A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials.
<h4>Background</h4>When rates of uptake of other drugs differ between treatment arms in long-term trials, the true benefit or harm of the treatment may be underestimated. Methods to allow for such contamination have often been limited by failing to preserve the randomization comparisons....
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2010
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oai:doaj.org-article:0cb9474b245145e6887b5c789122e9ec2021-11-25T06:26:50ZA novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials.1932-620310.1371/journal.pone.0008580https://doaj.org/article/0cb9474b245145e6887b5c789122e9ec2010-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20072614/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>When rates of uptake of other drugs differ between treatment arms in long-term trials, the true benefit or harm of the treatment may be underestimated. Methods to allow for such contamination have often been limited by failing to preserve the randomization comparisons. In the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study, patients were randomized to fenofibrate or placebo, but during the trial many started additional drugs, particularly statins, more so in the placebo group. The effects of fenofibrate estimated by intention-to-treat were likely to have been attenuated. We aimed to quantify this effect and to develop a method for use in other long-term trials.<h4>Methodology/principal findings</h4>We applied efficacies of statins and other cardiovascular drugs from meta-analyses of randomized trials to adjust the effect of fenofibrate in a penalized Cox model. We assumed that future cardiovascular disease events were reduced by an average of 24% by statins, and 20% by a first other major cardiovascular drug. We applied these estimates to each patient who took these drugs for the period they were on them. We also adjusted the analysis by the rate of discontinuing fenofibrate. Among 4,900 placebo patients, average statin use was 16% over five years. Among 4,895 assigned fenofibrate, statin use was 8% and nonuse of fenofibrate was 10%. In placebo patients, use of cardiovascular drugs was 1% to 3% higher. Before adjustment, fenofibrate was associated with an 11% reduction in coronary events (coronary heart disease death or myocardial infarction) (P = 0.16) and an 11% reduction in cardiovascular disease events (P = 0.04). After adjustment, the effects of fenofibrate on coronary events and cardiovascular disease events were 16% (P = 0.06) and 15% (P = 0.008), respectively.<h4>Conclusions/significance</h4>This novel application of a penalized Cox model for adjustment of a trial estimate of treatment efficacy incorporates evidence-based estimates for other therapies, preserves comparisons between the randomized groups, and is applicable to other long-term trials. In the FIELD study example, the effects of fenofibrate on the risks of coronary heart disease and cardiovascular disease events were underestimated by up to one-third in the original analysis.<h4>Trial registration</h4>Controlled-Trials.com ISRCTN64783481.John SimesMerryn VoyseyRachel O'ConnellPaul GlasziouJames D BestRussell ScottChristopher PardyKaren BythDavid R SullivanChristian EhnholmAnthony KeechFIELD Study InvestigatorsPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 5, Iss 1, p e8580 (2010) |
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Medicine R Science Q John Simes Merryn Voysey Rachel O'Connell Paul Glasziou James D Best Russell Scott Christopher Pardy Karen Byth David R Sullivan Christian Ehnholm Anthony Keech FIELD Study Investigators A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials. |
| description |
<h4>Background</h4>When rates of uptake of other drugs differ between treatment arms in long-term trials, the true benefit or harm of the treatment may be underestimated. Methods to allow for such contamination have often been limited by failing to preserve the randomization comparisons. In the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study, patients were randomized to fenofibrate or placebo, but during the trial many started additional drugs, particularly statins, more so in the placebo group. The effects of fenofibrate estimated by intention-to-treat were likely to have been attenuated. We aimed to quantify this effect and to develop a method for use in other long-term trials.<h4>Methodology/principal findings</h4>We applied efficacies of statins and other cardiovascular drugs from meta-analyses of randomized trials to adjust the effect of fenofibrate in a penalized Cox model. We assumed that future cardiovascular disease events were reduced by an average of 24% by statins, and 20% by a first other major cardiovascular drug. We applied these estimates to each patient who took these drugs for the period they were on them. We also adjusted the analysis by the rate of discontinuing fenofibrate. Among 4,900 placebo patients, average statin use was 16% over five years. Among 4,895 assigned fenofibrate, statin use was 8% and nonuse of fenofibrate was 10%. In placebo patients, use of cardiovascular drugs was 1% to 3% higher. Before adjustment, fenofibrate was associated with an 11% reduction in coronary events (coronary heart disease death or myocardial infarction) (P = 0.16) and an 11% reduction in cardiovascular disease events (P = 0.04). After adjustment, the effects of fenofibrate on coronary events and cardiovascular disease events were 16% (P = 0.06) and 15% (P = 0.008), respectively.<h4>Conclusions/significance</h4>This novel application of a penalized Cox model for adjustment of a trial estimate of treatment efficacy incorporates evidence-based estimates for other therapies, preserves comparisons between the randomized groups, and is applicable to other long-term trials. In the FIELD study example, the effects of fenofibrate on the risks of coronary heart disease and cardiovascular disease events were underestimated by up to one-third in the original analysis.<h4>Trial registration</h4>Controlled-Trials.com ISRCTN64783481. |
| format |
article |
| author |
John Simes Merryn Voysey Rachel O'Connell Paul Glasziou James D Best Russell Scott Christopher Pardy Karen Byth David R Sullivan Christian Ehnholm Anthony Keech FIELD Study Investigators |
| author_facet |
John Simes Merryn Voysey Rachel O'Connell Paul Glasziou James D Best Russell Scott Christopher Pardy Karen Byth David R Sullivan Christian Ehnholm Anthony Keech FIELD Study Investigators |
| author_sort |
John Simes |
| title |
A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials. |
| title_short |
A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials. |
| title_full |
A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials. |
| title_fullStr |
A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials. |
| title_full_unstemmed |
A novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials. |
| title_sort |
novel method to adjust efficacy estimates for uptake of other active treatments in long-term clinical trials. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2010 |
| url |
https://doaj.org/article/0cb9474b245145e6887b5c789122e9ec |
| work_keys_str_mv |
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