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      Lower health-related quality of life predicts all-cause hospitalization among HIV-infected individuals

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          Abstract

          Background

          Health-related quality of life (HRQOL) is a patient-centered outcome measure used in assessing the individual’s overall functional health status but studies looking at HRQOL as a predictive tool are few. This work examines whether summary scores of HRQOL are predictive of all-cause hospitalization in the US Military HIV Natural History Study (NHS) cohort.

          Methods

          The Short Form 36 (SF-36) was administered between 2006 and 2010 to 1711 NHS cohort members whose hospitalization records we had also obtained. Physical component summary scores (PCSS) and mental component summary scores (MCSS) were computed based on standard algorithms. Terciles of PCSS and MCSS were generated with the upper terciles (higher HRQOL) as referent groups. Proportional hazards multivariate regression models were used to estimate the hazard of hospitalization for PCSS and MCSS separately (models 1 and 2, respectively) and combined (model 3).

          Results

          The hazard ratios (HR) of hospitalization were respectively 2.12 times (95% CI: 1.59–2.84) and 1.59 times (95% CI: 1.19–2.14) higher for the lower and middle terciles compared to the upper PCSS tercile. The HR of hospitalization was 1.33 times (95% CI: 1.02–1.73) higher for the lower compared to the upper MCSS tercile. Other predictors of hospitalization were CD4 count < 200 cells/mm 3 (HR = 2.84, 95% CI: 1.96, 4.12), CD4 count 200–349 cells/mm 3 (HR = 1.67, 95% CI: 1.24, 2.26), CD4 count 350–499 cells/mm 3 (HR = 1.41, 95% CI: 1.09, 1.83), plasma viral load > 50 copies/mL (HR = 1.82, 95% CI: 1.46, 2.26), and yearly increment in duration of HIV infection (HR = 0.94, 95% CI: 0.93, 0.96) (model 3).

          Conclusion

          After controlling for factors associated with hospitalization among those with HIV, both PCSS and MCSS were predictive of all-cause hospitalization in the NHS cohort. HRQOL assessment using the SF-36 may be useful in stratifying hospitalization risk among HIV-infected populations.

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          Most cited references28

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          Self-ratings of health: do they also predict change in functional ability?

          E. L. Idler, S V Kasl (1995)
          Self-ratings of health by individuals responding to surveys have shown themselves to be potent predictors of mortality in a growing number of studies; they appear to contribute significant additional independent information to health status indicators gathered through self-reported health histories or medical examinations. A key question raised by these studies is: What are the mediating processes involved in the association? Specifically, do poor self-ratings increase the risk of disability and morbidity, and are these outcomes intervening steps in the link to mortality? In this report we address the first question, of self-ratings predicting future levels of functional disability, our choice of an index of overall impact of morbidity. Data come from the New Haven Established Populations for Epidemiologic Studies of the Elderly (EPESE) site (N = 2,812). Results show that self-ratings of health in 1982, net of baseline functional ability, health and sociodemographic status, are associated with changes in functional ability over periods of one through six years. These findings extend our understanding of the meaning of excellent, good, fair, and poor ratings of health, and that they have implications not just for survival but for the loss or maintenance of functional ability in daily life.
          Article 0 comments Cited 156 times – based on 0 reviews     Review now
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            Variables with time-varying effects and the Cox model: Some statistical concepts illustrated with a prognostic factor study in breast cancer

            Carine Bellera, Gaetan MacGrogan, Marc Debled … (2010)
            Background The Cox model relies on the proportional hazards (PH) assumption, implying that the factors investigated have a constant impact on the hazard - or risk - over time. We emphasize the importance of this assumption and the misleading conclusions that can be inferred if it is violated; this is particularly essential in the presence of long follow-ups. Methods We illustrate our discussion by analyzing prognostic factors of metastases in 979 women treated for breast cancer with surgery. Age, tumour size and grade, lymph node involvement, peritumoral vascular invasion (PVI), status of hormone receptors (HRec), Her2, and Mib1 were considered. Results Median follow-up was 14 years; 264 women developed metastases. The conventional Cox model suggested that all factors but HRec, Her2, and Mib1 status were strong prognostic factors of metastases. Additional tests indicated that the PH assumption was not satisfied for some variables of the model. Tumour grade had a significant time-varying effect, but although its effect diminished over time, it remained strong. Interestingly, while the conventional Cox model did not show any significant effect of the HRec status, tests provided strong evidence that this variable had a non-constant effect over time. Negative HRec status increased the risk of metastases early but became protective thereafter. This reversal of effect may explain non-significant hazard ratios provided by previous conventional Cox analyses in studies with long follow-ups. Conclusions Investigating time-varying effects should be an integral part of Cox survival analyses. Detecting and accounting for time-varying effects provide insights on some specific time patterns, and on valuable biological information that could be missed otherwise.
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              Changing patterns of mortality across Europe in patients infected with HIV-1. EuroSIDA Study Group.

