HIV–infected persons are at increased risk of pneumonia, even with highly active antiretroviral treatment (HAART). We examined the impact of pneumonia on mortality and identified prognostic factors for death among HIV–infected.In a nationwide, population-based cohort of individuals with HIV, we included persons hospitalized with pneumonia from the Danish National Hospital Registry and obtained mortality data from the Danish Civil Registration System. Comparing individuals with and without pneumonia, we used Poisson regression to estimate relative mortality and logistic regression to examine prognostic factors for death following pneumonia. From January 1, 1995, to July 1, 2008, we observed 699 episodes of first hospitalization for pneumonia among 4,352 HIV patients. Ninety-day mortality after pneumonia decreased from 22.4%  in 1995–1996 to 8.4% (95% CI: 6.1%–11.6%) in 2000–2008. Mortality remained elevated for more than a year after hospitalization for pneumonia: adjusted mortality rate ratio 5.38 (95% CI: 4.27–6.78), 1.80 (95% CI: 1.36–2.37), and 1.62 (95% CI: 1.32–2.00) for days 0–90, 91–365, and 366+, respectively. The following variables predicted mortality within 90 days following hospitalization for pneumonia (adjusted Odds Ratios): male sex , Charlson Comorbidity Index score ≥2 ; no current HAART ; history of AIDS ; age per 10 year increase ; and CD4+ cell count ≤200 .The first hospitalization for pneumonia among HIV–infected individuals was associated with elevated risk of death up to more than a year later. Use of HAART decreased the risk, independent of current CD4+ cell count. Prognosis following pneumonia improved over calendar time. Early in the HIV epidemic it was recognized that morbidity and mortality due to pneumonia were higher in HIV-infected persons than in the general population We conducted a nationwide, population-based cohort study among HIV-infected persons in Denmark from 1995 to 2008. Treatment for HIV infection in Denmark is restricted to 8 specialized centers. The Danish health care system provides free, tax-supported medical care for all residents, including antiretroviral treatment of HIV.+ cell count.The DHCS has established a prospective, dynamic, nationwide, population-based cohort of all HIV-infected individuals seen in Danish HIV clinics since 1 January 1995. DHCS has been described in detail elsewhere CRS is a national registry of all Danish residents, which contains information on date of birth, sex, date of migration, and date of death. A 10-digit personal registration number (CPR number), assigned at birth, uniquely identifies each person since 1968. The CRS is updated within a week of a person's birth, death, or emigration. Use of the CPR number enables Danish HIV clinics to avoid multiple registrations of the same patient and allows tracking of deaths and persons lost to follow-up due to emigration.NHR contains information on all patients discharged from Danish hospitals since 1977. Records for each hospitalization include CPR number, hospital department, inpatient and outpatient discharge diagnoses, and dates of admission and discharge. Diagnoses are coded by the treating physician according to the International Classification of Diseases, 8th revision (ICD-8) until the end of 1993 and 10th revision (ICD-10) thereafter.Pneumocystis jiroveci pneumonia was not counted as an episode of pneumonia.We identified the first hospitalization for pneumonia following HIV diagnosis. We used the NHR to identify all hospital stays with a discharge diagnosis of pneumonia using ICD-8 codes 471.x (influenza with pneumonia), 480.x-486.x (pneumonia), 073.x (ornithosis) and ICD-10 codes J11.0 (influenza with pneumonia), J12.x–J18.x (pneumonia), A481.x, (ornithosis), or A709.x (legionellosis). Thus, both community-acquired and hospital-acquired pneumonias were included. The pneumonia diagnoses recorded in the NHR were validated in a previous report Our study population consisted of persons in DHCS who were at least 16 years old on the date of HIV diagnosis and who had no recorded hospitalization for pneumonia before entering DHCS. Study subjects were followed from their registration in DHCS to death, loss to follow-up or 1 July 2008, whichever came first.HAART was defined as either a 3-drug regimen that included a non-nucleoside reverse transcriptase inhibitor, a protease inhibitor, and/or abacavir; or a 2-drug regimen with a combination of a non-nucleoside reverse transcriptase inhibitor and a boosted protease inhibitor.+ cell counts and viral load (VL)CD4 were estimated between measurements by carrying forward the value from the most recent measurement. + cell countNadir CD4 was defined as the lowest CD4+ cell count ever measured for a given patient.Comorbidity was assessed with the Charlson Comorbidity Index (CCI). The index, which includes 19 major disease categories, has been adapted and validated for use with hospital discharge data in ICD databases for predicting short- and long-term mortality CCI score was computed for each patient based on all available foregoing NHR discharge diagnoses. A previous AIDS diagnosis (conferring 6 CCI points) was not included in our computations Hepatitis C co-infection was defined as patients having at least 1 positive result on a hepatitis C virus (HCV)-antibody test or a positive result on HCV RNA test.The endpoint, defined a priori, was all-cause mortality following the hospital admission date for pneumonia. Causes of death, extracted from patient files and available in the DHCS database, were divided into HIV-related causes , serious non–AIDS causes , unnatural causes  and other/unknown causes.We first computed 30-day and 90-day cumulative mortality following the first hospitalization for pneumonia and constructed Kaplan-Meier survival curves, stratified into 3 calendar periods: 1995–1996 (“pre-HAART era”), 1997–1999 (“early HAART era”), and 2000–2008 (“late HAART era”).We then assessed the effect of a first hospitalization for pneumonia on mortality. We compared the mortality rate in persons who had no previous history of pneumonia (reference group) with that of persons with a first hospitalization for pneumonia within the last 0–90 days, within the last 91–365 days, and more than 365 days ago. Poisson regression analysis was used to adjust for potential confounders. The following time-dependent variables were forced into the model based on their presumed association with pneumonia and/or effect on mortality: CCI score (0–1/2+), age , and CD4+ cell count (continuous). Other variables were examined and included in the final model if they changed the effect measure by 10% or more. Constant variables were sex , hepatitis C coinfection (yes/no), injection drug use (IDU) as presumed mode of HIV infection (yes/no), and race (Caucasian/non-Caucasian). Time-dependent variables were history of AIDS (yes/no), current HAART (yes/no), years since entering the DHCS, and calendar time period (1995–96 vs. 1997–2008). Causes of death were tabulated for all four time periods.