Browsing by Author "Fadel, William"
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Item Adaptive empirical pattern transformation (ADEPT) with application to walking stride segmentation(Oxford University Press, 2021-04-10) Karas, Marta; Czkiewicz, Marcin Stra; Fadel, William; Harezlak, Jaroslaw; Crainiceanu, Ciprian M.; Urbanek, Jacek K.; Biostatistics, School of Public HealthQuantifying gait parameters and ambulatory monitoring of changes in these parameters have become increasingly important in epidemiological and clinical studies. Using high-density accelerometry measurements, we propose adaptive empirical pattern transformation (ADEPT), a fast, scalable, and accurate method for segmentation of individual walking strides. ADEPT computes the covariance between a scaled and translated pattern function and the data, an idea similar to the continuous wavelet transform. The difference is that ADEPT uses a data-based pattern function, allows multiple pattern functions, can use other distances instead of the covariance, and the pattern function is not required to satisfy the wavelet admissibility condition. Compared to many existing approaches, ADEPT is designed to work with data collected at various body locations and is invariant to the direction of accelerometer axes relative to body orientation. The method is applied to and validated on accelerometry data collected during a equation M1-m outdoor walk of equation M2 study participants wearing accelerometers on the wrist, hip, and both ankles. Additionally, all scripts and data needed to reproduce presented results are included in supplementary material available at Biostatistics online.Item An Analysis of Survival Data when Hazards are not Proportional: Application to a Cancer Treatment Study(2021-12) White, John Benjamin; Yiannoutsos, Constantin; Bakoyannis, Giorgos; Fadel, WilliamThe crossing of Kaplan-Meier survival curves presents a challenge when conducting survival analysis studies, making it unclear whether any of the study groups involved present any significant difference in survival. An approach involving the determination of maximum vertical distance between the curves is considered here as a method to assess whether a survival advantage exists between different groups of patients. The method is illustrated on a dataset containing survival times of patients treated with two cancer treatment regimes, one involving treatment by chemotherapy alone, and the other by treatment with both chemotherapy and radiotherapy.Item Association Between Tobacco Related Diagnoses and Alzheimer Disease: A Population Study(2022-05) Almalki, Amwaj Ghazi; Zhang, Pengyue; Johnson, Travis; Fadel, WilliamBackground: Tobacco use is associated with an increased risk of developing Alzheimer's disease (AD). 14% of the incidence of AD is associated with various types of tobacco exposure. Additional real-world evidence is warranted to reveal the association between tobacco use and AD in age/gender-specific subpopulations. Method: In this thesis, the relationships between diagnoses related to tobacco use and diagnoses of AD in gender- and age-specific subgroups were investigated, using health information exchange data. The non-parametric Kaplan-Meier method was used to estimate the incidence of AD. Furthermore, the log-rank test was used to compare incidence between individuals with and without tobacco related diagnoses. In addition, we used semi-parametric Cox models to examine the association between tobacco related diagnoses and diagnoses of AD, while adjusting covariates. Results: Tobacco related diagnosis was associated with increased risk of developing AD comparing to no tobacco related diagnosis among individuals aged 60-74 years (female hazard ratio [HR] =1.26, 95% confidence interval [CI]: 1.07 – 1.48, p-value = 0.005; and male HR =1.33, 95% CI: 1.10 - 1.62, p-value =0.004). Tobacco related diagnosis was associated with decreased risk of developing AD comparing to no tobacco related diagnosis among individuals aged 75-100 years (female HR =0.79, 95% CI: 0.70 - 0.89, p-value =0.001; and male HR =0.90, 95% CI: 0.82 - 0.99, p-value =0.023). Conclusion: Individuals with tobacco related diagnoses were associated with an increased risk of developing AD in older adults aged 60-75 years. Among older adults aged 75-100 years, individuals with tobacco related diagnoses were associated with a decreased risk of developing AD.Item Association of Health Status and Nicotine Consumption with SARS-CoV-2 positivity rates(BMC, 2021-10) Duszynski, Thomas J.; Fadel, William; Wools-Kaloustian, Kara K.; Dixon, Brian E.; Yiannoutsos, Constantin; Halverson, Paul K.; Menachemi, Nir; Epidemiology, School of Public HealthBACKGROUND: Much of what is known about COVID-19 risk factors comes from patients with serious symptoms who test positive. While risk factors for hospitalization or death include chronic conditions and smoking; less is known about how health status or nicotine consumption is associated with risk of SARS-CoV-2 infection among individuals who do not present clinically. METHODS: Two community-based population samples (including individuals randomly and nonrandomly selected for statewide testing, n = 8214) underwent SARS-CoV-2 testing in nonclinical settings. Each participant was tested for current (viral PCR) and past (antibody) infection in either April or June of 2020. Before testing, participants provided demographic information and self-reported health status and nicotine and tobacco behaviors (smoking, chewing, vaping/e-cigarettes). Using descriptive statistics and a bivariate logistic regression model, we examined the association between health status