Browsing by Author "Yiannoutsos, Constantin T."
Now showing 1 - 10 of 67
Results Per Page
Sort Options
Item Achieving consistency in measures of HIV-1 viral suppression across countries: derivation of an adjustment based on international antiretroviral treatment cohort data(Wiley, 2021) Johnson, Leigh F.; Kariminia, Azar; Trickey, Adam; Yiannoutsos, Constantin T.; Ekouevi, Didier K.; Minga, Albert K.; Pascom, Ana Roberta Pati; Han, Win Min; Zhang, Lei; Althoff, Keri N.; Rebeiro, Peter F.; Murenzi, Gad; Ross, Jonathan; Hsiao, Nei-Yuan; Marsh, Kimberly; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthIntroduction: The third of the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 targets is to achieve a 90% rate of viral suppression (HIV viral load <1000 HIV-1 RNA copies/ml) in patients on antiretroviral treatment (ART) by 2020. However, some countries use different thresholds when reporting viral suppression, and there is thus a need for an adjustment to standardize estimates to the <1000 threshold. We aim to propose such an adjustment, to support consistent monitoring of progress towards the "third 90" target. Methods: We considered three possible distributions for viral loads in ART patients: Weibull, Pareto and reverse Weibull (imposing an upper limit but no lower limit on the log scale). The models were fitted to data on viral load distributions in ART patients in the International epidemiology Databases to Evaluate AIDS (IeDEA) collaboration (representing seven global regions) and the ART Cohort Collaboration (representing Europe), using separate random effects models for adults and children. The models were validated using data from the World Health Organization (WHO) HIV drug resistance report and the Brazilian national ART programme. Results: Models were calibrated using 921,157 adult and 37,431 paediatric viral load measurements, over 2010-2019. The Pareto and reverse Weibull models provided the best fits to the data, but for all models, the "shape" parameters for the viral load distributions differed significantly between regions. The Weibull model performed best in the validation against the WHO drug resistance survey data, while the Pareto model produced uncertainty ranges that were too narrow, relative to the validation data. Based on these analyses, we recommend using the reverse Weibull model. For example, if a country reports an 80% rate of viral suppression at <200 copies/ml, this model estimates the proportion virally suppressed at <1000 copies/ml is 88.3% (0.800.56 ), with uncertainty range 85.5-90.6% (0.800.70 -0.800.44 ). Conclusions: Estimates of viral suppression can change substantially depending on the threshold used in defining viral suppression. It is, therefore, important that viral suppression rates are standardized to the same threshold for the purpose of assessing progress towards UNAIDS targets. We have proposed a simple adjustment that allows this, and this has been incorporated into UNAIDS modelling software.Item Active Tuberculosis Is Associated with Worse Clinical Outcomes in HIV-Infected African Patients on Antiretroviral Therapy(Public Library of Science, 2013) Siika, Abraham M.; Yiannoutsos, Constantin T.; Wools-Kaloustian, Kara K.; Musick, Beverly S.; Mwangi, Ann W.; Diero, Lameck O.; Kimaiyo, Sylvester N.; Tierney, William M.; Carter, Jane E.; Medicine, School of MedicineObjective: This cohort study utilized data from a large HIV treatment program in western Kenya to describe the impact of active tuberculosis (TB) on clinical outcomes among African patients on antiretroviral therapy (ART). Design: We included all patients initiating ART between March 2004 and November 2007. Clinical (signs and symptoms), radiological (chest radiographs) and laboratory (mycobacterial smears, culture and tissue histology) criteria were used to record the diagnosis of TB disease in the program's electronic medical record system. Methods: We assessed the impact of TB disease on mortality, loss to follow-up (LTFU) and incident AIDS-defining events (ADEs) through Cox models and CD4 cell and weight response to ART by non-linear mixed models. Results: We studied 21,242 patients initiating ART-5,186 (24%) with TB; 62% female; median age 37 years. There were proportionately more men in the active TB (46%) than in the non-TB (35%) group. Adjusting for baseline HIV-disease severity, TB patients were more likely to die (hazard ratio--HR = 1.32, 95% CI 1.18-1.47) or have incident ADEs (HR = 1.31, 95% CI: 1.19-1.45). They had lower median CD4 cell counts (77 versus 109), weight (52.5 versus 55.0 kg) and higher ADE risk at baseline (CD4-adjusted odds ratio = 1.55, 95% CI: 1.31-1.85). ART adherence was similarly good in both groups. Adjusting for gender and baseline CD4 cell count, TB patients experienced virtually identical rise in CD4 counts after ART initiation as those without. However, the overall CD4 count at one year was lower among patients with TB (251 versus 269 cells/µl). Conclusions: Clinically detected TB disease is associated with greater mortality and morbidity despite salutary response to ART. Data suggest that identifying HIV patients co-infected with TB earlier in the HIV-disease trajectory may not fully address TB-related morbidity and mortality.Item Adaptation of the Client Diagnostic Questionnaire for East Africa(Public Library of Science, 2024-03-19) Kwobah, Edith Kamaru; Goodrich, Suzanne; Kulzer, Jayne