Majority of previous studies of pegylated interferon α-2a (PegIFNα-2a) forced on naïve chronic hepatitis B (CHB) patients, and the data of PegIFNα-2a in therapy of patients with prior exposure to nucleos(t)ide analogues is rare. This study aimed to investigate the predictive role of serum quantitative hepatitis B surface antigen (HBsAg) in predicting sustained response of PegIFNα-2a in HBeAg-positive CHB patients with prior lamivudine exposure.Forty-six patients with prior lamivudine exposure received PegIFNα-2a for 12 months and followed-up for 6 months. The clinical features of responders and non-responders were compared, and the predictive role of quantitative HBsAg in predicting responders at the end of follow-up was evaluated. Responders were defined as an ALT normalization, HBeAg seroconversion and sustained virological response at the end of follow-up.In this cohort, only 26.1% (12/46) patients were responders. The baseline characteristics of the responders and non-responders were similar; however, the rates of ALT normalization, HBV DNA undetectability and HBeAg seroconversion were all significantly higher in responders than that in non-responders. During the treatment and follow-up, the HBsAg levels were all significantly lower in responders than that in non-responders. In predicting reponders, the serum HBsAg cutoff of 6000 IU/mL at months 6 had a positive predictive value of 73.3 and a negative predictive value of 96.8%, and with an area under the receiver operating characteristic curve of 0.869.The responders toward PegIFNα-2a in CHB patients with prior lamivudine exposure is not high, and serum HBsAg <6000 IU/Ml at months 6 of on-treatment had a high value to predict long-term outcomes of treatment. Hepatitis B virus (HBV) infection is a global public health problem . It is ePrevious studies had reported that the serum HBsAg level has some relationship with intrahepatic cccDNA , and serBesides NAs agents, interferon α (IFNα), especially its pegylated form, also has been approved and widely used in therapy of CHB in clinical practice . And theCurrently, how to identify and use indicators to predict treatment response has been widely concerned. In present study, we will evaluate the effectiveness of quantification of serum HBsAg in predicting the response of pegylated interferon α-2a in HBeAg-positive CHB patients with prior lamivudine exposure, and the findings of this study would provide an important reference for helping CHB patients achieve sustained curative response.5 copies/mL, and elevated serum alanine amino-transferase (ALT) value. The exclusion criteria were as follows: ①co-infection with other hepatitis virus or human immunodeficiency virus; ②evidence of other causes of liver disease, such as autoimmune hepatitis and primary biliary cirrhosis; ③evidence of advanced liver diseases, such as decompensated cirrhosis, severe hepatitis, and hepatic carcinoma; ④poor compliance or no availability of detailed laboratory test results.HBeAg-positive chronic hepatitis B patients with prior lamivudine exposure and received pegylated interferon alfa-2a for recurring antiviral therapy were screened in this study, all of them were followed up at the Digestion Department of Chengdu Military General Hospital from January 2007 to December 2012. The inclusion criteria were as follows: adults (18–70 years), prior lamivudine exposure for more than 1 years, positive HBeAg statue, HBV DNA levels higher than 1.0×10^This study was carried out in accordance with the ethics committee of Chengdu Military General Hospital and informed consent was obtained from each participant.This is a prospective observational study, and all eligible participants were administered pegylated interferon alfa-2a (PegINFα-2a)  at a dose of 180 μg once a week by subcutaneous injection for 12 months. Quantification of serum HBsAg was carried out at baseline, months 3, 6 and at the end of treatment (12 months), and the quantitative HBV DNA and liver function was also assessed at each time-point.According to the follow-up outcomes in this study, patients were designated as either responders or nonresponders. Responders were defined as an ALT normalization, accompanying with HBeAg seroconversion at the end of treatment and the presence of a sustained virological response. Patients who did not achieve the above-mentioned criteria were defined as NRs. And sustained virological response was defined as undetectable serum HBV DNA both at the end of therapy and 6-month of follow-up.Liver function was studied using an automatic biochemical analyzer, serum HBV DNA was quantified by PCR assay with a lower limit of detection of 1000 copies/mL , and serum HBsAg was measured quantitatively by a Roche chemiluminescence assay .P-value of less than 0.05 was considered statistically significant.Quantitative variables were expressed as mean and standard deviation. Categorical variables were presented as counts and percentages. The comparisons of quantitative variables were performed using T-test, and comparisons of qualitative variables were performed using Chi-square test or Fisher’s exact test as appropriate. The accuracy of serum HBsAg to predict response was assessed using the receiver operating characteristic (ROC) curve. All P-values were two-tailed. A A total of 59 patients were screened in this study and only 46 CHB patients (32 men and 14 women) were included. The other 13 patient were excluded because of poor compliance to treatment (N=6), prior lamivudine exposure less than 1 years(N=5), and HCV confection(N=2). Of patients included in this study, 26.1% (12/46) patients were responders and 73.9% (34/46) patients were non-responders towards PegIFN α-2a 12-month treatment, and their detailed demographic and clinical characteristics were shown in Table P=0.0439). As compared to nonresponders, the undetectability rate of serum HBV DNA was significantly lower in responders since months 6 of treatment. In respect to HBeAg seroconversion, we also found that its rate either at months 12 of treatment or 6-month follow-up  was significantly higher in responders than that in non-responders.At the end of 12-month PegINFα-2a treatment, both serum ALT and HBV DNA levels were lower than that at baseline for all patients. The subgroup comparison of serum ALT and HBV DNA levels between responders and nonresponders during the treatment are presented in Table As Table P<0.0001). At months 6, the cutoff of 6000 IU/mL of HBsAg had a positive predictive value (PPV) of 73.3% and a negative predictive value (NPV) of 96.8% for predicting responders at the six-month of follow-up after PegIFN α-2a treatment, and the corresponding area under the ROC curve at months 6 were 0.869.Among 15 patients with HBsAg levels < 6000 IU/mL at months 6, 73.3% (11/15) were responders at the six-month of follow-up; among 31 patients with HBsAg levels ≥ 6000 IU/mL at months 6, 3.2% (1/31) were responder at the six-month of follow-up; and the difference between them was statistic significantly  undetectable HBV DNA, 78.3% (36/46) ALT normalization, and higher to 50% (23/46) HBeAg seroconversion, the combined response  was just 26.1%. So the salvage therapy of PegIFNα-2a for CHB patients with prior NAs exposure was not ideal, and how to optimize the existing treatment strategies and early predict long-term responses was necessary and important for the management of CHB.In past decade, many evidence indicated that the intrahepatic cccDNA decreasing would be probably an ideal prognostic variable in predicting long-term outcomes of antiviral treatment , but it As we know, current therapeutic agents cannot completely remove HBV from liver; and the goal of antiviral treatment is just to slow down the progression of liver disease to cirrhosis and hepatocellular carcinoma, with the ultimate goal of improving survival. The HBsAg loss and eventual seroconversion would signify the best outcome possible for patients with CHB . It has In summary, the percentage of responders toward PegIFNα-2a in CHB patients with prior lamivudine exposure is not high; but the early decrease of serum HBsAg (< 6000 IU/mL at months 6) could be used as a predictor of sustained combined response. Due to the limitation of relatively small sample size, longer follow-up and larger sample size prospective trials should be required to confirm our findings.The contents are solely the responsibility of the authors.Zeng WZ conceived the study and revised the manuscript critically for important intellectual content. Weng M, Wu XL and Zhang Y made substantial contributions to its design, acquisition, analysis and interpretation of data. Jiang MD, Wang Z, Zhou DJ and He X participated in the design, analysis and interpretation of data. All authors read and approved the final manuscript.


Observational studies suggest that HIV-focused pharmacies can improve antiretroviral therapy (ART) refill adherence, but there is a lack of clear documentation about the kind and variability of adherence interventions that are conducted.To use qualitative research methods to obtain an in-depth understanding of how ART adherence support and counseling is provided in human immunodeficiency virus (HIV)-focused community pharmacies. To determine relevant facilitators and barriers around adherence support from both patient’s and pharmacist’s perspectives.A qualitative research study of patients who patronized and pharmacists who were employed at HIV-focused pharmacies in the San Francisco Bay Area was conducted. Participants were recruited using flyers at HIV clinics and community-based organizations and using blurbs in newsletters. Transcripts were analyzed using grounded theory methods to determine emergent themes in the data.19 eligible patients with a self-reported diagnosis of HIV, who were taking their current ART regimen for at least 3 months, and who obtained their ART from a community pharmacy in the San Francisco Bay Area were included; 9 pharmacists who were employed at 9 different pharmacy locations frequented by participants were interviewed. Emergent themes included descriptions of pharmacy adherence counseling and support, roles and responsibilities regarding medication adherence, barriers to providing adherence support, and feeling connected as a facilitator to adherence support relationships.Pharmacists provide diverse types of ART adherence support and are uniquely positioned to help clients manage their medications. Additional training on developing relationships with patients and advertising their adherence services may further the role of community pharmacists in supporting antiretroviral adherence.


