66 research outputs found
Regression Modeling of Longitudinal Outcomes With Outcome-Dependent Observation Times
Conventional longitudinal data analysis methods typically assume that outcomes are independent of the data-collection schedule. However, the independence assumption may be violated when an event triggers outcome assessment in between prescheduled follow-up visits. For example, patients initiating warfarin therapy who experience poor anticoagulation control may have extra physician visits to monitor the impact of necessary dose changes. Observation times may therefore be associated with outcome values, which may introduce bias when estimating the effect of covariates on outcomes using standard longitudinal regression methods. We consider a joint model approach with two components: a semi-parametric regression model for longitudinal outcomes and a recurrent event model for observation times. The semi-parametric model includes a parametric specification for covariate effects, but allows the effect of time to be unspecified. We formulate a framework of outcome-observation dependence mechanisms to describe conditional independence between the outcome and observation-time processes given observed covariates or shared latent variables.
We generalize existing methods for continuous outcomes by accommodating any combination of mechanisms through the use of observation-level weights and/or patient-level latent variables. We develop new methods for binary outcomes, while retaining the flexibility of a semi-parametric approach. We extend these methods to account for discontinuous risk intervals in which patients enter and leave the at-risk set multiple times during the study. Our methods are based on counting process approaches, rather than relying on possibly intractable likelihood-based or pseudo-likelihood-based approaches, and provide marginal, population-level inference. In simulations, we evaluate the statistical properties of our proposed methods. Comparisons are made to `naive\u27 approaches that do not account for outcome-dependent observation times. We illustrate the utility of our proposed methods using data from a randomized trial of interventions designed to improve adherence to warfarin therapy and a randomized trial of malaria vaccines among children in Mali
Regression modeling of longitudinal binary outcomes with outcome-dependent observation times
Conventional longitudinal data analysis methods assume that outcomes are independent of the data-collection schedule. However, the independence assumption may be violated, for example, when adverse events trigger additional physician visits in between prescheduled follow-ups. Observation times may therefore be associated with outcome values, which may introduce bias when estimating the eect of covariates on outcomes using standard longitudinal regression methods. Existing semi-parametric methods that accommodate outcome-dependent observation times are limited to the analysis of continuous outcomes. We develop new methods for the analysis of binary outcomes, while retaining the exibility of semi-parametric models. Our methods are based on counting process approaches, rather than relying on possibly intractable likelihood-based or pseudo-likelihood-based approaches, and provide marginal, population-level inference. In simulations, we evaluate the statistical properties of our proposed methods. Comparisons are made to \u27naive\u27 GEE approaches that either do not account for outcome-dependent observation times or incorporate weights based on the observation-time process. We illustrate the utility of our proposed methods using data from a randomized controlled trial of interventions designed to improve adherence to warfarin therapy. We show that our method performs well in the presence of outcome-dependent observation times, and provide identical inference to \u27naive\u27 approaches when observation times are not associated with outcomes
Consumer Awareness and Acceptance of Aquaculture Practices and Products in Penang, Malaysia
High demand of seafood products combined with over-harvesting of wild catch aquatic products have elevated aquaculture as the alternative way to strike a balance between seafood product supply and demand. However, uncontrolled aquaculture activities are found to affect the environment negatively as well as the health of consumers. Better awareness and understanding can regulate aquaculture practices and bring about environmental health through consumers’ pressure on the aquaculture production system. This study aimed to identify consumers’ perception on aquaculture industry, to study consumers’ awareness on sustainability of aquaculture practice and also to find ways to increase consumers’ awareness and acceptance of sustainable aquaculture practice and its products. A mixed research method was used in this study combining quantitative questionnaire survey of respondents who bought aquaculture products at wet markets in Penang, and qualitative in-depth focus group discussions (FGDs) with a number of selected respondents. Research findings show that most of the respondents are aware that aquaculture might give lots of negative effects to human health and the environment but, they still chose to buy aquaculture products due to cheaper price than wild catch seafood products. Hence, from the findings, it is clear that even though people have awareness, they have little choice but to accept the quality of aquaculture products. However, the results also show that enhancing consumer awareness and understanding empowers consumers to put pressures on producers paving the way towards sustainable aquaculture and greater acceptance of aquaculture practices and products
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An Active Learning Approach for Rapid Characterization of Endothelial Cells in Human Tumors
Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers
Acute gastrointestinal and genitourinary toxicity of image-guided intensity modulated radiation therapy for prostate cancer using a daily water-filled endorectal balloon
