A comparative investigation of methods for longitudinal data with limits of detection through a case study. 2016

P Fu, and J Hughes, and G Zeng, and S Hanook, and J Orem, and O W Mwanda, and S C Remick
Case Western Reserve University School of Medicine, Comprehensive Cancer Center, Cleveland, Ohio, USA pxf16@po.cwru.edu.

The statistical analysis of continuous longitudinal data may be complicated since quantitative levels of bioassay cannot always be determined. Values beyond the limits of detection (LOD) in the assays may not be observed and thus censored, rendering complexity to the analysis of such data. This article examines how both left-censoring and right censoring of HIV-1 plasma RNA measurements, collected for the study on AIDS-related Non-Hodgkin's lymphoma (AR-NHL) in East Africa, affects the quantification of viral load and explores the natural history of viral load measurements over time in AR-NHL patients receiving anticancer chemotherapy. Data analyses using Monte Carlo EM algorithm (MCEM) are compared to analyses where the LOD or LOD/2 (left censoring) value is substituted for the censored observations, and also to other methods such as multiple imputation, and maximum likelihood estimation for censored data (generalized Tobit regression). Simulations are used to explore the sensitivity of the results to changes in the model parameters. In conclusion, the antiretroviral treatment was associated with a significant decrease in viral load after controlling the effects of other covariates. A simulation study with finite sample size shows MCEM is the least biased method and the estimates are least sensitive to the censoring mechanism.