Since 2010, World Health Organization (WHO) guidelines discourage using stavudine in first-line regimens due to frequent and severe side effects. This study describes the implementation of this recommendation and trends in usage of antiretroviral therapy combinations in a cohort of HIV-positive patients in rural Tanzania.We analyzed longitudinal, prospectively collected clinical data of HIV-1 infected adults initiating antiretroviral therapy within the Kilombero Ulanga Antiretroviral Cohort (KIULARCO) in Ifakara, Tanzania from 2007-2011.3 (IQR 81-273). The percentage of prescriptions containing stavudine in initial regimens fell from a maximum of 75.3% in 2008 to 10.7% in 2011. TDF/FTC/EFV became available in 2009 and was used in 41.9% of patients initiating cART in 2011. An overall on-treatment analysis revealed that d4T/3TC/NVP and AZT/3TC/EFV were the most prescribed combinations in each year, including 2011 . Of those receiving stavudine in 2011, 659 (89.1%) initiated it before 2011.This analysis included data of 3008 patients. Median age was 38 (interquartile range [IQR] 31-45) years, 1962 (65.2%) of all subjects were female, and median CD4+ cell count at enrollment was 168 cells/mmInitial cART with stavudine declined to low levels according to recommendations but the overall use of stavudine remained substantial, as individuals already on cART containing stavudine were not changed to alternative drugs. Our findings highlight the critical need to exchange stavudine in treatment regimens of patients who initiated therapy in earlier years. The revision of the World Health Organization (WHO) HIV treatment guidelines in 2010 brought several changes to the management of HIV patients . In the The goal of phasing out stavudine still competes in budgetary terms with other priorities in advancing cART as direct drug costs of stavudine were still at around 50% compared to alternative regimens in 2011 -8 and fuMany national HIV programs have consecutively adopted the recommendations of the WHO, including the National AIDS Control Program (NACP) of Tanzania: In February 2009, the preferred regimen was changed from d4T/3TC/NVP to AZT/3TC/EFV and TDF/FTC/EFV was introduced as an alternative option [In order to describe how recommendations issued by the WHO eventually permeate to treating clinicians in low-income countries, this study describes prescription trends of antiretroviral therapy combinations in a large cohort of HIV patients in rural Tanzania over a five-year period.We analysed data of HIV-1 infected adults (≥ 18 years of age) initiating cART within the Kilombero Ulanga Antiretroviral Cohort (KIULARCO) at the chronic disease clinic at the St. Francis Referral Hospital in Ifakara. The hospital is the most important health care facility in the rural Kilombero and Ulanga Districts of the Morogoro Region in Southern Tanzania, providing treatment and care for a population of about 600,000 inhabitants. Demographic, clinical and laboratory data were prospectively collected from consenting patients at each consultation at the clinic. Medical doctors and clinical officers filled in standardized paper forms which consecutively where double entered into an electronic database . Treatment failure was defined clinically or immunologically according to WHO criteria . Antiretroviral therapy combinations used for cases of treatment failure are referred to as second-line treatment regimens. Data collected from the 1st of January 2007 until the 31st of December 2011 were included in the analysis. In case a subject received > 1 regimen in one calendar year, all combinations prescribed during that year were included in the overall prescription analysis. Patients who initiated cART before 2007 were included in the overall prescription analysis. There was no active tracking mechanism of patients lost to follow-up during the study period. Continuous variables are expressed as median (interquartile range) and frequencies (percentages) for categorical variables. For calculation of p-values for trend, a chi-square statistic for trend was used. All statistical analyses were performed using Stata 11.2 .All subjects included were given oral and written information about the collection of their clinical data and signed an informed consent form. Ethical approval was granted by the local Ethical Committee of the Ifakara Health Institute and the Medical Research Coordination Committee of the National Institute of Medical Research of Tanzania.This analysis included data of 3008 patients Figure . Of thesFrom 2007 until the end of 2008, d4T/3TC/NVP and AZT/3TC/EFV were the two major combinations used as first-line regimens with proportions of 71.4% and 23.3% in 2008, respectively . On the other hand, the percentage of female patients receiving the nevirapine containing regimens d4T/3TC/NVP and AZT/3TC/NVP was higher than those of male patients but these differences were not statistically significant . There was no difference of gender concerning AZT/3TC/EFV (2011: p = 0.82).The ratio of second-line (i.e. treatment combinations used in case of treatment failure) to total regimens remained stable over time (p for trend = 0.13) with a maximum of 33 (1.7%) patients in 2011. Of these, 31 (93.9%) received a combination of ABC/ddI/LPVr and 2 (6.1%) ABC/ddI/SQVr.Over the whole period of observation, 242 of 1475 (16.4%) subjects receiving any regimen containing stavudine at any point during their follow-up were changed to alternative first-line combinations excluding stavudine after a median of 1.0 (IQR 0.4-1.8) years. The most common replacement was a fixed dose combination of AZT/3TC/NVP which accounted for 40% (97/242) of substitutions overall  when compared to expected therapeutic failure rates  which miThere are several limitations to this study. Due to high rate of patients lost to follow-up, individual follow-up times are short given the overall five year study period, which limits the value of statements about trends in long term therapy. Reasons for treatment modifications were not recorded in a standardized manner. This flaw limits causal analysis of prescription dynamics, particularly those associated with side effects of stavudine.Updated guidelines and modern pharmaceuticals have been adopted efficiently in this Tanzanian cohort. Consistent with these, the general usage of stavudine remained very substantial still in 2011: It declined to low levels in antiretroviral combinations of patients initiating cART. However, the majority of subjects being prescribed stavudine primarily in earlier years are not changed to more modern combinations.Monitoring of drug prescriptions is a simple and feasible approach to identify deficits in implementation of treatment guidelines.3TC: Lamivudine; ABC: Abacavir; AZT: Zidovudine; cART: Combined Antiretroviral Therapy; d4T: Stavudine; ddI: Didanosine; DHHS: US Department of Health and Human Services; EFV: Efavirenz; FTC: Emtricitabine; KIULARCO: Kilombero Ulanga Antiretroviral Cohort; LPVr: Lopinavir / Ritonavir; NACP: National AIDS Control Program; NVP: Nevirapine; SQVr: Saquinavir / Ritonavir; SSA: Sub-Saharan Africa; TDF: Tenofovir; WHO: World Health Organization.The authors declare that they have no competing interest.FF conceived of the study. FF and EL carried out the analysis of cohort data. FF, EL, TG, CH, MT and MB drafted the manuscript. TG, MT, GM, BJ and CH participated in the design of the study and the KIULARCO cohort. MB supervised the scientific work, participated in design and coordination. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2334/14/90/prepub


HIV-1 genotypic susceptibility scores (GSSs) were proven to be significant prognostic factors of fixed time-point virologic outcomes after combination antiretroviral therapy (cART) switch/initiation. However, their relative-hazard for the time to virologic failure has not been thoroughly investigated, and an expert system that is able to predict how long a new cART regimen will remain effective has never been designed.th day after treatment start, defined as the first HIV-1 RNA > 400 copies/ml, censoring at last available HIV-1 RNA before treatment discontinuation. We assessed the relative hazard/importance of GSSs according to distinct interpretation systems  and other covariates by means of Cox regression and random survival forests (RSF). Prediction models were validated via the bootstrap and c-index measure.We analyzed patients of the Italian ARCA cohort starting a new cART from 1999 onwards either after virologic failure or as treatment-naïve. The time to virologic failure was the endpoint, from the 90The dataset included 2337 regimens from 2182 patients, of which 733 were previously treatment-naïve. We observed 1067 virologic failures over 2820 persons-years. Multivariable analysis revealed that low GSSs of cART were independently associated with the hazard of a virologic failure, along with several other covariates. Evaluation of predictive performance yielded a modest ability of the Cox regression to predict the virologic endpoint (c-index≈0.70), while RSF showed a better performance . Variable importance according to RSF was concordant with the Cox hazards.GSSs of cART and several other covariates were investigated using linear and non-linear survival analysis. RSF models are a promising approach for the development of a reliable system that predicts time to virologic failure better than Cox regression. Such models might represent a significant improvement over the current methods for monitoring and optimization of cART. Modern combination antiretroviral therapy (cART) can suppress plasma viral load to undetectable levels in a large proportion of HIV-1 infected patients. The risk for a patient to experience virologic failure has been decreasing consistently during the last decade in high-income countries .Part of this high rate of virologic success may be due to the increasing ability of more potent and tolerable antiretroviral drugs targeting a wider range of molecular targets, providing physicians the opportunity to tailor cART regimens according to patients' background and to manage treatment failure promptly. Additionally, better understanding of the mechanisms of drug resistance allows optimization of treatment regimens based on an individual's virus genotype. Although the prevalence of drug resistance seems to be decreasing in recent years , despiten-weeks) after cART initiation or switch  days from the cART start date, without other therapies used during that time interval except the failing regimen, when applicable.The following variables were coupled with each patient's record of cART switch/initiation and subsequent HIV-1 RNA determinations: calendar year; baseline HIV-1 RNA, obtained within  days from the cART start date, without other treatment changes during that time interval; baseline CD4+ T cell count,  days from the cART start date; age; gender; mode of HIV-1 transmission; nationality; previous AIDS-defining events, hepatitis B/C virus co-infection (either HBsAg or HCV antibody positive serostatus); time passed from the first HIV-1 positive antibody test to the first cART initiation; duration of prior antiretroviral exposure; number of previous antiretroviral therapy switches (any drug change for any reason); previous drug class exposures (combinations of NRTI/NNRTI/PI/other