and use of tobacco or nicotine with SARS-CoV-2 positivity on either PCR or antibody tests. RESULTS: Compared to people with self-identified "excellent" or very good health status, those reporting "good" or "fair" health status had a higher risk of past or current infections. Positive smoking status was inversely associated with SARS-CoV-2 infection. Chewing tobacco was associated with infection and the use of vaping/e-cigarettes was not associated with infection. CONCLUSIONS: In a statewide, community-based population drawn for SARS-CoV-2 testing, we find that overall health status was associated with infection rates. Unlike in studies of COVID-19 patients, smoking status was inversely associated with SARS-CoV-2 positivity. More research is needed to further understand the nature of this relationship.Item Clinical comparison and agreement of PCR, antigen, and viral culture for the diagnosis of COVID-19: Clinical Agreement Between Diagnostics for COVID19(Elsevier, 2022) Agard, Amanda; Elsheikh, Omar; Bell, Drew; Relich, Ryan F.; Schmitt, Bryan H.; Sadowski, Josh; Fadel, William; Webb, Douglas H.; Dbeibo, Lana; Kelley, Kristen; Carozza, Mariel; Lei, Guang-Shen; Calkins, Paul; Beeler, Cole; Medicine, School of MedicineThe aim of this study is to compare the COVID-19 nasopharyngeal PCR (NP PCR) to antigen, nasal PCR, and viral culture. One-hundred-and-fourteen risk-stratified patients were tested by culture, nasal PCR, NP PCR, and Ag testing. Twenty (48%) of the high risk and 23 (32%) of the low risk were NP PCR positive. Compared with NP PCR, the sensitivity of nasal PCR, Sofia Ag, BinaxNOW Ag, and culture were 44%, 31%, 37%, and 15%. In the high risk group, the sensitivity of these tests improved to 71%, 37%, 50%, and 22%. Agreement between tests was highest between nasal PCR and both antigen tests. Patients who were NP PCR positive but antigen negative were more likely to have remote prior COVID-19 infection (p<0.01). Nasal PCR and antigen positive patients were more likely to have symptoms (p = 0.01).Item The Great One Is Born: Wayne Gretzky's Monumental Season(2019-05) Ison, Tyler; Fadel, William; Lourens, Spencer; Zhang, YingStatistics and athletic sports have always had a strong connection that many critics, fans and statisticians utilize to determine how successful a team or an individual player might be over an entire season or even throughout one’s career. The success of a player or team is often characterized by investigating the consistency that has been shown throughout the season or career, which has led to more investigation of the streakiness of players. Studies have been done to examine great streaks, such as Joe DiMaggio’s 56 game hitting streak or Tiger Woods’ 142 consecutive cuts made streak, but what about the outstanding streak that occurred during the 1983-1984 NHL season? Wayne Gretzky, of the Edmonton Oilers, managed to showcase just how elite he was as a playmaker during that season. Gretzky produced a remarkable 51-game point streak, in which he recorded at least one goal or point in 51 consecutive games; a streak that has not received the recognition that it deserves. Using game-by-game data for the entire 1983-1984 NHL season for all players, the research looks at not only the evaluation of Gretzky’s streak, but also compares his production and streak to the remainder of the league. Gretzky demonstrated why he is one of the greatest players to ever step foot on the ice, and his elite status is shown throughout this analysis. Comparing Gretzky’s streak to that of DiMaggio’s was shown to be a little challenging but, some general conclusions were made based on the comparison of analyses that were performed; but without the proper statistics being readily available, it is hard to adequately dictate which streak is ultimately more impressive or more rare.Item Insights in Response to Statewide COVID-19 Sampling in Indiana(2023-05) Shields, David William, Jr.; Yiannoutsos, Constantin; Fadel, William; Bakoyannis, GiorgosDuring 2020, the Indiana State Department of Health conducted a longitudinal study of novel severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus, the cause of COVID-19 disease, to understand the number of past and current infections as well as the prevalence of disease in the State of Indiana by conducting a survey to participants as well as administering testing for exposure to SARS-COV-2. The study consisted of 3 waves of testing, each spread months apart, consisting of a random sample and a non-random sample. The non-random sample was used to ensure the sample population was representative of the state of Indiana and was used as stratum in the logistic regression model, allowing for the adjustment for nonresponse. These finding indicate that persons of non-White race and persons of Hispanic ethnicity had highest risk of exposure to the virus. Understanding the disparity in health in various racial and ethnic populations and addressing how different communities are impacted by the pandemic, as well as working with the community is paramount when attempting to mitigate a pandemic. In addition, understanding the data from the ambient pandemic when instituting measures to mitigate the spread of viruses is also extremely important for managing health emergencies such as the COVID-19 pandemic.Item Prediction of sustained harmonic walking in the free-living environment using raw accelerometry data(IOP Publishing, 2018-02-28) Urbanek, Jacek K.; Zipunnikov, Vadim; Harris, Tamara; Fadel, William; Glynn, Nancy; Koster, Annemarie; Caserotti, Paolo; Crainiceanu, Ciprian; Harezlak, Jaroslaw; Biostatistics, School of Public HealthOBJECTIVE: Using raw, sub-second-level