Lewis; Kanyesigye, Michael; Obatsa, Sarah; Cheruiyot, Julius; Kiprono, Lorna; Kibet, Colma; Ochieng, Felix; Bukusi, Elizabeth A.; Ofner, Susan; Brown, Steven A.; Yiannoutsos, Constantin T.; Atwoli, Lukoye; Wools-Kaloustian, Kara; Medicine, School of MedicineResearch increasingly involves cross-cultural work with non-English-speaking populations, necessitating translation and cultural validation of research tools. This paper describes the process of translating and criterion validation of the Client Diagnostic Questionnaire (CDQ) for use in a multisite study in Kenya and Uganda. The English CDQ was translated into Swahili, Dholuo (Kenya) and Runyankole/Rukiga (Uganda) by expert translators. The translated documents underwent face validation by a bilingual committee, who resolved unclear statements, agreed on final translations and reviewed back translations to English. A diagnostic interview by a mental health specialist was used for criterion validation, and Kappa statistics assessed the strength of agreement between non-specialist scores and mental health professionals' diagnoses. Achieving semantic equivalence between translations was a challenge. Validation analysis was done with 30 participants at each site (median age 32.3 years (IQR = (26.5, 36.3)); 58 (64.4%) female). The sensitivity was 86.7%, specificity 64.4%, positive predictive value 70.9% and negative predictive value 82.9%. Diagnostic accuracy by the non-specialist was 75.6%. Agreement was substantial for major depressive episode and positive alcohol (past 6 months) and alcohol abuse (past 30 days). Agreement was moderate for other depressive disorders, panic disorder and psychosis screen; fair for generalized anxiety, drug abuse (past 6 months) and Post Traumatic Stress Disorder (PTSD); and poor for drug abuse (past 30 days). Variability of agreement between sites was seen for drug use (past 6 months) and PTSD. Our study successfully adapted the CDQ for use among people living with HIV in East Africa. We established that trained non-specialists can use the CDQ to screen for common mental health and substance use disorders with reasonable accuracy. Its use has the potential to increase case identification, improve linkage to mental healthcare, and improve outcomes. We recommend further studies to establish the psychometric properties of the translated tool.Item Advanced Modeling of Longitudinal Spectroscopy Data(2014) Kundu, Madan Gopal; Harezlak, Jaroslaw; Randolph, Timothy W.; Sarkar, Jyotirmoy; Steele, Gregory K.; Yiannoutsos, Constantin T.Magnetic resonance (MR) spectroscopy is a neuroimaging technique. It is widely used to quantify the concentration of important metabolites in a brain tissue. Imbalance in concentration of brain metabolites has been found to be associated with development of neurological impairment. There has been increasing trend of using MR spectroscopy as a diagnosis tool for neurological disorders. We established statistical methodology to analyze data obtained from the MR spectroscopy in the context of the HIV associated neurological disorder. First, we have developed novel methodology to study the association of marker of neurological disorder with MR spectrum from brain and how this association evolves with time. The entire problem fits into the framework of scalar-on-function regression model with individual spectrum being the functional predictor. We have extended one of the existing cross-sectional scalar-on-function regression techniques to longitudinal set-up. Advantage of proposed method includes: 1) ability to model flexible time-varying association between response and functional predictor and (2) ability to incorporate prior information. Second part of research attempts to study the influence of the clinical and demographic factors on the progression of brain metabolites over time. In order to understand the influence of these factors in fully non-parametric way, we proposed LongCART algorithm to construct regression tree with longitudinal data. Such a regression tree helps to identify smaller subpopulations (characterized by baseline factors) with differential longitudinal profile and hence helps us to identify influence of baseline factors. Advantage of LongCART algorithm includes: (1) it maintains of type-I error in determining best split, (2) substantially reduces computation time and (2) applicable even observations are taken at subject-specific time-points. Finally, we carried out an in-depth analysis of longitudinal changes in the brain metabolite concentrations in three brain regions, namely, white matter, gray matter and basal ganglia in chronically infected HIV patients enrolled in HIV Neuroimaging Consortium study. We studied the influence of important baseline factors (clinical and demographic) on these longitudinal profiles of brain metabolites using LongCART algorithm in order to identify subgroup of patients at higher risk of neurological impairment.Item Assessing HIV-infected patient retention in a program of differentiated care in sub-Saharan Africa: a G-estimation approach(De Gruyter, 2023-09-18) Yiannoutsos, Constantin T.; Wools-Kaloustian, Kara; Musick, Beverly S.; Kosgei, Rose; Kimaiyo, Sylvester; Siika, Abraham; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthDifferentiated care delivery aims to simplify care of people living with HIV, reflect their preferences, reduce burdens on the healthcare system, maintain care quality and preserve resources. However, assessing