Rapid declines in total lymphocyte counts and hemoglobin concentration prior to AIDS among HIV-1-infected men

Multicenter Study of Controlling Nutritional Status (CONUT) Score as a Prognostic Factor in Patients With HIV-Related Renal Cell Carcinoma

Objective

In recent years, the controlled nutritional status (CONUT) score has been widely recognized as a new indicator for assessing survival in patients with urological neoplasms, including renal, ureteral, and bladder cancer. However, the CONUT score has not been analyzed in patients with HIV-related urological neoplasms. Therefore, we aimed to evaluate the prognostic significance of the CONUT score in patients with HIV-related renal cell carcinoma (RCC).

Methods

A total of 106 patients with HIV-related RCC were recruited from four hospitals between 2012 and 2021, and all included patients received radical nephrectomy or partial nephrectomy. The CONUT score was calculated by serum albumin, total lymphocyte counts, and total cholesterol concentrations. Patients with RCC were divided into two groups according to the optimal cutoff value of the CONUT score. Survival analysis of different CONUT groups was performed by the Kaplan–Meier method and a log rank test. A Cox proportional risk model was used to test for correlations between clinical variables and cancer-specific survival (CSS), overall survival (OS), and disease-free survival (DFS). Clinical variables included age, sex, hypertension, diabetes, tumor grade, Fuhrman grade, histology, surgery, and CD4+ T lymphocyte count.

Result

The median age was 51 years, with 93 males and 13 females. At a median follow-up of 41 months, 25 patients (23.6%) had died or had tumor recurrence and metastasis. The optimal cutoff value for the CONUT score was 3, and a lower CONUT score was associated with the Fuhrman grade (P=0.024). Patients with lower CONUT scores had better CSS (HR 0.197, 95% CI 0.077-0.502, P=0.001), OS (HR 0.177, 95% CI 0.070-0.446, P<0.001) and DFS (HR 0.176, 95% CI 0.070-0.444, P<0.001). Multivariate Cox regression analysis indicated that a low CONUT score was an independent predictor of CSS, OS and DFS (CSS: HR=0.225, 95% CI 0.067-0.749, P=0.015; OS: HR=0.201, 95% CI 0.061-0.661, P=0.008; DFS: HR=0.227, 95% CI 0.078-0.664, P=0.007). In addition, a low Fuhrman grade was an independent predictor of CSS (HR 0.192, 95% CI 0.045-0.810, P=0.025), OS (HR 0.203, 95% CI 0.049-0.842, P=0.028), and DFS (HR 0.180, 95% CI 0.048-0.669, P=0.010), while other factors, such as age, sex, hypertension, diabetes, tumor grade, histology, surgery, and CD4+ T lymphocyte count, were not associated with survival outcome.

Conclusion

The CONUT score, an easily measurable immune-nutritional biomarker, may provide useful prognostic information in HIV-related RCC.

Patterns and rates of viral evolution in HIV-1 subtype B infected females and males

Biological sex differences affect the course of HIV infection, with untreated women having lower viral loads compared to their male counterparts but, for a given viral load, women have a higher rate of progression to AIDS. However, the vast majority of data on viral evolution, a process that is clearly impacted by host immunity and could be impacted by sex differences, has been derived from men. We conducted an intensive analysis of HIV-1 gag and env-gp120 evolution taken over the first 6–11 years of infection from 8 Women’s Interagency HIV Study (WIHS) participants who had not received combination antiretroviral therapy (ART). This was compared to similar data previously collected from men, with both groups infected with HIV-1 subtype B. Early virus populations in men and women were generally homogenous with no differences in diversity between sexes. No differences in ensuing nucleotide substitution rates were found between the female and male cohorts studied herein. As previously reported for men, time to peak diversity in env-gp120 in women was positively associated with time to CD4+ cell count below 200 (P = 0.017), and the number of predicted N-linked glycosylation sites generally increased over time, followed by a plateau or decline, with the majority of changes localized to the V1-V2 region. These findings strongly suggest that the sex differences in HIV-1 disease progression attributed to immune system composition and sensitivities are not revealed by, nor do they impact, global patterns of viral evolution, the latter of which proceeds similarly in women and men.