classes); previous suboptimal treatment (less than three drugs in a regimen); achievement of an HIV-1 RNA < = 50 copies/ml at any time point during the cART follow up; a baseline HIV-1 The baseline HIV-1 genotype was successively processed by calculating the GSS using the latest available version from 3 interpretation systems  with respect to the associated cART. We used the standard susceptible/intermediate/resistant categorization for all GSS, as by the output by the HIVdb web-service . UnassigCox multivariable proportional hazard regression (with robust variance estimation via a grouped jackknife)  and randi Ydenote the observed time (either censoring time or event time) for subject i, and let i Cbe the indicator that the time corresponds to an event (i.e. if i C= 1 the event occurred and if i C= 0 the time is a censoring time). The hazard function Λ(t|X) for the Cox proportional hazard model has the formThe Cox proportional hazard model is a general non-parametric regression technique which is not based on any assumptions concerning the underlying survival distribution. The model assumes that the underlying hazard rate  is a function of the independent covariates. Let t for an individual with covariate vector (explanatory variables) X. The term Λ0(t) is called the baseline hazard, and it is the hazard for the respective individual when all independent variable values are equal to zero. The model is called proportional hazard because, while no assumptions are made about the shape of the underlying hazard function, the model equations specify a multiplicative relationship between the underlying hazard function and the log-linear function of the covariates. There is a log-linear relationship between the independent variables and the underlying hazard function. In addition, given two observations with different values for the independent variables, the ratio of the hazard functions for those two observations does not depend on time.This expression gives the hazard at time h on a given predictor x takes always the form x ≤ c and x >c. This split induces two children nodes and two sub-sets of survival data. A good split should maximize survival differences across the two sets of data. Let 1 t<2 t< ... <n tbe the distinct death times in the parent node h, and let i,j dand i,j Yequal the number of deaths and individuals at risk at time i tin the children nodes j = 1, 2. Note that i,j Yis the number of individuals in the child node j who are alive at time it, or who have an event (death) at time it. The log-rank statistics for a node split at value c for a variable x isRSF are an extension used to analyze censored data of the random forests machine-learning method, an ensemble of several decision trees for classification and regression. A random survival tree is a special form of decision tree for survival analysis. The tree is constructed using a training data set made of observation data points of time, status/event, and associated predictor covariates. A binary tree is grown by inferring node splits upon the set of covariates as follows. The space of observations is recursively divided into two disjoint sub-spaces, thus inferring a node split, based on an optimal cut-off value of a predictor. The log-rank statistic is used usually as a criterion for node splitting in survival trees. In detail, a proposed split at node L  is, the better the split is. Each tree node contains the number of total and censored observations falling into the current category, as well as a Kaplan-Maier estimation of the cumulative survival for the group is calculated at the end nodes. Since the predictive performance of one survival/decision tree can be poor, different trees can be combined together to obtain improved performance. RSF are an ensemble average of different survival trees. Each tree is grown on different bootstrap samples of the original data set, and a randomization is introduced in the recursive node splitting phase by considering a random sub-set of predictors at each step. These characteristics enable to approximate complex functions with a generally low generalization error. One theoretical advantage of RSF over the Cox regression is that the latter relies on the restrictive assumption of the proportional hazards. In addition, RSF manage automatically the non-linear interactions among variables, whilst in Cox regression non-linear and higher-order interactions need to be explored explicitly.The larger the absolute value for Cox regression and RSF models were fitted on the whole study population and on the subset of therapy-naïve patients. An additional sensitivity analysis was carried out by considering only those patients with at least two follow-up HIV-1 RNA determinations, where a HIV-1 RNA viral load < = 50 copies/ml occurred at any time point during the cART follow up.agreement for any two randomly chosen observations, where agreement means that the observation with the shorter survival time of the two also has the larger risk score. A previous study in the different context of breast cancer research successfully used the c-index to compare RFS and Cox regression [The predictive ability of the RSF and Cox regression was evaluated by means of the Harrell's c-index measure , comparigression .The free software environment for statistical computing and graphics "R" was employed for all statistical analyses and graph generations . BesidesA total of 2,337 cART regimens from 2,158 patients were considered. The proportion of patients who were previously therapy-naïve was 34% (n = 733). Table We observed 1,067 virologic failures over 2,820 person years of follow-up (rate = 37.8 per 100 person years). By Kaplan-Meier estimation, median (95% CI) time to virologic failure was 659 (533-784) days for all patients, and 2,510  days for those previously therapy-naïve. By two years, the estimated proportion of patients not experiencing virologic failure was 0.48 (0.46-0.51) when considering the whole set of patients, and 0.71 (0.67-0.75) for those previously therapy-naïve.Multivariable Cox analysis revealed that higher GSSs (each fitted in separate models including the other covariates), a more recent calendar year, patients administered 2NRTI+1PI/r, as compared to those undertaking 2NRTI+1NNRTI, and younger age were independently associated with a decreased hazard of virologic failure. Conversely, a higher HIV-1 RNA, a lower CD4+ count, and previous drug class exposure were associated with an increased hazard. Table null = -7573.536, Lextended = -7361.47, χ2 = 424.13 on 41 degrees of freedom, p < 0.0001).The evaluation of extra-sample predictive performance  is shown in Figure The c-index performance of RSF, grown with the limited number of 30 trees due to the high computational burden, using the same covariate settings as in the multivariable Cox regression, were 0.7298 (0.009) for Rega, 0.7276 (0.009) for ANRS, and 0.7319 (0.008) for HIVdb.By executing all pairwise Student's t-tests (adjusted for multiple comparisons with the Benjamini-Hochberg method) comparing the c-index distributions, we find statistically significant differences between univariable vs. multivariable Cox models, univariable Cox models vs. RSF, and multivariable Cox models vs. RSF . When comparing the performance of Rega, ANRS and HIVdb within the same model settings, we found evidence of a significantly better performance of HIVdb as compared to ANRS in the univariable Cox (p < 0.0001), multivariable Cox and (p = 0.053), and RSF (p = 0.0005). HIVdb outperformed Rega only under the univariable Cox modeling. Conversely, Rega and ANRS did not show any appreciable difference in any of the within-model c-index distributions. However, it has to be noted that all the GSS had the same average c-index values up to the third decimal.When executing a sensitivity analysis on the subset of treatment-naïve patients (n = 733), multivariable Cox regression confirmed the relative hazards of the GSS of the regimen , and of HIV-1 RNA . Other factors independently associated with the endpoint were being non-Italian born , subtype C , and calendar year 2004 . Differences among cART regimens were not relevant.In a second sensitivity analysis, only patients who reached an HIV-1 RNA < = 50 copies/ml from the cART start date onwards were selected . By fitting a multivariable Cox regression, variables independently associated with the endpoint were consistent with those obtained for the subset of treatment-naïve patients (data not shown).In this study we investigated linear and non-linear survival models for predicting the time to virologic failure in HIV-1-infected patients undergoing a new cART regimen, with the aim to assess both prognostic factors of virologic failure and performance of predictions, in light of the development of a reliable expert system.In contrast to 2NRTI+1PI/r, older age, higher HIV-1 RNA, and lower CD4+ counts, an increased hazard of virologic failure was associated with low GSSs of cART, a less recent calendar year, administration of 2NRTI+1NNRTI, and the ART-naïve status. HIV-1 RNA and GSS remained associated with the endpoint when considering only treatment-naïve patients in a sensitivity analysis.When looking at the goodness-of-fit of the models, the inclusion of additional covariates besides the GSS in a multivariable Cox regression yielded a significant improvement in the likelihood. Furthermore, RSF proved to be a promising approach, improving performance over that obtained by using the Cox method.This study has some limitations. First, there was a study selection bias, since only cART regimens that were undertaken for at least 90 days were considered. Early-switches and simplifications were excluded from the analysis. In addition, the main study endpoint was a pure virologic criterion and did not include stops due to other reasons. Although we selected only clinics with the ability to perform ultra-sensitive assays, the viral load threshold at > 400 copies/ml was arbitrary and might not capture all the actual virologic failures. Other thresholds for defining virologic failure, such as a viral load > 50 copies/ml or > 1,000 copies/ml might overestimate or underestimate true failure, respectively. We observed a lower hazard of virologic failure for regimens containing ritonavir-boosted PI as compared to those containing NNRTI, and this might be a reflection of both the selection bias and the endpoint definition.In regards to the statistical methods, we did not investigate the potential benefit in terms of likelihood fit given by the inclusion of interaction terms in the Cox regression. It is possible that a Cox model with higher-order interactions is able to reach the performance obtained by using the RSF. For the practical perspective of a time to event prediction model, Cox regression presents some problems with the baseline hazard function estimation, while the RSF gives output in terms of mortality ensembles. We also tested accelerated failure time models, which are able to give reliable predictions in terms of actual time scales, and their performance was comparable to the results of the Cox regression (data not shown).This study demonstrates the feasibility of an expert system that predicts the actual time course of a new cART as the estimate of time to virologic failure, and the reliability of the system's predictions can be improved both by including additional covariates besides the viral genotype and by using non-linear regression techniques. The implementation of such a system would create a more clinically-oriented treatment decision tool and more effectively tailor patient cART regimens.ADL received speakers' honoraria, served as consultant or participated in advisory boards for GlaxoSmithKline, Gilead, Bristol-Myers Squibb, Abbott Virology, Tibotec-Janssen, Siemens Diagnostics, and Monogram Biosciences.MZ received research funding from Pfizer, served as a consultant for Abbott Molecular, Boehringer Ingelheim, Gilead Sciences, and Janssen, and served on speakers' bureaus for Abbott, Bristol-Myers Squibb, Merck, and Pfizer.SDG received speakers' honoraria or consultancy fees from Abbott, GlaxoSmithKline, Gilead, Boehringer Ingelheim, Jansen-Tibotec, Merck-Sharp & Dohme, and Bristol Myers Squibb.BB has received funds for speaking, consultancy and travel from ViiV Healthcare, Gilead Sciences, Abbott Molecular, Janssen-Cilag and Siemens Health Care.Other authors: none to declare.MCFP: statistical analyses, machine learning modeling, manuscript writing; SDG: study design; IF: data base administration, data extraction; GM, BB, AC, GP, PB, VM, EP, ADB, VG, MDP: local data base administration, local data manipulation and provision to the ARCA cohort, clinical activity, patient care; MZ: molecular biology expertise, sequencing; ADL: research group leading, manuscript revision. