RESUMEN
OBJECTIVE: The aim of this study was to evaluate associations of antiretroviral therapy (ART) and comorbidities with neurocognitive impairments (NCIs) in ART-naive HIV-1-infected patients in clinical practice. DESIGN: A retrospective study was conducted in ART-naive patients with HIV-1 diagnosis between January 2009 and December 2013 in the United States. METHODS: The primary outcome was any NCI that included HIV-associated neurocognitive disorders (HAND), Alzheimer's disease, Parkinson's disease, multiple sclerosis, and other dementias. RESULTS: A total of 47â862 patients met eligibility criteria (30â828 antiretroviral-treated and 17â034 antiretroviral-untreated). The median age was 45 years [interquartile range (IQR) 35--52] with 31% of patients aged at least 50 years. Seventy-five percent were men. Overall, ART was associated with reduced risks of any NCI (hazard ratio 0.41, 95% CI: 0.37--0.45), HAND (hazard ratio 0.57, 95% CI: 0.48--0.69), Alzheimer's disease (hazard ratio 0.36, 95% CI: 0.24--0.54), Parkinson's disease (hazard ratio 0.36, 95% CI: 0.25--0.51), multiple sclerosis (hazard ratio 0.26, 95% CI: 0.18--0.37), and other dementias (hazard ratio 0.50, 95% CI: 0.45--0.55). Meanwhile, the risk of any NCI was significantly increased in patients with various comorbidities including cardiac arrhythmia, paralysis, other neurological disorders, complicated diabetes, hypothyroidism, renal failure, lymphoma, rheumatoid arthritis, weight loss, and depression as compared with patients without those comorbidities. CONCLUSION: ART may reduce the risk of NCIs in HIV-infected patients in general. Further research to investigate NCIs on specific antiretroviral regimens and comorbidities may provide insights regarding the long-term clinical care of these patients.
Asunto(s)
Antirretrovirales/efectos adversos , Terapia Antirretroviral Altamente Activa/efectos adversos , Infecciones por VIH/tratamiento farmacológico , VIH-1 , Trastornos Neurocognitivos/epidemiología , Adolescente , Adulto , Anciano , Antirretrovirales/uso terapéutico , Recuento de Linfocito CD4 , Comorbilidad , Infecciones por VIH/complicaciones , Infecciones por VIH/epidemiología , Humanos , Masculino , Persona de Mediana Edad , Trastornos Neurocognitivos/diagnóstico , Estudios RetrospectivosRESUMEN
Analysis of liver safety data has to be multivariate by nature and needs to take into account time dependency of observations. Current standard tools for liver safety assessment such as summary tables, individual data listings, and narratives address these requirements to a limited extent only. Using graphics in the context of a systematic workflow including predefined graph templates is a valuable addition to standard instruments, helping to ensure completeness of evaluation, and supporting both hypothesis generation and testing. Employing graphical workflows interactively allows analysis in a team-based setting and facilitates identification of the most suitable graphics for publishing and regulatory reporting. Another important tool is statistical outlier detection, accounting for the fact that for assessment of Drug-Induced Liver Injury, identification and thorough evaluation of extreme values has much more relevance than measures of central tendency in the data. Taken together, systematical graphical data exploration and statistical outlier detection may have the potential to significantly improve assessment and interpretation of clinical liver safety data. A workshop was convened to discuss best practices for the assessment of drug-induced liver injury (DILI) in clinical trials.
Asunto(s)
Enfermedad Hepática Inducida por Sustancias y Drogas/etiología , Ensayos Clínicos como Asunto/métodos , Proyectos de Investigación , Enfermedad Hepática Inducida por Sustancias y Drogas/diagnóstico , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos/diagnóstico , Humanos , Medición de Riesgo/métodos , Factores de TiempoRESUMEN
PURPOSE: Identifying drug-induced liver injury is a critical task in drug development and postapproval real-world care. Severe liver injury is identified by the liver chemistry threshold of alanine aminotransferase (ALT) >3× upper limit of normal (ULN) and bilirubin >2× ULN, termed Hy's law by the Food and Drug Administration. These thresholds require discontinuation of the causative drug and are seldom exceeded in most patient populations. However, because maintenance of therapy is critical in the treatment of advanced cancer, customized thresholds may be useful in oncology patient populations, particularly for those with baseline liver chemistries elevations. METHODS: Liver chemistry data from 31 aggregated oncology clinical trials were modeled through a truncated robust multivariate outlier detection (TRMOD) method to develop the decision boundary or threshold for examining liver injury in oncology clinical trials. RESULTS: The boundary of TRMOD identified outliers with an ALT limit 5.0× ULN and total bilirubin limit 2.7× ULN. In addition, TRMOD was applied to the aggregated oncology data to examine fold-baseline ALT and total bilirubin, revealing limits of ALT 6.9× baseline and bilirubin 6.5× baseline. Similar ALT and bilirubin threshold limits were observed for oncology patients both with and without liver metastases. CONCLUSIONS: These higher liver chemistry thresholds examining fold-ULN and fold-baseline data may be valuable in identifying potential severe liver injury and detecting liver safety signals of clinical concern in oncology clinical trials and postapproval settings while helping to avoid premature discontinuation of curative therapy.
Asunto(s)
Alanina Transaminasa/metabolismo , Bilirrubina/metabolismo , Enfermedad Hepática Inducida por Sustancias y Drogas/diagnóstico , Ensayos Clínicos como Asunto , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos , Oncología Médica/estadística & datos numéricos , Modelos Estadísticos , Enfermedad Hepática Inducida por Sustancias y Drogas/epidemiología , Enfermedad Hepática Inducida por Sustancias y Drogas/etiología , Enfermedad Hepática Inducida por Sustancias y Drogas/metabolismo , Ensayos Clínicos como Asunto/estadística & datos numéricos , Humanos , Pruebas de Función Hepática , Análisis Multivariante , Neoplasias/tratamiento farmacológico , Neoplasias/patologíaRESUMEN
There are many data mining techniques for processing and general learning of multivariate data. However, we believe the wavelet transformation and latent variable projection method are particularly useful for spectroscopic and chromatographic data. Projection based methods are designed to handle hugely multivariate nature of such data effectively. For the actual analysis of the data we have used latent variable projection methods such as principal component analysis (PCA) and partial least squares projection to latent structures based discriminant analysis (PLS-DA) to analyze the raw data presented to the participants of the First Duke Proteomics Data Mining Conference. PCA was used to solve problem #1 (clustering problem) and the PLS-DA was used to solve problem #2 (classification problem). The idea of internal and external cross-validation was used to validate the model obtained from the classification analysis. The simple two-component PLS-DA model obtained from the analysis performed well. The model has completely separated the two groups from all the data. The same model applied on two-thirds of the data showed good performance by external validation with independent test set of remaining 13 specimens obtained by setting aside the spectra of every third specimen (accuracy of 85%).