Simulation study of joint transition and Weibull survival model with shared parameters

This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^

Estimating parameters in Markov models for longitudinal studies with missing data or surrogate outcomes

The discrete-time Markov chain is commonly used in describing changes of health states for chronic diseases in a longitudinal study. Statistical inferences on comparing treatment effects or on finding determinants of disease progression usually require estimation of transition probabilities. In many situations when the outcome data have some missing observations or the variable of interest (called a latent variable) can not be measured directly, the estimation of transition probabilities becomes more complicated. In the latter case, a surrogate variable that is easier to access and can gauge the characteristics of the latent one is usually used for data analysis. ^ This dissertation research proposes methods to analyze longitudinal data (1) that have categorical outcome with missing observations or (2) that use complete or incomplete surrogate observations to analyze the categorical latent outcome. For (1), different missing mechanisms were considered for empirical studies using methods that include EM algorithm, Monte Carlo EM and a procedure that is not a data augmentation method. For (2), the hidden Markov model with the forward-backward procedure was applied for parameter estimation. This method was also extended to cover the computation of standard errors. The proposed methods were demonstrated by the Schizophrenia example. The relevance of public health, the strength and limitations, and possible future research were also discussed. ^

An ordinal logistic regression model with misclassification of the outcome variable and categorical covariate

Ordinal outcomes are frequently employed in diagnosis and clinical trials. Clinical trials of Alzheimer's disease (AD) treatments are a case in point using the status of mild, moderate or severe disease as outcome measures. As in many other outcome oriented studies, the disease status may be misclassified. This study estimates the extent of misclassification in an ordinal outcome such as disease status. Also, this study estimates the extent of misclassification of a predictor variable such as genotype status. An ordinal logistic regression model is commonly used to model the relationship between disease status, the effect of treatment, and other predictive factors. A simulation study was done. First, data based on a set of hypothetical parameters and hypothetical rates of misclassification was created. Next, the maximum likelihood method was employed to generate likelihood equations accounting for misclassification. The Nelder-Mead Simplex method was used to solve for the misclassification and model parameters. Finally, this method was applied to an AD dataset to detect the amount of misclassification present. The estimates of the ordinal regression model parameters were close to the hypothetical parameters. β1 was hypothesized at 0.50 and the mean estimate was 0.488, β2 was hypothesized at 0.04 and the mean of the estimates was 0.04. Although the estimates for the rates of misclassification of X1 were not as close as β1 and β2, they validate this method. X 1 0-1 misclassification was hypothesized as 2.98% and the mean of the simulated estimates was 1.54% and, in the best case, the misclassification of k from high to medium was hypothesized at 4.87% and had a sample mean of 3.62%. In the AD dataset, the estimate for the odds ratio of X 1 of having both copies of the APOE 4 allele changed from an estimate of 1.377 to an estimate 1.418, demonstrating that the estimates of the odds ratio changed when the analysis includes adjustment for misclassification. ^

Biomarker circadian rhythm profiles in critically ill mechanically ventilated patients

Objective: To explore the natural trajectory of core body temperature (CBT) and cortisol (CORT) circadian rhythms in mechanically ventilated intensive care unit (MV ICU) patients. ^ Design: Prospective, observational, time-series pilot study. ^ Setting: Medical-surgical and pulmonary ICUs in a tertiary care hospital. ^ Sample: Nine (F = 3, M = 6) adults who were mechanically ventilated within 12 hrs of ICU admission with mean ± SD age of 65.2 ± 14 years old. ^ Measurements: Core body temperature and environmental measures of light, sound, temperature, and relative humidity were logged in 1-min intervals. Hourly urine specimens and 2-hr interval blood specimens were collected for up to 7 consecutive days for CORT assay. Mechanical ventilation days, ICU length of stay, and ICU mortality were documented. Acute Physiology and Chronic Health Evaluation (APACHE) II scores were computed for each study day. The data of each biologic and environmental variable were analyzed using single cosinor analysis of 24-hr serial segments. One patient did not complete the study because mortality occurred within 8 hrs of enrollment. Nine ICU patients completed the study in 1.6 to 7.0 days. ^ Results: No normal circadian rhythm pattern was found when the cosinor-derived parameters of amplitude (one-half the peak-trough variability) and acrophase (peak time) were compared with cosinor-derived parameter reference ranges of healthy, diurnally active humans, although 83% of patient-day CBT segments showed statistically significant (p ≤ .05) and biologically meaningful (R2≥ 0.30) 24-hr rhythms with abnormal cosinor parameters. Cosinor parameters of the environmental temporal profiles showed 27% of light, 76% of ambient temperature, and 78% of relative humidity serial segments had a significant and meaningful 24-hr diurnal pattern. Average daily light intensity varied from 34 to 187 lx with a maximum light exposure of 1877 lx. No sound measurement segment had a statistically significant cosine pattern, and numerous 1-minute interval peaks ≥ 60 dB occurred around the clock. Average daily ambient temperature and relative humidity varied from 19 to 24°C and from 25% to 61%, respectively. There was no statistically significant association between CBT or clinical outcomes and cosinor-derived parameters of the environmental variables. Circadian rhythms of urine and plasma CORT were deferred for later analysis. ^ Conclusions: The natural trajectory of the CBT circadian rhythm in MV ICU patients demonstrated persistent cosinor parameter alteration, even when a significant and meaningful 24-hr rhythm was present. The ICU environmental measures showed erratic light and sound exposures. Room temperature and relative humidity data produced the highest rate of significant and meaningful diurnal 24-hr patterns. Additional research is needed to clarify relations among the CBT biomarker of the circadian clock and environmental variables of MV ICU patients. ^