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6947/11/40/prepubSupplementary material. Supplementary figures describing performance and variable importance measures of Random Survival Forests.Click here for file


Routine HIV viral load (VL) testing is not available in India. We compared test performance characteristics of immunologic failure (IF) against the gold standard of virologic failure (VF), examined evolution of drug resistance among those who stayed on a failing regimen because they did not meet criteria for IF and assessed implications for second-line therapy.Participants on first-line highly active antiretroviral therapy (HAART) in Bangalore, India, were monitored for 24 months at six-month intervals, with CD4 count, VL and genotype, if VL>1000 copies/ml. Standard WHO criteria were used to define IF; VF was defined as having two consecutive VL>1000 copies/ml or one VL>10,000 copies/ml. Resistance was assessed using standard International AIDS Society-USA (IAS-USA) recommendations.Of 522 participants , 57 (10.9%) had VF, 38 (7.3%) had IF and 13 (2.5%) had both VF and IF. The sensitivity of immunologic criteria to detect VF was 22.8%, specificity was 94.6% and positive predictive value was 34.2%. Forty-four participants with VF only continued on their failing first-line regimen; by the end of the study period, 90.9% had M184V, 63.6% had thymidine analogue mutations (TAMs), 34.1% had resistance to tenofovir, and 63.6% had resistance to etravirine.WHO IF criteria have low sensitivity for detecting VF, and the presence of IF poorly predicts VF. Relying on CD4 counts leads to unnecessary switches to second-line HAART and continuation of failing regimens, jeopardizing future therapeutic options. Universal access to VL monitoring would avoid costly switches to second-line HAART and preserve future treatment options. An estimated 6.6 million HIV-infected individuals are receiving highly active antiretroviral therapy (HAART) in resource-limited settings . In IndiTreatment failure can be defined as progression of disease after initiation of HAART. Failure can be assessed by clinical , immunologic (a decline in CD4 count) or virologic  criteria . It has The aims of this longitudinal analysis were to (1) evaluate the sensitivity, specificity and positive predictive value (PPV) of WHO-proposed criteria for treatment failure based on CD4 count, to detect true treatment failure based on virologic criteria in an Indian setting; and (2) assess the consequences of remaining on a failing regimen among those who do not meet criteria for IF but are, in fact, failing by virologic criteria, by examining the evolution of drug resistance and implications for second-line antiretroviral therapy.The data presented in the present study were collected as part of a two-year observational cohort study of adherence to HAART among HIV-infected adults attending public and private clinics in Bangalore, India. The full methods of this study have been published elsewhere .The study was conducted at three clinics  in Bangalore, India. Bangalore is a major metropolitan city in Karnataka, which is one of the six states in India with a high HIV prevalence . The mosOnce patients are on a stable first-line regimen, they are monitored every six months, and treatment monitoring includes weight, haemoglobin, alanine aminotransferase (ALT), and CD4 count. Routine VL monitoring is not available. Patients suspected of having treatment failure for WHO-defined immunologic and clinical criteria are referred to select government HIV treatment centres designated as Centers for Excellence for evaluation for second-line therapy . BeginniParticipants were eligible if they were 18 years or older, were HIV infected, were on antiretroviral therapy for at least one month (and therefore not HAART naïve) at the time of enrolment, and were willing to participate in all follow-up visits. A total of 533 consecutive patients seeking care at the three clinic sites in Bangalore who met eligibility criteria were enrolled and followed in the study between August 2007 and December 2011. In this analysis, we included the 522 patients who had CD4 and VL data available at time points six or more months after starting HAART.The study was approved by the institutional review boards of the University of California–San Francisco and St John's National Academy of Health Sciences.Potential participants were referred to the study interviewers by clinic staff. Following referral, participants were taken to a separate room for eligibility confirmation and the study interview. If found eligible, participants were monitored every 3 months for 24 months and were interviewed to assess adherence. Blood work was done every six months. All patients provided written informed consent.Participants’ blood was drawn by trained staff phlebotomists. CD4 cell count, HIV plasma VL, HIV genotype, and if VL>1000 copies/ml were assessed at six-month intervals. CD4 cell counts were performed on whole-blood specimens collected in an EDTA (ethylenediaminetetraacetic acid) tube using a single-platform flow cytometry assay . A real-time polymerase chain reaction (PCR) assay with a fluorescein-labelled TaqMan probe was used for the quantitation of VL. The test was developed and its performance characteristics were determined at Molecular Diagnostics and Genetics, Reliance Life Sciences . This assay can reliably detect an HIV RNA level of 100 copies/ml of blood. The HIV-1 drug resistance assay was performed at YRGCARE Infectious Diseases Laboratory  using an in-house method . The perThe results of the VL testing were provided to the patients and their treating clinicians. Providers then were able to use these results as well as other relevant information to make treatment-related decisions for each patient, such as clinical data; national guidelines at the time the study was conducted; and, for patients in the private clinic setting, their ability to pay for second-line therapy. These physicians may have been limited in their ability to refer to second-line therapy because second-line therapy was available only through small pilot programmes in a few centrally located care settings in India.3.We used standard WHO-defined criteria for IF in this analysis since these are the same criteria adopted by NACO in India. A participant was categorized as having IF if he or she met one of the following three criteria after at least six months on HAART: (1) fall of CD4 count to pre-therapy baseline or below, (2) ≥50% fall of absolute CD4 count from the on-treatment peak value or (3) persistent CD4 levels below 100 cells/mmVF was defined as, after at least six months on HAART, having a VL greater than 1000 copies/ml at two consecutive measurements (six months apart at study visits) or one VL measure >10,000 copies/ml.We used the International AIDS Society-USA (IAS-USA) recommendations  to categt-test (age), Mann-Whitney U-test (CD4 and time on HAART), or χ2-test . Due to small numbers, no gender-specific analyses were done on the genotyping data. Analyses were done in SPSS, version 18.0.2 , and Stata, version 12.1 .Descriptive statistics includes means, standard deviations, medians and proportions when appropriate. Performance of the immunologic criteria was assessed by calculating their sensitivity, specificity and PPV, with exact confidence intervals, using VF as the “gold standard.” These analyses were performed both on the sample as a whole, and for males and females separately. One participant who identified as transgender was included in the analyses of the whole sample, but excluded from the analyses by gender. Differences between men and women were assessed via a n=353; 67.6%), and the mean age was 37.5 (standard deviation (SD): 8.5)  were on nevirapine-based regimens, and 40.4% (n=211) were on d4T-containing regimens. Seventy-seven per cent of participants were on their first-ever ART regimen; the remaining were also on first-line agents, but may have undergone some treatment modification for toxicity or drug interactions. Female patients were significantly younger  and had a higher median CD4 count at study enrolment  : 8.5) . At the r males) .A total of 57 (10.9%) patients experienced VF during the study; 13 of the 57 patients met criteria for IF at the time VF was detected, leaving 44 patients with VF only . An addin=25) of participants with VF at their baseline visit had an M184V mutation. Nearly one-half  of these participants had at least one TAM: 20.7% (n=6) had one TAM, 17.2% (n=5) had two TAMs, and 10.3% (n=3) had three or more TAMs, indicating that they may have been failing for many months by the time they enrolled in the study. Additionally, two participants were found to have the 69 insertion site mutation, and four more patients had K65R or K70E. Six of the 29 participants (20.7%) had evidence of genotypic resistance to tenofovir. With regard to NNRTI mutations, more than one-half of the participants with VF at enrolment  had Y181C owing to the prevalence of nevirapine use in first-line regimens. Seven (24.1%) had K103N, seven (24.1%) had G190A and six (20.7%) had K101E. All but two patients (93.1%) were resistant to both nevirapine and efavirenz. Based on the NNRTI mutations that were present, and using the weighted genotypic score for the determination of etravirine susceptibility as outlined above, 18 of the 29 participants (62.1%) had a calculated etravirine score of 2.5 or greater, corresponding to intermediate- or high-level resistance to etravirine.Of the 44 total patients with VF only, 19 (43.2%) eventually developed IF during the study follow-up period. Median time from VF to IF in this subset of patients was 18 months. We assessed the evolution of drug resistance in these 44 patients between the time VF was detected and either the end of the study period or the time when IF was detected, when