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.^

Analyzing left-truncated right-censored data with uncertain onset time with parametric models

Prevalent sampling is an efficient and focused approach to the study of the natural history of disease. Right-censored time-to-event data observed from prospective prevalent cohort studies are often subject to left-truncated sampling. Left-truncated samples are not randomly selected from the population of interest and have a selection bias. Extensive studies have focused on estimating the unbiased distribution given left-truncated samples. However, in many applications, the exact date of disease onset was not observed. For example, in an HIV infection study, the exact HIV infection time is not observable. However, it is known that the HIV infection date occurred between two observable dates. Meeting these challenges motivated our study. We propose parametric models to estimate the unbiased distribution of left-truncated, right-censored time-to-event data with uncertain onset times. We first consider data from a length-biased sampling, a specific case in left-truncated samplings. Then we extend the proposed method to general left-truncated sampling. With a parametric model, we construct the full likelihood, given a biased sample with unobservable onset of disease. The parameters are estimated through the maximization of the constructed likelihood by adjusting the selection bias and unobservable exact onset. Simulations are conducted to evaluate the finite sample performance of the proposed methods. We apply the proposed method to an HIV infection study, estimating the unbiased survival function and covariance coefficients. ^

Assessing the patterns of colorectal cancer treatment, adherence to treatment guidelines and survival in Texas

Colorectal cancer (CRC) is the third leading cancer in both incidence and mortality in Texas. This study investigated the adherence of CRC treatment to standard treatment guidelines and the association between standard treatment and CRC survival in Texas. The author used Texas Cancer Registry (TCR) and Medicare linked data to study the CRC treatment patterns and factors associated with standard treatment in patients who were more than 65 years old and were diagnosed in 2001 through 2007. We also determined whether adherence to standard treatment affect patients' survival. Multiple logistic regression and Cox regression analysis were used to analyze our data. Both regression models are adjusted for demographic characteristics and tumor characteristics. We found that for the 3977 regional colon cancer patients 80 years old or younger, 60.2% of them received chemotherapy, in adherence to the recommended treatment guidelines. People with younger age, female gender, higher education and lower comorbidity score are more likely adherent to this surgery guideline. Patients' adherence to chemotherapy in this cohort have better survival compared to those who are not (HR: 0.76, 95% CI: 0.68-0.84). For the 12709 colon cancer patients treated with surgery, 49.3% have more than 12 lymph nodes removed, in adherence to the treatment guidelines. People with younger age, female gender, higher education, regional stage, lager tumor size and lower comorbidity score are more likely to adherent to this surgery guideline. Patients with more than 12 lymph nodes removed in this cohort have better survival (HR: 0.86, 95% CI: 0.82-0.91). For the 1211 regional rectal cancer patients 80 years old or younger, 63.2% of them were adherent to radiation treatment. People with smaller tumor size and lower comorbidity score are more likely to adherent to this radiation guideline. There is no significant survival difference between radiation adherent patients and non-adherent patients (HR: 1.03, 95% CI: 0.82-1.29). For the 1122 regional rectal cancer patients 80 years old or younger who were treated with surgery, 76.0% of them received postoperative chemotherapy, in adherence to the treatment guidelines. People with younger age and smaller comorbidity score are related with higher adherence rate. Patients adherent with adjuvant chemotherapy in this cohort have better survival than those were not adherent (HR: 0.60, 95% CI: 0.45-0.79).^

Modelling seed germination in forest tree species through survival analysis. The Pinus pinea L. case study

The direct application of existing models for seed germination may often be inadequate in the context of ecology and forestry germination experiments. This is because basic model assumptions are violated and variables available to forest managers are rarely used. In this paper, we present a method which addresses the aforementioned shortcomings. The approach is illustrated through a case study of Pinus pinea L. Our findings will also shed light on the role of germination in the general failure of natural regeneration in managed forests of this species. The presented technique consists of a mixed regression model based on survival analysis. Climate and stand covariates were tested. Data for fitting the model were gathered from a 5-year germination experiment in a mature, managed P. pinea stand in the Northern Plateau of Spain in which two different stand densities can be found. The model predictions proved to be unbiased and highly accurate when compared with the training data. Germination in P. pinea was controlled through thermal variables at stand level. At microsite level, low densities negatively affected the probability of germination. A time-lag in the response was also detected. Overall, the proposed technique provides a reliable alternative to germination modelling in ecology/forestry studies by using accessible/ suitable variables. The P. pinea case study highlights the importance of producing unbiased predictions. In this species, the occurrence and timing of germination suggest a very different regeneration strategy from that understood by forest managers until now, which may explain the high failure rate of natural regeneration in managed stands. In addition, these findings provide valuable information for the management of P. pinea under climate-change conditions.

