Total Lymphocyte Count as surrogate marker for CD4 Cell Count in HIV-Infected Individuals in Gondar University Hospital, Northwest Ethiopia

Robust approach to combining multiple markers to improve surrogacy

Identifying effective and valid surrogate markers to make inference about a treatment effect on long-term outcomes is an important step in improving the efficiency of clinical trials. Replacing a long-term outcome with short-term and/or cheaper surrogate markers can potentially shorten study duration and reduce trial costs. There is sizable statistical literature on methods to quantify the effectiveness of a single surrogate marker. Both parametric and nonparametric approaches have been well developed for different outcome types. However, when there are multiple markers available, methods for combining markers to construct a composite marker with improved surrogacy remain limited. In this paper, building on top of the optimal transformation framework of Wang et al. (2020), we propose a novel calibrated model fusion approach to optimally combine multiple markers to improve surrogacy. Specifically, we obtain two initial estimates of optimal composite scores of the markers based on two sets of models with one set approximating the underlying data distribution and the other directly approximating the optimal transformation function. We then estimate an optimal calibrated combination of the two estimated scores which ensures both validity of the final combined score and optimality with respect to the proportion of treatment effect explained by the final combined score. This approach is unique in that it identifies an optimal combination of the multiple surrogates without strictly relying on parametric assumptions while borrowing modeling strategies to avoid fully nonparametric estimation which is subject to the curse of dimensionality. Our identified optimal transformation can also be used to directly quantify the surrogacy of this identified combined score. Theoretical properties of the proposed estimators are derived, and the finite sample performance of the proposed method is evaluated through simulation studies. We further illustrate the proposed method using data from the Diabetes Prevention Program study.

Age-stratified pediatric reference values of lymphocytes in the Moroccan population

The number of circulating lymphocytes is altered in a number of diseases including either increase (lymphocytosis) or decrease (lymphocytopenia). Therefore, the assessment of total blood lymphocyte numbers and the relative distribution of lymphocyte subsets is a critical front-line tool in the clinical diagnosis of a number of diseases, including pediatric diseases and disorders. However, the interpretation of this data requires comparison of patient's results to reliable reference values. Blood lymphocyte subpopulation numbers are also subject to genetic polymorphisms, immunogenic and environmental factors and vary greatly between populations. While the best practice reference values should be established within local representative populations of healthy subjects, to date, Caucasian reference values are used in Morocco due to the absence of indigenous reference values. Potential differences in blood lymphocyte subpopulation reference values between Caucasian versus Moroccan populations can adversely affect the diagnosis of pediatric and childhood diseases and disorders such as primary immunodeficiency (PID) in Morocco.

OBJECTIVE

The aim of this study was to establish the age-stratified normal reference values of blood lymphocyte subsets for the pediatric Moroccan population.

METHODS

We measured the concentration of lymphocyte subpopulations by flow cytometry from 83 Moroccan healthy subjects stratified into 5 age groups of 0-1, 1-2, 2-6, 6-12 and > 12-18 (adult).

RESULTS

The absolute and relative amounts of the main lymphocyte subsets of T-cells, B cells and Natural Killer (NK) cells were measured and compared to previously described reference values from Cameroonian, Turkish, American and Dutch populations. Additionally, we also observed an age-related decline in the absolute population sizes of lymphocyte subsets within our study group. Relative proportions of CD3+CD4+ helper T lymphocytes decreased with increasing age and by 12 years-adult age, both proportions of CD3+CD4+ helper T lymphocytes and CD3+CD8+ cytotoxic T lymphocytes, as well as CD3-CD19+ B lymphocytes were also decreased. Finally, we compared the median values and range of our Moroccan study group with that of published results from Cameroon, Turkey, USA and Netherlands and observed significant differences in median and mean values of absolute number and relative proportions of lymphocyte subsets especially at 0-1 years and 1-2 years age groups. Above age 12 years, the Moroccan values were lower. For NK cells, the Moroccan values are also lower.

CONCLUSIONS

The results of this study have a significant impact in improving the threshold values of the references intervals routinely used in the diagnosis of paediatric diseases such as PIDs or mother-to-child transmitted HIV within the Moroccan population.

Modelling of viral load dynamics and CD4 cell count progression in an antiretroviral naive cohort: using a joint linear mixed and multistate Markov model

Background

Patients infected with HIV may experience a succession of clinical stages before the disease diagnosis and their health status may be followed-up by tracking disease biomarkers. In this study, we present a joint multistate model for predicting the clinical progression of HIV infection which takes into account the viral load and CD4 count biomarkers.