presumably the patient would be referred for second-line therapy. Twenty-nine of these 44 patients already had VF at enrolment into the study and had been on therapy for a median of 25 months at the time of their initial study visit . A majorFifteen participants developed VF during the study. The only NRTI mutation detected in any of these participants was M184V, with eight of the 15 patients (53.3%) harbouring this mutation. None of the participants who developed VF during the study were resistant to tenofovir at the time that treatment failure was detected. There were a few NNRTI mutations present: two patients had Y181C, two had K103N, five had G190A and one had K101E. A total of nine (60.0%) were resistant to nevirapine and efavirenz. However, only two patients (13.3%) had an etravirine mutation score of ≥2.5.n=15) were found to have mutations that would confer high-level resistance to tenofovir. Based on the NNRTI mutations present, 63.6% (n=28) of participants had etravirine mutation scores ≥2.5, associated with intermediate- or high-level resistance to etravirine.The 44 participants with VF only and without evidence of IF (includes 29 with VF at baseline and the 15 who developed VF during the study) were followed for a median of 18 months (either until the end of the study or until they developed evidence of IF) while they remained on a failing regimen. During this time, seven additional participants developed M184V, three developed 69 insertion site mutations and two developed Q151M. Twenty additional TAMs also developed in the 44 participants. When the evolution of NNRTI mutations was assessed, three more participants developed K103N, two more developed Y181C, and six more each developed G190A and K101E. By the end of the study period, 34.1% of participants  had the M184V mutation; six (46.2%) had any TAMs, with a majority having 3 or more TAMs; 8 (61.5%) had predicted resistance to tenofovir; and 9 (69.2%) had an etravirine mutation score ≥2.5.In this longitudinal study of 522 HIV-infected participants on first-line HAART in Bangalore, India, we found that WHO-defined criteria for IF are insensitive at detecting virologic treatment failure and, more importantly, that the delay in diagnosis of treatment failure results in accumulation of a substantial number of drug-resistant mutations and has the potential to have a significant impact on the efficacy of second-line antiretroviral treatment.Participants who developed VF during the study period, and thus were recognized as having treatment failure immediately, did not have any mutations associated with tenofovir resistance at the time of VF. However, by the end of a follow-up period of a median of 18 months, when participants finally developed evidence of IF, one in three participants had mutations that conferred high-level resistance to tenofovir. Subtype C HIV-1 virus is predominant in India, and it has been previously established that in this subtype, K65R is selected for by on-going exposure to d4T and leads to tenofovir cross-resistance . AlthougFurthermore, based on the presence of TAMs and other NRTI mutations, a substantial proportion of individuals in our cohort also had complete resistance to AZT and d4T, essentially making the whole NRTI class of drugs a nonviable option for a significant number of patients needing second-line therapy. Similar concerns have been reported in studies from Africa, where 17%–53% of patients with treatment failure had no active NRTI options –30. ThisAccording to India's 2011 national guidelines, when patients meet the criteria for IF, they are tested to confirm VF and then empirically started on ritonavir-boosted atazanavir, tenofovir and lamivudine. In nearly one-third of patients, this would mean that they will be receiving PI monotherapy since the other two drugs in the regimen are completely inactive or only partially active. Although a recent AIDS Clinical Trials Group (ACTG) study has shown some promise with lopinavir-ritonavir monotherapy in resource-limited settings in the short term , this maEtravirine is a second-generation NNRTI that has been shown to be effective in achieving virologic suppression when given in combination with other fully active drugs in patients with prior treatment experience . HoweverOur findings regarding the sensitivity of WHO's IF criteria to detect VF are in line with similar studies conducted in Africa, where subtype C virus also predominates. Sensitivity of WHO-defined criteria for IF to detect VF ranged from 21 to 58% –14, depeThe prevalence of VF was fairly low in our setting: approximately 10% of participants were found to have VF. This contributed to the low PPV of 34%. However, this number is slightly lower than what others have reported: 36.8% in South Africa  and 70% There are several limitations to this study. Patients were not HAART naïve at the time of enrolment, and we did not have baseline genotypes to determine the contribution of transmitted drug resistance to, or the impact of previous treatment regimens on, virologic treatment failure. However, studies from other parts of India show that the prevalence of drug resistance in HAART-naïve patients is between 3% and 5% in south India –39. SecoIn resource-limited settings, HIV drug resistance is a threat to the long-term effectiveness of antiretroviral treatment. It is unlikely that resistance testing will be available at the level of the individual patient in the near future. Additionally, treatment changes based on individual patient testing are not feasible due to limited access to second- and third-line agents. The best way to ensure treatment success with second-line agents may be through early detection of treatment failure. WHO IF criteria have low sensitivity for detecting VF, and the presence of IF poorly predicts VF. Relying on CD4 count data alone would lead to a substantial number of unnecessary switches to second-line HAART. Although there are some conflicting studies , routine


HIV and anaemia are major health challenges in Africa. Anaemia in HIV-infected individuals is associated with more rapid disease progression and a poorer prognosis if not addressed appropriately. This study aimed at determining the severity and types of anaemia among HIV infected children and its effect on short term response to antiretroviral therapy (ART).At baseline, clinical and haematological parameters of 257 HIV-infected ART-naïve children aged 3 months to 18 years were assessed to determine the prevalence, severity and types of anaemia. ART eligible patients were started on therapy according to WHO criteria, enrolled (n=88) into an observational cohort and followed up for 6 months.Anaemia was present in 148/257 (57.6%) of children, including (93/148) 62.2% with mild anaemia, 47/148 (32.0%) moderate anaemia, and 7/148 (4.8%) with severe anaemia. The mean haemoglobin (hb) was lower among children with more advanced HIV disease (p<0.0001). Microcytic-hypochromic anaemia (44.9%) was the commonest type of anaemia. Anaemia was independently associated with young age (p <0.0001), advanced HIV WHO disease stage (p = 0.034) and low CD4 percentage (p = 0.048). The proportion of children who had attained viral suppression  at 3 months was significantly lower among the anaemic children, 31/58 (53.4%) compared to the non-anaemic children 26/30 (86.7%) (p=0.002). However, the difference in clinical and immunological response between the anaemic and non-anaemic patients did not reach statistical significance.Anaemia is highly prevalent among HIV-infected children in a rural Ugandan clinic and is associated with poorer virological suppression. However, the anaemia did not impact clinical and immunological response to ART among these children. Anaemia has been recognized as an important clinical problem in HIV-infected patients-3 with aStudies done earlier found an association between the presence of anaemia at baseline and decreased survival as well as increased disease progression in patients with HIV infection,8. Even Most of the studies on the HIV-anaemia interplay were done in developed countries and mainly included adults. The effect of the presence of anaemia on response to ART in HIV-infected children has not been studied. This study described the prevalence, severity and types of anaemia among ART-naïve HIV-infected children presenting at Mbarara Regional Referral Hospital (MRRH), a tertiary centre in western Uganda, and examined the effect of baseline anaemia on subsequent response to ART.We used a hybrid of two designs. First, we conducted a baseline evaluation of newly diagnosed HIV positive ART-naïve patients aged 3 months to 18 years attending MRRH from November 2007 to June 2009. HIV-1 is the vastly predominant strain in this region of Africa. The disAll patients were subjected to a standardized laboratory assessment consisting of haematological, virological and clinical chemistry tests prior to initiation and during follow-up on ART. Haematological indices including, haemoglobin concentration (Hb), red blood cell indices (mean corpuscular volume [MCV] and mean corpuscular haemoglobin [MCH]), were determined using an automated hematology analyser - COULTER® Ac·T™ 5diff CP (Cap Pierce). A thin CD4/CD8 counts were measured by Flowcytometry using a BD FACSCalibur™ flow cytometer. Viral lEligibility for initiation of ART was based on clinical and immunological criteria outlined in the then current WHO guidelines. The firAnaemia was defined and graded according to age-appropriate reference standards published by WHO.Patients started on ART were reassessed for short-term outcome at 3 and 6 months. Their clinical status was assessed on occurrence of opportunistic infections (O.Is) and growth indices. Immunological response was measured by increase in CD4+ from baseline; defined as adequate if increase was ≥ 10% at 3 months, and ≥ 15% at 6 months. Virological response was measured as a fall in viral load from baseline; defined as adequate if viral load was <400 copies/ml by 6 months.Sample size calculation was aimed at detecting a difference in the mean rise in CD4% on ART between anaemic and non-anaemic children at baseline. A sample size of 128 patients (64 per group) gave a power of 80% to detect a difference of 7 percentage points with a two sided alpha type 1 error of 0.05. Data were analyzed using SPSS® program version 12.0.Contingency tables were constructed to determine the relationship between anaemia and HIV disease stage. Odds ratios with 95% confidence intervals were calculated to determine the strength of association between the presence of anaemia and the HIV disease stage. For categorical variables with more than two categories such as types of anaemia, Chi-Square test for association was used to determine the association. Significant factors were included in a multiple logistic regression model to determine those which were independently associated with presence of anaemia.To estimate the impact of baseline anaemia on short-term response to ART, comparisons of immunological and virological responses between anaemic and non-anaemic groups were conducted using two methods. First, the proportion of children who registered a rise in CD4% of 10% at 3 months and 15% at 6 months was compared between the two categories (anaemic vs. non-anaemic) for children less than 5 years . Secondly, a comparison of mean rise in CD4% at 3 and 6 months was done between initially anaemic and non-anaemic children.To assess viral load response, we calculated the proportion of children who had achieved viral load suppression to undetectable levels at 3 and 6 months of ART by anaemia status. Means of viral load were also calculated for the two groups and compared at different follow-up time points using the t- test. These variables; CD4+ and viral load were tested and met the assumptions for the t-test.The research was approved by the Faculty of Medicine Research and Ethics Committee and the Institutional Review Board of Mbarara University. All mothers/guardians of enrolled children gave written informed consent to participate in the study. Patients received the standard of care, including free ART and management of anaemia according to standard protocol.A total of 276 HIV-infected children presented to the HIV clinic at MRRH between November 2007 and June 2009, but only 257 patients met the criteria and were enrolled into the study. We excluded 19 children who were already receiving ART. Of the 257 recruited patients, 23(8.9%) were in WHO clinical stage I, 66 (25.7%) were in stage II. During the analysis, stage I and II were combined and termed as early stage disease. WHO clinical stage III had 117(45.5%) while 51(19.8%) were in stage IV (AIDS). Stage III and IV were also grouped together and called late HIV clinical stage and therefore met the WHO criteria to start ART. They accounted for 168 (65.4%) of the total patients. However, only 98 (59%) were started on ART in time for the study. The age range was 4–207 months with a median of 48 months (SD 54.6), but 224(87%) were 12–180 months.Haemoglobin levels ranged from 4.3-16.0g/dl with a median Hb of 10.5g/dl (SD 2.01). A total of 148 out of 257 (57.6%) patients had anaemia at enrolment. Most patients (62.2%) had mild anaemia, 32.0% had moderate anaemia while 4.8% had severe anaemia. The most common type of anaemia was microcytic-hypochromic in 66 (44.9%) patients, followed by normocytic-hypochromic in 39 (26.5%), 28 (19.0%) patients had normocytic-normochromic anaemia and 12 (8.2%) patients had a mixed picture.Pneumocystis jiroveci pneumonia (PJP) prophylaxis was also significantly associated with anaemia . Other factors significantly associated with the presence of anaemia included presence of OIs, previous hospital admission, and presence of severe malnutrition (weight for age Z-scores (WAZ) or weight for height Z-scores (WHZ) <−3.0 SD). The use of co-trimoxazole (TMP/SMZ) for . Other fReticulocyte counts ranged from 0.3-11.6. Anaemic patients had a significantly higher mean reticulocyte count of 3.1 compared to 1.2 (p <0.0001) among non anaemic patients.HIV disease stage  was significantly associated with both the presence and severity of anaemia. Late stage HIV-disease (WHO stage III and IV) patients were 4 times more likely to be anaemic. Mean CD4+ values were significantly lower in the anaemic group (p = 0.04) Table.10) compared to 4.92 log 10 for the non-anaemic group (p = 0.011).The severity of anaemia generally increased with advancing WHO clinical stage (p<0.0001). Forty four out of 47 (96%) patients with moderate anaemia and all 7 patients with severe anaemia were in stage III or IV. Anaemic patients had a significantly higher baseline viral load . At 6 months, the anaemic patients had attained a mean CD4+ rise of 14.9 compared to the non-anaemic with 15.9. This difference was not significant (p=0.751).10) among anaemic patients compared to 2.42 log10 for non-anaemic patients (p = 0.002). Overall, the proportion of children who attained a viral load suppression to undetectable levels by 3 months was higher among non-anaemic compared to the anaemic children (p=0.002) (TableThe mean fall in viral load at 3 months was significantly lower (1.92 logOur study found a high prevalence of anaemia among HIV-infected paediatric patients presenting at an urban HIV clinic in Uganda, majority of them with mild anaemia. The frequency as well as severity of anaemia correlated with advanced clinical and immunological HIV disease stage. The study also found a significant association between the presence of anaemia and a poorer short-term virologic response to HAART.Anaemia in HIV-infected children is multi-factorial and takes varying morphological types,20. As iAlthough the mean reticulocyte count was significantly higher among patients who were anaemic at baseline, about 25% of these patients had a normal or low reticulocyte count at baseline suggesting either bone marrow suppression as the cause or, at least, a sub-optimal bone marrow response to the anaemia.In this study, advanced HIV clinical stage was founAs would be expected from previous studies,25 most Virological response, however, was significantly better among non-anaemic patients compared to those with anaemia, especially in the first 3 months on ART. Compared to initially anaemic patients, non-anaemic patients achieved a higher mean reduction in viral load and a significantly higher proportion attained complete viral suppression. Several previous studies have highlighted the importance of anaemia as an independent prognostic factor in HIV-infected individuals. Anaemia increases the risk of progression to AIDS-10 as weIn this study we focused on the more immediate outcomes of treatment with antiretroviral drugs, i.e. viral suppression, rise in CD4+ counts and short-term clinical improvement. Our findings, while reaffirming the importance of anaemia as a poor prognostic factor in HIV-infected children, suggest that the observed poorer outcome in anaemic HIV-infected children is, at least in part, mediated by a suboptimal virological response to HAART. The mechanism of the blunted virological response observed in anaemic children is not clear. Our study enrolled only ART-naïve children and did not include testing for viral resistance to antiretroviral drugs. It is possible that anaemic children who did not respond adequately to ART harboured some drug resistant strains; the risk of this could be expected to be higher in relation to the higher baseline viral loads observed among anaemic children. Other mechanisms might relate to possible poorer bioavailability of drugs in the sicker, anaemic children.Regardless of the mechanism, recognition of anaemia at initiation of ART could be useful to alert clinicians to children requiring closer monitoring for possible treatment failure. Furthermore, since correction of anaemia has been shown to improve prognosis, monitoring of haemoglobin during ART should help identify those children whose anaemia does not quickly respond to ART and thus require further investigation and specific treatment to correct anaemia.Results of this study need to be interpreted cautiously in light of some important limitations. Firstly, the exact causes of anaemia in these patients were not determined. A causal relationship should not be inferred about the association between anaemia and ART response, however using our multiple regression analysis, anemia remained a significant predictor of virological response. Secondly, the lack of data on anaemia in a comparable group of HIV negative children in the same setting limits our ability to interpret the prevalence results. Thirdly, failure to achieve sample size for the cohort due to limited time may have affected the results of the effect of baseline anaemia on subsequent effect on response to ART. However, the prospective cohort design, with longitudinal data collected suggests that the association between anaemia and ART response warrants further study in a larger cohort.In a group of HIV infected children in a rural Ugandan clinic the prevalence of anaemia was high but mostly mild. Microcytic-hypochromic anaemia was the most frequent type. Both the frequency and severity of anaemia were associated with advancing clinical and immunological HIV disease stage. Virological response to HAART was significantly better among children with no anaemia at baseline. Treatment with HAART improved anaemia in most HIV-infected children without additional treatments directed specifically at the anaemia. A thorough search for correctable causes of anaemia may need to be applied to HIV-infected children whose anaemia does not quickly improve on ART alone.The authors declared that they have no competing interest.ENR was a recipient of Master of Medicine in Paediatrics and Child health, conceived of the study, and participated in its design and coordination, data collection, analysis and writing the manuscript. JK participated in study design and coordination, read and advised at all stages of writing the thesis and writing of the final manuscript. FB participated in the design of the study, interpretation of results and writing of the final manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2431/12/170/prepub


One isolate (08MB08ZA) was HIV-1 subtype B while another (08MB26ZA) was related to HIV-1 subtype J. HIV-1 subtype recombination analysis with REGA assigned the pol sequence to HIV subtype J (11_cpx) with a bootstrap value of 75%. The prevalence of drug resistance mutations observed in the population studied was relatively higher than previously reported from other parts of South Africa. In addition, this is apparently the first report of an HIV-1 subtype J-like virus from northeastern South Africa.Data on antiretroviral drug resistance among drug-naïve persons are important in developing sentinel surveillance policies. This study was conducted to determine the prevalence of antiretroviral drug resistance mutations among drug-naïve HIV-infected individuals attending a voluntary testing and counselling centre at the Mankweng Hospital in northeastern South Africa. In total, 79 drug-naïve HIV-positive individuals were sequentially recruited during February 2008–December 2008. Drug resistance mutations were determined using the calibrated population resistance tool available on the Stanford HIV drug resistance database. Viral DNA was obtained from 57 (72%) of the 79 individuals. Reliable nucleotide sequences were obtained for 54 reverse transcriptase (RT) and 54 protease (PR) gene regions from 54 individuals. Overall, five sequences (9.3%) harboured drug resistance mutations . Four (7.4%) of these were nucleoside RT inhibitor mutations , and one (1.9%) was a PR inhibitor mutation (M46I). No major non-nucleoside RT resistance mutation was detected. Several minor resistance mutations and polymorphisms common in subtype C viruses were observed in the PR and RT genes. Phylogenetic analysis of the partial  The health and quality of life of patients infected with HIV/AIDS have dramatically improved since the introduction of highly-active antiretroviral therapy (HAART) in 1996 . HoweverIn the developed world, HAART has been used with remarkable success, and treatment is accompanied with regular virologic monitoring, including measurements of viral load and testing of drug resistance to guide management of patients ,6. On thSouth Africa has one of the highest HIV/AIDS prevalence in the world, and the South African National HIV and Syphilis Survey in 2007 showed that the estimated prevalence was 28%  samples were processed for total RNA extraction within 48 hours while stored at 4 °C. However, 10 samples, due to transportation