+ cell count thus could cancel out the effect of previous AIDS); IDU as mode of HIV exposure which is interdependent with hepatitis C status; and HIV RNA which is interdependent with use of HAART.Finally, we used logistic regression to identify prognostic factors for 30-day and 90-day mortality following hospitalization for pneumonia. In the unadjusted analyses we included all the variables listed above as of the time of admission, as well as log-transformed HIV RNA (continuous). In the adjusted analyses of 30-day and 90-day mortality we included all variables from the unadjusted analyses in the models, except: nadir CD4+ cell count because this variable and history of AIDS are interdependent  for statistical analyses. The study was approved by the Danish Data Protection Agency. In Denmark, a national board (The Danish Data protection Agency) approved the studies. Informed consent was waived. Informed consent was not required by Danish law in order to conduct cohort studies.Between 1 January 1995 and 1 July 2008, 699 episodes of an initial hospitalization for pneumonia were observed among 4,352 persons who were at least 16 years old and had no recorded hospitalization for pneumonia before entering the DHCS cohort. Characteristics of persons in our study population at the time of the initial hospitalization for pneumonia are shown in Overall 30-day risk of death after first hospitalization for pneumonia was 6.4% (95% CI: 4.8%–8.5%) see . It was adj], 95% CI: 4.27–6.78). Mortality was also elevated for days 91–365  and days 366+ . Causes of death for persons in all four time strata are presented in The effect of first-time hospitalization for pneumonia on mortality among all HIV-infected persons is shown in adj = 4.07, 95% CI: 2.03–8.17), male sex , no current HAART , history of AIDS , latest CD4+ cell count ≤200 cells/µl  and age .In the adjusted logistic regression analysis, the following variables were associated with increased 30-day mortality after a first hospitalization for pneumonia : CCI scoadj = 3.86, 95% CI: 2.19–6.78), male sex , no current HAART , previous AIDS , CD4+ cell count ≤200  and age . Among patients on HAART neither the duration of HAART use or HIV RNA (<50 vs. ≥50 copies/mL) were protective (data not shown).Variables associated with increased 90-day mortality were : CCI scoThis study found that short-term mortality after a first hospitalization for pneumonia among HIV-infected individuals decreased from the pre-HAART to the late-HAART era. Despite this decrease over time, an episode of hospitalization due to pneumonia remains associated with an increased mortality among HIV patients. Prognostic factors were male sex, age, pre-existing comorbidity, low CD4 cell count, older age, and absence of HAART treatment. Several studies have shown that persons on HAART have a reduced risk of pneumonia compared to those not on HAART The strengths of our study include use of a population-based, nationwide cohort with nearly complete inclusion and minor loss to follow-up; access to complete hospitalization data and vital statistics; and availability of electronically collected longitudinal data on viral load and CD4+ cell counts. The quality of the data minimized selection and information biases. Because we considered only the first hospitalization for pneumonia, our estimates were not biased by multiple pneumonia episodes occurring in highly susceptible individuals.i.e., patients on HAART had an a priori reduced risk of death for example due to a healthier lifestyle compared to HAART-naïve patients).Our study had a number of limitations. First, previous studies have found identifiable bacterial pathogens in 24%–38% of HIV-infected patients with pneumonia The incidence rates of pneumonia in HIV-infected individuals decreased from 51 hospitalizations per 1000 person-years during 1995–1996 to 20 hospitalizations per 1000 person-years during 2005–2007 Contrary to studies on invasive pneumococcal disease i.e., pulmonary and extrapulmonary tuberculosis, pneumocystis jiroveci (carinii) pneumonia and esophageal candidiases) In a study of non-HIV infected individuals aged 40–64 hospitalized for the first time with pneumonia, 30-day mortality was 7.8%, and 90-day mortality was 11.6% Others have found a four to five-fold increased risk of death (follow-up ≤51 months) among HIV-infected persons with pneumonia, compared to those without pneumonia We found that HAART use improved the prognosis after a pneumonia-related hospitalization also after adjusting for CD4+ cell count, which is in line with results from earlier studies We observed a lower short term mortality among females than males. In the HIV Epidemiologic Research (HER) Study on pneumonia Kohli et al. found in-hospital mortality after bacterial pneumonia to be 7.7% among females In conclusion, a first hospitalization for pneumonia in HIV-infected individuals predicted an increased risk of death beyond one year. Among those hospitalized with pneumonia, use of HAART was associated with a reduced risk of death, independent of CD4 cell counts. While the former finding may indicate that acquisition of pneumonia is a marker of frailty, the latter may indicate that this frailty can be partly offset by use of HAART. These findings support the need for additional research to assess the role of HAART in reducing morbidity and mortality associated with non-AIDS-defining infections. Promotion of early HAART initiation may not only lead to reduced mortality after pneumonia, it may also reduce the risk of acquiring pneumonia severe enough to require hospitalization


