On the assessment of various factors effecting the improvement in CD4 count of aids patients undergoing antiretroviral therapy using generalized Poisson regression

Grover, Gurprit; Ravi, Vadlamani; Swain, Prafulla Kumar

doi:10.1080/02664763.2014.999649

Cited by 12 publications

(10 citation statements)

References 22 publications

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“…Therefore, modeling and analysis of factors affecting the number of CD4 cells in AIDS research is important. Several generalized linear models are available for modeling the counting data including Poisson and Negative Binomial (NB) as well as Generalized Poisson regression models (GPR) [ 12 , 19 , 24 – 26 ]. In recent years, these models have been used extensively in epidemiology and health studies [ 12 , 19 , 26 – 28 ].…”

Section: Introductionmentioning

confidence: 99%

Factors related to baseline CD4 cell counts in HIV/AIDS patients: comparison of poisson, generalized poisson and negative binomial regression models

et al. 2021

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Objective CD4 Lymphocyte Count (CD4) is a major predictor of HIV progression to AIDS. Exploring the factors affecting CD4 levels may assist healthcare staff and patients in management and monitoring of health cares. This retrospective cohort study aimed to explore factors associated with CD4 cell counts at the time of diagnosis in HIV patients using Poisson, Generalized Poisson, and Negative Binomial regression models. Results Out of 4402 HIV patients diagnosis in Iran from 1987 to 2016, 3030 (68.8%) were males, and the mean age was 34.8 ± 10.4 years. The results indicate that the Negative Binomial model outperformed the other models in terms of AIC, log-likelihood and RMSE criteria. In this model, factors include sex, age, clinical stage and Tuberculosis (TB) co-infection were significantly associated with CD4 count (P < 0.05). Conclusion Given the effect of age, sex, clinical stage and stage of HIV on CD4 count of the patients, adopting policies and strategies to increase awareness and encourage people to seek early HIV testing and care is advantageous.

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Section: Introductionmentioning

confidence: 99%

Factors related to baseline CD4 cell counts in HIV/AIDS patients: comparison of poisson, generalized poisson and negative binomial regression models

et al. 2021

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“…The changes in the CD4 + cell counts are important indicators of the response to ART. Initial CD4 + cell count, age, gender, smoking, unemployment, WHO stage, hospital, opportunistic infections, body mass index, changing doctors during outpatient follow up, use of alcohol and drugs, and duration of treatment (in months) are some of the significant determinants that affect CD4 + cell count progression of patients on ART (3)(4)(5).…”

Section: Introductionmentioning

confidence: 99%

Progression of HIV Disease Among Patients on ART in Ethiopia: Application of Longitudinal Count Models

Andualem

Ayele

2020

Front. Public Health

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Although the world has been fighting HIV disease in unity and patients are getting antiretroviral therapy treatment, HIV disease continues to be a serious health issue for some parts of the world. A large number of AIDS-related deaths and co-morbidities are registered every year in resource-limited countries like Ethiopia. Most studies that have assessed the progression of the disease have used models that required a continuous response. The main objective of this study was to make use of appropriate statistical models to analyze routinely collected HIV data and identify risk factors associated with the progression of the CD4 + cell count of patients under ART treatment in Debre Markos Referral Hospital, Ethiopia. In this longitudinal retrospective study, routine data of 445 HIV patients registered for ART treatment in the Hospital were used. As overdispersion was detected in the data, and Poisson-Gamma, Poisson-Normal, and Poisson-Gamma-Normal models were applied to account for overdispersion and correlation in the data. The Poisson-Gamma-Normal model with a random intercept was selected as the best model to fit the data. The findings of the study revealed the time on treatment, sex of patients, baseline WHO stage, and baseline CD4 + cell count as significant factors for the progression of the CD4 + cell count.

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“…Derives some traits from quasi-likelihood, but it should be noted that this theory assumes that ϕ is known [27]. With this assumption, it is seen that quasilikelihood is the actual log likelihood if and only if the response yi comes from an exponential family model with parameter-one (GLM family with ϕ = 1) [28]. The algorithm for estimating Quasi-Poisson regression parameters can be expressed as the iterative weighted least square (IWLS).…”

Section: Quasi-poisson Regressionmentioning

confidence: 99%

Overcoming Overdispersion on Direct Mathematics Learning Model Using the Quasi Poisson Regression

Hartono¹,

Tinungki²,

Jakaria³

et al. 2021

Advances in Social Science, Education and Humanities Research

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The study aims to overcome the overdispersion in the final exam score of Calculus subject. The occurrence of a gap in the score is inseparable from the influence of internal factors and external factors. The internal factors are factors that originate within students themselves. In contrast, external factors are factors that exist outside of students that can affect students' success or failure, such as learning environment, the physical environment where the exam takes place, infrastructure and facility that are owned and used by students, and their condition during the exam. The connection of these factors to the gap in final exam scores can be approached with Poisson regression analysis because Poisson Regression assumes a Poisson distribution of response variables with equidispersion. It is necessary to conduct a research to find out the factors that cause the diversity of the final score in order to overcome, that is by implementing direct learning. The results obtained show that with the application of direct mathematics learning, there is no overdispersion, while the low score of the final exam results in an increase, resulting in the variance of final exam results to be smaller than the average score.

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On the assessment of various factors effecting the improvement in CD4 count of aids patients undergoing antiretroviral therapy using generalized Poisson regression

Cited by 12 publications

References 22 publications

Factors related to baseline CD4 cell counts in HIV/AIDS patients: comparison of poisson, generalized poisson and negative binomial regression models

Factors related to baseline CD4 cell counts in HIV/AIDS patients: comparison of poisson, generalized poisson and negative binomial regression models

Progression of HIV Disease Among Patients on ART in Ethiopia: Application of Longitudinal Count Models

Overcoming Overdispersion on Direct Mathematics Learning Model Using the Quasi Poisson Regression

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