Evaluation of Non-Viral Surrogate Markers as Predictive Indicators for Monitoring Progression of Human Immunodeficiency Virus Infection: An Eight-Year Analysis in a Regional Center

Suitable methods for clinical monitoring of HIV-infected patients are crucial in resource-poor settings. Demographic data, clinical staging, and laboratory findings for 112 asymptomatic subjects positive for HIV were assessed at the first admission and the last visit from 2002 to 2010. Cox regression analysis showed hemoglobin (Hb) (HR = 0.643, P = 0.021) to be a predictive indicator for disease progression, while CD4, CD8, and platelet counts showed low HRs, despite having significant probability values. Hb and total lymphocyte count (TLC) rapidly declined from stage II to III (10.9 and 29.6%, respectively). Reduced CD4 and platelet counts and Hb during stage I were associated with disease progression, and TLC was correlated with CD4 counts at the last follow-up (P < 0.001). However, WHO TLC cutoff of 1,200 cell/mm(3) had 26.1% sensitivity and 98.6% specificity. ROC curve analysis suggested that a TLC cutoff of 1,800 cell/mm(3) was more reliable in this region. Statistical analysis and data mining findings showed that Hb and TLC, and their rapid decline from stage II to III, in addition to reduced platelet count, could be valuable markers for a surrogate algorithm for monitoring of HIV-infected subjects and starting anti-viral therapy in the absence of sophisticated detection assays.

Is total lymphocyte count a predictor for CD4 cell count in initiation antiretroviral therapy in HIV-infected patients?

BACKGROUND

Since laboratory assessments of HIV-infected patients by flow cytometric methods are expensive and unavailable in resource-limited countries, total lymphocyte count by haematology cell counter is supposed to be a suitable surrogate marker to initiate and monitor course of the disease in these patients. The aim of this study was to evaluate the utility of total lymphocyte count as a surrogate marker for CD4 count in HIV-infected patients.

PATIENTS AND METHODS

In a prospective study 560 HIV-positive individuals evaluated for total and CD4 lymphocyte count. For correlation between CD4 count and total lymphocyte count, haemoglobin and haematocrit we defined cut-off values as 200 cell/μl, 1200 cell/μl, 12 gr/dl and 30%, respectively, and compared CD4 count with each parameter separately. Positive predictive value, negative predictive value, sensitivity and specificity of varying total lymphocyte count cutoffs were computed for CD4 count ≤ 200 cell/μl and ≤ 350 cell/μl.

RESULTS

Strong degree of correlation was noted between CD4 and total lymphocyte count (r: 0.610, P < 0.001). Mean and standard deviation of total lymphocyte count, haemoglobin and haematocrit in relation to CD4 count were calculated which indicated significant correlation between these variables. Kappa coefficient for agreement was also calculated which showed fair correlation between CD4 200 cell/μl and total lymphocyte count 1200 cell/μl (0.35).

CONCLUSION

This study reveals that despite low sensitivity and specificity of total lymphocyte count as a surrogate marker for CD4, total lymphocyte count is of great importance and benefit in resource-limited settings.

Total lymphocyte count is a good marker for HIV-related mortality and can be used as a tool for starting HIV treatment in a resource-limited setting

OBJECTIVES

Total lymphocyte counts (TLC) may be used as an alternative for CD4 cell counts to monitor HIV infection in resource-limited settings, where CD4 cell counts are too expensive or not available.

METHODS

We used prospectively collected patient data from an urban HIV clinic in Indonesia. Predictors of mortality were identified via Cox regression, and the relation between TLC and CD4 cell counts was calculated by linear regression. Receiver operating characteristics (ROC) curves were used to choose the cut-off values of TLC corresponding with CD4 cell counts <200 and ≤350 cells/μl. Based on these analyses, we designed TLC-based treatment algorithms.