Successful antiretroviral treatment is dependent on sustaining high rates of adherence. In the southern African context, only a handful of studies  have looked at the determinants including a health behaviour theory of adherence to antiretroviral therapy. The aim of this study is to assess factors including the information, motivation and behavioural skills model (IMB) contributing to antiretroviral (ARV) adherence six months after commencing ARVs at three public hospitals in KwaZulu-Natal, South Africa.Using systematic sampling, 735 HIV-positive patients were selected prior to commencing on ART from outpatient departments from three hospitals and followed-up at six months and interviewed with a questionnaire.A good proportion of patients were found to be adherent using both adherence instruments . After adjusting for significant socio-economic variables, both the VAS and the dose, schedule and food adherence indicator found levels of adherence amongst urban residents to be almost 3 times greater than that of rural residents. After adjusting for health-related variables, for both indicators better adherence was associated with low depression and poorer adherence was associated with poor environmental factors. Adjusted odds ratios for adherence when taking into account different behavioural variables were for both adherence indicators, discrimination experiences were associated with lower adherence, and higher scores in adherence information and behavioural skills were associated with higher adherence. For the VAS adherence indicator, higher social support scores were associated with higher adherence. For the dose, schedule and food adherence indicator, using herbal medicines for HIV was associated with lower adherence.For the patients in this study, particularly those not living in urban areas, additional support may be needed to ensure patients are able to attend appointments or obtain their medications more easily. Adherence information and behavioural skills as part of the IMB model should be strengthened to improve adherence. Further psychological support is also required and patients' perceived need for ARTs should be routinely assessed. The clinical efficacy of antiretroviral therapies (ART) in suppressing the HIV virus and improving survival rates for those living with HIV has been well documented -5. HowevA meta-analysis conducted by Mills et al. , examineThere is a lack of studies investigating treatment competency factors and also utilizing a health behaviour theory such as the Health Belief Model  in relatThis is a cross-sectional study of all treatment-naúve patients (N = 735) recruited from all three public hospitals in Uthukela health district in KwaZulu-Natal from October 2007 to February 2008. The District has one regional and two district hospitals, one private hospital, three primary health care facilities, 24 fixed clinics and 17 mobile clinics with 177 visiting points . InitiatAll ARV-naúve patients who were about to commence ARVs (18 years and above) and who consecutively attended the HIV clinics during the recruitment period were eligible for this study. Physicians from the three selected public clinics asked every consecutively visiting ART-naïve patient meeting the inclusion criteria of being 18 years or over if they would like to complete a confidential survey and interview concerning their health and social situation. This would include information from their medical records on details of their medical condition, laboratory tests and treatment. If the potential participant indicated an interest in participating, the health care provider then referred them to an external HSRC research assistant for possible research participation. The interviews were conducted by four trained external HSRC researchers (one or two per HIV clinic) in interview administration of the semi-structure interview schedule. Interviewers were trained over one week in questionnaire administration and ethics procedures. Recruitment took place over a period of four months, with 97.8% participation rate. The questionnaire was translated into the major language spoken in the study area (Zulu) and verified by a second translator. Where inconsistencies were found, these were corrected. Pre-testing of the questionnaire was completed with five HIV-positive persons not involved in the study. More details about the setting, sampling procedure and recruitment have been described elsewhere . PatientEthics approval was obtained from the HSRC ethics committee and approval was obtained from the Provincial Department of Health in KwaZulu-Natal.Patients were interviewed with an anonymous questionnaire that requests information on sociodemographic characteristics, clinical history and health-related characteristics and health beliefs. Clinical data relating to date of HIV diagnosis, HIV acquisition and transmission risk factors, current CD4 cell count, viral load (Chiron 3.0 bDNA), opportunistic infections, HIV and non-HIV medications was obtained from the medical chart.The SSC-HIVrev is a 72-item checklist of HIV/AIDS specific physical and psychological symptoms, scored using the following scale: 0 = not present today, 1 = mild, 2 = moderate, 3 = severe . Female-The WHOQOL-HIV BREF is based on the WHOQOLHIV measure, one of the two World Health Organization's QoL instruments for use with HIV-infected populations . This inIdentification Test (AUDIT)-C focuses solely upon consumption of alcohol  . BecauseItems were adapted to assess internalized AIDS stigma from a scale developed to measure AIDS related stigma beliefs in general South African populations. We selected seven items from the AIDS-Related Stigma Scale  and refrTo assess AIDS-related discrimination, we asked participants if they had experienced seven discrimination-related events, e.g., whether they had been treated differently since they had disclosed their HIV status to friends and family; whether being HIV positive had caused them to lose a job or a place to stay; and whether they had experienced discrimination because they are HIV positive. Response options were "yes" or "no". Cronbach's alpha for this sample was 0.54.Three items were drawn from the Social Support Questionnaire to assess perceived social support . The itedepressive symptoms using the 10-item version of the Centers for Epidemiologic Studies Depression Scale (CES-D) [We assessed  (CES-D) . The CES (CES-D) . CronbacARV treatment adherence was assessed by two self-reported adherence measures - the Adult AIDS Clinical Trials Group (AACTG) adherence instrument and the 30-day visual analog scale (VAS). The AACTG consists of nine questions that assess adherence from the previous 1-4 days, within the past week, prior to the interview. The instrument also assesses reasons for non-adherence . The 30-Dose adherence was assessed by asking participants to report on how many days they had missed taking all their doses during the past 4 days. Dose non-adherence was defined as having missed all doses on at least one day during the past 4 days.Adherence to scheduling was measured by the question "Most anti-HIV medications need to be taken on a schedule, such as '2 times a day' or '3 times a day' or 'every 8 hours.' The participants were asked to report how closely they followed their specific schedule over the last 4 days using a 5-point Likert scale, ranging from "never" to "all the time." Schedule non-adherence was