Circadian rhythm profiles in porcine ICU subjects

Purpose: To explore the natural trajectory of circadian rhythms of sedation requirement, core body temperature (CBT), pulmonary mechanics (PM), and gas exchange (GE) in mechanically ventilated swine, as these variables affect the duration of mechanical ventilation. ^ Design: A secondary analysis to describe and compare circadian rhythms of study variables in swine mechanically ventilated for ≤ 7 days. ^ Setting: Porcine Intensive Care Unit (ICU).^ Sample: Six male swine. ^ Methods: Sedation requirements were recorded hourly and the CBT, PM and GE variables were sampled every 1 s – 1 min for ≤ 7 days. The data sets for each pig with > 5 days ICU length of stay were divided into one section representing the first 3 days and one section representing subsequent days. The Lomb periodogram was used to estimate the circadian time period for each variable, and cosinor analysis with the estimated time period to obtain amplitude and mesor. Circadian to ultradian bandpower ratio to assess rhythm quality and stability over time and goodness-of-fit index to describe biological significance of a rhythm were used. Together, these two parameters were used to define rhythm robustness over time. The masking effect of sedation as a potential confounder of the circadian rhythms of CBT, PM, and GE was explored, and circadian rhythm profiles of CBT of pigs in the ICU setting were compared with those of the same pigs in the ambulatory setting. ^ Results: All pigs had significant rhythms in CBT, respiratory rate, and peripheral oxygen saturation across ICU data sets. Healthier pigs had more robust rhythms of study variables over time. Sedation did not appear to mask the circadian rhythms of CBT, PM, and GE. The circadian rhythm of CBT was less robust in the ICU setting than in the ambulatory setting. ^ Conclusions: Individual subject observations provided preliminary evidence that robustness of rhythms varies with subject acuity. Comparison of profiles of circadian rhythms among ICU subjects with similar acuity and disease processes is warranted to determine if the profiles in the present study are reproducible. Identification of consistent patterns may provide insight into subject morbidity and timing of such therapeutic interventions as weaning from mechanical ventilation. ^

A simulation study of the standard design, the rolling six design, the CRM, and the modified CRM in Phase I clinical trials

The Phase I clinical trial is considered the "first in human" study in medical research to examine the toxicity of a new agent. It determines the maximum tolerable dose (MTD) of a new agent, i.e., the highest dose in which toxicity is still acceptable. Several phase I clinical trial designs have been proposed in the past 30 years. The well known standard method, so called the 3+3 design, is widely accepted by clinicians since it is the easiest to implement and it does not need a statistical calculation. Continual reassessment method (CRM), a design uses Bayesian method, has been rising in popularity in the last two decades. Several variants of the CRM design have also been suggested in numerous statistical literatures. Rolling six is a new method introduced in pediatric oncology in 2008, which claims to shorten the trial duration as compared to the 3+3 design. The goal of the present research was to simulate clinical trials and compare these phase I clinical trial designs. Patient population was created by discrete event simulation (DES) method. The characteristics of the patients were generated by several distributions with the parameters derived from a historical phase I clinical trial data review. Patients were then selected and enrolled in clinical trials, each of which uses the 3+3 design, the rolling six, or the CRM design. Five scenarios of dose-toxicity relationship were used to compare the performance of the phase I clinical trial designs. One thousand trials were simulated per phase I clinical trial design per dose-toxicity scenario. The results showed the rolling six design was not superior to the 3+3 design in terms of trial duration. The time to trial completion was comparable between the rolling six and the 3+3 design. However, they both shorten the duration as compared to the two CRM designs. Both CRMs were superior to the 3+3 design and the rolling six in accuracy of MTD estimation. The 3+3 design and rolling six tended to assign more patients to undesired lower dose levels. The toxicities were slightly greater in the CRMs.^