RESULTS

Of 889 antiretroviral treatment (ART)-naïve subjects included, 66% had CD4 cell counts <200 and 81% had 350 ≤ cells/μl at baseline. TLC and CD4 cell count were equally strong predictors of mortality in our population, where ART was started based on CD4 cell count criteria. The correlation coefficient (R) between TLC and √CD4 was 0.70. Optimal cut-off values for TLC to identify patients with CD4 cell counts <200 and ≤350 cells/μl were 1500 and 1700 cells/μl, respectively. Treatment algorithms based on a combination of TLC, gender, oral thrush, anaemia and body mass index performed better in terms of predictive value than WHO staging or TLC alone. In our cohort, such an algorithm would on average have saved $14.05 per patient.

CONCLUSION

Total lymphocyte counts is a good marker for HIV-associated mortality. Simple algorithms including TLC can prioritize patients for HIV treatment in a resource-limited setting, until affordable CD4 cell counts will be universally available.

Biomarkers predicting progression of human immunodeficiency virus-related disease

Biomarkers in predicting the progression of HIV infected individuals to a state of HIV disease (AIDS) are studied over more than a decade. Use of surrogate markers in the past for tracking clinical progression of the disease was limited, as little knowledge existed about the disease. The aim of this review was to address various changes in biomarker related studies taking place over the last five years, especially the trend towards use of newer biomarkers and experimentation with novel molecules in a quest for halting HIV disease progression. An open search of PUBMED database was made with search 'key words' such as 'Biomarkers' and 'AIDS (Acquired Immunodeficiency Syndrome)'.The following were the inclusion criteria for articles: a) all articles published in English language, b) years of publication between 2002-2008 and c) articles limited to adult population. This yielded a total of 417 articles. The criteria used for further judging these studies considered a) type of research design, b) number of biomarkers studied, c) validity of the biomarkers, d) techniques to assess the biomarkers and the impact of the studies in furthering biomarker research, e) sample size for the studies and f) article title or abstracts having the following key words 'biomarker' or 'biomarkers' and 'predict progression to AIDS'. A total of 27 abstracts were reviewed and 12 studies met the above criteria. These 12 different studies consisted of three reviews, four cohort designs, three cross-sectional designs, one each of an observational, and an in-vitro design. The various biomarkers emerging as a results were primarily a mix of viral, neural, immunological, HLA (human leukocyte antigen) markers along with lymphocyte counts. Although there have been quite a few advancements in biomarker-related studies, majority of the novel biomarkers discovered need to be further evaluated and replicated in bigger, long-term efficacy trials. Efforts should also be made to discover newer genetic markers of disease progression. Biomarker feedback, a new concept, can be utilized in future studies addressing prevention of HIV infection or halting disease progression.

Evaluation of human immunodeficiency virus biomarkers: inferences from interval and clinical cohort studies

INTRODUCTION

Among individuals infected with the human immunodeficiency virus (HIV), biomarkers that predict mortality are also used to determine the time when antiretroviral therapy is initiated. No studies have evaluated the impact of the frequency of marker measurements for either their predictive value of mortality or how they may influence inference of the effect of therapy initiation in analyses from observational data.

METHODS

We identified 244 persons who were contemporaneously enrolled in both the AIDS Link to the IntraVenous Experience (an interval cohort) and the Johns Hopkins HIV Clinical Cohort between 1995 and 2004. Data from each study were used separately in 2 ways. We applied time-dependent proportional hazards models to examine the predictive associations between markers and mortality, and marginal structural models to examine the causal inference of therapy on mortality. Biomarkers were used to derive the inverse probability weights.