defined as having missed scheduling in the past 4 days. Adherence to dietary instructions was measured by first asking "Do any of your anti-HIV medications have special food instructions, such as 'take with food' or 'on an empty stomach' or 'with plenty of fluids'?" If the response was "yes," participants were asked to rate how often they had followed dietary instructions over the last 4 days using a 5-point Likert scale, ranging from never" to "all the time." Schedule non-adherence was defined as having missed scheduling in the past 4 days. Food non-adherence was defined as not having followed special instructions over the last 4 days.LifeWindows Information-Motivation-Behavioural Skills ART adherence questionnaire (LW-IMB-AAQ) [The IMB-AAQ) ,39. EachData were analyzed using Statistical Package for the Social Sciences (SPSS) for Windows software application programme version 17.0. Frequencies, means, standard deviations, median, interquartile range, were calculated to describe the sample. Uni- and bi-variate analyses and, multiple logistic regressions were used to investigate associations between the outcomes ART adherence and socioeconomic variables, health related variables, and behavioural variables as well as information-mativation-behavioural skills model variables. Associations were considered significant at P < 0.05. Separate multivariable logistic regression analyses were conducted for socio-demographic variables, health related variables and behavioural variables (moderating factors) and information-mativation-behavioural skills model variables and ART adherence. All variables statistically significant at the P < .01 level in bivariate analyses were included in the multivariate model. No significant interactions were found between socioeconomic variables, health related variables, behavioural variables and information-mativation-behavioural skills model variables.Of 735 patients  who completed assessments prior to initiation of ARVs, 525 were able to complete the assessment at six months follow-up. Of the original cohort, 75 had died, 57 had been transferred, 54 could not be traced, 23 refused the interview and 1 interview was incomplete. At six months following proposed ARV initiation, 519 patients started therapy and six failed to start treatment. Over the six month period 24 patients (4.6%) had temporarily suspended ARVs because of side effects, and three (0.6%) had changed their ARVs. HIV medications for 411 (79.2%) patients included Lamivudine (3TC), Stavudine (d4T) + Efavirenz (Stocrin) and for 108 (20.8%) Lamivudine (3TC), Stavudine (d4T) + Nevirapine. Fixed dose combination of ARVs was not available for patients on this programme during the time of the study.2 = 8.13, P = .004) and had a lower CD4 cell count  (v. Table Nearly three-quarters (73.5%) of the 519 patients who had initiated ARVs in this sample were female, 62.2% of whom were between 30 and 49 years old. Nearly three-quarters (73.3%) were never married, 61.9% had Grade 8 or higher formal education, almost all (98.8%) were Zulu and the largest religious affiliation was charismatic churches (38.5%). The majority of the sample (61.7%) lived in rural areas and was unemployed (59.6%). Only 31.7% of respondents had a formal salary as their main source of household income and 52.5% was in receipt of a disability grant. Those who were followed up at six months (n = 525) were compared to those who could not be followed up (n = 210) on sex, age, formal education, urban or rural residence, HIV symptoms, CD4 cell count and in recept of a disability grant. We found that those who could not be followed up were more likely to be male (χv. Table Most patients 75.2%) had been diagnosed with HIV in the year prior to study recruitment. The median CD4 count at follow-up was 130 cells/cu.mm compared to 119 cells/cu.mm prior to ARV initiation. The mean number of HIV symptoms reported at follow-up was 1.21, 6.6% of patients were receiving TB treatment, 10.3% had at least one hospital admission in the past six months, and 25.6% had seen an ARV treatment buddy at least once in the past six months. Patients with an identified adherence problem are referred to a treatment buddy . From those found non-adherent on the VAS (17.1%) 85.2% were also found to be non-adherent on the AACTG measure  427 patients (82.9%) were 95% adherent in the month prior to the survey. Results from the AACTG adherence instrument found that on the 4-day recall dose adherence, 15.5% of patients were non-adherent (having missed at least one full day of medication in the past four days). 70.8% of patients were adherent to all parameters . Pearson correlation among the two adherence outcome measures (VAS and AACTG) using categorical cutoffs to define adherence indicated a moderate level of association . The dose, schedule and food adherence indicator found adherence to be 3.3 times greater amongst patients with a CD4 count above 200 cells/uL, 4.6 times greater among patients with the 3TC, d4T + Nevirapine regimen and higher overall quality of life. The VAS adherence indicator found higher adherence amongst patients with lower scores in the Spirituality/religion/personal beliefs domain, with higher general health perception scores and with higher scores in social relationships domain v. Table .Table A good proportion of patients were found to be adherent using both adherence instruments . These good figures are similar to that of 77% found for African patients the meta-analysis by Mills and colleagues . Such goImportant socio-economic predictors of ART adherence in this South African sample include urban area of residence and adequate physical environment including transport and access to health services. Living in an urban area is likely to be associated with lower transport costs and fewer disruptions in access to medications, which other studies have found to be a facilitators of adherence ,18,20.For health-related variables in this sample, lower depression scores were significantly associated with higher adherence for both adherence indicators. Other studies have similarly found that psychological health ,20 is anWhilst the use of prayer predicted higher adherence in a Zambian study , the useBehavioural variables associated with greater adherence include, high scores for IMB adherence information and behavioural skills and not using herbal medicines. Having greater knowledge about HIV and ARVs and greater HIV treatment behavioural skills and not using herbal medicines are known facilitators of adherence and confirm the IMB mdel -20,40. EThis study also has limitations. For more than 95% of the patients studied viral loads were not available from medical