Statistical validation of intermediate endpoints for chronic diseases.

By L. Freedman, B. Graubard, A. Schatzkin. 1992

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Citations in the corpus

Random Effects Models for Longitudinal Data (2010, background): “Freedman, Graubard, and Schatzkin (1992) augmented Prentice’s hypothesis-testing based approach, with the estimation paradigm, through the so-called proportion of treatment effect explained.”
The validation of surrogate endpoints in meta-analyses of randomized experiments. (2000, methodology): “The non-significance of this test does not prove that the effect of treatment upon the true endpoint is fully captured by the surrogate, and therefore Freedman et al. (1992) proposed to calculate the proportion of the treatment effect explained by the surrogate.”
A general approach to causal mediation analysis. (2010, unknown): “First, Freedman et al. (1992) suggested the difference of coefficients method, which is based on the difference between 1 from Equation 17 and 3 from Equation 14.”
Principal Stratification in Causal Inference (2002, background): “There is currently growing literature on such " surrogate " or " biomarker " endpoint variables (e.g., Prentice, 1989; Freedman et al., 1992; Lin et al., 1997; Buyse et al., 2000).”
Relationship of Early Changes in Bone Resorption to the Reduction in Fracture Risk With Risedronate (2003, methodology): “The confidence intervals from the Freedman et al.20 analysis are wider than those obtained using the methods of Li et al.7; these wider intervals are probably attributable to the larger variability generated when fitting two separate statistical models compared with one model.”
Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index (2016, background): “Freedman et al. (1992) argued that the surrogate may not mediate all the effect of the treatment and developed a measure of the proportion of the treatment effect on the long-term outcome explained by the surrogate.”
Equivalence of the Mediation, Confounding and Suppression Effect (2000, background): “The interventions are designed to change constructs, which are thought to be causally related to the dependent variable ( Freedman, Graubard, & Schatzkin, 1992 ).”
Lower tidal volume ventilation and plasma cytokine markers of inflammation in patients with acute lung injury* (2005, background): “, IL-6), which was defined as the percent reduction in the log of the mortality odds ratio for ventilator treatment after adjusting for the marker (25).”
Related Causal Frameworks for Surrogate Outcomes (2009, background): “In more general terms, βA − γA has been interpreted as the part of the effect of A explained by S—expressed as a proportion of the total effect βA , it is 1 − γA /βA (Freedman, Graubard, and Schatzkin, 1992).”
Older women with diabetes have a higher risk of falls: a prospective study. (2002, methodology): “The contribution of each variable to increased risk among women with diabetes was assessed by comparing the coefficients of the diabetes variables in the age-adjusted logistic regression model with those in a model controlling for age and the risk factor of interest (20).”
Bounds on Direct Effects in the Presence of Confounded Intermediate Variables (2008, methodology): “Pearl (2001) gave a formal definition of the total effect decomposition into direct and indirect effects, and distinguished between the controlled direct effect and the natural direct effect, the former is obtained when intermediate variables are held constant at specific values.”
Transportability across studies: A formal approach (2011, background): “Although traditional deﬁnitions for a surrogate endpoint (e.g., Prentice (1989); Freedman et al. (1992); Lin et al. (1997); Buyse and Molenberghs (1998); Buyse et al. (2000)) are based on regressions, they are unwittingly motivated by causal considerations, and several attempts have been made since…”
On the use of surrogate end points in randomized trials (2000, background): “The implications of the criterion have been discussed in more detail in subsequent papers (Freedman et al., 1992; Buyse and Molenberghs, 1998).”
The Mediation Formula: A Guide to the Assessment of Causal Pathways in Nonlinear Models (2011, background): “, 2007b) and much controversy has developed as to which strategy should be used in assessing the size of mediation effects (MacKinnon and Dwyer, 1993; Freedman et al., 1992; Molenberghs et al., 2002; MacKinnon et al., 2007b; Glynn, 2009; Green et al., 2010).”