Adaptive clinical trial design for targeted therapy development

The development of targeted therapy involve many challenges. Our study will address some of the key issues involved in biomarker identification and clinical trial design. In our study, we propose two biomarker selection methods, and then apply them in two different clinical trial designs for targeted therapy development. In particular, we propose a Bayesian two-step lasso procedure for biomarker selection in the proportional hazards model in Chapter 2. In the first step of this strategy, we use the Bayesian group lasso to identify the important marker groups, wherein each group contains the main effect of a single marker and its interactions with treatments. In the second step, we zoom in to select each individual marker and the interactions between markers and treatments in order to identify prognostic or predictive markers using the Bayesian adaptive lasso. In Chapter 3, we propose a Bayesian two-stage adaptive design for targeted therapy development while implementing the variable selection method given in Chapter 2. In Chapter 4, we proposed an alternate frequentist adaptive randomization strategy for situations where a large number of biomarkers need to be incorporated in the study design. We also propose a new adaptive randomization rule, which takes into account the variations associated with the point estimates of survival times. In all of our designs, we seek to identify the key markers that are either prognostic or predictive with respect to treatment. We are going to use extensive simulation to evaluate the operating characteristics of our methods.^

Petrological parameters of sands and sandstones from DSDP and ODP holes in arc-related areas

Detrital modes for 524 deep-marine sand and sandstone samples recovered on circum-Pacific, Caribbean, and Mediterranean legs of the Deep Sea Drilling Project and the Ocean Drilling Program form the basis for an actualistic model for arc-related provenance. This model refines the Dickinson and Suczek (1979) and Dickinson and others (1983) models and can be used to interpret the provenance/tectonic history of ancient arc-related sedimentary sequences. Four provenance groups are defined using QFL, QmKP, LmLvLs, and LvfLvmiLvl ternary plots of site means: (1) intraoceanic arc and remnant arc, (2) continental arc, (3) triple junction, and (4) strike-slip-continental arc. Intraoceanic- and remnant-arc sands are poor in quartz (mean QFL%Q < 5) and rich in lithics (QFL%L > 75); they are predominantly composed of plagioclase feldspar and volcanic lithic fragments. Continental-arc sand can be more quartzofeldspathic than the intraoceanic- and remnant-arc sand (mean QFL%Q values as much as 10, mean QFL%F values as much as 65, and mean QmKP%Qm as much as 20) and has more variable lithic populations, with minor metamorphic and sedimentary components. The triple-junction and strike-slip-continental groups compositionally overlap; both are more quartzofeldspathic than the other groups and show highly variable lithic proportions, but the strike-slip-continental group is more quartzose. Modal compositions of the triple junction group roughly correlate with the QFL transitional-arc field of Dickinson and others (1983), whereas the strike-slip-continental group approximately correlates with their dissected-arc field.

Evaluación de clones de Populus spp., a los dos años de edad, en dos micrositios de la región pampeana, Argentina

La producción de álamos en la pampa ondulada de la provincia de Buenos Aires podría constituir una actividad alternativa y/o complementaria, debido a zonas ecológicas favorables para su cultivo. En este contexto es importante conocer el comportamiento de los clones en los diversos ambientes para poder definir cuáles de ellos podrían presentar mayor estabilidad para los diferentes sitios. El objetivo del trabajo fue estudiar la interacción existente entre los parámetros de crecimiento y supervivencia de 16 clones de Populus spp. en dos micrositios geomorfológicamente diferentes en la región pampeana, Argentina. Los clones en estudio provienen de cruzamientos intraespecíficos de P. deltoides e interespecíficos de P. deltoides x P. nigra (Populus x canadensis). Se plantaron en dos ensayos, uno por cada situación geomórfica: loma y bajo, y se completó con un análisis estadístico comparando los ensayos en forma individual y conjunta. Cada ensayo se instaló con un diseño de bloques completos al azar. Las variables analizadas fueron la supervivencia, la altura media y el área basal al concluir el segundo año de crecimiento. Para el sitio regional evaluado, la interacción entre los clones y los micrositios fue significativa para las variables altura y supervivencia. La mayor disponibilidad de agua en el micrositio bajo produjo mayores crecimientos clonales con diferencias significativas respecto del micrositio loma. La estabilidad de los atributos de supervivencia y crecimiento frente a los micrositios es un objetivo fundamental en las plantaciones clonales. Siendo los micrositios una realidad ambiental importante, propia como variable no controlable, la reducción de la variabilidad de respuesta ante ellos permitiría la constitución de unidades de manejo más homogéneas.