records; they had not been done. So an important outcome of ART and ART adherence viral suppression could not be assessed. The patients who died or were lost to follow-up in the first 6 months were not included in the present study (selection bias). Some factors such as food insecurity, transportation barriers, and structural barriers of ARV adherence were not assessed . FurtherThe adherence rate found in this study seems to be good. The use of two different adherence indicators was important for reducing bias through self-reporting and therefore enabling a greater potential range of determinants to be identified. Given the sample size and the large number of potential determinants of adherence in this study, variables were analysed in parsimonious subsets rather than one model. For the patients in this study, particularly those not living in urban areas, additional support may be needed to ensure patients are able to attend appointments or obtain their medications more easily. Adherence information and behavioural skills as part of the IMB model should be strengthened to improve adherence. Further psychological support is also required and patients' perceived need for ARTs should be routinely assessed. Although caution is urged in generalizing findings to other districts and provinces in the country, the results generally support the findings from other adherence studies in southern Africa.The authors declare that they have no competing interests.KP and NFDP conceptualized and designed the study, analysed and interpreted the data, drafted and revised the manuscript. SR participated in data collection, analysis and drafting of manuscript. JA participated in the design of the study and data analysis. All authors read and approved the final draft of the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/10/111/prepub


Treatment of chronic hepatitis C virus (HCV) has advanced considerably since the initial identification of the virus in the late 1980s. Preliminary treatment with conventional interferon monotherapy yielded disappointing sustained virologic response (SVR) rates of 10% to 15%.8Only a minority of HCV-infected patients will develop serious disease-related complications,11Predictors of response to therapy serve as decision tools for physicians to help identify patients who are likely or unlikely to achieve an SVR, and to consider pre-treatment counseling in those patients with a reduced likelihood of successful therapy, perhaps sparing them the side effects and cost of therapy. Therefore, knowledge of predictors to these therapies is extremely valuable. Traditional predictors of response identified in international studies regardless of genotype can be divided into three groups: (1) epidemiological factors including patient age, sex, and race, (2) viral factors, most importantly the pre-treatment viral load, rapid virologic response, and the genotype, and (3) histological factors including the amount of fibrosis and steatosis.457Annals, Al-Ashgar and colleagues report the results of their retrospective analysis of 148 HCV genotype 4 patients who underwent therapy with pegylated interferon alfa-2a plus ribavirin for 48 weeks.In this issue of the The study by Al-Ashgar and colleagues is significant in that it adds to the growing pool of data relating to the treatment of HCV genotype 4. It is important to note that this is the first large study from the region reporting on the efficacy of pegylated interferon alfa-2a in genotype 4 patients, in addition to the fact that it contributes essential knowledge on the predictors of virologic response. However, the study suffers from several shortcomings in design, and is hindered by unexpected and unconventional findings. The SVR observed in this study  is certainly lower than that reported previously in genotype 4 patients using pegylated interferon alfa-2b and weight-based, standard-dose ribavirin (e.g., 69% by Kamal,15The second important finding of this study is related to the predictors of response, where traditional predictors like pre-treatment viral load and extent of hepatic fibrosis fell by the wayside, and non-conventional factors like AST and AFP were identified to be predictive. In an earlier study of 250 Egyptian genotype 4 patients, the presence of severe fibrosis, hepatic steatosis, treatment with conventional interferon, and AFP level were found to predict SVR.151719An important lapse of this retrospective analysis is that the authors did not have adequate information on the form of antiviral therapy administered previously, whether it was conventional interferon vs. pegylated form, monotherapy vs. combination with ribavirin, or the duration of such therapy. Also, as has been convincingly demonstrated in earlier trials, a nonresponder to, or relapser after, previous antiviral therapy significantly affects the likelihood of response to subsequent interferon-based therapy. All such pertinent information is unavailable in the current study and may have affected the results of the univariate analysis. Moreover, because of the retrospective nature of the study, only 72 of the 96 patients who were analyzed had a pre-treatment liver biopsy. This, in part, may explain why none of the histological predictors were identified as opposed to almost all other genotype 4 and non-genotype 4 studies. Thus, the unavailability of this information in the current study may likely have affected the results of the univariate analysis, and in effect limits the overall scope of the study.Finally, the authors, while reporting SVR rates with an ITT methodology, did not maintain this while performing the regression analysis. ITT analysis denotes analyzing patients in the groups they were assigned to at the beginning of the study regardless of whether they actually completed therapy or not. Deviations from ITT analysis introduce potential investigator bias in interpretation of results with the inherent plausibility of overestimating drug efficacy.Despite these concerns, this study remains an important contribution to our understanding of virologic response in genotype 4 patients. Future studies should be directed at investigating the optimal duration of therapy utilizing the rapid virologic response and early viral kinetics.Major advances in the treatment of HCV in the last decade offer us hope that the day of curing all patients with HCV is not too far away. While we stand one step closer to our destiny today, our goal per se is aptly exemplified in the words of T.S Eliot: “Only those who risk going too far can possibly find out how far one can go.” And this time HCV patients with genotype 4 should journey the whole length and not be left behind.