RESULTS

The timing frequencies of marker measurements in the interval cohort (CD4 interquartile range = 175-194 days) were less heterogeneous than in the clinical cohort (interquartile range = 38-121 days). Despite this, the results were concordant for CD4 (R = 0.537 [95% confidence interval = 0.345-0.707] and (R = 0.488 [0.297-0.666], respectively). Similar concordance was found for the HIV-1 RNA and hemoglobin analyses. When evaluating the causal effect of highly active antiretroviral therapy (HAART), the relative hazards were 0.34 for the interval cohort study (95% CI = 0.15-0.77) and 0.27 for the clinical cohort study (0.11-0.66).

CONCLUSION

Utilizing a unique co-enrollment of patients in 2 different types of cohort studies, we find empirical evidence that inferences drawn from these different structures are similar.

Variation in protein levels obtained from human blood cells and biofluids for platelet, peripheral blood mononuclear cell, plasma, urine and saliva proteomics

Blood cells and biofluid proteomics are emerging as a valuable tool to assess effects of interventions on health and disease. This study is aimed to assess the amount and variability of proteins from platelets, peripheral blood mononuclear cells (PBMC), plasma, urine and saliva from ten healthy volunteers for proteomics analysis, and whether protein yield is affected by prolonged fasting. Volunteers provided blood, saliva and morning urine samples once a week for 4 weeks after an overnight fast. Volunteers were fasted for a further 24 h after the fourth sampling before providing their final samples. Each 10 mL whole blood provided 400-1,500 mug protein from platelets, and 100-600 mug from PBMC. 30 muL plasma depleted of albumin and IgG provided 350-650 mug protein. A sample of morning urine provided 0.9-8.6 mg protein/dL, and a sample of saliva provided 70-950 mug protein/mL. None of these yields were influenced by the degree of fasting (overnight or 36 h). In conclusion, in contrast to the yields from plasma, platelets and PBMC, the protein yields of urine and saliva samples were highly variable within and between subjects. Certain disease conditions may cause higher or lower PBMC counts and thus protein yields, or increased urinary protein levels.

Correlation analysis on total lymphocyte count and CD4 count of HIV-infected patients

OBJECTIVE

To determine the relationship between CD4 count and other blood indices and to explore the prediction of total lymphocyte count (TLC) for CD4 count in HIV-infected patients.

METHODS

Cross-sectional study was performed for the prediction of TLC and other indices for CD4 count, and historical cohort study was performed for the TLC changes as a surrogate for CD4 changes of patients on antiretroviral therapy (ART) to further understanding the utility of TLC changes for AIDS patients' management.

RESULTS

In our cross-sectional study, both TLC and white blood corpuscle count positively correlated to CD4 count, but differed in these patients. For patients on ART, the prediction of TLC for CD4 count is better than that of patient without ART. Further investigation of historical cohort study indicated that, among AIDS patients on highly active antiretroviral therapy, their TLC and haemoglobin changes also positively correlated to CD4 change, with a total correlation coefficient of 0.31 (p < 0.01) and 0.19 (p < 0.01) respectively. The prediction of TLC change for CD4 change differed each time point when patients underwent ART.

CONCLUSIONS

Total lymphocyte count and its change can be used as alternative in conjunction with other indices to CD4 count and its change in the management of HIV-infected individuals in China.

Complete blood cell count as a surrogate CD4 cell marker for HIV monitoring in resource-limited settings

BACKGROUND

A total lymphocyte count (TLC) of 1200 cells/mL has been used as a surrogate for a CD4 count of 200 cells/microL in resource-limited settings with varying results. We developed a more effective method based on a decision tree algorithm to classify subjects.

METHODS

A decision tree was used to develop models with the variables TLC, hemoglobin, platelet count, gender, body mass index, and antiretroviral treatment status of subjects from the University of Alabama at Birmingham (UAB) observational database. Models were validated on data from the Birmingham Veterans Affairs Medical Center (BVAMC) and Zambia, with primary decision trees also generated from these data.