Analysis of tape tether survival in LEO against orbital debris

The low earth orbit (LEO) environment contains a large number of artificial debris, of which a significant portion is due to dead satellites and fragments of satellites resulted from explosions and in-orbit collisions. Deorbiting defunct satellites at the end of their life can be achieved by a successful operation of an Electrodynamic Tether (EDT) system. The effectiveness of an EDT greatly depends on the survivability of the tether, which can become debris itself if cut by debris particles; a tether can be completely cut by debris having some minimal diameter. The objective of this paper is to develop an accurate model using power laws for debris-size ranges, in both ORDEM2000 and MASTER2009 debris flux models, to calculate tape tether survivability. The analytical model, which depends on tape dimensions (width, thickness) and orbital parameters (inclinations, altitudes) is then verified with fully numerical results to compare for different orbit inclinations, altitudes and tape width for both ORDEM2000 and MASTER2009 flux data.

A subset of skin tumor modifier loci determines survival time of tumor-bearing mice

Studies of mouse models of human cancer have established the existence of multiple tumor modifiers that influence parameters of cancer susceptibility such as tumor multiplicity, tumor size, or the probability of malignant progression. We have carried out an analysis of skin tumor susceptibility in interspecific Mus musculus/Mus spretus hybrid mice and have identified another seven loci showing either significant (six loci) or suggestive (one locus) linkage to tumor susceptibility or resistance. A specific search was carried out for skin tumor modifier loci associated with time of survival after development of a malignant tumor. A combination of resistance alleles at three markers [D6Mit15 (Skts12), D7Mit12 (Skts2), and D17Mit7 (Skts10)], all of which are close to or the same as loci associated with carcinoma incidence and/or papilloma multiplicity, is significantly associated with increased survival of mice with carcinomas, whereas the reverse combination of susceptibility alleles is significantly linked to early mortality caused by rapid carcinoma growth (χ2 = 25.22; P = 5.1 × 10−8). These data indicate that host genetic factors may be used to predict carcinoma growth rate and/or survival of individual backcross mice exposed to the same carcinogenic stimulus and suggest that mouse models may provide an approach to the identification of genetic modifiers of cancer survival in humans.

Regulation and localization of tyrosine216 phosphorylation of glycogen synthase kinase-3β in cellular and animal models of neuronal degeneration

Inactivation of glycogen synthase kinase-3β (GSK3β) by S9 phosphorylation is implicated in mechanisms of neuronal survival. Phosphorylation of a distinct site, Y216, on GSK3β is necessary for its activity; however, whether this site can be regulated in cells is unknown. Therefore we examined the regulation of Y216 phosphorylation on GSK3β in models of neurodegeneration. Nerve growth factor withdrawal from differentiated PC12 cells and staurosporine treatment of SH-SY5Y cells led to increased phosphorylation at Y216, GSK3β activity, and cell death. Lithium and insulin, agents that lead to inhibition of GSK3β and adenoviral-mediated transduction of dominant negative GSK3β constructs, prevented cell death by the proapoptotic stimuli. Inhibitors induced S9 phosphorylation and inactivation of GSK3β but did not affect Y216 phosphorylation, suggesting that S9 phosphorylation is sufficient to override GSK3β activation by Y216 phosphorylation. Under the conditions examined, increased Y216 phosphorylation on GSK3β was not an autophosphorylation response. In resting cells, Y216 phosphorylation was restricted to GSK3β present at focal adhesion sites. However, after staurosporine, a dramatic alteration in the immunolocalization pattern was observed, and Y216-phosphorylated GSK3β selectively increased within the nucleus. In rats, Y216 phosphorylation was increased in degenerating cortical neurons induced by ischemia. Taken together, these results suggest that Y216 phosphorylation of GSK3β represents an important mechanism by which cellular insults can lead to neuronal death.