UI MeSH Term Description Entries
D008137 Longitudinal Studies Studies in which variables relating to an individual or group of individuals are assessed over a period of time. Bogalusa Heart Study,California Teachers Study,Framingham Heart Study,Jackson Heart Study,Longitudinal Survey,Tuskegee Syphilis Study,Bogalusa Heart Studies,California Teachers Studies,Framingham Heart Studies,Heart Studies, Bogalusa,Heart Studies, Framingham,Heart Studies, Jackson,Heart Study, Bogalusa,Heart Study, Framingham,Heart Study, Jackson,Jackson Heart Studies,Longitudinal Study,Longitudinal Surveys,Studies, Bogalusa Heart,Studies, California Teachers,Studies, Jackson Heart,Studies, Longitudinal,Study, Bogalusa Heart,Study, California Teachers,Study, Longitudinal,Survey, Longitudinal,Surveys, Longitudinal,Syphilis Studies, Tuskegee,Syphilis Study, Tuskegee,Teachers Studies, California,Teachers Study, California,Tuskegee Syphilis Studies
D008228 Lymphoma, Non-Hodgkin Any of a group of malignant tumors of lymphoid tissue that differ from HODGKIN DISEASE, being more heterogeneous with respect to malignant cell lineage, clinical course, prognosis, and therapy. The only common feature among these tumors is the absence of giant REED-STERNBERG CELLS, a characteristic of Hodgkin's disease. Non-Hodgkin Lymphoma,Diffuse Mixed Small and Large Cell Lymphoma,Diffuse Mixed-Cell Lymphoma,Diffuse Small Cleaved-Cell Lymphoma,Diffuse Undifferentiated Lymphoma,Lymphatic Sarcoma,Lymphoma, Atypical Diffuse Small Lymphoid,Lymphoma, Diffuse,Lymphoma, Diffuse, Mixed Lymphocytic-Histiocytic,Lymphoma, High-Grade,Lymphoma, Intermediate-Grade,Lymphoma, Low-Grade,Lymphoma, Mixed,Lymphoma, Mixed Cell, Diffuse,Lymphoma, Mixed Lymphocytic-Histiocytic,Lymphoma, Mixed Small and Large Cell, Diffuse,Lymphoma, Mixed-Cell,Lymphoma, Mixed-Cell, Diffuse,Lymphoma, Non-Hodgkin's,Lymphoma, Non-Hodgkin, Familial,Lymphoma, Non-Hodgkins,Lymphoma, Nonhodgkin's,Lymphoma, Nonhodgkins,Lymphoma, Pleomorphic,Lymphoma, Small Cleaved Cell, Diffuse,Lymphoma, Small Cleaved-Cell, Diffuse,Lymphoma, Small Non-Cleaved-Cell,Lymphoma, Small Noncleaved-Cell,Lymphoma, Small and Large Cleaved-Cell, Diffuse,Lymphoma, Undifferentiated,Lymphoma, Undifferentiated, Diffuse,Lymphosarcoma,Mixed Small and Large Cell Lymphoma, Diffuse,Mixed-Cell Lymphoma,Mixed-Cell Lymphoma, Diffuse,Non-Hodgkin's Lymphoma,Reticulosarcoma,Reticulum Cell Sarcoma,Reticulum-Cell Sarcoma,Sarcoma, Lymphatic,Sarcoma, Reticulum-Cell,Small Cleaved-Cell Lymphoma, Diffuse,Small Non-Cleaved-Cell Lymphoma,Small Noncleaved-Cell Lymphoma,Undifferentiated Lymphoma,Diffuse Lymphoma,Diffuse Lymphomas,Diffuse Mixed Cell Lymphoma,Diffuse Mixed-Cell Lymphomas,Diffuse Small Cleaved Cell Lymphoma,Diffuse Undifferentiated Lymphomas,High-Grade Lymphoma,High-Grade Lymphomas,Intermediate-Grade Lymphoma,Intermediate-Grade Lymphomas,Low-Grade Lymphoma,Low-Grade Lymphomas,Lymphatic Sarcomas,Lymphocytic-Histiocytic Lymphoma, Mixed,Lymphocytic-Histiocytic Lymphomas, Mixed,Lymphoma, Diffuse Mixed-Cell,Lymphoma, Diffuse Undifferentiated,Lymphoma, High Grade,Lymphoma, Intermediate Grade,Lymphoma, Low Grade,Lymphoma, Mixed Cell,Lymphoma, Mixed Lymphocytic Histiocytic,Lymphoma, Non Hodgkin,Lymphoma, Non Hodgkin's,Lymphoma, Non Hodgkins,Lymphoma, Nonhodgkin,Lymphoma, Small Non Cleaved Cell,Lymphoma, Small Noncleaved Cell,Lymphosarcomas,Mixed Cell Lymphoma,Mixed Cell Lymphoma, Diffuse,Mixed Lymphocytic-Histiocytic Lymphoma,Mixed Lymphocytic-Histiocytic Lymphomas,Mixed Lymphoma,Mixed Lymphomas,Mixed-Cell Lymphomas,Non Hodgkin Lymphoma,Non Hodgkin's Lymphoma,Non-Cleaved-Cell Lymphoma, Small,Non-Hodgkins Lymphoma,Noncleaved-Cell Lymphoma, Small,Nonhodgkin's Lymphoma,Nonhodgkins Lymphoma,Pleomorphic Lymphoma,Pleomorphic Lymphomas,Reticulosarcomas,Reticulum Cell Sarcomas,Reticulum-Cell Sarcomas,Sarcoma, Reticulum Cell,Small Cleaved Cell Lymphoma, Diffuse,Small Non Cleaved Cell Lymphoma,Small Non-Cleaved-Cell Lymphomas,Small Noncleaved Cell Lymphoma,Small Noncleaved-Cell Lymphomas,Undifferentiated Lymphoma, Diffuse,Undifferentiated Lymphomas
D009010 Monte Carlo Method In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993) Method, Monte Carlo
D002986 Clinical Trials as Topic Works about pre-planned studies of the safety, efficacy, or optimum dosage schedule (if appropriate) of one or more diagnostic, therapeutic, or prophylactic drugs, devices, or techniques selected according to predetermined criteria of eligibility and observed for predefined evidence of favorable and unfavorable effects. This concept includes clinical trials conducted both in the U.S. and in other countries. Clinical Trial as Topic
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D003627 Data Interpretation, Statistical Application of statistical procedures to analyze specific observed or assumed facts from a particular study. Data Analysis, Statistical,Data Interpretations, Statistical,Interpretation, Statistical Data,Statistical Data Analysis,Statistical Data Interpretation,Analyses, Statistical Data,Analysis, Statistical Data,Data Analyses, Statistical,Interpretations, Statistical Data,Statistical Data Analyses,Statistical Data Interpretations
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000465 Algorithms A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. Algorithm
D012367 RNA, Viral Ribonucleic acid that makes up the genetic material of viruses. Viral RNA
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model

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