Methods

The data is from an ongoing prospective cohort study conducted among antiretroviral treatment (ART) naïve HIV-infected women in the province of KwaZulu-Natal, South Africa. We presented a joint model that consists of two related submodels: a Markov multistate model for CD4 cell count transitions and a linear mixed effect model for longitudinal viral load dynamics.

Results

Viral load dynamics significantly affect the transition intensities of HIV/AIDS disease progression. The analysis also showed that patients with relatively high educational levels (β = − 0.004; 95% confidence interval [CI]:-0.207, − 0.064), high RBC indices scores (β = − 0.01; 95%CI:-0.017, − 0.002) and high physical health scores (β = − 0.001; 95%CI:-0.026, − 0.003) were significantly were associated with a lower rate of viral load increase over time. Patients with TB co-infection (β = 0.002; 95%CI:0.001, 0.004), having many sex partners (β = 0.007; 95%CI:0.003, 0.011), being younger age (β = 0.008; 95%CI:0.003, 0.012) and high liver abnormality scores (β = 0.004; 95%CI:0.001, 0.01) were associated with a higher rate of viral load increase over time. Moreover, patients with many sex partners (β = − 0.61; 95%CI:-0.94, − 0.28) and with a high liver abnormality score (β = − 0.17; 95%CI:-0.30, − 0.05) showed significantly reduced intensities of immunological recovery transitions. Furthermore, a high weight, high education levels, high QoL scores, high RBC parameters and being of middle age significantly increased the intensities of immunological recovery transitions.

Conclusion

Overall, from a clinical perspective, QoL measurement items, being of a younger age, clinical attributes, marital status, and educational status are associated with the current state of the patient, and are an important contributing factor to extend survival of the patients and guide clinical interventions. From a methodological perspective, it can be concluded that a joint multistate model approach provides wide-ranging information about the progression and assists to provide specific dynamic predictions and increasingly precise knowledge of diseases.

Evaluation of Individual and Combined Markers of Urine Dipstick Parameters and Total Lymphocyte Count as a Substitute for CD4 Count in Low-Resource Communities in Ghana

We evaluated the individual and combined levels of urine dipstick and total lymphocyte count (TLC) as surrogate markers for CD4 count in a low-resource community in Ghana. This cross-sectional study recruited 200 HIV-infected patients from the Saint Francis Xavier Hospital, Assin Fosu, Ghana. Complete blood count, CD4 count, and urine dipstick analysis were measured for participants. The threshold values were determined as <350 cells/μl for CD4, <1200 cells/μl for TLC, and ≥+ on urine dipstick analysis. The mean age of participants was 43.09 years. Proteinuria ≥ + [aOR = 4.30 (3.0–18.5)], leukocyturia ≥ + [aOR = 2.91 (1.33–12.5)], hematuria ≥ + [aOR = 2.30 (1.08–9.64)], and TLC < 1200 cells/μl [aOR = 3.26 (3.94–15.29)] were significantly associated with increased risk of CD4 count < 350 cells/μl. Using the individual markers, the best substitute marker for predicting CD4 count < 350 cells/μl was proteinuria at a cutoff point ≥ 2++, AUC of 0.973, sensitivity of 97.6%, specificity of 100.0%, PPV of 100.0%, and NPV of 89.1%. A combination of ≤ 1200 TLC + ≥ 2++ (leukocyturia + proteinuria + hematuria) yielded an AUC of 0.980, sensitivity (72.8%), specificity (100.0%), PPV (100.0%), and NPV (97.9%). Proteinuria could serve as a noninvasive screening tool, but the combination of proteinuria, leukocyturia, hematuria, and TLC serves as a better substitute marker for CD4 count in monitoring the disease progression among HIV patients in low-resource communities.

Costs of HIV/AIDS treatment in Indonesia by time of treatment and stage of disease

BACKGROUND

We report an economic analysis of Human Immunodeficiency Virus (HIV) care and treatment in Indonesia to assess the options and limitations of costs reduction, improving access, and scaling up services.

METHODS

We calculated the cost of providing HIV care and treatment in a main referral hospital in West Java, Indonesia from 2008 to 2010, differentiated by initiation of treatment at different CD4 cell count levels (0-50, 50-100, 100-150, 150-200, and >200 cells/mm(3)); time of treatment; HIV care and opportunistic infections cost components; and the costs of patients for seeking and undergoing care.

DISCUSSION

Before antiretroviral treatment (ART) initiation, costs were dominated by laboratory tests (>65 %), and after initiation, by antiretroviral drugs (≥60 %). Average treatment costs per patient decreased with time on treatment (e.g. from US$580 per patient in the first 6 month to US$473 per patient in months 19-24 for those with CD4 cell counts under 50 cells/mm(3)). Higher CD4 cell counts at initiation resulted in lower laboratory and opportunistic infection treatment costs. Transportation cost dominated the costs of patients for seeking and undergoing care (>40 %).

