Browsing by Author "Department of Biostatistics, IU School of Medicine"

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    Confirmatory test of two factors and four subtypes of bipolar disorder based on lifetime psychiatric comorbidity
    (Cambridge, 2015-07) Monahan, Patrick O.; Stump, Timothy; Coryell, William H.; Harezlak, Jaroslaw; Marcoulides, George A.; Liu, Hai; Steeger, Christine M.; Mitchell, Philip B.; Wilcox, Holly C.; Hulvershorn, Leslie A.; Glowinski, Anne L.; Iyer-Eimerbrink, Priya Anapurna; McInnis, Melvin; Nurnberger, John I. Jr.; Department of Biostatistics, IU School of Medicine
    Background The first aim was to use confirmatory factor analysis (CFA) to test a hypothesis that two factors (internalizing and externalizing) account for lifetime co-morbid DSM-IV diagnoses among adults with bipolar I (BPI) disorder. The second aim was to use confirmatory latent class analysis (CLCA) to test the hypothesis that four clinical subtypes are detectible: pure BPI; BPI plus internalizing disorders only; BPI plus externalizing disorders only; and BPI plus internalizing and externalizing disorders. Method A cohort of 699 multiplex BPI families was studied, ascertained and assessed (1998–2003) by the National Institute of Mental Health Genetics Initiative Bipolar Consortium: 1156 with BPI disorder (504 adult probands; 594 first-degree relatives; and 58 more distant relatives) and 563 first-degree relatives without BPI. Best-estimate consensus DSM-IV diagnoses were based on structured interviews, family history and medical records. MPLUS software was used for CFA and CLCA. Results The two-factor CFA model fit the data very well, and could not be improved by adding or removing paths. The four-class CLCA model fit better than exploratory LCA models or post-hoc-modified CLCA models. The two factors and four classes were associated with distinctive clinical course and severity variables, adjusted for proband gender. Co-morbidity, especially more than one internalizing and/or externalizing disorder, was associated with a more severe and complicated course of illness. The four classes demonstrated significant familial aggregation, adjusted for gender and age of relatives. Conclusions The BPI two-factor and four-cluster hypotheses demonstrated substantial confirmatory support. These models may be useful for subtyping BPI disorders, predicting course of illness and refining the phenotype in genetic studies.
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    Marginal and Conditional Distribution Estimation from Double-Sampled Semi-Competing Risks Data
    (Wiley, 2015-03) Yu, Menggang; Yiannoutsos, Constantin T.; Department of Biostatistics, IU School of Medicine
    Informative dropout is a vexing problem for any biomedical study. Most existing statistical methods attempt to correct estimation bias related to this phenomenon by specifying unverifiable assumptions about the dropout mechanism. We consider a cohort study in Africa that uses an outreach programme to ascertain the vital status for dropout subjects. These data can be used to identify a number of relevant distributions. However, as only a subset of dropout subjects were followed, vital status ascertainment was incomplete. We use semi-competing risk methods as our analysis framework to address this specific case where the terminal event is incompletely ascertained and consider various procedures for estimating the marginal distribution of dropout and the marginal and conditional distributions of survival. We also consider model selection and estimation efficiency in our setting. Performance of the proposed methods is demonstrated via simulations, asymptotic study and analysis of the study data.
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    Primary care physician perceptions of adult survivors of childhood cancer
    (Ovid Technologies (Wolters Kluwer) - Lippincott Williams & Wilkins, 2014-03) Sima, Jody L.; Perkins, Susan M.; Haggstrom, David A.; Department of Biostatistics, IU School of Medicine
    Increasing cure rates for childhood cancers have resulted in a population of adult childhood cancer survivors (CCS) that are at risk for late effects of cancer-directed therapy. Our objective was to identify facilitators and barriers to primary care physicians (PCPs) providing late effects screening and evaluate information tools PCPs perceive as useful. We analyzed surveys from 351 practicing internal medicine and family practice physicians nationwide. A minority of PCPs perceived that their medical training was adequate to recognize late effects of chemotherapy (27.6%), cancer surgery (36.6%), and radiation therapy (38.1%). Most PCPs (93%) had never used Children's Oncology Group guidelines, but 86% would follow their recommendations. Most (84% to 86%) PCPs stated that they had never received a cancer treatment summary or survivorship care plan but (>90%) thought these documents would be useful. PCPs have a low level of awareness and receive inadequate training to recognize late effects. Overall, PCPs infrequently utilize guidelines, cancer treatment summaries, and survivorship care plans, although they perceive such tools as useful. We have identified gaps to address when providing care for CCS in routine general medical practice.