Colony-specific investigations reveal highly variable responses among individual corals to ocean acidification and warming

As anthropogenic climate change is an ongoing concern, scientific investigations on its impacts on coral reefs are increasing. Although impacts of combined ocean acidification (OA) and temperature stress (T) on reef-building scleractinian corals have been studied at the genus, species and population levels, there are little data available on how individual corals respond to combined OA and anomalous temperatures. In this study, we exposed individual colonies of Acropora digitifera, Montipora digitata and Porites cylindrica to four pCO2-temperature treatments including 400 µatm-28 °C, 400 µatm-31 °C, 1000 µatm-28 °C and 1000 µatm-31 °C for 26 days. Physiological parameters including calcification, protein content, maximum photosynthetic efficiency, Symbiodinium density, and chlorophyll content along with Symbiodinium type of each colony were examined. Along with intercolonial responses, responses of individual colonies versus pooled data to the treatments were investigated. The main results were: 1) responses to either OA or T or their combination were different between individual colonies when considering physiological functions; 2) tolerance to either OA or T was not synonymous with tolerance to the other parameter; 3) tolerance to both OA and T did not necessarily lead to tolerance of OA and T combined (OAT) at the same time; 4) OAT had negative, positive or no impacts on physiological functions of coral colonies; and 5) pooled data were not representative of responses of all individual colonies. Indeed, the pooled data obscured actual responses of individual colonies or presented a response that was not observed in any individual. From the results of this study we recommend improving experimental designs of studies investigating physiological responses of corals to climate change by complementing them with colony-specific examinations.

Magnetic hysteresis parameters of ODP Site 178-1096 (Table T1)

During Ocean Drilling Program (ODP) Leg 178, we drilled three sites on sediment drifts deposited on the continental rise on the western margin of the Antarctic Peninsula. These hemipelagic drifts were targeted for their potential to preserve a continuous record of the behavior of the West Antarctic Ice Sheet over the last 10 m.y. It has been proposed that drift development is linked to advances and retreats of the Antarctic continental ice sheet (Pudsey and Camerlenghi, 1998, doi:10.1017/S0954102098000376, and references therein; Barker, Camerlenghi, Acton, et al., 1999, doi:10.2973/odp.proc.ir.178.1999). However, the sediment is characterized by a very low carbonate content, with foraminifers restricted to very narrow intervals. This lack of carbonate precludes the construction of a delta18O or CaCO3 stratigraphy, depriving these sites of an important chronologic tool and global ice volume proxy.

Global Ocean Particulate Organic Carbon flux merged with satellite parameters

The efficiency of the biological pump of carbon to the deep ocean depends largely on the biologically mediated export of carbon from the surface ocean and its remineralization with depth. Global satellite studies have primarily focused on chlorophyll concentration and net primary production (NPP) to understand the role of phytoplankton in these processes. Recent satellite retrievals of phytoplankton composition now allow for the size of phytoplankton cells to be considered. Here, we improve understanding of phytoplankton size structure impacts on particle export, remineralization and transfer. Particulate organic carbon (POC) flux observations from sediment traps and 234Th are compiled across the global ocean. Annual climatologies of NPP, percent microplankton, and POC flux at four time series locations and within biogeochemical provinces are constructed, and sinking velocities are calculated to align surface variables with POC flux at depth. Parameters that characterize POC flux vs. depth (export flux ratio, labile fraction, remineralization length scale) are then fit to the aligned dataset. Times of the year dominated by different size compositions are identified and fit separately in regions of the ocean where phytoplankton cell size showed enough dynamic range over the annual cycle. Considering all data together, our findings support the paradigm of high export flux but low transfer efficiency in more productive regions and vice versa for oligotrophic regions. However, when parsing by dominant size class, we find periods dominated by small cells to have both greater export flux and lower transfer efficiency than periods when large cells comprise a greater proportion of the phytoplankton community.

Phytoplankton composition and biomass and its fluorescence parameters in waters of the Nha Trang Bay, South China Sea

Species composition and abundance of phytoplankton and chlorophyll concentration were measured at three horizons of 9 stations in the Nha Trang Bay of the South China Sea in March 1998. Vertical distribution of fluorescence parameters, temperature and irradiance were measured in the 0-18 m layer of the water column at 21 stations. It was shown that according to biomass (B) and chlorophyll concentration (Chl) the Bay is mezotrophic. B and Chl in the water column increased seaward. Mean values of Chl in the southern part of the Bay exceeded those in northern part. Mean values of B were similar. B and Chl in the bottom layer exceeded ones in the upper layer. Diatoms dominated in species diversity and abundance. Diatom Guinardia striata made the main contribution to phytoplankton biomass. Similarity of phytoplankton was high. In the upper layer phytoplankton was photoinhibited during the most part of the light period, but at the bottom photosynthetic activity was high. Water column B varied in an order of magnitude during the daily cycle mainly because of B variations in the bottom layer due to tide flow.

Natural fluctuations and gradients in the experimental design:research bias in the field of ocean acidification

These data form the basis of an analysis of a prevalent research bias in the field of ocean acidification, notably the ignoring of natural fluctuations and gradients in the experimental design. The data are extracted from published work and own experiments.