accelerometry data, we propose and validate a method for identifying and characterizing walking in the free-living environment. We focus on sustained harmonic walking (SHW), which we define as walking for at least 10 s with low variability of step frequency. APPROACH: We utilize the harmonic nature of SHW and quantify the local periodicity of the tri-axial raw accelerometry data. We also estimate the fundamental frequency of the observed signals and link it to the instantaneous walking (step-to-step) frequency (IWF). Next, we report the total time spent in SHW, number and durations of SHW bouts, time of the day when SHW occurred, and IWF for 49 healthy, elderly individuals. MAIN RESULTS: The sensitivity of the proposed classification method was found to be 97%, while specificity ranged between 87% and 97% and the prediction accuracy ranged between 94% and 97%. We report the total time in SHW between 140 and 10 min d-1 distributed between 340 and 50 bouts. We estimate the average IWF to be 1.7 steps-per-second. SIGNIFICANCE: We propose a simple approach for the detection of SHW and estimation of IWF, based on Fourier decomposition.Item Spatial Transcriptomics Analysis Reveals Transcriptomic and Cellular Topology Associations in Breast and Prostate Cancers(2022-05) Alsaleh, Lujain; Johnson, Travis S.; Fadel, William; Tu, WanzhuBackground: Cancer is the leading cause of death worldwide and as a result is one of the most studied topics in public health. Breast cancer and prostate cancer are the most common cancers among women and men respectively. Gene expression and image features are independently prognostic of patient survival. However, it is sometimes difficult to discern how the molecular profile, e.g., gene expression, of given cells relate to their spatial layout, i.e., topology, in the tumor microenvironment (TME). However, with the advent of spatial transcriptomics (ST) and integrative bioinformatics analysis techniques, we are now able to better understand the TME of common cancers. Method: In this paper, we aim to determine the genes that are correlated with image topology features (ITFs) in common cancers which we denote topology associated genes (TAGs). To achieve this objective, we generate the correlation coefficient between genes and image features after identifying the optimal number of clusters for each of them. Applying this correlation matrix to heatmap using R package pheatmap to visualize the correlation between the two sets. The objective of this study is to identify common themes for the genes correlated with ITFs and we can pursue this using functional enrichment analysis. Moreover, we also find the similarity between gene clusters and some image features clusters using the ranking of correlation coefficient in order to identify, compare and contrast the TAGs across breast and prostate cancer ST slides. Result: The analysis shows that there are groups of gene ontology terms that are common within breast cancer, prostate cancer, and across both cancers. Notably, extracellular matrix (ECM) related terms appeared regularly in all ST slides. Conclusion: We identified TAGs in every ST slide regardless of cancer type. These TAGs were enriched for ontology terms that add context to the ITFs generated from ST cancer slides.Item Successive Wave Analysis to Assess Nonresponse Bias in a Statewide Random Sample Testing Study for SARS-CoV-2(Wolters Kluwer, 2022) Duszynski, Thomas J.; Fadel, William; Dixon, Brian E.; Yiannoutsos, Constantin; Halverson, Paul K.; Menachemi, Nir; Epidemiology, School of Public HealthIntroduction: Nonresponse bias occurs when participants in a study differ from eligible nonparticipants in ways that can distort study conclusions. The current study uses successive wave analysis, an established but underutilized approach, to assess nonresponse bias in a large-scale SARS-CoV-2 prevalence study. Such an approach makes use of reminders to induce participation among individuals. Based on the response continuum theory, those requiring several reminders to participate are more like nonrespondents than those who participate in a study upon first invitation, thus allowing for an examination of factors affecting participation. Methods: Study participants from the Indiana Population Prevalence SARS-CoV-2 Study were divided into 3 groups (eg, waves) based upon the number of reminders that were needed to induce participation. Independent variables were then used to determine whether key demographic characteristics as well as other variables hypothesized to influence study participation differed by wave using chi-square analyses. Specifically, we examined whether race, age, gender, education level, health status, tobacco behaviors, COVID-19-related symptoms, reasons for participating in the study, and SARS-CoV-2 positivity rates differed by wave. Results: Respondents included 3658 individuals, including 1495 in wave 1 (40.9%), 1246 in wave 2 (34.1%), and 917 in wave 3 (25%), for an overall participation rate of 23.6%. No significant differences in any examined variables were observed across waves, suggesting similar characteristics among those needing additional reminders compared with early participants. Conclusions: Using established techniques, we found no evidence of nonresponse bias in a random sample with a relatively low response rate. A hypothetical additional wave of participants would be unlikely to change original study conclusions. Successive wave analysis is an effective and easy tool that can allow public health researchers to assess, and possibly adjust for, nonresponse in any epidemiological survey that uses reminders to encourage participation.