| Type | Journal Article |
|---|---|
| Author | Michael C. Donohue |
| Author | Oliver Langford |
| Author | Philip S. Insel |
| Author | Christopher H. van Dyck |
| Author | Ronald C. Petersen |
| Author | Suzanne Craft |
| Author | Gopalan Sethuraman |
| Author | Rema Raman |
| Author | Paul S. Aisen |
| Author | For the Alzheimer's Disease Neuroimaging Initiative |
| URL | https://onlinelibrary.wiley.com/doi/abs/10.1002/pst.2285 |
| Volume | n/a |
| Issue | n/a |
| Publication | Pharmaceutical Statistics |
| ISSN | 1539-1612 |
| Extra | _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/pst.2285 |
| DOI | 10.1002/pst.2285 |
| Accessed | 1/11/2023, 6:15:16 AM |
| Library Catalog | Wiley Online Library |
| Language | en |
| Abstract | Mixed model repeated measures (MMRM) is the most common analysis approach used in clinical trials for Alzheimer's disease and other progressive diseases measured with continuous outcomes over time. The model treats time as a categorical variable, which allows an unconstrained estimate of the mean for each study visit in each randomized group. Categorizing time in this way can be problematic when assessments occur off-schedule, as including off-schedule visits can induce bias, and excluding them ignores valuable information and violates the intention to treat principle. This problem has been exacerbated by clinical trial visits which have been delayed due to the COVID19 pandemic. As an alternative to MMRM, we propose a constrained longitudinal data analysis with natural cubic splines that treats time as continuous and uses test version effects to model the mean over time. Compared to categorical-time models like MMRM and models that assume a proportional treatment effect, the spline model is shown to be more parsimonious and precise in real clinical trial datasets, and has better power and Type I error in a variety of simulation scenarios. |
| Date Added | 1/11/2023, 6:15:16 AM |
| Modified | 1/11/2023, 7:16:13 AM |
| Type | Journal Article |
|---|---|
| Author | Christy Cassarly |
| Author | Renee’ H. Martin |
| Author | Marc Chimowitz |
| Author | Edsel A. Peña |
| Author | Viswanathan Ramakrishnan |
| Author | Yuko Y. Palesch |
| URL | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0187050 |
| Volume | 12 |
| Issue | 10 |
| Pages | e0187050 |
| Publication | PLOS ONE |
| ISSN | 1932-6203 |
| Date | Oct 26, 2017 |
| Extra | Publisher: Public Library of Science |
| Journal Abbr | PLOS ONE |
| DOI | 10.1371/journal.pone.0187050 |
| Accessed | 12/16/2022, 7:03:44 AM |
| Library Catalog | PLoS Journals |
| Language | en |
| Abstract | Historically, ordinal measures of functional outcome have been dichotomized for the primary analysis in acute stroke therapy trials. A number of alternative methods to analyze the ordinal scales have been proposed, with an emphasis on maintaining the ordinal structure as much as possible. In addition, despite the availability of longitudinal outcome data in many trials, the primary analysis consists of a single endpoint. Inclusion of information about the course of disease progression allows for a more complete understanding of the treatment effect. Multistate Markov modeling, which allows for the full ordinal scale to be analyzed longitudinally, is compared with previously suggested analytic techniques for the ordinal modified Rankin Scale (dichotomous-logistic regression; continuous-linear regression; ordinal- shift analysis, proportional odds model, partial proportional odds model, adjacent categories logit model; sliding dichotomy; utility weights; repeated measures). In addition, a multistate Markov model utilizing an estimate of the unobservable baseline outcome derived from principal component analysis is compared Each of the methods is used to re-analyze the National Institute of Neurological Diseases and Stroke tissue plasminogen activator study which showed a consistently significant effect of tissue plasminogen activator using a global test of four dichotomized outcomes in the analysis of the primary outcome at 90 days post-stroke in the primary analysis. All methods detected a statistically significant treatment effect except the multistate Markov model without predicted baseline (p = 0.053). This provides support for the use of the estimated baseline in the multistate Markov model since the treatment effect is able to be detected with its inclusion. Multistate Markov modeling allows for a more refined examination of treatment effect and describes the movement between modified Rankin Scale states over time which may provide more clinical insight into the treatment effect. Multistate Markov models are feasible and desirable in describing treatment effect in acute stroke therapy trials. |