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A phase I/II trial of hydroxychloroquine in conjunction with radiation therapy and concurrent and adjuvant temozolomide in patients with newly diagnosed glioblastoma multiforme
Preclinical studies indicate autophagy inhibition with hydroxychloroquine (HCQ) can augment the efficacy of DNA-damaging therapy. The primary objective of this trial was to determine the maximum tolerated dose (MTD) and efficacy of HCQ in combination with radiation therapy (RT) and temozolomide (TMZ) for newly diagnosed glioblastoma (GB). A 3 + 3 phase I trial design followed by a noncomparative phase II study was conducted in GB patients after initial resection. Patients received HCQ (200 to 800 mg oral daily) with RT and concurrent and adjuvant TMZ. Quantitative electron microscopy and immunoblotting were used to assess changes in autophagic vacuoles (AVs) in peripheral blood mononuclear cells (PBMC). Population pharmacokinetic (PK) modeling enabled PK-pharmacodynamic correlations. Sixteen phase I subjects were evaluable for dose-limiting toxicities. At 800 mg HCQ/d, 3/3 subjects experienced Grade 3 and 4 neutropenia and thrombocytopenia, 1 with sepsis. HCQ 600 mg/d was found to be the MTD in this combination. The phase II cohort (n = 76) had a median survival of 15.6 mos with survival rates at 12, 18, and 24 mo of 70%, 36%, and 25%. PK analysis indicated dose-proportional exposure for HCQ. Significant therapy-associated increases in AV and LC3-II were observed in PBMC and correlated with higher HCQ exposure. These data establish that autophagy inhibition is achievable with HCQ, but dose-limiting toxicity prevented escalation to higher doses of HCQ. At HCQ 600 mg/d, autophagy inhibition was not consistently achieved in patients treated with this regimen, and no significant improvement in overall survival was observed. Therefore, a definitive test of the role of autophagy inhibition in the adjuvant setting for glioma patients awaits the development of lower-toxicity compounds that can achieve more consistent inhibition of autophagy than HCQ
Chest radiography versus lung ultrasound for identification of acute respiratory distress syndrome: a retrospective observational study
Abstract Background Lung ultrasound may be a reasonable alternative to chest radiography for the identification of acute respiratory distress syndrome (ARDS), but the diagnostic performance of lung ultrasound for ARDS is uncertain. We therefore analyzed the clinical outcomes of ARDS diagnosed according to the Berlin Definition, using either chest radiography (Berlin-CXR) or lung ultrasound (Berlin-LUS) as an alternative imaging method. Methods This was a retrospective observational study in a 20-bed medical intensive care unit (ICU). Patients who required noninvasive ventilation or invasive ventilation for hypoxemic respiratory failure on ICU admission from August 2014 to March 2017 were included. Both chest radiography and lung ultrasound were performed routinely upon ICU admission. Comparisons were made using either the Berlin-CXR or Berlin-LUS definitions to diagnose ARDS with respect to the patient characteristics and clinical outcomes for each definition. ICU and hospital mortality were the main outcome measures for both definitions. Results The first admissions of 456 distinct patients were analyzed. Compared with the 216 patients who met the Berlin-CXR definition (ICU mortality 19.4%, hospital mortality 36.1%), 229 patients who met the Berlin-LUS definition (ICU mortality 22.7%, hospital mortality 34.5%) and 79 patients who met the Berlin-LUS but not the Berlin-CXR definition (ICU mortality 21.5%, hospital mortality 29.1%) had similar outcomes. In contrast, the 295 patients who met either definition had higher mortality than the 161 patients who did not meet either definition (ICU mortality 20.0% versus 12.4%, P = 0.041; hospital mortality 34.2% versus 24.2%, P = 0.027). Compared with Berlin-CXR, Berlin-LUS had a positive predictive value of 0.66 (95% confidence interval 0.59–0.72) and a negative predictive value of 0.71 (0.65–0.77). Among the 216 Berlin-CXR ARDS patients, 150 patients (69.4%) also fulfilled Berlin-LUS definition. Conclusions For the identification of ARDS using the Berlin definition, both chest radiography and lung ultrasound were equally related to mortality. The Berlin definition using lung ultrasound helped identify patients at higher risk of death, even if these patients did not fulfill the conventional Berlin definition using chest radiography. However, the moderate overlap of patients when chest imaging modalities differed suggests that chest radiography and lung ultrasound should be complementary rather than used interchangeably
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10.1111/medu.14333MEDICAL EDUCATION54111068-106
Kikuchi–Fujimoto Disease Post COVID-19 Vaccination: Case Report and Review of Literature
With the rapid development of various coronavirus disease 2019 (COVID-19) vaccines in a bid to counter and contain the COVID-19 pandemic, unusual and uncommon side effects of COVID-19 vaccination have been increasingly reported in the literature. Ipsilateral lymphadenopathy is a fairly common side effect of vaccination of any kind, with its etiology most commonly related to reactive lymphadenopathy. However, Kikuchi–Fujimoto Disease (KFD) or necrotizing histiocytic lymphadenitis is rarely observed post-vaccination, with only one other case of KFD post COVID-19 vaccination reported to date. We report two more cases of KFD post COVID-19 vaccination in the Asian population, highlighting the clinical course and salient clinical, radiological and histologic findings. In addition, we provide a literature review of the existing cases of lymphadenopathy post COVID-19 vaccination with cytologic and/or histologic correlation
Association of fluid balance with mortality in sepsis is modified by admission hemoglobin levels: A large database study
10.1371/journal.pone.0252629PLoS ONE166-June025262
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