HAART rollout in Latin America and the Caribbean has increased from approximately 210,000 in 2003 to 390,000 patients in 2007, covering 62% (51%–70%) of eligible patients, with considerable variation among countries. No multi-cohort study has examined rates of and reasons for change of initial HAART in this region.Antiretroviral-naïve patients > = 18 years who started HAART between 1996 and 2007 and had at least one follow-up visit from sites in Argentina, Brazil, Chile, Haiti, Honduras, Mexico and Peru were included. Time from HAART initiation to change  was estimated using Kaplan-Meier techniques. Cox proportional hazards modeled the associations between change and demographics, initial regimen, baseline CD4 count, and clinical stage.Of 5026 HIV-infected patients, 35% were female, median age at HAART initiation was 37 years , and median CD4 count was 105 cells/uL . Estimated probabilities of changing within 3 months and one year of HAART initiation were 16%  15–17%) and 28% (95% CI 27–29%), respectively. Efavirenz-based regimens and no clinical AIDS at HAART initiation were associated with lower risk of change (hazard ratio (HR) = 1.7 (95% CI 1.1–2.6) and 2.1 (95% CI 1.7–2.5) comparing neverapine-based regimens and other regimens to efavirenz, respectively; HR = 1.3 (95% CI 1.1–1.5) for clinical AIDS at HAART initiation). The primary reason for change among HAART initiators were adverse events (14%), death (5.7%) and failure (1.3%) with specific toxicities varying among sites. After change, most patients remained in first line regimens.Adverse events were the leading cause for changing initial HAART. Predictors for change due to any reason were AIDS at baseline and the use of a non-efavirenz containing regimen. Differences between participant sites were observed and require further investigation. An estimated 1.93 million people live with HIV in Latin America and the Caribbean, comprising 5.7% of all infected persons worldwide; the adult prevalence in this region is 0.5%Treatment toxicities and adherence problems may lead to suboptimal therapy, discontinuation, and treatment failure. Early modification of initial highly active antiretroviral therapy (HAART) has been associated with poor clinical outcomesThe frequency and reasons for HAART change have been assessed by cohort studies from resource-rich and -limited settings, but Latin America and the Caribbean have been largely underrepresented in these studiesThe Caribbean, Central and South America Network for HIV Research (CCASAnet) collaboration includes sites from seven nations: Argentina, Brazil, Chile, Haiti, Honduras, Mexico, and Peru. In an earlier study of antiretroviral-naïve subjects starting HAART, mortality rates in the CCASAnet cohort were similar to those reported for resource-limited settings with a 1-year probability of death for the combined cohort of 8.3%, although this varied considerably across sitesThis study was conducted according to the principles expressed in the Declaration of Helsinki. Institutional Review Board approval was obtained locally for each participating site and the coordinating centre: Comité de Bioética de Fundación Huésped; Comitê de Ética em Pesquisa-Universidade Federal Do Río De Janeiro; Comité Ético-Científico del Servicio de Salud Metropolitano Central, Ministerio de Salud, Gobierno de Chile; Human Research Protections Programs, Division of Research Integrity, Weill Cornell Medical College; Comité de Ética en Investigación Biomédica de la Unidad de Investigación Científica, Facultad de Ciencias Médicas, Universidad Nacional Autónoma de Honduras; Comité Institucional de Investigación Biomédica en Humanos, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán; Vicerrectorado de Investigación, Dirección Universitaria de Investigación, Ciencia y Tecnología-DUICT, Universidad Peruana Cayetano Heredia; Institutional Review Board, Vanderbilt University.All data were de-identified prior to being transmitted to the Vanderbilt Data Coordinating Centre.In each of the countries contributing data to this study, ethical regulations and policies permit retrospective analysis of de-identified clinical data without informed consent when the research is approved by an appropriately constituted ethics committee or Institutional Review Board. These approvals were obtained in all cases and the need to obtain informed consent was waived by all of the ethics committees of the participating sites.www.ccasanet.vanderbilt.edu) has been described elsewherewww.iedea-hiv.org). The cohort includes 7 sites: Fundación Huésped in Buenos Aires, Argentina (FH-Argentina); Hospital Universitário Clementino Fraga Filho in Rio de Janeiro, Brazil (HUCFF-Brazil); Fundación Arriarán in Santiago, Chile (FA-Chile); Le Groupe Haïtien d'Etude du Sarcome de Kaposi et des Infections Opportunistes in Port-au-Prince, Haiti (GHESKIO-Haiti); Instituto Hondureño de Seguridad Social Hospital de Especialidades and Hospital Escuela in Tegucigalpa, Honduras (IHSS/HE-Honduras); Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán in Mexico City, Mexico (INNSZ-México); and Instituto de Medicina Tropical Alexander Von Humboldt in Lima, Peru (IMTAvH-Peru). Each cohort was established at a different time between 1996 and 2002 not necessarily reflecting the availability of HAART in each country.The CCASAnet cohort  while on their first HAART as having discontinued treatment. Patients without a visit for 6 months were classified as LTFU. The 6-month interval was chosen to include the longest interval between regular visits in participant sites, although most sites scheduled visits every 3 months.Baseline CD4 count was defined as the measurement closest to HAART initiation but not more than 6 months prior to, or 7 days after, the date of HAART start. Baseline HIV-1 plasma viral load (PVL) was defined as the pre-HAART measurement closest to, but not more than 6 months prior to, HAART initiation. Baseline weight and hemoglobin were defined as the measurements closest to HAART initiation within +/− 30 days. HAART was defined as protease inhibitor (PI)-based (1 ritonavir-boosted or unboosted PI plus ≥2 nucleoside reverse-transcriptase inhibitors [NRTI]), non-nucleoside reverse transcriptase (NNRTI)-based (1 NNRTI plus ≥2 NRTIs), or other combinations (including triple NRTI regimens and any other regimen containing a minimum of three drugs). Clinical stage of disease was defined as AIDS , non-AIDS, or unknown.http://www.r-project.org). Analysis scripts are available at http://ccasanet.vanderbilt.edu/files/public/switch.nwKaplan-Meier estimates computed probabilities of change per site. Time was measured from the start of HAART and ended at the earliest of regimen