RESULTS

A total of 1189 patients from the UAB observational database were included. The UAB decision tree classified a CD4 count < or =200 cells/microL as better than a TLC cut-point of 1200 cells/mL, based on the area under the curve of the receiver-operator characteristic curve (P < 0.0001). When applied to data from the BVAMC and Zambia, the UAB-based decision tree performed better than the TLC cut-point of 1200 cells/mL (BVAMC: P < 0.0001; Zambia: P = 0.0009) but worse than a decision tree based on local data (BVAMC: P < or = 0.0001; Zambia: P < or = 0.0001).

CONCLUSION

A decision tree algorithm based on local data identifies low CD4 cell counts better than one developed from a different population or a TLC cut-point of 1200 cells/mL.

Comorbidities and mortality among children hospitalized with diarrheal disease in an area of high prevalence of human immunodeficiency virus infection

PURPOSE

To describe the profile of comorbidities in children admitted with diarrhea to an urban hospital with high human immunodeficiency virus (HIV) prevalence in South Africa and to examine the contribution of comorbidities to inpatient mortality.

METHODS

Data from a retrospective random sample of 319 children were extracted and analyzed from a total of 1145 children hospitalized for diarrhea in 2001. We used multiple logistic regression models to determine the independent effects of HIV infection, malnutrition, pneumonia and bacteremia on inpatient mortality.

RESULTS

Overall 68% of the diarrheal admissions were classified as HIV-infected and 61% were classified as malnourished, with 53% having evidence of both. HIV infection was strongly associated with malnutrition, pneumonia and bacteremia. Inpatient mortality was 14% [95% confidence interval (CI), 11-19%]. Mortality was higher among HIV-infected than among uninfected children [crude odds ratio (OR), 6.0; 95% CI 2.1-17.0]. History of low birth weight, previous admission, malnutrition, HIV infection, pneumonia, bacteremia, low hemoglobin, total white blood cell count and serum albumin were significant predictors of mortality in univariate analyses. After adjustment, severe malnutrition (OR 2.1; 95% CI 1.0-4.9), bacteremia (OR 2.9; 95% CI 1.2-7.2) and pneumonia (OR 3.9; 95% CI 1.3-12.0) remained independent predictors of mortality, whereas the association between HIV infection and mortality was significantly diminished (OR 4.0; 95% CI 0.8-18.1).

CONCLUSION

In a setting of high HIV prevalence, malnutrition, bacteremia and pneumonia contribute independently to death in children hospitalized with diarrheal disease.

Disease Progression Among Untreated HIV-Infected Patients in South Ethiopia: Implications for Patient Care

CONTEXT

The natural course of HIV disease progression among resource-poor patient populations has not been clearly defined.

OBJECTIVE

To describe predictors of HIV disease progression as seen at an outpatient clinic in a resource-limited setting in rural Ethiopia.

DESIGN

This prospective cohort study included all adult HIV patients who visited an outpatient clinic at Arba Minch hospital in South Ethiopia between January 30, 2003 and April 1, 2004. Clinical and hematologic measurements were done at baseline and every 12 weeks thereafter until the patient was transferred, put on antiretroviral therapy, was lost to follow-up, or died. Community agents reported patient status every month.

SETTING

A district hospital with basic facilities for HIV testing and patient monitoring.

MAIN OUTCOME MEASURES

Death, diagnosis of tuberculosis, and change in disease stage.

RESULTS

We followed 207 patients for a median duration of 19 weeks (range, 0-60 weeks). A total of 132 (64%) of them were in WHO stage III. The overall mortality rate was 46 per 100 person-years of observation (PYO). Mortality increased with advancing disease stage. Diarrhea, oral thrush, and low total lymphocyte count were significant markers of mortality. The incidence of tuberculosis was 9.9 per 100 PYO. Baseline history of easy fatigability and fever were strongly associated with subsequent development of tuberculosis.