program effectiveness using observational data is difficult due to confounding by indication and randomized trials may be infeasible. Also, benefits can reach patients directly, through enrollment in the program, and indirectly, by increasing quality of and accessibility to care. Low-risk express care (LREC), the program under evaluation, is a nurse-centered model which assigns patients stable on ART to a nurse every two months and a clinician every third visit, reducing annual clinician visits by two thirds. Study population is comprised of 16,832 subjects from 15 clinics in Kenya. We focus on patient retention in care based on whether the LREC program is available at a clinic and whether the patient is enrolled in LREC. We use G-estimation to assess the effect on retention of two “strategies”: (i) program availability but no enrollment; (ii) enrollment at an available program; versus no program availability. Compared to no availability, LREC results in a non-significant increase in patient retention, among patients not enrolled in the program (indirect effect), while enrollment in LREC is associated with a significant extension of the time retained in care (direct effect). G-estimation provides an analytical framework useful to the assessment of similar programs using observational data.Item Assessment of Risk Behaviors in Patients With Opioid Prescriptions: A Study of Indiana’s Inspect Data(Wiley, 2017-12) Greene, Marion S.; Chambers, Robert Andrew; Yiannoutsos, Constantin T.; Wright, Eric R.; Steele, Gregory K.; Zollinger, Terrell W.; Health Policy and Management, School of Public HealthBackground and Objectives Prescription Drug Monitoring Programs (PDMPs) can serve as screening tools and support the clinical decision‐making process in patients receiving opioids. The objective of the study was to utilize 2014 INSPECT (Indiana's PDMP) data to identify factors that increase patients’ likelihood to engage in opioid‐related risk behaviors. Methods Based on a literature review, four risk behaviors were identified: Receiving >90 morphine milligram equivalents (MME), having >4 opioid prescribers, obtaining opioids from >4 pharmacies, and concurrent use of opioids and benzodiazepines. Two binary logistic regression analyses (engaging in at least one risk behaviors; engaging in all four risk behaviors) and an ordinal regression analysis (engaging in 0–4 risk behaviors) were conducted to identify factors associated with these opioid‐related risk behaviors. Results Of the 1,538,120 unique opioid patients included in the study, 18.4% engaged in one, 5.3% in two, 1.6% in three, and .4% in all four risk behaviors. Depending on the model, prescribing a second monthly opioid increased patients’ odds to engage in risk behaviors by a factor of 10 or more and prescribing two or more benzodiazepines annually increased the odds at least 13‐fold. Conclusions and Scientific Significance About one‐fourth of all patients consuming opioids engaged in one or more risk behaviors; higher number of opioid prescriptions and addition of even a small number of benzodiazepine prescriptions dramatically increased these odds. PDMPs can be helpful in identifying opioid users at high‐risk for misuse. This information could be used to target efforts to reduce the prescription drug epidemic.Item AUCTSP: an improved biomarker gene pair class predictor(BMC, 2018-06-26) Kagaris, Dimitri; Khamesipour, Alireza; Yiannoutsos, Constantin T.; Biostatistics, School of Public HealthThe Top Scoring Pair (TSP) classifier, based on the concept of relative ranking reversals in the expressions of pairs of genes, has been proposed as a simple, accurate, and easily interpretable decision rule for classification and class prediction of gene expression profiles. The idea that differences in gene expression ranking are associated with presence or absence of disease is compelling and has strong biological plausibility. Nevertheless, the TSP formulation ignores significant available information which can improve classification accuracy and is vulnerable to selecting genes which do not have differential expression in the two conditions ("pivot" genes). RESULTS: We introduce the AUCTSP classifier as an alternative rank-based estimator of the magnitude of the ranking reversals involved in the original TSP. The proposed estimator is based on the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) and as such, takes into account the separation of the entire distribution of gene expression levels in gene pairs under the conditions considered, as opposed to comparing gene rankings within individual subjects as in the original TSP formulation. Through extensive simulations and case studies involving classification in ovarian, leukemia, colon, breast and prostate cancers and diffuse large b-cell lymphoma, we show the superiority of the proposed approach in terms of improving classification accuracy, avoiding overfitting and being less prone to selecting non-informative (pivot) genes. CONCLUSIONS: The proposed AUCTSP is a simple yet reliable and robust rank-based classifier for gene expression classification. While the AUCTSP works by the same principle as TSP, its ability to determine the top scoring gene pair based on the relative rankings of two marker genes across all subjects as opposed to each individual subject results in significant performance gains in classification accuracy. In addition, the proposed