- Email: [email protected]
P31 A bayesian belief network for exploratory longitudinal analysis
Abstracts
performances of these estimates are compared in terms of bias, mean squared error, and coverage probability. P30
EXPERIENCE WITH MULTIVARIATE SURVIVAL ANALYSIS FOR CLINICAL TRIALS Mark L. Van Natta, Miihele Donithan,
Franklin
Sun and James Tonascia
The Johns Hopkins University Baltimore, Maryland Public domain software providing a practical implementation of Cox’s regression models for multiple events data has recently become available: MULCOX2 (Lin, 1993) and PHLEV (Therneau, 1994). The methodology employs marginal proportional hazards models and robust variance estimation to extend the usual Cox regression model to allow multiple events -either distinct types of events for a given unit or multiple, correlated events of the same type occurring in clusters of units. This approach appears to be widely applicable and may increase the efficiency of treatment effects estimation by making fuller use of the time-to-event outcome data collected in many clinical trials. MULCOX2 is a Fortran program and PHLEV is available in “S” or as a SAS macro. The results of practical experience with these two programs including implementation in a Windows 3.1 environment, data analysis of a variety of multiple event data (including the use of time-dependent covariates), and software extensions is reported. Examples presented use data from the Foscamet-Ganciclovir CMV Retinitis Trial conducted by the Studies of the Ocular Complications of AIDS (SOCA) Research Group.
P31 A BAYESIAN BELIEF NETWORK FOR EXPLORATORY LONGITUDINAL ANALYSIS Ellii Clarke Maryland Medical Research Institute Baltimore, Maryland A Bayesian Belief Network (BBN) can be a valuable tool for exploratory analysis of longitudinal studies, including clinical trials and epidemiological studies. The method is an extension of statistical path analysis. A BBN is essentially a probabilistic expert system based upon hypothesized conditional relationships between discrete variables and upon a priori probabilities of these relationships. The system is structured as a network, with the nodes representing variables and the connections representing conditional probabilities. To investigate the changes in probabilities of the values of variables in the network, associated variables are assigned specific values. These assigned values create changes in the conditional probabilities throughout the network. This example of a BBN is based upon data collected from a sample of girls (N = 500) during the first 5 years of the NHLBI Growth and Health Study. The variables in the BBN are race, and annual measurements of blood pressure, body mass index, maturation stage, total cholesterol, and caloric intake. The continuous variables are converted to discrete variables using quartiles. The structure of the network is determined by the known temporal By orderings of variables and by tests for conditional associations between variables. specifying different structures, BBNs can be used to estimate the importance of main effects
Abstracts
and interactions in a model. This developing area of research in both statistics and computer science can greatly facilitate the analysis of large and complex data sets. I’32 EXPERIENCE WITH PREPLANNED META ANALYSES IN LINKED CLINICAL TRIALS AIMED AT REDUCING FRAILTY IN OLDER ADULTS Kenneth B. Schechtman, Michael A. J. Philip Miller and Washington St. Louis,
Province, Jane E. Ross&r-Fornoff, the FICSIT group University Missouri
The NIH sponsored “Frailty and Injuries: Cooperative Studies of Intervention Techniques (FICSIT) was a multicenter clinical investigation aimed at reducing frailty and falling in older adults. The unique design included eight clinical centers, each running its own clinical trial. Although seven of the trials involved exercise, details of the interventions and of both entry criteria and primary outcomes differed across sites. Despite these differences, the sites were linked by jointly defined common baseline and outcome measures that were collected at all sites using the same protocol and that were managed by a coordinating center using traditional multicenter trial practices. Thus, all sites collected both site specitic and common data. In addition to standard demographics, the common data included information about gait, balance, strength, depression, cognition, falls, and injuries. The predelined analytic strategy in FICSIT was to employ meta analytic techniques. In comparison to standard meta analyses based on literature searches, anticipated advantages included the absence of publication bias because trials were preselected, identical definitions and protocols for all meta analyzed outcome measures, no temporal bias, and the ability to analyze data after adjusting for variables which differed across sites because raw data were available. Moreover, the meta analytic approach is less complex than using a single large pooled analysis. Despite the benefits, we had difficulty (1) deciding which domains of multifaceted interventions were responsible for outcomes and (2) dete rmining the role of exercise intensity. These problems were due primarily to the small number of trials available for analysis. We conclude: Although important deficiencies are present, preplanned meta analyses have several key benefits when applied to data gathered using the FICSIT model. P33 LONGITUDINAL ANALYSIS OF BINARY DATA IN THE V.A. COOPERATIVE STUDY OF SULFASALAZINE FOR THE TREATMENT OF SERONEGATIVE SPONDYLOARTHROPATHIES Dome&
Reda, Robert Anderson, Mazen Ahdellatif, David Wiims and Daniel Clegg VA Medical Center Hines, Illinois
We recently analyzed data for a multi-hospital randomized clinical trial to evaluate the effectiveness of sulfasalazine compared to placebo for the treatment of ankylosing spondylitis (AS), Reiter’s syndrome (RS), and psoriatic arthritis @-%A). As the study was designed, the primary outcome measure was the percentage of treatment responders after nine months (i.e., the final time point). The statistical analysis was based on the &i-square test. The results indicated that sulfasalazine was ineffective for AS, possibly effective for RS and deiinitely effective for PsA.
