9 resultados para item response theory

em DigitalCommons@The Texas Medical Center


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The Work Limitations Questionnaire (WLQ) is used to determine the amount of work loss and productivity which stem from certain health conditions, including rheumatoid arthritis and cancer. The questionnaire is currently scored using methodology from Classical Test Theory. Item Response Theory, on the other hand, is a theory based on analyzing item responses. This study wanted to determine the validity of using Item Response Theory (IRT), to analyze data from the WLQ. Item responses from 572 employed adults with dysthymia, major depressive disorder (MDD), double depressive disorder (both dysthymia and MDD), rheumatoid arthritis and healthy individuals were used to determine the validity of IRT (Adler et al., 2006).^ PARSCALE, which is IRT software from Scientific Software International, Inc., was used to calculate estimates of the work limitations based on item responses from the WLQ. These estimates, also known as ability estimates, were then correlated with the raw score estimates calculated from the sum of all the items responses. Concurrent validity, which claims a measurement is valid if the correlation between the new measurement and the valid measurement is greater or equal to .90, was used to determine the validity of IRT methodology for the WLQ. Ability estimates from IRT were found to be somewhat highly correlated with the raw scores from the WLQ (above .80). However, the only subscale which had a high enough correlation for IRT to be considered valid was the time management subscale (r = .90). All other subscales, mental/interpersonal, physical, and output, did not produce valid IRT ability estimates.^ An explanation for these lower than expected correlations can be explained by the outliers found in the sample. Also, acquiescent responding (AR) bias, which is caused by the tendency for people to respond the same way to every question on a questionnaire, and the multidimensionality of the questionnaire (the WLQ is composed of four dimensions and thus four different latent variables) probably had a major impact on the IRT estimates. Furthermore, it is possible that the mental/interpersonal dimension violated the monotonocity assumption of IRT causing PARSCALE to fail to run for these estimates. The monotonicity assumption needs to be checked for the mental/interpersonal dimension. Furthermore, the use of multidimensional IRT methods would most likely remove the AR bias and increase the validity of using IRT to analyze data from the WLQ.^

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This study proposed a novel statistical method that modeled the multiple outcomes and missing data process jointly using item response theory. This method follows the "intent-to-treat" principle in clinical trials and accounts for the correlation between outcomes and missing data process. This method may provide a good solution to chronic mental disorder study. ^ The simulation study demonstrated that if the true model is the proposed model with moderate or strong correlation, ignoring the within correlation may lead to overestimate of the treatment effect and result in more type I error than specified level. Even if the within correlation is small, the performance of proposed model is as good as naïve response model. Thus, the proposed model is robust for different correlation settings if the data is generated by the proposed model.^

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A subscale was developed to assess the quality of life of cancer patients with a life expectancy of six months or less. Phase I of this study identified the major concerns of 74 terminally ill cancer patients (19 with breast cancer, 19 with lung cancer, 18 with colorectal cancer, 9 with renal cell cancer, 9 with prostate cancer), 39 family caregivers, and 20 health care professionals. Patients interviewed were being treated at the University of Texas M. D. Anderson Cancer Center or at the Hospice at the Texas Medical Center in Houston. In Phase II, 120 patients (30 with breast cancer, 30 with lung cancer, 30 with colorectal cancer, 15 with prostate cancer, and 15 with renal cell cancer) rated the importance of these concerns for quality of life. Items retained for the subscale were rated as "extremely important" or "very important" by at least 60% of the sample and were reported as being applicable by at least two-thirds of the sample. The 61 concerns that were identified were formatted as a questionnaire for Phase III. In Phase III, 356 patients (89 with breast cancer, 88 with lung cancer, 88 with colorectal cancer, 44 with prostate cancer, and 47 with renal cell cancer) were interviewed to determine the subscale's reliability and sensitivity to change in clinical status. Both factor analysis and item response theory supported the inclusion of the same 35 items for the subscale. Internal consistency reliability was moderate to high for the subscale's domains: spiritual (0.87), existential (0.76), medical care (0.68), symptoms (0.67), social/family (0.66), and emotional (0.61). Test-retest correlation coefficients also were high for the domains: social/family (0.86), emotional (0.83), medical care (0.83), spiritual (0.75), existential (0.75), and symptoms (0.81).^ In addition, concurrent validity was supported by the high correlation between the subscale's symptom domain and symptom items from the European Organization for Research and Treatment of Cancer (EORTC) scale (r = 0.74). Patients' functional status was assessed with the Eastern Cooperative Oncology Group (ECOG) Performance status rating. When ECOG categories were compared to subscale domains, patients who scored lower in functional status had lower scores in the spiritual, existential, social/family, and emotional domains. Patients who scored lower in physical well-being had higher scores in the symptom domain. Patient scores in the medical care domain were similar for each ECOG category. The results of this study support the subscale's use in assessing quality of life and the outcomes of palliative treatment for cancer patients in their last six months of life. ^

