin et al. [58] | ITT (treatment regimen) | Time-to-event | HR | Cox proportional hazards model | Propensity score matching | N.A. | Participants assigned to treatment groups at start of follow-up based on their data available at that time | Could not be determined |
38 | Fu et al. [59] | PP (treatment regimen) | Time-to-event | RD | Pooled logistic regression | Cloning approach + IPCW | Cloning approach + IPCW | Cloning approach + IPCW | Could not be determined |