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Research Articles

Teasing Out the Overall Survival Benefit With Adjustment for Treatment Switching to Multiple Treatments

, , , & ORCID Icon
Pages 592-601 | Received 07 Oct 2019, Accepted 01 Apr 2021, Published online: 18 May 2021

References

  • Agency, E. M. (2017), “Ich e9 (r1) Addendum on Estimands and Sensitivity Analysis in Clinical Trials to the Guideline on Statistical Principles for Clinical Trials.”
  • Bond, S., and Allison, A. (2019), rpsftm: Rank Preserving Structural Failure Time Models, R package version 1.2.6.
  • Branson, M., and Whitehead, J. (2002), “Estimating a Treatment Effect in Survival Studies in Which Patients Switch Treatment,” Statistics in Medicine, 21, 2449–2463. DOI: 10.1002/sim.1219.
  • Breiman, L. (2001), “Random Forests,” Machine Learning, 45, 5–32. DOI: 10.1023/A:1010933404324.
  • Brilleman, S. (2019), simsurv: Simulate Survival Data, R package version 0.2.3.
  • Burton, A., Altman, D. G., Royston, P., and Holder, R. L. (2006), “The Design of Simulation Studies in Medical Statistics,” Statistics in Medicine, 25, 4279–4292. DOI: 10.1002/sim.2673.
  • Chan, A.-W., and Altman, D. G. (2005), “Epidemiology and Reporting of Randomised Trials Published in Pubmed Journals,” The Lancet, 365, 1159–1162. DOI: 10.1016/S0140-6736(05)71879-1.
  • Cox, D. R. (2018), Analysis of Survival Data, Chapman and Hall/CRC.
  • Graffeo, N., Latouche, A., and Chevret, S. (2019), ipcwswitch: Inverse Probability of Censoring Weights to Deal with Treatment Switch in Randomized Clinical Trials, R package version 1.0.3.
  • Grafféo, N., Latouche, A., Le Tourneau, C., and Chevret, S. (2019), “ipcwswitch: an r Package for Inverse Probability of Censoring Weighting With an Application to Switches in Clinical Trials,” Computers in Biology and Medicine, 111, 103339. DOI: 10.1016/j.compbiomed.2019.103339.
  • Henshall, C., Latimer, N. R., Sansom, L., and Ward, R. L. (2016), “Treatment Switching in Cancer Trials: Issues and Proposals,” International Journal of Technology Assessment in Health Care, 32, 167–174. DOI: 10.1017/S026646231600009X.
  • Hernán, M. A., Brumback, B., and Robins, J. M. (2001), “Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments,” Journal of the American Statistical Association, 96, 440–448. DOI: 10.1198/016214501753168154.
  • Hernán, M. A., Cole, S. R., Margolick, J., Cohen, M., and Robins, J. M. (2005), “Structural Accelerated Failure Time Models for Survival Analysis in Studies With Time-varying Treatments,” Pharmacoepidemiology and Drug Safety, 14, 477–491. DOI: 10.1002/pds.1064.
  • Hernán, M. A., and Robins, J. M. (2010), Causal Inference, Boca Raton, CRC Press.
  • Howe, C. J., Cole, S. R., Chmiel, J. S., and Munoz, A. (2011), “Limitation of Inverse Probability-of-censoring Weights in Estimating Survival in the Presence of Strong Selection Bias,” American Journal of Epidemiology, 173, 569–577. DOI: 10.1093/aje/kwq385.
  • Ishwaran, H., Kogalur, U. B., Blackstone, E. H., Lauer, M. S. (2008), “Random Survival Forests,” The Annals of Applied Statistics, 2, 841–860. DOI: 10.1214/08-AOAS169.
  • Latimer, N. R. (2015), “Treatment Switching in Oncology Trials and the Acceptability of Adjustment Methods,” Expert Review of Pharmacoeconomics & Outcomes Research, 15, 561–564.
  • Latimer, N. R., Abrams, K., Lambert, P., Crowther, M., Wailoo, A., Morden, J., Akehurst, R., and Campbell, M. (2017), “Adjusting for Treatment Switching in Randomised Controlled Trials–A Simulation Study and a Simplified Two-stage Method,” Statistical Methods in Medical Research, 26, 724–751. DOI: 10.1177/0962280214557578.