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It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

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Acute central nervous system (CNS) injuries such as spinal cord injury, traumatic brain injury, autoimmune encephalomyelitis, and ischemic stroke are associated with significant morbidity, mortality, and health care costs worldwide. Preliminary research has shown potential neuroprotection associated with adult tissue derived stem/progenitor cell based therapies. While initial research indicated that engraftment and transdifferentiation into neural cells could explain the observed benefit, the exact mechanism remains controversial. A second hypothesis details localized stem/progenitor cell engraftment with alteration of the loco-regional milieu; however, the limited rate of cell engraftment makes this theory less likely. There is a growing amount of preclinical data supporting the idea that, after intravenous injection, stem/progenitor cells interact with immunologic cells located in organ systems distant to the CNS, thereby altering the systemic immunologic/inflammatory response. Such distant cell "bioreactors" could modulate the observed post-injury pro-inflammatory environment and lead to neuroprotection. In this review, we discuss the current literature detailing the above mechanisms of action for adult stem/progenitor cell based therapies in the CNS.

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Background: Inflammation is implicated in the development of cancer related fatigue (CRF). However there is limited literature on the mediators of inflammation (namely), cytokines and their receptors, associated with clinically significant fatigue and response to treatment. Methods: We reviewed 37 advanced cancer patients with fatigue (≥4/10), who participated in two Randomized Controlled Trials, of anti-inflammatory agents (Thalidomide and Dexamethasone) for CRF. Responders showed improvement in FACIT-F subscale at the end of study (Day 15). Baseline patient characteristics and symptoms were assessed by FACIT-F, ESAS; serum cytokines [IL-1β and receptor antagonist (IL-1RA), IL-6, IL-6R, TNF-α and sTNF-R1 and R2, IL-8, IL-10, IL-17] levels measured by Luminex. Data were analyzed using principal component analysis (PCA) [reporting cumulative variance (variance) for the first four components] to determine their association with fatigue and response to treatment. Results: Females were 54%. Mean (SD) was as follows for age, 61(14); baseline FACIT (F) scores, 21.4(8.6); ESAS Fatigue item, 6.5(1.9); and FACIT-F change, 6.4(9.7); ESAS (fatigue) change, -2 (2.41). Baseline median in pg/mL for IL-6, TNF-α, IL-1β were 31.9; 18.9; 0.55, respectively. Change in IL-6 negatively correlated with change in FACIT-F scores (p=0.02). Baseline CRF (FACIT-F score) was associated with IL-6, IL-6R and IL-17, Variance = 78% whereas IL-10, IL-1RA, TNF-α and IL-1β were associated with improvement of CRF, Variance=74%. Conversely, IL-6 and IL-8 were associated with no improvement or worsening of CRF, Variance= 93%. Conclusions: Change in IL-6 negatively correlated with change in FACIT-F scores. IL-6, IL-6R and IL-17 are associated with CRF while IL-6 and IL-8 were associated with no improvement of CRF. Further studies are warranted confirm our findings.

