The effect of longitudinal body weight and CD4 cell progression for the survival of HIV/AIDS patients

Abstarct

It is about half a century since the HIV epidemic has been a menace to this world. Since then, several risk factors have been investigated for the prevalence of the disease, and the survival of Human Immunodeficiency Virus/Acquired Immune Deficiency Syndrome (HIV/AIDS) patients. The main purpose of the current study was to examine the current patient status in contrast with baseline facts and investigate the separate and joint effects of body weight and CD4 cell count progression for the survival of HIV/AIDS patients. A retrospective cohort study was conducted among HIV/AIDS patients, who were under Antiretroviral Therapy (ART) follow-up during 11 September 2013—5 September 2016 at Mekelle General Hospital, Ethiopia. A total of 216 HIV/AIDS patients were selected by using a systematic random sampling technique. Based on the complexity of the data and the desired objectives of the study, the authors have considered linear mixed-effects model (LMM) for continuous responses body weight and CD4 count, a Cox proportional hazard model for the survival outcome (time to death) and Joint model of longitudinal and survival outcome. The mean age, hemoglobin level, and body weight of HIV/AIDS patients at the start of ART were 34.8 years, 13.6 g/100 ml, and 49.2 kg, respectively. The average number of baseline CD4 cells count was 311.04 cells per mm³ with a standard deviation of 161 cells per mm³ of blood implying that patients were at a higher risk of getting HIV/AIDS-related illness. Out of 216 HIV/AIDS patients, 134 (62%) were female and 130 (60%) lived in an urban area. Similarly, among the sampled HIV/AIDS patients 23 (10.6%) were with HIV/TB co-infected. The present study has concerned on the comparison of separate and joint modeling. The results clearly demonstrate that the joint modeling of longitudinally CD4 count and weight measurements with survival outcomes fit the current dataset better than those obtained from the separate model, of course the authors realize in some specific cases both separate and joint analysis were consistent. However, the joint models were simpler as compared to the separate models as their effective member of parameters was smaller. In the analysis of joint modeling of longitudinal $\sqrt{CD4cell}$ and log (body-weight) progression with survival time to death of HIV/AIDS patients, considered various sub-models and various significant factors were identified. In the event process the sub-model, Baseline CD4, fair, and good adherence, HIV/Tuberculosis (TB), and sex were significant factors of risk to short survival Time-to-Death on HIV/AIDS patients. In the first longitudinal process sub-model, Baseline CD4, Ambulatory functional status, HIV/TB (yes), Time*Ambulatory functional status, Time*Working functional status, and Time*Baseline CD4 were the significant factors of $\sqrt{CD4cell}$ count progression. Moreover, In the second longitudinal process sub-model, visit time of follow-up, age, sex (male), baseline weight, Time*Ambulatory, and Time*Working functional status were the significant factors of log 10 (bodyweight) progression. In the present study, appropriate models were chosen and important significant factors also identified. Hence, the authors strongly suggest that special intervention, clinical practice, and health policy revision should be made on the risk factors that potentially determine the survival of HIV/AIDS patients.

Keywords:

• ART
• CD4 cell
• HIV/AIDS
• longitudinal data analysis
• statistical joint modeling

PUBLIC INTEREST STATEMENT

HIV is a major health problem worldwide despite enormous efforts to control its spread. This study would be used to the natural and most appropriate statistical models to study body weight & CD4 cell count progression on the survival time-to-death of HIV-infected patients under ART in which most efficient estimates would be obtained. Therefore, the importance of this study would have the most efficient statistical model to fit bodyweight & CD4 cell count progression on survival time-to-death of HIV-infected patients under ART follow-up. And also, it provides important information for both HIV patients and ART service providers (health experts) to give more attention and work on the risk factors that are responsible for a change in body weight & CD4 cell count on survival time-to-death of the HIV patients. It would also be useful to input other researchers who want to conduct research on a similar area/title.

Acknowledgements

The authors would like to express their profound gratitude to the Management of Mekelle General Hospital for unlimited access to the pertinent medical registers from which they could extract the data used for the current study. Moreover, the authors are highly thankful to University Gondar Postgraduate Program Directorate for subsidizing finance throughout the entire study.

Disclosure statement

The authors declare that they have no competing interests.

Ethics approval and consent to participate

Ethical clearance was obtained from the Ethical Review Committee of the University of Gondar College of Natural and Computational Science. The names of the subjects were not extracted to ensure the privacy of HIV/AIDS patients, and confidentiality was maintained throughout the data collection process and analysis. To collect the data, permission was obtained from administrative officers of Mekelle general hospital.

Data availability statement

The authors have considered HIV/AIDS datasets from Mekelle General Hospital patient history card and are now attached as supplementary materials of the submission system.

Authors’ contributions

GGG has made contributions on conceptualized the research problem, acquisition of data, designed the study, performed the statistical analysis, interpretation of data, and revised & drafting the manuscript. ZGA and DMC have played a great role in the re-vision of the research design, data analysis, manuscript write-up, editing the entire manuscript, and being ready for publication. Finally, all authors have read and approved the final manuscript before submission.

Additional information

Funding

This manuscript did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Notes on contributors

Dessie Melese Chekole

Mr. Dessie Melese is a lecturer at the University of Gondar, College of Natural and Computational Sciences, Department of Statistics, Gondar, Ethiopia. He graduated from the University of Gondar in Statistics (BSc in Statistics and MSc in Biostatistics). From August 2011 to June 2016, he served as a Junior Statistician at the Central Statistics Agency, Gondar Branch, Ethiopia. Currently, he works as a lecturer at the University of Gondar, Department of Statistics. His responsibilities are teaching different courses of statistics, consulting and advising students on the academic issues and on their senior research project, working on research and community service at both team and individual level, and strongly participating in different national and international conferences and giving/participating different advanced statistical software trainings. He has conducted more than nine research works, including the current on these areas.