  • Latimer, N. R., Abrams, K. R., et al. (2014a), “Nice DSU Technical Support Document 16: Adjusting Survival Time Estimates in the Presence of Treatment Switching,” available at http://nicedsu.org.uk/wp-content/uploads/2016/03/TSD16_Treatment_Switching.pdf.
  • Latimer, N. R., Abrams, K. R., Lambert, P. C., Crowther, M. J., Wailoo, A. J., Morden, J. P., Akehurst, R. L., and Campbell, M. J. (2014b), “Adjusting Survival Time Estimates to Account for Treatment Switching in Randomized Controlled Trials? An Economic Evaluation Context: Methods, Limitations, and Recommendations,” Medical Decision Making, 34, 387–402. DOI: 10.1177/0272989X13520192.
  • Latimer, N. R., Abrams, K. R., Lambert, P. C., Morden, J. P., and Crowther, M. J. (2018), “Assessing Methods for Dealing With Treatment Switching in Clinical Trials: A Follow-up Simulation Study,” Statistical Methods in Medical Research, 27, 765–784. DOI: 10.1177/0962280216642264.
  • Liaw, A., and Wiener, M. (2002), “Classification and Regression by Randomforest,” R News, 2, 18–22.
  • Mallinckrodt, C., Molenberghs, G., Lipkovich, I., and Ratitch, B. (2019), Estimands, Estimators and Sensitivity Analysis in Clinical Trials, CRC Press.
  • Pepe, M. S., and Fleming, T. R. (1989). “Weighted Kaplan–Meier Statistics: A Class of Distance Tests for Censored Survival Data.” Biometrics, 497–507. DOI: 10.2307/2531492.
  • Robins, J. M., Blevins, D., Ritter, G., and Wulfsohn, M. (1992), “G-estimation of the Effect of Prophylaxis Therapy for Pneumocystis Carinii Pneumonia on the Survival of Aids Patients,” Epidemiology, 319–336.
  • Robins, J. M., and Finkelstein, D. M. (2000), “Correcting for Noncompliance and Dependent Censoring in an Aids Clinical Trial With Inverse Probability of Censoring Weighted (IPCW) Log-rank Tests,” Biometrics, 56, 779–788. DOI: 10.1111/j.0006-341X.2000.00779.x.
  • Robins, J. M., and Greenland, S. (1994), “Adjusting for Differential Rates of Prophylaxis Therapy for PCP in High-versus Low-dose AZT Treatment Arms in an Aids Randomized Trial,” Journal of the American Statistical Association, 89, 737–749. DOI: 10.1080/01621459.1994.10476807.
  • Robins, J. M., and Tsiatis, A. A. (1991), “Correcting for Non-compliance in Randomized Trials Using Rank Preserving Structural Failure Time Models,” Communications in Statistics–Theory and Methods, 20, 2609–2631. DOI: 10.1080/03610929108830654.
  • Segal, M. R. (2004), “Machine Learning Benchmarks and Random Forest Regression.”
  • Watkins, C., Huang, X., Latimer, N., Tang, Y., and Wright, E. J. (2013), “Adjusting Overall Survival for Treatment Switches: Commonly Used Methods and Practical Application,” Pharmaceutical Statistics, 12, 348–357. DOI: 10.1002/pst.1602.
  • White, I. R. (2005), “Uses and Limitations of Randomization-based Efficacy Estimators,” Statistical Methods in Medical Research, 14, 327–347. DOI: 10.1191/0962280205sm406oa.
  • White, I. R., Walker, S., Babiker, A. G., and Darbyshire, J. H. (1997), “Impact of Treatment Changes on the Interpretation of the Concorde Trial,” Aids, 11, 999–1006.
  • Yamaguchi, T. and Ohashi, Y. (2004), “Adjusting for Differential Proportions of Second-line Treatment in Cancer Clinical Trials. Part I: Structural Nested Models and Marginal Structural Models to Test and Estimate Treatment Arm Effects,” Statistics in Medicine, 23, 1991–2003. DOI: 10.1002/sim.1816.

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