131 research outputs found

    Uncertainty in Semantic Schema Integration

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    In this paper we present a new method of semantic schema integration, based on uncertain semantic mappings. The purpose of semantic schema integration is to produce a unified representation of multiple data sources. First, schema matching is performed to identify the semantic mappings between the schema objects. Then, an integrated schema is produced during the schema merging process based on the identified mappings. If all semantic mappings are known, schema merging can be performed (semi-)automatically

    Using joint models to study the association between CD4 count and the risk of death in TB/HIV data

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    BACKGROUND: The association structure linking the longitudinal and survival sub-models is of fundamental importance in the joint modeling framework and the choice of this structure should be made based on the clinical background of the study. However, this information may not always be accessible and rationale for selecting this association structure has received relatively little attention in the literature. To this end, we aim to explore four alternative functional forms of the association structure between the CD4 count and the risk of death and provide rationale for selecting the optimal association structure for our data. We also aim to compare the results obtained from the joint model to those obtained from the time-varying Cox model. METHODS: We used data from the Centre for the AIDS Programme of Research in South Africa (CAPRISA) AIDS Treatment programme, the Starting Antiretroviral Therapy at Three Points in Tuberculosis (SAPiT) study, an open-label, three armed randomised, controlled trial between June 2005 and July 2010 (N=642). In our analysis, we combined the early and late integrated arms and compared results to the sequential arm. We utilized the Deviance Information Criterion (DIC) to select the final model with the best structure, with smaller values indicating better model adjustments to the data. RESULTS: Patient characteristics were similar across the study arms. Combined integrated therapy arms had a reduction of 55% in mortality (HR:0.45, 95% CI:0.28-0.72) compared to the sequential therapy arm. The joint model with a cumulative effects functional form was chosen as the best association structure. In particular, our joint model found that the area under the longitudinal profile of CD4 count was strongly associated with a 21% reduction in mortality (HR:0.79, 95% CI:0.72-0.86). Where as results from the time-varying Cox model showed a 19% reduction in mortality (HR:0.81, 95% CI:0.77-0.84). CONCLUSIONS: In this paper we have shown that the “current value” association structure is not always the best structure that expresses the correct relationship between the outcomes in all settings, which is why it is crucial to explore alternative clinically meaningful association structures that links the longitudinal and survival processes

    Fatigue after a first attack of suspected multiple sclerosis

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    Background: Fatigue is reported by more than 75% of multiple sclerosis (MS) patients. In an earlier study, we showed that fatigue is not only a common symptom in patien

    Sex-based differences in cardiovascular proteomic profiles and their associations with adverse outcomes in patients with chronic heart failure

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    BACKGROUND: Studies focusing on sex differences in circulating proteins in patients with heart failure with reduced ejection fraction (HFrEF) are scarce. Insight into sex-specific cardiovascular protein profiles and their associations with the risk of adverse outcomes may contribute to a better understanding of the pathophysiological processes involved in HFrEF. Moreover, it could provide a basis for the use of circulating protein measurements for prognostication in women and men, wherein the most relevant protein measurements are applied in each of the sexes. METHODS: In 382 patients with HFrEF, we performed tri-monthly blood sampling (median follow-up: 25 [13-31] months). We selected all baseline samples and two samples closest to the primary endpoint (PEP: composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization) or censoring. We then applied an aptamer-based multiplex proteomic assay identifying 1105 proteins previously associated with cardiovascular disease. We used linear regression models and gene-enrichment analysis to study sex-based differences in baseline levels. We used time-dependent Cox models to study differences in the prognostic value of serially measured proteins. All models were adjusted for the MAGGIC HF mortality risk score and p-values for multiple testing. RESULTS: In 104 women and 278 men (mean age 62 and 64 years, respectively) cumulative PEP incidence at 30 months was 25% and 35%, respectively. At baseline, 55 (5%) out of the 1105 proteins were significantly different between women and men. The female protein profile was most strongly associated with extracellular matrix organization, while the male profile was dominated by regulation of cell death. The association of endothelin-1 (Pinteraction < 0.001) and somatostatin (Pinteraction = 0.040) with the PEP was modified by sex, independent of clinical characteristics. Endothelin-1 was more strongly associated with the PEP in men (HR 2.62 [95%CI, 1.98, 3.46], p < 0.001) compared to women (1.14 [1.01, 1.29], p = 0.036). Somatostatin was positively associated with the PEP in men (1.23 [1.10, 1.38], p < 0.001), but inversely associated in women (0.33 [0.12, 0.93], p = 0.036). CONCLUSION: Baseline cardiovascular protein levels differ between women and men. However, the predictive value of repeatedly measured circulating proteins does not seem to differ except for endothelin-1 and somatostatin

    Joint modeling of longitudinal markers and time-to-event outcomes: an application and tutorial in patients after surgical repair of transposition of the great arteries