method tends to avoid selection of non-informative (pivot) genes as members of the top-scoring pair.Item Bayesian estimation of SARS-CoV-2 prevalence in Indiana by random testing(NAS, 2021-02) Yiannoutsos, Constantin T.; Halverson, Paul K.; Menachemi, Nir; Biostatistics, School of Public HealthFrom 25 to 29 April 2020, the state of Indiana undertook testing of 3,658 randomly chosen state residents for the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, the agent causing COVID-19 disease. This was the first statewide randomized study of COVID-19 testing in the United States. Both PCR and serological tests were administered to all study participants. This paper describes statistical methods used to address nonresponse among various demographic groups and to adjust for testing errors to reduce bias in the estimates of the overall disease prevalence in Indiana. These adjustments were implemented through Bayesian methods, which incorporated all available information on disease prevalence and test performance, along with external data obtained from census of the Indiana statewide population. Both adjustments appeared to have significant impact on the unadjusted estimates, mainly due to upweighting data in study participants of non-White races and Hispanic ethnicity and anticipated false-positive and false-negative test results among both the PCR and antibody tests utilized in the study.Item CD4 trajectory adjusting for dropout among HIV-positive patients receiving combination antiretroviral therapy in an East African HIV care centre(Wiley, 2014-08-14) Kiragga, Agnes N.; Lok, Judith J.; Musick, Beverly S.; Bosch, Ronald J.; Mwangi, Ann; Wools-Kaloustian, Kara K.; Yiannoutsos, Constantin T.; East Africa IeDEA Regional Consortium; Medicine, School of MedicineObjective: Estimates of CD4 response to antiretroviral therapy (ART) obtained by averaging data from patients in care, overestimate population CD4 response and treatment program effectiveness because they do not consider data from patients who are deceased or not in care. We use mathematical methods to assess and adjust for this bias based on patient characteristics. Design: We examined data from 25,261 HIV-positive patients from the East Africa IeDEA Consortium. Methods: We used inverse probability of censoring weighting (IPCW) to represent patients not in care by patients in care with similar characteristics. We address two questions: What would the median CD4 be "had everyone starting ART remained on observation?" and "were everyone starting ART maintained on treatment?" Results: Routine CD4 count estimates were higher than adjusted estimates even under the best-case scenario of maintaining all patients on treatment. Two years after starting ART, differences between estimates diverged from 30 cells/µL, assuming similar mortality and treatment access among dropouts as patients in care, to over 100 cells/µL assuming 20% lower survival and 50% lower treatment access among dropouts. When considering only patients in care, the proportion of patients with CD4 above 350 cells/µL was 50% adjusted to below 30% when accounting for patients not in care. One-year mortality diverged 6-14% from the naïve estimates depending on assumptions about access to care among lost patients. Conclusions: Ignoring mortality and loss to care results in over-estimation of ART response for patients starting treatment and exaggerates the efficacy of treatment programs administering it.Item Cerebrospinal fluid neopterin decay characteristics after initiation of antiretroviral therapy(Springer Nature, 2013-05-10) Yilmaz, Aylin; Yiannoutsos, Constantin T.; Fuchs, Dietmar; Price, Richard W.; Crozier, Kathryn; Hagberg, Lars; Spudich, Serena; Gisslén, Magnus; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthBackground: Neopterin, a biomarker of macrophage activation, is elevated in the cerebrospinal fluid (CSF) of most HIV-infected individuals and decreases after initiation of antiretroviral therapy (ART). We studied decay characteristics of neopterin in CSF and blood after commencement of ART in HIV-infected subjects and estimated the set-point levels of CSF neopterin after ART-mediated viral suppression. Methods: CSF and blood neopterin were longitudinally measured in 102 neurologically asymptomatic HIV-infected subjects who were treatment-naïve or had been off ART for ≥ 6 months. We used a non-linear model to estimate neopterin decay in response to ART and a stable neopterin set-point attained after prolonged ART. Seven subjects with HIV-associated dementia (HAD) who initiated ART were studied for comparison. Results: Non-HAD patients were followed for a median 84.7 months. Though CSF neopterin concentrations decreased rapidly after ART initiation, it was estimated that set-point levels would be below normal CSF neopterin levels (<5.8 nmol/L) in only 60/102 (59%) of these patients. Pre-ART CSF neopterin was the primary predictor of set-point (P <0.001). HAD subjects had higher baseline median CSF neopterin levels than non-HAD subjects (P <0.0001). Based on the non-HAD model, only 14% of HAD patients were predicted to reach normal levels. Conclusions: After virologically suppressive ART, abnormal CSF neopterin levels persisted in 41% of non-HAD and the majority of HAD patients. ART is not fully effective in ameliorating macrophage activation in CNS as well as blood, especially in subjects with higher pre-ART levels of immune activation.