change, discontinuation, death, last visit before LTFU, last visit before the database closing, or 365 days. The closing date was defined separately for each site as the date of the most recent visit recorded in the database, and ranged from March 2007 to June 2008. The relationship between time to change and baseline variables was assessed using Cox proportional hazards models applied separately for each site. The primary multivariable analyses only included baseline predictors whose hazard ratio could be computed for all sites. Secondary, site-specific multivariable analyses included other routinely collected predictors with >50% non-missing data. In multivariable analyses, missing values of baseline predictors were accounted for using multiple imputation techniques applied separately within each siteA total of 5026 naïve patients starting HAART with at least one follow-up visit were included. Patient characteristics at HAART initiation are summarized by site in Most regimen changes were simple drug substitutions followed by other regimen changes and discontinuations.Of 1288 living patients whose initial HAART was changed, 1147 (89%) switched to a different regimen, 104 (8%) did not start a second regimen during the observed follow-up, and 37 (3%) re-started their initial regimen after an interruption ≥30 days. For those patients who re-started the same regimen during the first year, the median time of interruption was 78 days. For those who switched to a different regimen, the vast majority (83%) started within a week of initial HAART discontinuation and 90% within a month. Among those who started a second regimen while in follow-up, 74% were NNRTI-based and 5% were first line PI-based. Of 1013 living patients who stopped their initial ZDV-containing regimen, 487 had a second regimen containing ZDV, 452 had a second regimen not containing ZDV, and 74 did not start a second regimen. Clinical AIDS at HAART initiation and non-efavirenz based regimens were associated with a higher hazard of change in unadjusted analyses for most sites and in the combined cohort (data not shown). Multivariable analyses for each site and pooled across sites are given in Multivariable analyses including HIV-1 RNA, hemoglobin, weight, and more refined regimen categories were performed for sites with sufficient data and are shown in The reported reasons for change during the first year are given in The most common AE were hematological toxicity (6.7%), skin rash (3%) and gastrointestinal intolerance (1.9%), with substantial heterogeneity between sites. Of HAART initiators in IHSS/HE-Honduras, 3.7% changed regimens during the first year due to hematological adverse events, compared to 15.8% in IMTAvH-Peru. Among those with hematological adverse events, 73% were anemia, 4%. The distribution of HAART initiators changing due to skin rash also varied with FH-Argentina, FA-Chile and IMTAvH-Peru reporting 4.0%, 7.3%, and 5.5%, respectively, and other sites reporting <2%.Within the first 3 months, AE were also the most common reported reason for changing regimens. Ten percent of patients changed regimens due to adverse events: 4.7% due to hematological toxicity and 2.8% due to skin rash. Forty-two patients from GHESKIO-Haiti who were on 3TC,ABC,ZDV switched to 3TC,ZDV,EFV in April/May of 2003 because this regimen became available and was deemed superior; each of these 42 patients had been on their initial regimen for less than 3 months.For all NNRTI, boosted PI, and unboosted-PI-based regimens, AE were the main reason for change, although type of AE varied according to class. The most common AE for efavirenz-based regimens were hematological (5.7%), central nervous system (2.2%), and skin (1.6%); for nevirapine-based regimens: hematological (9.7%), skin (5.8%), liver (0.7%), and gastrointestinal intolerance (0.7%); for boosted PI-based regimens: gastrointestinal intolerance (8.3%), hematological (2.6%), and kidney (1.8%); and for unboosted PI- based regimens: gastrointestinal intolerance (7%), hematological (4.8%), and skin (1.1%).Thirty patients died within 30 days of changing their initial HAART regimen. Adverse events were the reported reasons for change for 21 of these 30 patients. Most of these deaths were HIV-related or unspecified ; other causes included anemia 2, unspecified pulmonary infection 2, chronic renal failure 1, unspecified cancer 1, pancytopenia 1, and missing cause of death 10This is the first multi-cohort study in Latin America and the Caribbean to describe rates of and reasons for changing initial HAART regimen. We found high rates of change early after treatment initiation with substantial variation across sites, ranging from 8–28% in the first 3 months and 18–41% in the first year. These rates are similar to those reported in other cohortsAlso in agreement with other studiesGHESKIO-Haiti, with more advanced disease at baseline, had unexpectedly lower rates of change/discontinuation due to adverse events than other sites. However, the rates were similar when deaths were included as discontinuations. The availability of alternative drugs more than the occurrence of adverse events may explain this low rate.As expected and previously reportedInterruption in drug supply prompted changes in 2% of HAART initiators per site: its importance cannot be minimized since interruptions <30 days were ignored. Continuous provision of therapy is a key component of any successful HIV program, as treatment interruptions affect program effectivenessConsistent with previous studies, individuals who died while on their first regimen were censored at the time of death in our primary analyses For the combined cohort, clinical AIDS prior to HAART initiation was identified as an independent predictor for treatment change. For FH-Argentina, in contrast to other sites, there was an increased risk of change at higher CD4 counts. A previous report suggested that patients with higher CD4 counts were at higher risk of GI intolerance whereas misclassification of gastrointestinal intolerance can occur in patients with low CD4 and associated opportunistic diseasesEfavirenz-based regimens had the lowest hazard for change. The increased hazard for change of NVP-based regimens was especially pronounced in IMTAvH-Peru. This may be explained by the use of fixed dose combinations containing ZDV and anemia frequency. In spite of the high proportions of hematological toxicity, the hazards of change for ZDV- and non-ZDV-containing regimens were similar. We believe that since patients with anemia at baseline were typically assigned to non-ZDV containing regimens (primarily d4T), ZDV-treated patients were “protected” from subsequent change due to anemia. However, baseline anemia