CONCLUSIONS

Costs of providing ART are highest during the early phase of treatment. Costs reductions can potentially be realized by early treatment initiation and applying alternative laboratory tests with caution. Scaling up ART at the community level in certain high prevalence settings may improve early uptake, adherence, and reduce transportation costs.

Serum Adenosine Deaminase (ADA) Activity: A Novel Screening Test to Differentiate HIV Monoinfection From HIV-HBV and HIV-HCV Coinfections

BACKGROUND

CD4(+) cell count, the common HIV infection screening test, is costly and unable to differentiate HIV monoinfection from its concurrent infection with hepatitis B or C virus. We aimed to ascertain diagnostic value of serum adenosine deaminase (ADA) activity as a useful tool to differentiate HIV mono- and co-infection.

METHODS

Blood samples were collected from 30 HIV-HBV and 30 HIV-HCV coinfected patients, 33 HIV positive subjects, and 72 controls. CD4(+) cell count, serum total ADA (tADA), and ADA1, and ADA2 isoenzyme activities were determined and their sensitivity and specificity were computed.

RESULTS

tADA and ADA2 activities were significantly higher and CD4(+) counts were markedly lower in all patients compared with controls. Strong inverse agreements between CD4(+) cell counts and both tADA and ADA2 activities were observed. Serum tADA and ADA1 activities showed the highest specificity and the highest sensitivity, respectively, for differentiating HIV monoinfection from HIV-HBV and HIV-HCV coinfections.

CONCLUSIONS

We showed strong agreement and correlation between CD4(+) cell count and ADA enzyme activity. Based on high ADA sensitivity and specificity, it is concluded that determination of ADA activity might be a novel diagnostic tool to distinguish of HIV monoinfection from its coinfection with HBV or HCV.

Evaluation of treatment outcomes for patients on first-line regimens in US President's Emergency Plan for AIDS Relief (PEPFAR) clinics in Uganda: predictors of virological and immunological response from RV288 analyses

OBJECTIVES

Viral load (VL) monitoring is recommended, but seldom performed, in resource-constrained countries. RV288 is a US President's Emergency Plan for AIDS Relief (PEPFAR) basic programme evaluation to determine the proportion of patients on treatment who are virologically suppressed and to identify predictors of virological suppression and recovery of CD4 cell count. Analyses from Uganda are presented here.

METHODS

In this cross-sectional, observational study, patients on first-line antiretroviral therapy (ART) (efavirenz or nevirapine+zidovudine/lamivudine) from Kayunga District Hospital and Kagulamira Health Center were randomly selected for a study visit that included determination of viral load (HIV-1 RNA), CD4 cell count and clinical chemistry tests. Subjects were recruited by time on treatment: 6-12, 13-24 or >24 months. Logistic regression modelling identified predictors of virological suppression. Linear regression modelling identified predictors of CD4 cell count recovery on ART.

RESULTS

We found that 85.2% of 325 subjects were virologically suppressed (viral load<47 HIV-1 RNA copies/ml). There was no difference in the proportion of virologically suppressed subjects by time on treatment, yet CD4 counts were higher in each successive stratum. Women had higher median CD4 counts than men overall (406 vs. 294 cells/μL, respectively; P<0.0001) and in each time-on-treatment stratum. In a multivariate logistic regression model, predictors of virological suppression included efavirenz use [odds ratio (OR) 0.47; 95% confidence interval (CI) 0.22-1.02; P=0.057], lower cost of clinic visits (OR 0.815; 95% CI 0.66-1.00; P=0.05), improvement in CD4 percentage (OR 1.06; 95% CI 1.014-1.107; P=0.009), and care at Kayunga vs. Kangulamira (OR 0.47; 95% CI 0.23-0.92; P=0.035). In a multivariate linear regression model of covariates associated with CD4 count recovery, time on highly active antiretroviral therapy (ART) (P<0.0001), patient satisfaction with care (P=0.038), improvements in total lymphocyte count (P<0.0001) and haemoglobin concentration (P=0.05) were positively associated, whereas age at start of ART (P=0.0045) was negatively associated with this outcome.

CONCLUSIONS

High virological suppression rates are achievable on first-line ART in Uganda. The odds of virological suppression were positively associated with efavirenz use and improvements in CD4 cell percentage and total lymphocyte count and negatively associated with the cost of travel to the clinic. CD4 cell reconstitution was positively associated with CD4 count at study visit, time on ART, satisfaction with care at clinic, haemoglobin concentration and total lymphocyte count and negatively associated with age.

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.