Retinoic acid (RA) and As2O3 treatment in transgenic models of acute promyelocytic leukemia (APL) unravel the distinct nature of the leukemogenic process induced by the PML-RARα and PLZF-RARα oncoproteins

Acute promyelocytic leukemia (APL) is associated with chromosomal translocations always involving the RARα gene, which variably fuses to one of several distinct loci, including PML or PLZF (X genes) in t(15;17) or t(11;17), respectively. APL in patients harboring t(15;17) responds well to retinoic acid (RA) treatment and chemotherapy, whereas t(11;17) APL responds poorly to both treatments, thus defining a distinct syndrome. Here, we show that RA, As2O3, and RA + As2O3 prolonged survival in either leukemic PML-RARα transgenic mice or nude mice transplanted with PML-RARα leukemic cells. RA + As2O3 prolonged survival compared with treatment with either drug alone. In contrast, neither in PLZF-RARα transgenic mice nor in nude mice transplanted with PLZF-RARα cells did any of the three regimens induce complete disease remission. Unexpectedly, therapeutic doses of RA and RA + As2O3 can induce, both in vivo and in vitro, the degradation of either PML-RARα or PLZF-RARα proteins, suggesting that the maintenance of the leukemic phenotype depends on the continuous presence of the former, but not the latter. Our findings lead to three major conclusions with relevant therapeutic implications: (i) the X-RARα oncoprotein directly determines response to treatment and plays a distinct role in the maintenance of the malignant phenotype; (ii) As2O3 and/or As2O3 + RA combination may be beneficial for the treatment of t(15;17) APL but not for t(11;17) APL; and (iii) therapeutic strategies aimed solely at degrading the X-RARα oncoprotein may not be effective in t(11;17) APL.

Anti-PSCA mAbs inhibit tumor growth and metastasis formation and prolong the survival of mice bearing human prostate cancer xenografts

Prostate stem-cell antigen (PSCA) is a cell-surface antigen expressed in normal prostate and overexpressed in prostate cancer tissues. PSCA expression is detected in over 80% of patients with local disease, and elevated levels of PSCA are correlated with increased tumor stage, grade, and androgen independence, including high expression in bone metastases. We evaluated the therapeutic efficacy of anti-PSCA mAbs in human prostate cancer xenograft mouse models by using the androgen-dependent LAPC-9 xenograft and the androgen-independent recombinant cell line PC3-PSCA. Two different anti-PSCA mAbs, 1G8 (IgG1κ) and 3C5 (IgG2aκ), inhibited formation of s.c. and orthotopic xenograft tumors in a dose-dependent manner. Furthermore, administration of anti-PSCA mAbs led to retardation of established orthotopic tumor growth and inhibition of metastasis to distant sites, resulting in a significant prolongation in the survival of tumor-bearing mice. These studies suggest PSCA as an attractive target for immunotherapy and demonstrate the therapeutic potential of anti-PSCA mAbs for the treatment of local and metastatic prostate cancer.

Erythropoietin induces tumor regression and antitumor immune responses in murine myeloma models

Recombinant human erythropoietin (rHuEpo) has been used successfully in the treatment of cancer-related anemia. Clinical observations with several patients with multiple-myeloma treated with rHuEpo has shown, in addition to the improved quality of life, a longer survival than expected, considering the poor prognostic features of these patients. Based on these observations, we evaluated the potential biological effects of rHuEpo on the course of tumor progression by using murine myeloma models (MOPC-315-IgAλ2 and 5T33 MM-IgG2b). Here we report that daily treatment of MOPC-315 tumor-bearing mice with rHuEpo for several weeks induced complete tumor regression in 30–60% of mice. All regressors that were rechallenged with tumor cells rejected tumor growth, and this resistance was tumor specific. The Epo-triggered therapeutic effect was shown to be attributed to a T cell-mediated mechanism. Serum Ig analysis indicated a reduction in MOPC-315 λ light chain in regressor mice. Intradermal inoculation of 5T33 MM tumor cells followed by Epo treatment induced tumor regression in 60% of mice. The common clinical manifestation of myeloma bone disease in patients with multiple-myeloma was established in these myeloma models. Epo administration to these tumor-bearing mice markedly prolonged their survival and reduced mortality. Therefore, erythropoietin seems to act as an antitumor therapeutic agent in addition to its red blood cell-stimulating activity.

A joint hazard and time scaling model to compare survival curves.