              J. Bruun, S Vella, P. Gargalianos … (1998)
              The introduction of combination antiretroviral therapy and protease inhibitors has led to reports of falling mortality rates among people infected with HIV-1. We examined the change in these mortality rates of HIV-1-infected patients across Europe during 1994-98, and assessed the extent to which changes can be explained by the use of new therapeutic regimens. We analysed data from EuroSIDA, which is a prospective, observational, European, multicentre cohort of 4270 HIV-1-infected patients. We compared death rates in each 6 month period from September, 1994, to March, 1998. By March, 1998, 1215 patients had died. The mortality rate from March to September, 1995, was 23.3 deaths per 100 person-years of follow-up (95% CI 20.6-26.0), and fell to 4.1 per 100 person-years of follow-up (2.3-5.9) between September, 1997, and March, 1998. From March to September, 1997, the death rate was 65.4 per 100 person-years of follow-up for those on no treatment, 7.5 per 100 person-years of follow-up for patients on dual therapy, and 3.4 per 100 person-years of follow-up for patients on triple-combination therapy. Compared with patients who were followed up from September, 1994, to March, 1995, patients seen between September, 1997, and March, 1998, had a relative hazard of death of 0.16 (0.08-0.32), which rose to 0.90 (0.50-1.64) after adjustment for treatment. Death rates across Europe among patients infected with HIV-1 have been falling since September, 1995, and at the beginning of 1998 were less than a fifth of their previous level. A large proportion of the reduction in mortality could be explained by new treatments or combinations of treatments.
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                Author and article information

                Contributors
                Leonard Emuren:
                ORCID: http://orcid.org/0000-0002-7294-9907
                leoemuren@yahoo.com
                Brian K. Agan: idcrp@idcrp.org
                Journal
                Journal ID (nlm-ta): Health Qual Life Outcomes
                Journal ID (iso-abbrev): Health Qual Life Outcomes
                Title: Health and Quality of Life Outcomes
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1477-7525
                Publication date (Electronic): 30 May 2018
                Publication date PMC-release: 30 May 2018
                Publication date Collection: 2018
                Volume: 16
                Electronic Location Identifier: 107
                Affiliations
                [1 ]ISNI 0000 0001 2181 3113, GRID grid.166341.7, Department of Epidemiology and Biostatistics, Dornsife School of Public Health, , Drexel University, ; Philadelphia, PA USA
                [2 ]ISNI 0000 0001 2182 3733, GRID grid.255414.3, Department of Pediatrics, , Eastern Virginia Medical School, ; Norfolk, VA USA
                [3 ]ISNI 0000 0004 0426 1259, GRID grid.414165.3, Children’s Hospital of the King’s Daughters, ; 601 Children’s Lane, Norfolk, VA 23507 USA
                [4 ]ISNI 0000 0001 0421 5525, GRID grid.265436.0, Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, , Uniformed Services University of the Health Sciences, ; Bethesda, MD USA
                [5 ]ISNI 0000 0004 0614 9826, GRID grid.201075.1, Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., ; Bethesda, MD USA
                Author information
                http://orcid.org/0000-0002-7294-9907
                Article
                Publisher ID: 931
                DOI: 10.1186/s12955-018-0931-x
                PMC ID: 5977458
                PubMed ID: 29848332
                SO-VID: 061940a2-756e-4c47-8edd-7fcf80930eac
                Copyright © © The Author(s). 2018
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                Date received : 25 October 2017
                Date accepted : 10 May 2018
                Funding
                Funded by: National Institute of Allergy and Infectitious Diseases, National Institutes of Health
                Award ID: Y1-AI-5072 (Inter-Agency Agreement)
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2018

                ScienceOpen disciplines: Health & Social care
                Keywords: hiv,human immunodeficiency virus,hrqol,health-related quality of life,haart,highly active antiretroviral therapy,pcss,physical component summary scores,mcss,mental component summary scores,hospitalization
                Data availability:
                ScienceOpen disciplines: Health & Social care
                Keywords: hiv, human immunodeficiency virus, hrqol, health-related quality of life, haart, highly active antiretroviral therapy, pcss, physical component summary scores, mcss, mental component summary scores, hospitalization

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