logistics, were stored at 4 °C for four days before RNA isolation. Whole blood was spun at 3,000 rpm for three minutes. Plasma was aspirated aseptically and stored at −80 ˚C for subsequent RNA extraction. Data on viral load and CD4 count were not available.Viral RNA was isolated using the viral mini RNA kit  and stored at −80 °C until used. Two protocols were used at different times for amplifying the HIV polymerase gene. In one protocol, a one-tube RT-polymerase chain reaction (RT-PCR) was performed with AMV RT  and Taq DNA polymerase (Invitrogen), followed by a nested PCR as previously described . This geSubtyping of HIV was done by phylogenetic analysis. Polymerase sequences (880 bp) comprising the complete PR and partial RT genes of test viruses were aligned using ClustalX with representative subtype reference sequences  obtained from GenBank . Previouhttp://cpr.stanford.edu/cpr/servlet/CPR). The CPR tool analyzes submitted sequences for resistance mutations based on the surveillance transmitted drug resistance mutations list of the World Health Organization  tool (version 5.0) beta contained in the Stanford HIV Drug Resistance database  years. The proportion of women and men was 73.4% and 25% respectively. About 80% of the study subjects were single, and 22.8% were married. The most important risk factor for HIV transmission based on responses to the questionnaire was sexual intercourse (97.5%). However, the questionnaire was not designed to determine whether it was heterosexual or homosexual. In 89.9% of the participants, the most probable place of HIV infection was South Africa. About 47% of the subjects were infected in 2008 while the remaining subjects estimated that they were infected during 2000-2007. The highest level of education for 79.7% of the participants was grade 6 and above but no university graduates were recorded within the participants. Details of the demographic and socioeconomic characteristics of the study population are shown in the Table.Viral DNA was obtained for 57 (72%) of the 79 individuals. Reliable nucleotide sequences were obtained for 54 RT genes and 54 PR genes, on which genetic subtyping and drug resistance mutation analyses were done. Using the CRP analysis for surveillance drug resistance mutations, five (9.3%) of the 54 sequences had mutations associated with drug resistance . These included four NRTI mutations  harboured by sequences 08MB38ZA, 08MB26ZA, 08MB27ZA, and 08MB29ZA respectively, and one PI resistance mutation (M46I) observed in sequence 08MB62ZA. No NNRTI mutation was detected, and no sequence harboured more than one resistance mutation.pol sequences showed that 52 (96.3%) of the 54 isolates were HIV-1 subtype C. One isolate (08MB08ZA) was HIV-1 subtype B while isolate 08MB26ZA was observed to be related to HIV-1 subtype J reference sequences . Furthermore, the observed prevalence was also relatively higher compared to what has been previously reported from other parts of South Africa. For example, a surveillance study of drug resistance mutations in naïve persons in Gauteng province in 2002 and 2004 reported a 4.2% prevalence . SimilarIn the present study, all the observed resistance mutations were detected in different individuals, with 2008 being the probable year of infection. Mutations in D67E, D67G, and T69D were detected in three women while T215Y and M46I were detected in two men. Several polymorphisms, such as K20R, M36I, and I93L, common in HIV-1 subtype C viruses and associated with drug resistance site, were also observed as has been previously reported . AccordiAt the time of the present study, a combination regimen of stavudine, lamivudine, and efavirenz was the recommended first-line regimen, with nevirapine replacing efavirenz for women of childbearing age. A PI-containing regimen was used for children aged less than three years and in second-line regimen for adults .The study participants claimed not to have been treated with ARVs before the initiation of the study. Most study patients would benefit from the current first-line treatment regimen based on their viral genetic profiles. However, it is difficult to predict the spread of mutations observed and the implications on treatment outcomes at the population level. The resistance mutations described herein were observed after four years of the availability of treatment in the public health sector in the study area. It should also be noted that, although access to treatment in the public sector began in 2004, ARVs were available through the private sector before 2004, albeit at a higher cost and limited access. Accepting that the study participants had no prior exposure to ARVs, the mutations may have been acquired from transmitted viruses. Although the participants were apparently healthy, the absence of viral load and measurements of CD4 count do not allow a good estimation of their immunologic and virologic state. Mutations may revert over time in the absence of drug pressure, leading to a possible underestimation of transmitted resistance viruses. DNA amplification could not be obtained from about 25% of the samples probably because of very low viral loads, since most patients were asymptomatic. Subsequent surveillance studies are needed to confirm the findings of this report and to generate data relevant to sentinel surveillance policy and treatment-initiation guidelines.The identification of subtype C viruses as the predominant subtype is in agreement with findings of previous genotyping studies in northern South Africa ,12. HoweThe study was supported by a research grant awarded to Pascal O. Bessong by the National Department of Health and the National Research Foundation of South Africa. Permission to publish the results was obtained from the National Department of Health. The authors are grateful to Dr. C. Clark, Dr. S. Maweya, and Ms Khanyisa Sono of the Mankweng Hospital, South Africa, for recruiting the patients. The cooperation of the study participants is appreciated.


Data regarding CD4+ recovery after switching from protease inhibitor (PI)-based regimens to regimens not containing PI are scarce.3 after the switch, and the area-under-the-curve (AUC) of the CD4+ after the switch.Subjects with virological success on first-PI-regimens who switched to NNRTI therapy (NNRTI group) or to nucleoside reverse transcriptase (NRTI)-only (NRTI group) were studied. The effect of the switch on the ongoing CD4+ trend was assessed by two-phase linear regression (TPLR), allowing us to evaluate whether a change in the CD4+ trend (hinge) occurred and the time of its occurrence. Furthermore, we described the evolution of the frequencies in CD4-count classes across four relevant time-points . Finally, we explored whether the CD4+ counts evolved differently in patients who switched to NNRTI or NRTI-only regimens by considering: the overall CD4+ trends, the time to CD4+≥ 500/mm3 (P = 0.0024), and, finally, no significant differences in the CD4+ T-cell AUC after the switch after adjusting for possible confounders (propensity score and pre-switch AUC). Persistence at CD4+ < 200/mm3 was observed in 34/435 (7.5%) patients, and a decrease below this level was found in only 10/259 (3.9%) with baseline CD4+ ≥ 350/mm3.Eight hundred and ninety-six patients, followed for a median of 2,121 days, were included. At TPLR, hinges occurred in 581/844 (68.9%), but in only 40/581 (6.9%) within a time interval (180 days) compatible with a possible relationship to the switch; furthermore, in 19/40 cases, CD4+ counts appeared to decrease after the hinges. In comparison with the NNRTI group, the NRTI group showed CD4+ count greater at baseline (P = 0.0234) and before the switch (P ≤ 0.0001), superior CD4+ T-cell increases after HAART was started, lower probability of not achieving CD4+ ≥ 500/mmSwitching from first-line PI to NNRTI- or NRTI-based regimens did not seem to impair CD4+ trend over long-term follow-up. Although the greater CD4+ increases in patients who switched to the NRTI-only regimen was due to higher CD4+ counts before the switch, several statistical analyses consistently showed that switching to this regimen did not damage the ongoing immune-reconstitution. Lastly, the observation that CD4+ T-cell counts remained low or decreased in the long term despite virological success merits further investigation. The introduction of protease inhibitors (PI) as part of highly active antiretroviral therapy (HAART) in 1996 improved the clinical outcome of HIV-infected patients, decreased mortality rates by 3 to 10-fold and transformed HIV into a chronic disease ,3.Several studies demonstrated a positive effect of PI on CD4+ recovery over short-term follow-up , especiaData on CD4+ evolution after switching PI have been limited by short follow-up and small numbers of patients ,17-22. MIn planning a treatment simplification strategy, low cost and preservation of all the remaining classes  are two important benefits of switching to nucleoside reverse-transcriptase inhibitor (NRTI)-only regimens. In treatment simplification, the risk of virological failures, demonstrated with regimens containing only NRTI as first-line , has beeTherefore, the aim of the present study was to characterize the patterns of CD4+ responses in HIV-infected patients receiving virologically effective HAART regimens who changed from PI to regimens not containing PI: specifically, NNRTI or NRTI-only regimens. We evaluated whether this switch modified the ongoing evolutionary pattern of CD4+ T-cell count over long-term follow-up.Retrospective inter-cohort study in patients achieving HIV-RNA < 500 copies/ml after 12 months of a first antiretroviral regimen including PI.We followed 896 patients  from MASTER, ICONA, Chelsea & Westminster, S. Raffaele and Modena HIV cohort databases, who initiated antiretroviral therapy with 2NRTI+PI (boosted or not by ritonavir) between 1997 to 2006. Follow-up was censored at loss to follow-up, death, two consecutive HIV-RNA≥ 500 copies/ml, or treatment discontinuation, whichever occurred first. The chosen threshold for viral suppression was HIV-RNA < 500 copies/ml since ultra-sensitive assays were not available throughout the study period.Patients were grouped according to treatment change: 671 patients switched to non-NRTI (NNRTI)-based therapy (NNRTI group); 225 patients switched to NRTI-only (NRTI group).The study was approved by the ethics committees of each participating center and the written consent was obtained from the participants.3/day decrease or increase, was considered to express a decreasing or an increasing trend, respectively.In order to provide reliable estimates, we evaluated patients with ≥ 10 CD4+ determinations. A two-phase linear regression  was fitt3). As a per-patient analysis, we recorded the frequencies of stable, decreasing or increasing patterns at the above four time-points, considering, for simplicity, the three classes: CD4+ ≤ 200, 201-350, and > 350/mm3.First, to compare CD4+ trends, we described the overall CD4-patterns across four relevant time-points  together with their percentage changes from baseline and the evolution of the frequencies in four CD4+ classes  was applied taking individualization into account according to Liang . A refer©  were useWe calculated the area under the curve (AUC) of the CD4-counts (log-transformed), adjusted for time (divided by the days of follow-up) as a summary statistic of the overall amount of CD4+ at each time point. In particular, we derived: (i) the pre-switch AUC from before the start of therapy  to the therapy switch, and (ii) the post-switch AUC from the first CD4-count immediately after the switch  until the last observation.To compare non-randomized groups, the propensity score of belonging to the NNRTI or NRTI group was calculated using a multiple logistic model . The effOwing to the large sample size of at least 225 patients, it was possible to demonstrate a very low effect size of about 0.25 (a difference of 25% in the variability of the phenomenon investigated), which could be clinically insignificant.