To provide a more general method for comparing survival experience, we propose a model that independently scales both hazard and time dimensions. To test the curve shape similarity of two time-dependent hazards, h1(t) and h2(t), we apply the proposed hazard relationship, h12(tKt)/ h1(t) = Kh, to h1. This relationship doubly scales h1 by the constant hazard and time scale factors, Kh and Kt, producing a transformed hazard, h12, with the same underlying curve shape as h1. We optimize the match of h12 to h2 by adjusting Kh and Kt. The corresponding survival relationship S12(tKt) = [S1(t)]KtKh transforms S1 into a new curve S12 of the same underlying shape that can be matched to the original S2. We apply this model to the curves for regional and local breast cancer contained in the National Cancer Institute's End Results Registry (1950-1973). Scaling the original regional curves, h1 and S1 with Kt = 1.769 and Kh = 0.263 produces transformed curves h12 and S12 that display congruence with the respective local curves, h2 and S2. This similarity of curve shapes suggests the application of the more complete curve shapes for regional disease as templates to predict the long-term survival pattern for local disease. By extension, this similarity raises the possibility of scaling early data for clinical trial curves according to templates of registry or previous trial curves, projecting long-term outcomes and reducing costs. The proposed model includes as special cases the widely used proportional hazards (Kt = 1) and accelerated life (KtKh = 1) models.

Disentangling the impact of seroconversion age and set-point viral load on ART-free HIV survival

Thesis (Master's)--University of Washington, 2016-06

Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

Estimates of sex- and age-class-specific survival probabilities for a southern Great Barrier Reef green sea turtle population

Sex- and age-class-specific survival probabilities of a southern Great Barrier Reef green sea turtle population were estimated using a capture - mark - recapture (CMR) study and a Cormack - Jolly - Seber (CJS) modelling approach. The CMR history profiles for 954 individual turtles tagged over a 9-year period ( 1984 - 1992) were classified into three age classes ( adult, subadult, juvenile) based on somatic growth and reproductive traits. Reduced-parameter CJS models, accounting for constant survival and time-specific recapture, fitted best for all age classes. There were no significant sex-specific differences in either survival or recapture probabilities for any age class. Mean annual adult survival was estimated at 0.9482 (95% CI: 0.92 - 0.98) and was significantly higher than survival for either subadults or juveniles. Mean annual subadult survival was 0.8474 ( 95% CI: 0.79 - 0.91), which was not significantly different from mean annual juvenile survival estimated at 0.8804 ( 95% CI: 0.84 - 0.93). The time-specific adult recapture probabilities were a function of sampling effort but this was not the case for either juveniles or subadults. The sampling effort effect was accounted for explicitly in the estimation of adult survival and recapture probabilities. These are the first comprehensive sex- and age-class-specific survival and recapture probability estimates for a green sea turtle population derived from a long-term CMR program.

Hypoxic/ischemic models in newborn piglet: Comparison of constant FiO(2) versus variable FiO(2) delivery

A comparison of a constant (continuous delivery of 4% FiO(2)) and a variable (initial 5% FiO(2) with adjustments to induce low amplitude EEG (LAEEG) and hypotension) hypoxic/ischemic insult was performed to determine which insult was more effective in producing a consistent degree of survivable neuropathological damage in a newborn piglet model of perinatal asphyxia. We also examined which physiological responses contributed to this outcome. Thirty-nine 1-day-old piglets were subjected to either a constant hypoxic/ischemic insult of 30- to 37-min duration or a variable hypoxic/ischemic insult of 30-min low peak amplitude EEG (LAEEG < 5 mu V) including 10 min of low mean arterial blood pressure (MABP < 70% of baseline). Control animals (n = 6) received 21% FiO(2) for the duration of the experiment. At 72 h, the piglets were euthanased, their brains removed and fixed in 4% paraformaldehyde and assessed for hypoxic/ischemic injury by histological analysis. Based on neuropathology scores, piglets were grouped as undamaged or damaged; piglets that did not survive to 72 h were grouped separately as dead. The variable insult resulted in a greater number of piglets with neuropathological damage (undamaged = 12.5%, damaged = 68.75%, dead = 18.75%) while the constant insult resulted in a large proportion of undamaged piglets (undamaged = 50%, damaged = 22.2%, dead = 27.8%). A hypoxic insult varied to maintain peak amplitude EEG < 5 mu V results in a greater number of survivors with a consistent degree of neuropathological damage than a constant hypoxic insult. Physiological variables MABP, LAEEG, pH and arterial base excess were found to be significantly associated with neuropathological outcome. (c) 2006 Elsevier B.V. All rights reserved.