S
Sylvain Durrleman
Researcher at National Institutes of Health
Publications - 11
Citations - 2500
Sylvain Durrleman is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Equivalence (measure theory) & Population. The author has an hindex of 8, co-authored 9 publications receiving 2161 citations.
Papers
More filters
Journal ArticleDOI
Flexible regression models with cubic splines
TL;DR: In this article, the authors describe the use of cubic splines in regression models to represent the relationship between the response variable and a vector of covariates, which can help prevent the problems that result from inappropriate linearity assumptions.
Journal ArticleDOI
The Non-Hodgkin Lymphoma Pathologic Classification Project. Long-term follow-up of 1153 patients with non-Hodgkin lymphomas.
Richard Simon,Sylvain Durrleman,Richard T. Hoppe,Gianni Bonadonna,Clara D. Bloomfield,Richard A. Rudders,Bruce D. Cheson,Costan W. Berard +7 more
TL;DR: The probability of long-term survival for unselected patients with non-Hodgkin lymphoma can be substantial and depends on the histologic subtype of the tumor and the extent of dissemination.
Journal ArticleDOI
Planning and monitoring of equivalence studies.
TL;DR: In this article, the authors review the special characteristics of these trials and describe sequential monitoring of equivalence studies using repeated confidence intervals, and discuss the choice of some important design parameters.
Journal ArticleDOI
The use of putative placebo in active control trials: two applications in a regulatory setting.
Sylvain Durrleman,Philip Chaikin +1 more
TL;DR: Two methods of putative placebo analysis for assessing assay sensitivity in active controlled trials were used in securing regulatory approval for docetaxel in the treatment of locally advanced or metastatic breast cancer after failure of prior chemotherapy, and for enoxaparin in thetreatment of acute coronary syndrome.
Journal ArticleDOI
Planning and monitoring of equivalence studies
TL;DR: It is shown how sequential monitoring of equivalence studies using repeated confidence intervals may be of particular value in this setting and critically discuss the choice of some important design parameters.