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A novel estimand to adjust for rescue treatment in randomized clinical trials

(2021) STATISTICS IN MEDICINE. 40(9). p.2257-2271
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Abstract
The interpretation of randomized clinical trial results is often complicated by intercurrent events. For instance, rescue medication is sometimes given to patients in response to worsening of their disease, either in addition to the randomized treatment or in its place. The use of such medication complicates the interpretation of the intention-to-treat analysis. In view of this, we propose a novel estimand defined as the intention-to-treat effect that would have been observed, had patients on the active arm been switched to rescue medication if and only if they would have been switched when randomized to control. This enables us to disentangle the treatment effect from the effect of rescue medication on a patient's outcome, while tempering the strong extrapolations that are typically needed when inferring what the intention-to-treat effect would have been in the absence of rescue medication. We propose a novel inverse probability weighting method for estimating this effect in settings where the decision to initiate rescue medication is made at one prespecified time point. This estimator relies on specific untestable assumptions, in view of which we propose a sensitivity analysis. We use the method for the analysis of a clinical trial conducted by Janssen Pharmaceuticals, in which patients with type 2 diabetes mellitus can switch to rescue medication for ethical reasons. Monte Carlo simulations confirm that the proposed estimator is unbiased in moderate sample sizes.
Keywords
Statistics and Probability, Epidemiology, causal inference, intercurrent events, mediation, posttreatment confounding, treatment discontinuation, treatment switching

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MLA
Michiels, Hege, et al. “A Novel Estimand to Adjust for Rescue Treatment in Randomized Clinical Trials.” STATISTICS IN MEDICINE, vol. 40, no. 9, 2021, pp. 2257–71, doi:10.1002/sim.8901.
APA
Michiels, H., Sotto, C., Vandebosch, A., & Vansteelandt, S. (2021). A novel estimand to adjust for rescue treatment in randomized clinical trials. STATISTICS IN MEDICINE, 40(9), 2257–2271. https://doi.org/10.1002/sim.8901
Chicago author-date
Michiels, Hege, Cristina Sotto, An Vandebosch, and Stijn Vansteelandt. 2021. “A Novel Estimand to Adjust for Rescue Treatment in Randomized Clinical Trials.” STATISTICS IN MEDICINE 40 (9): 2257–71. https://doi.org/10.1002/sim.8901.
Chicago author-date (all authors)
Michiels, Hege, Cristina Sotto, An Vandebosch, and Stijn Vansteelandt. 2021. “A Novel Estimand to Adjust for Rescue Treatment in Randomized Clinical Trials.” STATISTICS IN MEDICINE 40 (9): 2257–2271. doi:10.1002/sim.8901.
Vancouver
1.
Michiels H, Sotto C, Vandebosch A, Vansteelandt S. A novel estimand to adjust for rescue treatment in randomized clinical trials. STATISTICS IN MEDICINE. 2021;40(9):2257–71.
IEEE
[1]
H. Michiels, C. Sotto, A. Vandebosch, and S. Vansteelandt, “A novel estimand to adjust for rescue treatment in randomized clinical trials,” STATISTICS IN MEDICINE, vol. 40, no. 9, pp. 2257–2271, 2021.
@article{8710276,
  abstract     = {{The interpretation of randomized clinical trial results is often complicated by intercurrent events. For instance, rescue medication is sometimes given to patients in response to worsening of their disease, either in addition to the randomized treatment or in its place. The use of such medication complicates the interpretation of the intention-to-treat analysis. In view of this, we propose a novel estimand defined as the intention-to-treat effect that would have been observed, had patients on the active arm been switched to rescue medication if and only if they would have been switched when randomized to control. This enables us to disentangle the treatment effect from the effect of rescue medication on a patient's outcome, while tempering the strong extrapolations that are typically needed when inferring what the intention-to-treat effect would have been in the absence of rescue medication. We propose a novel inverse probability weighting method for estimating this effect in settings where the decision to initiate rescue medication is made at one prespecified time point. This estimator relies on specific untestable assumptions, in view of which we propose a sensitivity analysis. We use the method for the analysis of a clinical trial conducted by Janssen Pharmaceuticals, in which patients with type 2 diabetes mellitus can switch to rescue medication for ethical reasons. Monte Carlo simulations confirm that the proposed estimator is unbiased in moderate sample sizes.}},
  author       = {{Michiels, Hege and Sotto, Cristina and Vandebosch, An and Vansteelandt, Stijn}},
  issn         = {{0277-6715}},
  journal      = {{STATISTICS IN MEDICINE}},
  keywords     = {{Statistics and Probability,Epidemiology,causal inference,intercurrent events,mediation,posttreatment confounding,treatment discontinuation,treatment switching}},
  language     = {{eng}},
  number       = {{9}},
  pages        = {{2257--2271}},
  title        = {{A novel estimand to adjust for rescue treatment in randomized clinical trials}},
  url          = {{http://dx.doi.org/10.1002/sim.8901}},
  volume       = {{40}},
  year         = {{2021}},
}

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