© version 9.1.Statistical analyses were performed using SASRegarding the baseline characteristics of the 896 patients Table , no stat3 per day) than in the NNRTI group (418 ± 236.6 cells/mm3 per day).In fact, more patients in the NRTI group initiated HAART in the period 2001-2003 than patients in the NNRTI group. Moreover, there was a statistically significant difference between the CD4+ counts in favour of the NRTI group (P = 0.0234) at baseline. This difference was also apparent for the CD4+ classes, though at a borderline significance level (P = 0.0782). Also, the CD4+ AUC before the switch was significantly greater (P < 0.0001) in the NRTI group  or nevirapine (298/671 = 44.41%). Zidovudine was prescribed in 350/671 (52.16%) patients, tenofovir in 44/671 (6.56%) and the association of tenofovir/didanosine in 15/671 (2.23%). Regarding the group 2, zidovudine was prescribed in 186/225 (82.67%) patients (P < 0.0001 vs. group 1), tenofovir in 18/225 (8%) and the association of tenofovir/didanosine in only 2 patients.Among 844/896 (94.2%) patients with ≥ 10 CD4+ determinations, a two-phase linear regression model fitted better (P < 0.10) than a simple linear regression in 436/627 (69.5%) patients in the NNRTI group and in 145/217 (66.8%) in the NRTI group. The hinges occurred at medians of 617 days (IQR: 336-1041) and 737 days (IQR: 392-1223) before the therapy switch and at medians of 308 days (IQR: 135-579) and 404 days (IQR: 218-722) after HAART initiation in the NNRTI and in the NRTI group, respectively.Table 3 per day) than in the NNRTI group (418 ± 236.6 cells/mm3 per day), as well as the CD4+ count before the switch (P < 0.0001).Medians, percentage increases and strata of CD4-count during the study are shown in Table 3 was always about 5%. Among patients with baseline CD4-count ≤ 200/mm3, a transition to upper CD4+ strata occurred in 316/342 (92.4%) and 85/93 (91.3%) in the NNRTI and in the NRTI group, respectively. Among patients with baseline CD4+ count between 201 and 350/mm3, 126/146 (86.3%) in the NNRTI group and 53/56 (94.64%) in the NRTI group had an increase to upper CD4+ strata, while two (1.37%) in the NNRTI group and two (3.57%) in the NRTI group had a decrease to ≤ 200 CD4+/mm3. Lastly, a decrease to CD4+ T-cell count ≤ 350/mm3 was found in 7/183 (3.8%) and 3/76 (3.95%) patients with baseline CD4+ T-cell count > 350/mm3 in the NNRTI group and in the NRTI group, respectively.Of note, the percentage of patients with CD4+ ≤ 200/mm3 in at least two sequential determinations after HAART are depicted in Figure 3 followed for a median of 943  days, the probability of not achieving a confirmed CD4-count ≥ 500/mm3 was higher in the NNRTI group than in the NRTI group . In particular, at one year it was 0.85 (95%CI = 0.81-0.89) vs. 0.79 (0.73-0.85), and at three years 0.54 (0.50-0.58) vs. 0.38 (0.30-0.46).Survival probabilities for not obtaining CD4+ ≥ 500/mmRegarding FNMEM, the two population curves of the CD4+ increase after the commencement of HAART to the last observation for the NNRTI group and the NRTI group and the reference bands  are depiThere was a statistically significant difference in the CD4+ counts Table  in favou3 per day) than in the NNRTI group (574 ± 266.5 cells/mm3 per day). However, the change in the CD4+ AUC (difference between before and after the switch) proved statistically insignificant .Furthermore, the CD4+ AUC was significantly greater (P < 0.0001) in the NRTI group  under virologically effective regimens, switching to regimens not including PI. Linear regression analysis seemed to rule out the possibility that switching from PI to alternative regimens caused immune damage. In fact, in 31.2% of patients, no hinges could be detected, while among those who presented a hinge, its relationship to the switch was reliable (≤ 180 days) in only 6.9% (40/581) patients. Moreover, a decreasing trend was demonstrated in only half (19/40). While the CD4+ T-cell count increased more in patients who were switched to NRTI-only regimens than in those who were switched to NRTI+NNRTI, this was probably because, in the NRTI group, the CD4+ T-cell count at baseline was higher and CD4+ T-cell count increase before the switch was greater. In fact, ANCOVA models adjusted both for the propensity score and for pre-switch AUC demonstrated no significant differences in the post-switch AUC.Regarding the main object of this paper  our results are consistent with the meta-analysis by Bucher et al.  on simplOther studies assessed CD4+ increases upon initiation of antiretroviral therapy indicating that CD4+ increases were better with PI  compared with NNRTI or triple NRTI regimens even though virological responses were similar among the three regimens or better with NNRTI than with PI boosted by ritonavir . Our anaRegarding the second objective (description of the long-term CD4+ counts), we found a plateau in CD4+ increase emerging from year 4 after HAART initiation. This evidence confirms previous results showing that the increase in CD4+T-cell count after HAART had a steep initial phase, followed by a second phase during which the increase was slower but continuing in patients who maintained HIV-RNA <1,000 copies/ml ,33-35, oDecreasing CD4+ patterns could be due either to the exhaustion of the regenerative capacity of the immune system , or to the fact that <500 HIV-RNA copies/ml as a cut-off could have covered incomplete viral suppression. While we await a demonstration that low-level viral replication, assessed by ultrasensitive assays, affects the regenerative capacity of the immune system, strict monitoring of CD4-count must be recommended even in those with long-term virological control. Moreover, we should experiment with interventions to slow or reverse unfavorable CD4+ trends and we should address whether eventual CD4+ decrease impacts on the virological and clinical outcomes of therapy.From a clinical point of view, our results may provoke some considerations. First, we confirmed, using a large cohort over a long follow-up, that switching form PI-regimens to regimens not containing PI is a viable strategy since immune-reconstitution is not compromised. Importantly, although we did not assess clinical outcomes or quality of life, CD4+ increase has been correlated with improvement in both measures .Regarding the type of regimen to which patients were switched, long-term evolution of CD4+ count did not appear to be impaired by the use of NRTI-only combinations that, owing to their suboptimal virological efficacy, have been progressively abandoned even for simplification as initial treatment of previously naive patients . By contThis work has limitations that need to be considered. The first limitation is that it was not a randomized clinical trial in which patients were randomized to continue PI or switch to alternative regimens. For example, it is possible that patients whose CD4+ counts did not increase as expected were either not switched or switched to regimens containing NNRTI but not to NRTI-only. However, we limited this bias by excluding from the study patients who continued on PI since their characteristics were too unbalanced compared with the other two groups, especially for CD4+ trend during the follow-up. Notwithstanding the exclusion of this group, a selection bias could have occurred favoring, in particular, the NRTI group. For this reason, we conducted several analyses to overcome the unbalance between the groups, even adjusting for propensity score and CD4+ count preceding the switch, all pointing to the fact that the switch and the choice of one regimen or the other did not impair the ongoing immune-reconstitution in our patients. The second limitation is that, by definition, all patients with virological failure were excluded from the study. Should patients in the NRTI group had failed more frequently, they would have been favored in this analysis. The third limitation is that, as discussed above, we used the 500 copies/ml cut-off as indicative of undetectable HIV RNA and this could have masked immune damage exerted by low-level viral load. However, ultrasensitive tests were not available for most patients at the time of the study and there is still a lack of data indicating that immune-reconstitution is different among patients with lower levels of plasma HIV load. The fourth limitation is that we did not focus on specific drugs, since we were interested in treatment strategy and consideration of multiple drugs would have reduced the power of the study to a significant extent.In conclusion, switching from first-line PI-containing regimens to NNRTI or NRTI-based regimens in the presence of <500 copies/ml HIV RNA did not appear to damage the CD4+ trend that was ongoing before the switch. Moreover, as far as long-term immunological outcome is concerned, we suggest that NRTI-only regimens be further evaluated for use in selected patients who are responding (and did not fail before) to other regimens. Lastly, we tried to provide unbiased results notwithstanding the observational nature of the study by analyzing the data from several aspects using pertinent statistical approaches. However, it is still possible that our results reflect a best case scenario regarding CD4+ immune recovery, especially in patients switched to NRTI-only. Since alternative drugs and classes are available and, for some of them, a beneficial effect on CD4+ reconstitution has been hypothesized (e.g. CCR5 co-receptor inhibitors ), our apCT and GC have received unrestricted educational grants (as speakers of for participation to conferences) from Abbott, Gilead, Merck, GSK, BMS, Schering Plough, Roche s.p.a. CM has received fees and funding from Abbott, Gilead, Merck, GSK, BMS, Pfizer, Roche s.p.a. AC has served as a consultant and received honoraria from Abbott, Gilead, Merck, GSK, BMS, Tibotec. The other authors have no financial interests to disclose in relationship to this paper.CT conceived of the study and drafted the manuscript; ADM provided data and revised the manuscript critically for important intellectual content; AP provided data and revised the manuscript critically for important intellectual content; GL set up the database and performed descriptive statistical analyses; GCo provided data; AA provided data; ADL provided data; CM provided data; ACa provided data; PC provided data; LM provided data; AC provided data; GC participated in study design and coordinated the study; HL participated in the statistical analysis; BMC participated in study design, performed statistical analyses and drafted the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2334/11/23/prepub