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PLoS ONE (1)
The International Journal of Biostatistics (1)
Wolfson, Julian (3)
Gilbert, Peter (2)
Corey, Lawrence (1)
DeCamp, Allan (1)
Frahm, Nicole (1)
Friedrich, David P. (1)
Gabriel, Erin (1)
Gilbert, Peter B. (1)
Goepfert, Paul (1)
Gray, Clive M. (1)
Hertz, Tomer (1)
Hudgens, Michael G. (1)
Janes, Holly (1)
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McElrath, M. Juliana (1)
Mullins, James I. (1)
Rolland, Morgane (1)
Year of Publication
Statistical identifiability and the surrogate endpoint problem, with application to vaccine trials
Given a randomized treatment Z, a clinical outcome Y, and a biomarker S measured some fixed time after Z is administered, we may be interested in addressing the surrogate endpoint problem by evaluating whether S can be used to reliably predict the effect of Z on Y. Several recent proposals for the statistical evaluation of surrogate value have been based on the framework of principal stratification. In this paper, we consider two principal stratification estimands: joint risks and marginal risks. Joint risks measure causal associations of treatment effects on S and Y, providing insight into the surrogate value of the biomarker, but are not statistically identifiable from vaccine trial data. While marginal risks do not measure causal associations of treatment effects, they nevertheless provide guidance for future research, and we describe a data collection scheme and assumptions under which the marginal risks are statistically identifiable. We show how different sets of assumptions affect the identifiability of these estimands; in particular, we depart from previous work by considering the consequences of relaxing the assumption of no individual treatment effects on Y before S is measured. Based on algebraic relationships between joint and marginal risks, we propose a sensitivity analysis approach for assessment of surrogate value, and show that in many cases the surrogate value of a biomarker may be hard to establish, even when the sample size is large.
Estimated likelihood; Identifiability; Principal stratification; Sensitivity analysis; Surrogate endpoint; Vaccine trials
Commentary on “Principal Stratification — a Goal or a Tool?” by Judea Pearl
Gilbert, Peter B.
Hudgens, Michael G.
The International Journal of Biostatistics
This commentary takes up Pearl's welcome challenge to clearly articulate the scientific value of principal stratification estimands that we and colleagues have investigated, in the area of randomized placebo-controlled preventive vaccine efficacy trials, especially trials of HIV vaccines. After briefly arguing that certain principal stratification estimands for studying vaccine effects on post-infection outcomes are of genuine scientific interest, the bulk of our commentary argues that the “causal effect predictiveness” (CEP) principal stratification estimand for evaluating immune biomarkers as surrogate endpoints is not of ultimate scientific interest, because it evaluates surrogacy restricted to the setting of a particular vaccine efficacy trial, but is nevertheless useful for guiding the selection of primary immune biomarker endpoints in Phase I/II vaccine trials and for facilitating assessment of transportability/bridging surrogacy.
principal stratification; causal inference; vaccine trial
MRKAd5 HIV-1 Gag/Pol/Nef Vaccine-Induced T-Cell Responses Inadequately Predict Distance of Breakthrough HIV-1 Sequences to the Vaccine or Viral Load
Friedrich, David P.
Mullins, James I.
McElrath, M. Juliana
Gray, Clive M.
The sieve analysis for the Step trial found evidence that breakthrough HIV-1 sequences for MRKAd5/HIV-1 Gag/Pol/Nef vaccine recipients were more divergent from the vaccine insert than placebo sequences in regions with predicted epitopes. We linked the viral sequence data with immune response and acute viral load data to explore mechanisms for and consequences of the observed sieve effect.
Ninety-one male participants (37 placebo and 54 vaccine recipients) were included; viral sequences were obtained at the time of HIV-1 diagnosis. T-cell responses were measured 4 weeks post-second vaccination and at the first or second week post-diagnosis. Acute viral load was obtained at RNA-positive and antibody-negative visits.
Vaccine recipients had a greater magnitude of post-infection CD8+ T cell response than placebo recipients (median 1.68% vs 1.18%; p = 0·04) and greater breadth of post-infection response (median 4.5 vs 2; p = 0·06). Viral sequences for vaccine recipients were marginally more divergent from the insert than placebo sequences in regions of Nef targeted by pre-infection immune responses (p = 0·04; Pol p = 0·13; Gag p = 0·89). Magnitude and breadth of pre-infection responses did not correlate with distance of the viral sequence to the insert (p>0·50). Acute log viral load trended lower in vaccine versus placebo recipients (estimated mean 4·7 vs 5·1) but the difference was not significant (p = 0·27). Neither was acute viral load associated with distance of the viral sequence to the insert (p>0·30).
Despite evidence of anamnestic responses, the sieve effect was not well explained by available measures of T-cell immunogenicity. Sequence divergence from the vaccine was not significantly associated with acute viral load. While point estimates suggested weak vaccine suppression of viral load, the result was not significant and more viral load data would be needed to detect suppression.
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