| Date Added | 12/16/2022, 7:03:44 AM |
| Modified | 12/16/2022, 7:04:29 AM |
| Type | Journal Article |
|---|---|
| Author | Isabelle L. Smith |
| Author | Jane E. Nixon |
| Author | Linda Sharples |
| URL | http://onlinelibrary.wiley.com/doi/abs/10.1002/sim.8882 |
| Rights | © 2021 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. |
| Volume | n/a |
| Issue | n/a |
| Publication | Statistics in Medicine |
| ISSN | 1097-0258 |
| Date | 2021 |
| Extra | _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.8882 |
| DOI | https://doi.org/10.1002/sim.8882 |
| Accessed | 2/12/2021, 11:20:57 AM |
| Library Catalog | Wiley Online Library |
| Language | en |
| Abstract | For clinical trials where participants pass through a number of discrete health states resulting in longitudinal measures over time, there are several potential primary estimands for the treatment effect. Incidence or time to a particular health state are commonly used outcomes but the choice of health state may not be obvious and these estimands do not make full use of the longitudinal assessments. Multistate models have been developed for some diseases and conditions with the purpose of understanding their natural history and have been used for secondary analysis to understand mechanisms of action of treatments. There is little published on the use of multistate models as the primary analysis method and potential implications on design features, such as assessment schedules. We illustrate methods via analysis of data from a motivating example; a Phase III clinical trial of pressure ulcer prevention strategies. We clarify some of the possible estimands that might be considered and we show, via a simulation study, that under some circumstances the sample size could be reduced by half using a multistate model based analysis, without adversely affecting the power of the trial. |
| Date Added | 2/12/2021, 11:20:57 AM |
| Modified | 2/25/2021, 8:34:44 AM |
| Type | Journal Article |
|---|---|
| Author | Stephen Senn |
| Author | Lynda Stevens |
| Author | Nish Chaturvedi |
| URL | https://pubmed.ncbi.nlm.nih.gov/10734289 |
| Volume | 19 |
| Pages | 861-877 |
| Publication | Stat Med |
| Date | 2000 |
| Extra | Citation Key: sen00rep tex.citeulike-article-id= 13265118 tex.citeulike-linkout-0= http://dx.doi.org/10.1002/(SICI)1097-0258(20000330)19:6%3C861::AID-SIM407%3E3.0.CO;2-F tex.posted-at= 2014-07-14 14:09:49 tex.priority= 0 |
| DOI | 10.1002/(SICI)1097-0258(20000330)19:6<861::AID-SIM407>3.0.CO;2-F |
| Date Added | 7/7/2018, 1:38:33 PM |
| Modified | 6/12/2020, 6:11:53 AM |
| Type | Journal Article |
|---|---|
| Author | Julio M. Singer |
| Author | Dalton F. Andrade |
| URL | http://dx.doi.org/10.2307/2533973 |
| Volume | 53 |
| Pages | 729-735 |
| Publication | Biometrics |
| Date | 1997 |
| Extra | Citation Key: sin97reg tex.citeulike-article-id= 13264865 tex.citeulike-linkout-0= http://dx.doi.org/10.2307/2533973 tex.posted-at= 2014-07-14 14:09:44 tex.priority= 0 |
| DOI | 10.2307/2533973 |
| Date Added | 7/7/2018, 1:38:33 PM |
| Modified | 11/8/2019, 8:01:59 AM |
problems with using baseline measurement as covariate
| Type | Journal Article |
|---|---|
| Author | J. N. S. Matthews |
| URL | http://dx.doi.org/10.1002/sim.4780120105 |
| Volume | 12 |
| Pages | 27-37 |
| Publication | Stat Med |
| Date | 1993 |
| Extra | Citation Key: mat93ref tex.citeulike-article-id= 13264584 tex.citeulike-linkout-0= http://dx.doi.org/10.1002/sim.4780120105 tex.posted-at= 2014-07-14 14:09:38 tex.priority= 0 |
| DOI | 10.1002/sim.4780120105 |
| Date Added | 7/7/2018, 1:38:33 PM |
| Modified | 11/8/2019, 8:01:59 AM |
| Type | Journal Article |
|---|---|
| Author | J. N. S. Matthews |
| Author | Douglas G. Altman |
| Author | M. J. Campbell |
| Author | Patrick Royston |
| URL | http://dx.doi.org/10.1136/bmj.300.6719.230 |
| Volume | 300 |
| Pages | 230-235 |
| Publication | BMJ |
| Date | 1990 |
| Extra | Citation Key: mat90ana tex.citeulike-article-id= 13264583 tex.citeulike-linkout-0= http://dx.doi.org/10.1136/bmj.300.6719.230 tex.posted-at= 2014-07-14 14:09:38 tex.priority= 0 Letter to editor by S. Senn in same issue |
| DOI | 10.1136/bmj.300.6719.230 |
| Date Added | 7/7/2018, 1:38:33 PM |
| Modified | 11/8/2019, 8:01:59 AM |