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    BACKGROUND: Most patients with congenital heart disease survive into adulthood; however, residual abnormalities remain and management of the patients is life-long and personalized. Patients with surgical repair of transposition of the great arteries, for example, face the risk to develop neoaortic valve regurgitation. Cardiologists update the prognosis of the patient intuitively with updated information of the cardiovascular status of the patient, for instance from echocardiographic imaging.METHODS: Usually a time-dependent version of the Cox model is used to analyze repeated measurements with a time-to-event outcome. New statistical methods have been developed with multiple advantages, of which the most prominent one being the joint model for longitudinal and time-to-event outcome. In this tutorial, the joint modeling framework is introduced and applied to patients with transposition of the great arteries after surgery with a long-term follow-up, where repeated echocardiographic values of the neoaortic root are evaluated against the risk of neoaortic valve regurgitation.RESULTS: The data are analyzed with the time-dependent Cox model as benchmark method, and the results are compared with a joint model, leading to different conclusions. The flexibility of the joint model is shown by adding the growth rate of the neoaortic root to the model and adding repeated values of body surface area to obtain a multimarker model. Lastly, it is demonstrated how the joint model can be used to obtain personalized dynamic predictions of the event.CONCLUSIONS: The joint model for longitudinal and time-to-event data is an attractive method to analyze data in follow-up studies with repeated measurements. Benefits of the method include using the estimated natural trajectory of the longitudinal outcome, great flexibility through multiple extensions, and dynamic individualized predictions.Development and application of statistical models for medical scientific researc

    Defining Optimal Health Range for Thyroid Function Based on the Risk of Cardiovascular Disease.

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    Reference ranges of thyroid-stimulating hormone (TSH) and free thyroxine (FT4) are defined by their distribution in apparently healthy populations (2.5th and 97.5th percentiles), irrespective of disease risk, and are used as cutoffs for defining and clinically managing thyroid dysfunction. To provide proof of concept in defining optimal health ranges of thyroid function based on cardiovascular disease (CVD) mortality risk. In all, 9233 participants from the Rotterdam Study (mean age, 65.0 years) were followed up (median, 8.8 years) from baseline to date of death or end of follow-up period (2012), whichever came first (689 cases of CVD mortality). We calculated 10-year absolute risks of CVD mortality (defined according to the SCORE project) using a Fine and Gray competing risk model per percentiles of TSH and FT4, modeled nonlinearly and with sex and age adjustments. Overall, FT4 level &gt;90th percentile was associated with a predicted 10-year CVD mortality risk &gt;7.5% (P = 0.005). In men, FT4 level &gt;97th percentile was associated with a risk of 10.8% (P &lt; 0.001). In participants aged ≄65 years, absolute risk estimates were &lt;10.0% below the 30th percentile (∌14.5 pmol/L or 1.10 ng/dL) and ≄15.0% above the 97th percentile of FT4 (∌22 pmol/L or 1.70 ng/dL). We describe absolute 10-year CVD mortality risks according to thyroid function (TSH and FT4) and suggest that optimal health ranges for thyroid function can be defined according to disease risk and are possibly sex and age dependent. These results need to be replicated with sufficient samples and representative populations

    A proof of principle for using adaptive testing in routine Outcome Monitoring: the efficiency of the Mood and Anxiety Symptoms Questionnaire -Anhedonic Depression CAT

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    <p>Abstract</p> <p>Background</p> <p>In Routine Outcome Monitoring (ROM) there is a high demand for short assessments. Computerized Adaptive Testing (CAT) is a promising method for efficient assessment. In this article, the efficiency of a CAT version of the Mood and Anxiety Symptom Questionnaire, - Anhedonic Depression scale (MASQ-AD) for use in ROM was scrutinized in a simulation study.</p> <p>Methods</p> <p>The responses of a large sample of patients (<it>N </it>= 3,597) obtained through ROM were used. The psychometric evaluation showed that the items met the requirements for CAT. In the simulations, CATs with several measurement precision requirements were run on the item responses as if they had been collected adaptively.</p> <p>Results</p> <p>CATs employing only a small number of items gave results which, both in terms of depression measurement and criterion validity, were only marginally different from the results of a full MASQ-AD assessment.</p> <p>Conclusions</p> <p>It was concluded that CAT improved the efficiency of the MASQ-AD questionnaire very much. The strengths and limitations of the application of CAT in ROM are discussed.</p

    Joint modeling of longitudinal outcomes and survival using latent growth modeling approach in a mesothelioma trial

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    Joint modeling of longitudinal and survival data can provide more efficient and less biased estimates of treatment effects through accounting for the associations between these two data types. Sponsors of oncology clinical trials routinely and increasingly include patient-reported outcome (PRO) instruments to evaluate the effect of treatment on symptoms, functioning, and quality of life. Known publications of these trials typically do not include jointly modeled analyses and results. We formulated several joint models based on a latent growth model for longitudinal PRO data and a Cox proportional hazards model for survival data. The longitudinal and survival components were linked through either a latent growth trajectory or shared random effects. We applied these models to data from a randomized phase III oncology clinical trial in mesothelioma. We compared the results derived under different model specifications and showed that the use of joint modeling may result in improved estimates of the overall treatment effect
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