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The research literature on adolescent pregnancy indicates a relationship between early prenatal care and positive pregnancy outcomes, yet fewer than half of pregnant teenagers seek prenatal care in the first trimester of pregnancy. Although social support theory speculates that there should be a relationship between support and health outcomes, available studies do not reflect the processes by which pregnant adolescents use their social resources in making decisions about their pregnancies. This study describes the processes by which the adolescent comes to accept the reality of her pregnancy.^ Drawing from the social-psychological theories of illness behavior and symbolic interactionism, this study examines the symptom diagnosis and help seeking behavior of the pregnant adolescent. This approach describes how the adolescent interprets events and draws conclusions based on her social reality.^ Interviews were conducted with ten young women, aged 15-17, who had recently delivered a first child. Onset of prenatal care ranged from the third month to the seventh month. None were married, and all but two lived with a parent. All but one were currently in school. Initial unstructured interviews were attempted to construe the modes of expression of the young women regarding the event of pregnancy. Subsequent interviews elicited the processes of recognition and explanation of symptoms of pregnancy.^ Analysis revealed a consistent natural history in the subjects' experiences as they come to accept the reality of pregnancy. Symptom appraisal and definition involves noticing changes in themselves, and evaluating and attempting to find suitable explanations for these symptoms. Lay consultation from friends and family aids in identifying the symptoms and to receive suggestions for treatment. It is at this point that prenatal care is usually initiated. Finally the young women describe the integration of pregnancy into their belief systems. ^

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An exact knowledge of the kinetic nature of the interaction between the stimulatory G protein (G$\sb{\rm s}$) and the adenylyl cyclase catalytic unit (C) is essential for interpreting the effects of Gs mutations and expression levels on cellular response to a wide variety of hormones, drugs, and neurotransmitters. In particular, insight as to the association of these proteins could lead to progress in tumor biology where single spontaneous mutations in G proteins have been associated with the formation of tumors (118). The question this work attempts to answer is whether the adenylyl cyclase activation by epinephrine stimulated $\beta\sb2$-adrenergic receptors occurs via G$\sb{\rm s}$ proteins by a G$\sb{\rm s}$ to C shuttle or G$\sb{\rm s}$-C precoupled mechanism. The two forms of activation are distinguishable by the effect of G$\sb{\rm s}$ levels on epinephrine stimulated EC50 values for cyclase activation.^ We have made stable transfectants of S49 cyc$\sp-$ cells with the gene for the $\alpha$ protein of G$\sb{\rm s}$ $(\alpha\sb{\rm s})$ which is under the control of the mouse mammary tumor virus LTR promoter (110). Expression of G$\sb{\rm s}\alpha$ was then controlled by incubation of the cells for various times with 5 $\mu$M dexamethasone. Expression of G$\sb{\rm s}\alpha$ led to the appearance of GTP shifts in the competitive binding of epinephrine with $\sp{125}$ICYP to the $\beta$-adrenergic receptors and to agonist dependent adenylyl cyclase activity. High expression of G$\sb{\rm s}\alpha$ resulted in lower EC50's for the adenylyl cyclase activity in response to epinephrine than did low expression. By kinetic modelling, this result is consistent with the existence of a shuttle mechanism for adenylyl cyclase activation by hormones.^ One item of concern that remains to be addressed is the extent to which activation of adenylyl cyclase occurs by a "pure" shuttle mechanism. Kinetic and biochemical experiments by other investigators have revealed that adenylyl cyclase activation, by hormones, may occur via a Gs-C precoupled mechanism (80, 94, 97). Activation of adenylyl cyclase, therefore, probably does not occur by either a pure "'Shuttle" or "Gs-C Precoupled" mechanism, but rather by a "Hybrid" mechanism. The extent to which either the shuttle or precoupled mechanism contributes to hormone stimulated adenylyl cyclase activity is the subject of on-going research. ^

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Group sequential methods and response adaptive randomization (RAR) procedures have been applied in clinical trials due to economical and ethical considerations. Group sequential methods are able to reduce the average sample size by inducing early stopping, but patients are equally allocated with half of chance to inferior arm. RAR procedures incline to allocate more patients to better arm; however it requires more sample size to obtain a certain power. This study intended to combine these two procedures. We applied the Bayesian decision theory approach to define our group sequential stopping rules and evaluated the operating characteristics under RAR setting. The results showed that Bayesian decision theory method was able to preserve the type I error rate as well as achieve a favorable power; further by comparing with the error spending function method, we concluded that Bayesian decision theory approach was more effective on reducing average sample size.^