performances of these estimates are compared in terms of bias, mean squared error, and coverage probability. P30
EXPERIENCE WITH MULTIVARIATE SURVIVAL ANALYSIS FOR CLINICAL TRIALS Mark L. Van Natta, Miihele Donithan,
Franklin
Sun and James Tonascia
The Johns Hopkins University Baltimore, Maryland Public domain software providing a practical implementation of Cox’s regression models for multiple events data has recently become available: MULCOX2 (Lin, 1993) and PHLEV (Therneau, 1994). The methodology employs marginal proportional hazards models and robust variance estimation to extend the usual Cox regression model to allow multiple events -either distinct types of events for a given unit or multiple, correlated events of the same type occurring in clusters of units. This approach appears to be widely applicable and may increase the efficiency of treatment effects estimation by making fuller use of the time-to-event outcome data collected in many clinical trials. MULCOX2 is a Fortran program and PHLEV is available in “S” or as a SAS macro. The results of practical experience with these two programs including implementation in a Windows 3.1 environment, data analysis of a variety of multiple event data (including the use of time-dependent covariates), and software extensions is reported. Examples presented use data from the Foscamet-Ganciclovir CMV Retinitis Trial conducted by the Studies of the Ocular Complications of AIDS (SOCA) Research Group.
P31 A BAYESIAN BELIEF NETWORK FOR EXPLORATORY LONGITUDINAL ANALYSIS Ellii Clarke Maryland Medical Research Institute Baltimore, Maryland A Bayesian Belief Network (BBN) can be a valuable tool for exploratory analysis of longitudinal studies, including clinical trials and epidemiological studies. The method is an extension of statistical path analysis. A BBN is essentially a probabilistic expert system based upon hypothesized conditional relationships between discrete variables and upon a priori probabilities of these relationships. The system is structured as a network, with the nodes representing variables and the connections representing conditional probabilities. To investigate the changes in probabilities of the values of variables in the network, associated variables are assigned specific values. These assigned values create changes in the conditional probabilities throughout the network. This example of a BBN is based upon data collected from a sample of girls (N = 500) during the first 5 years of the NHLBI Growth and Health Study. The variables in the BBN are race, and annual measurements of blood pressure, body mass index, maturation stage, total cholesterol, and caloric intake. The continuous variables are converted to discrete variables using quartiles. The structure of the network is determined by the known temporal By orderings of variables and by tests for conditional associations between variables. specifying different structures, BBNs can be used to estimate the importance of main effects
Abstracts
and interactions in a model. This developing area of research in both statistics and computer science can greatly facilitate the analysis of large and complex data sets. I’32 EXPERIENCE WITH PREPLANNED META ANALYSES IN LINKED CLINICAL TRIALS AIMED AT REDUCING FRAILTY IN OLDER ADULTS Kenneth B. Schechtman, Michael A. J. Philip Miller and Washington St. Louis,
Province, Jane E. Ross&r-Fornoff, the FICSIT group University Missouri
The NIH sponsored “Frailty and Injuries: Cooperative Studies of Intervention Techniques (FICSIT) was a multicenter clinical investigation aimed at reducing frailty and falling in older adults. The unique design included eight clinical centers, each running its own clinical trial. Although seven of the trials involved exercise, details of the interventions and of both entry criteria and primary outcomes differed across sites. Despite these differences, the sites were linked by jointly defined common baseline and outcome measures that were collected at all sites using the same protocol and that were managed by a coordinating center using traditional multicenter trial practices. Thus, all sites collected both site specitic and common data. In addition to standard demographics, the common data included information about gait, balance, strength, depression, cognition, falls, and injuries. The predelined analytic strategy in FICSIT was to employ meta analytic techniques. In comparison to standard meta analyses based on literature searches, anticipated advantages included the absence of publication bias because trials were preselected, identical definitions and protocols for all meta analyzed outcome measures, no temporal bias, and the ability to analyze data after adjusting for variables which differed across sites because raw data were available. Moreover, the meta analytic approach is less complex than using a single large pooled analysis. Despite the benefits, we had difficulty (1) deciding which domains of multifaceted interventions were responsible for outcomes and (2) dete rmining the role of exercise intensity. These problems were due primarily to the small number of trials available for analysis. We conclude: Although important deficiencies are present, preplanned meta analyses have several key benefits when applied to data gathered using the FICSIT model. P33 LONGITUDINAL ANALYSIS OF BINARY DATA IN THE V.A. COOPERATIVE STUDY OF SULFASALAZINE FOR THE TREATMENT OF SERONEGATIVE SPONDYLOARTHROPATHIES Dome&
Reda, Robert Anderson, Mazen Ahdellatif, David Wiims and Daniel Clegg VA Medical Center Hines, Illinois
We recently analyzed data for a multi-hospital randomized clinical trial to evaluate the effectiveness of sulfasalazine compared to placebo for the treatment of ankylosing spondylitis (AS), Reiter’s syndrome (RS), and psoriatic arthritis @-%A). As the study was designed, the primary outcome measure was the percentage of treatment responders after nine months (i.e., the final time point). The statistical analysis was based on the &i-square test. The results indicated that sulfasalazine was ineffective for AS, possibly effective for RS and deiinitely effective for PsA.