Methodological Research and Collaboration

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Methodological Research and Collaboration

• Lan Kong
• Assistant professor
• Department of Biostatistics
• November 11, 2009

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Outline

• Introduction
• Methodological Research
• Survival analysis
• Clinical trials
• Collaboration
• Projects
• Motivated problems

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Introduction

• Joined the Biostat dept in August 2003
• PhD in Biostat from UNC-Chapel Hill
• In collaboration with critical care medicine
  dept.
• On doctoral exam committee
• Courses intend to teach survival analysis,
  advanced categorical data analysis, or estimating
  equation method.

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Methodological research

• Survival analysis
• Study design case-cohort
• Model semiparametric transformation models and
  accelerated failure time model.
• Approach estimating equation method, inverse of
  probability weighting technique
• Statistical theory U-statistics, finite
  population sampling, martingales,
  empirical/stochastic process

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Case-cohort design (Prentice, 1986)
Subcohort
Full cohort
Complete data available for Subcohort
Additional Cases outside the subcohort
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Semiparametric Survival Models

• Cox model
• ?(t)?0(t)exp(ßZ), ?0(t) unspecified
• Transformation models
• h(T) -ßZe OR gSz(t)h(t)ßZ
• h unknown, e has known CDF F(.), g-11-F.
• Accelerated failure time model
• log(T) -ßZe, e has unspecified CDF.

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Methodological Research (cont.)

• Clinical trials
• Problem Multiplicity issues
• Example
• Multi-dose clinical trials--correlations among
  multiple comparisons
• Statistical concerns familywise Type I error and
  power

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Family-Wise Error (FWE)

• Probability that at least one hypothesis is
  incorrectly declared significant.
• Strongly control of FWE
• FWE is protected for any composite null
  hypothesis
• Closed testing procedures strongly control the FWE

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Multiple testing procedures

• Analysis strategies
• Perform a sequence of tests in a pre-specified
  order through the closed testing principle
• 1. Global assessment of any dose effect
• 2. Comparisons of doses to Placebo
• 3. Other comparisons among doses
• Manage multiplicity within the respective steps
  by Hochberg method (BKA, 1988), closed testing
  procedure.

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Vaccine trials

• Problem
• Inferiority/Equivalence assessment
• Multiplicity due to multiple endpoints (immune
  responses)
• Statistical concerns
• How correlations among endpoints affect study
  design of inferiority/EQ trials (power, sample
  size)?

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Hypotheses

H0 (inf) H1 (noninf)
T-C
-K 0
H0 (noneq) H1 (eq) H0 (noneq)
T-C
-K 0 K
T treatment group, C control group
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Further questions of interest

• How to handle multiple endpoints in multi-dose
  clinical trials?
• How to simultaneously assess inferiority/EQ on
  some endpoints and superiority on the others?

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Collaboration

• Projects mainly involved
• Genetic and inflammatory markers of Sepsis
  (GenIMS)
• Economic Analysis of the Pulmonary Artery
  Catheter Use (EA-PAC)
• Prolonged Outcomes of Nitric Oxide for Ventilated
  Premature Babies (PRONOX)

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Statistical problems motivated from
collaborative projects
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Genetic data

• Explore how the candidate markers interactively
  affect the outcome (Selection of subset from a
  list of candidate genetic markers)
• Statistical learning method
• Pattern recognition approach
• Haplotype analysis for survival data to
  accommodate missing genotypes, case-cohort design

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Missing and/or truncated data

• Examples inflammatory marker data are below
  detectable limit, the measurement on the severity
  of sepsis are heavily missing
• Longitudinal analysis of truncated inflammatory
  marker (extension of Tobit model)
• Jointly modeling several truncated inflammatory
  markers
• Testing whether the missing is informative in the
  non-monotone missing pattern
• Jointly modeling the longitudinal outcome and
  longitudinal covariates

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Quality of Life and Cost data

• Various types of outcomes survival data, cost
  data, quality of life data.
• Informative censoring
• Modeling quality adjusted survival
• Jointly modeling QOL with survival data
• Cost-effective analysis in presence of repeated
  measures and missing data

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Related papers

Kong L, Cai J, Sen PK. Weighted estimating
equations for semiparametric transformation
models with censored data from a case-cohort
design. Biometrika 2004 91(2)305-319. Kong L,
Cai J, Sen PK. Asymptotic results for fitting
semiparametric transformation models to failure
time data from a case-cohort design. Statistica
Sinica 2004, in press. Kong L. Analysis of
case-cohort data with accelerated failure time
model, in preparation
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Related papers (cont.)

Kong L, Kohberger R, Koch G. Type I error and
power in non-inferiority/equivalence trials with
correlated multiple endpoints an example from
vaccine development trials. Journal of
Biopharmaceutical Statistics 2004
14(4)893-907. Kong L, Koch G, Liu T, Wang H.
Performance of some multiple testing procedures
to compare three doses of a test drug and
placebo. Pharmaceutical Statistics 2004, in
press. Kong L, Kohberger R, Koch G.
Equivalence/non-inferiority assessment on
multiple proportion outcomes. In preparation.