Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

Evaluation of PRESAGE® dosimeters for brachytherapy sources and the 3D dosimetry and characterization of the new AgX100 125I seed model

With continuous new improvements in brachytherapy source designs and techniques, method of 3D dosimetry for treatment dose verifications would better ensure accurate patient radiotherapy treatment. This study was aimed to first evaluate the 3D dose distributions of the low-dose rate (LDR) Amersham 6711 OncoseedTM using PRESAGE® dosimeters to establish PRESAGE® as a suitable brachytherapy dosimeter. The new AgX100 125I seed model (Theragenics Corporation) was then characterized using PRESAGE® following the TG-43 protocol. PRESAGE® dosimeters are solid, polyurethane-based, 3D dosimeters doped with radiochromic leuco dyes that produce a linear optical density response to radiation dose. For this project, the radiochromic response in PRESAGE® was captured using optical-CT scanning (632 nm) and the final 3D dose matrix was reconstructed using the MATLAB software. An Amersham 6711 seed with an air-kerma strength of approximately 9 U was used to irradiate two dosimeters to 2 Gy and 11 Gy at 1 cm to evaluate dose rates in the r=1 cm to r=5 cm region. The dosimetry parameters were compared to the values published in the updated AAPM Report No. 51 (TG-43U1). An AgX100 seed with an air-kerma strength of about 6 U was used to irradiate two dosimeters to 3.6 Gy and 12.5 Gy at 1 cm. The dosimetry parameters for the AgX100 were compared to the values measured from previous Monte-Carlo and experimental studies. In general, the measured dose rate constant, anisotropy function, and radial dose function for the Amersham 6711 showed agreements better than 5% compared to consensus values in the r=1 to r=3 cm region. The dose rates and radial dose functions measured for the AgX100 agreed with the MCNPX and TLD-measured values within 3% in the r=1 to r=3 cm region. The measured anisotropy function in PRESAGE® showed relative differences of up to 9% with the MCNPX calculated values. It was determined that post-irradiation optical density change over several days was non-linear in different dose regions, and therefore the dose values in the r=4 to r=5 cm regions had higher uncertainty due to this effect. This study demonstrated that within the radial distance of 3 cm, brachytherapy dosimetry in PRESAGE® can be accurate within 5% as long as irradiation times are within 48 hours.

Endogenous nitric oxide regulates p53 signaling and DNA damage-induced apoptosis in melanoma cells

Nitric oxide is involved in a multitude of processes including regulation of vascular tone, neurotransmission, immunity, and cancer. Evidence suggests that nitric oxide exhibits anti-apoptotic activity in melanoma cells. Our laboratory showed that tumor expression of inducible nitric oxide synthase correlated strongly with poor survival in stage III and IV melanoma patients, suggesting an antagonistic role for nitric oxide in melanoma response to therapy. Therefore, the hypothesis that endogenously produced nitric oxide antagonizes chemotherapy-induced apoptosis was formed. Using cisplatin as a model for DNA damage in melanoma cell lines, the capacity of nitric oxide to regulate cell growth and apoptotic responses to cisplatin treatment was examined. The depletion of endogenously generated nitric oxide resulted in changes in cell cycle regulation and enhanced cisplatin-induced apoptosis in melanoma cells. Since nitric oxide was shown to be involved in the regulation of p53 stability, conformation and DNA binding activity, whether signaling through wild-type p53 in melanoma cells is regulated by nitric oxide was tested. Cisplatin-induced p53 accumulation and p21Waf1/Cip1/Sdi1 expression in nitric oxide-depleted melanoma cells were found to be strongly suppressed. When p53 binding to the p21Waf1/Cip1/Sdi1 promoter was examined, it was found that nitric oxide depletion significantly reduced the cisplatin-induced formation of p53-DNA complexes. These results suggest that nitric oxide is required for activation of wild-type p53 after DNA damage in melanoma cells. Finally, whether signaling through p53 controls melanoma response to DNA damage was examined. Transfection of a plasmid containing a dominant negative form of mutated p53 inhibited p21 Waf1/Cip1/Sdi1 expression and concomitantly enhanced apoptosis after cisplatin treatment. These data suggest that the induction of wild-type p53 protects melanoma cells against DNA damage via the up-regulation of p21 Waf1/Cip1/Sdi1. Together, these data strongly support the model that endogenous nitric oxide is required for p53 activation and p21Waf1/Cip1/Sdi1 expression after DNA damage, which can enhance melanoma resistance to therapy. Thus, in context of melanoma cells with wild-type p53 , low levels of endogenous constitutively-produced nitric oxide appear to facilitate the activation of p53 in response to DNA damage, thereby allowing for cell cycle arrest via p21Waf1/Cip1/Sdi1 induction, adequate DNA repair, and ultimately enhanced resistance to apoptosis. ^

Longitudinal categorical data analysis: A continuous -time Markov chain approach

In this dissertation, we propose a continuous-time Markov chain model to examine the longitudinal data that have three categories in the outcome variable. The advantage of this model is that it permits a different number of measurements for each subject and the duration between two consecutive time points of measurements can be irregular. Using the maximum likelihood principle, we can estimate the transition probability between two time points. By using the information provided by the independent variables, this model can also estimate the transition probability for each subject. The Monte Carlo simulation method will be used to investigate the goodness of model fitting compared with that obtained from other models. A public health example will be used to demonstrate the application of this method. ^