CONCLUSION

The mortality rate and the incidence of tuberculosis in our cohort are among the highest ever reported in sub-Saharan Africa. We identified oral thrush, diarrhea, and total lymphocyte count as predictors of mortality, and easy fatigability and fever as predictors of tuberculosis. The findings have practical implications for patient care in resource-limited settings.

Application of case-crossover and case-time-control study designs in analyses of time-varying predictors of T-cell homeostasis failure

PURPOSE

To evaluate the association of sexual behavior and recreational drug exposures with T-cell homeostasis failure (TCHF), which corresponds to the onset of a rapid decline in an individual's T lymphocyte count, which occurs on average approximately 1.75 years prior to an initial diagnosis of acquired immunodeficiency syndrome (AIDS).

METHODS

A case-crossover design and a case-time-control design, both nested within the Multicenter AIDS Cohort Study of 4954 homosexual and bisexual men initiated in 1983.

RESULTS

In the case-crossover analysis, use of both recreational drugs and hashish were found to be protective against TCHF (odds ratios < or = 0.41), based on comparisons with four earlier control periods. However, a significant decreasing trend in the prevalence of these exposures was observed over time, thus motivating the implementation of the case-time-control design. Using the latter approach, the associations of drug use (odds ratio=0.53; 95% confidence interval (CI): 0.22, 1.28) and hashish use (odds ratio=0.46; 95% CI: 0.20, 1.05) with TCHF were no longer statistically significant.

CONCLUSIONS

The difference in inferences between these approaches demonstrates the importance of evaluating temporal trends in exposures when using a case-crossover design.

Changes in Total Lymphocyte Count as a Surrogate for Changes in CD4 Count Following Initiation of HAART: Implications for Monitoring in Resource-Limited Settings

BACKGROUND

A major obstacle to the administration of highly active antiretroviral therapy (HAART) in resource-limited settings is the high cost of CD4 count testing. The total lymphocyte count (TLC) has been proposed as a surrogate marker to monitor immune response to therapy.

OBJECTIVE

To assess, in a developed country setting, the capability and clinical utility of TLC change as a surrogate marker for CD4 count change in monitoring patients on HAART.

METHODS

Longitudinal co-variation between changes in TLC and concomitant changes in CD4 count following the initiation of HAART was examined using a retrospective cohort study of 126 HIV-positive patients attending The Miriam Hospital, Brown University, Providence, RI. Analyses included evaluation of the direction of TLC change as a marker for direction of CD4 change, using sensitivity and specificity; evaluation of absolute change in TLC as a marker for benchmark changes in CD4 (> or =50 over 6 months, > or =100 over 12 months), using receiver-operator characteristic (ROC) curves; and a regression model of change in TLC as a function of change in CD4, to understand within-individual variation of longitudinal TLC measures.

RESULTS

In the first 24 months of HAART, the sensitivity of a TLC increase as a marker for CD4 count increase over the same time period ranged from 86-94%, and the specificity ranged from 80-85%. The median change in TLC among patients with a CD4 count rise of > or =100 cells/mm at 1 year of HAART was +766 cells/mm while that of patients with a CD4 count rise of <100 cells/m was +100 cells/mm. The area under the corresponding ROC curve was 0.89, suggesting that change in TLC discriminates well between those with 1-year CD4 change of > or =100 vs. those with change <+100. From a regression analysis, we found that mean change in TLC per 1 cell/mm change in CD4 count was 7.3 (SE 1.2, P < 0.001). The degree of this association varied from individual to individual but was positive for all individuals.

CONCLUSIONS

Within the first 2 years of HAART, the direction of change in TLC appears to be a strong marker for direction of concomitant change in CD4 count (sensitivity 86-94% and specificity 80-85%, depending on length of interval). Positive and negative predictive values depend on the proportion of CD4 changes that are positive. In this cohort, that proportion is 87.9%, which yields high positive predictive value (96-98%) but lower negative predictive value (43-63%). Findings from the regression model suggest that taking multiple measurements of TLC at more frequent intervals may reduce variability and potentially improve predictive accuracy.