status was not consistently collected for all sites.We failed to identify consistent associations between gender or age and risk of antiretroviral change, although other studies have found that younger age and female gender predict changeAfter the first change, most patients remained on regimens within the same class. The outcome of second regimens was not assessed as it was beyond the scope of this study.Our study had several limitations. Adverse events or regimen failures were computed only if they prompted regimen change. Therefore, their frequency cannot be used to estimate their occurrence, but rather the frequency of events deemed significant enough to prompt a regimen change. Strategies for changing regimens varied throughout the region and have evolved over time. Therefore, differences between sites regarding rates of toxicities, for example, may reflect site differences in guidelines for changing regimens or availability of alternative regimens. In addition, these data were collected retrospectively, and differences between sites in reasons for change and adverse events may reflect varying levels of data capture. Results of pooled analyses should be treated with caution given the heterogeneity seen in our cohortWe did not consider treatment modifications or interruptions shorter than 30 days because registration of such events varied across sites and shorter discontinuations were less likely to have been recorded. We recognize the potential impact of minor interruptions on treatment outcomes, particularly using NNRTI-based regimens; such interruptions occur frequently in real life but generally have not been considered in other cohort studiesAlthough we controlled for key variables such as CD4 count and clinical stage, patients were not randomly assigned to their initial regimens, so rates of change may be higher for certain regimens due to baseline characteristics rather than the regimen itself. However, most of the associations observed in this study are similar to those reported elsewhereIn conclusion, the high rate of change due to adverse events is consistent with studies from other cohorts. Heterogeneity between sites may be explained by differences in baseline characteristics at HAART initiation, programmatic differences, demographics and population genetics. Unfortunately, with only 7-sites, we are unable to perform analyses to investigate the impact of site-specific factors on regimen change. Efavirenz-based regimens were widely used and showed a lower rate of discontinuation compared to nevirapine or PI-based treatments.Table S1Adjusted Hazard Ratios  for Regimen Change in First Year by most Common Regimens.(0.04 MB DOC)Click here for additional data file.Table S2Adjusted Hazard Ratios  for Regimen Change/Discontinuation in First Year counting Death as a Discontinuation.(0.06 MB DOC)Click here for additional data file.Table S3Adjusted Hazard Ratios  for Regimen Change/Discontinuation in First Year, counting Death and Loss to Follow-up as Discontinuations.(0.06 MB DOC)Click here for additional data file.Table S4Adjusted Hazard Ratios  for Regimen Change/Discontinuation in the First Year including available Predictors for each Site.(0.09 MB DOC)Click here for additional data file.


Ultra-deep pyrosequencing (UDPS) allows identification of rare HIV-1 variants and minority drug resistance mutations, which are not detectable by standard sequencing.Here, UDPS was used to analyze the dynamics of HIV-1 genetic variation in reverse transcriptase (RT) (amino acids 180–220) in six individuals consecutively sampled before, during and after failing 3TC and AZT containing antiretroviral treatment. Optimized UDPS protocols and bioinformatic software were developed to generate, clean and analyze the data. The data cleaning strategy reduced the error rate of UDPS to an average of 0.05%, which is lower than previously reported. Consequently, the cut-off for detection of resistance mutations was very low. A median of 16,016  sequence reads were obtained per sample, which allowed detection and quantification of minority resistance mutations at amino acid position 181, 184, 188, 190, 210, 215 and 219 in RT. In four of five pre-treatment samples low levels (0.07–0.09%) of the M184I mutation were observed. Other resistance mutations, except T215A and T215I were below the detection limit. During treatment failure, M184V replaced M184I and dominated the population in combination with T215Y, while wild-type variants were rarely detected. Resistant virus disappeared rapidly after treatment interruption and was undetectable as early as after 3 months. In most patients, drug resistant variants were replaced by wild-type variants identical to those present before treatment, suggesting rebound from latent reservoirs.With this highly sensitive UDPS protocol preexisting drug resistance was infrequently observed; only M184I, T215A and T215I were detected at very low levels. Similarly, drug resistant variants in plasma quickly decreased to undetectable levels after treatment interruption. The study gives important insights into the dynamics of the HIV-1 quasispecies and is of relevance for future research and clinical use of the UDPS technology. Within an HIV-1 infected individual, selective pressures, such as the host immune response and ART, influence the evolution of the virus. This leads to the formation of a diverse pool of closely related virus variants called a quasispecies Drug resistance does not generally develop in patients who are adherent to modern combination antiretroviral treatment (cART), but may develop very quickly during suboptimal treatment. Primary resistance mutations are often associated with a fitness cost, and therefore resistant virus variants are usually replaced by wild-type variants if cART is interrupted. Studies have suggested that these rebounding wild-type variants originate either from wild-type virus that had been archived in latently infected cells before start of therapy Newly developed high-throughput sequencing technologies have revolutionized genetic research. One such technology is massive parallel pyrosequencing in vivo dynamics of HIV quasispecies in longitudinally collected plasma samples from six individuals who started treatment before the cART era. We analyzed a region of pol corresponding to amino acids 180–220 in the RT. This region includes the following important and well-defined drug resistance mutations to nucleoside RT inhibitors (NRTIs) and non-nucleoside RT inhibitors (NNRTIs): L210W, T215Y/F and K219Q/E associated with resistance to zidovudine (AZT) and stavudine (d4T); M184I/V associated with resistance to lamivudine (3TC) and emtricitabine (FTC); and Y181C/I/V, Y188C/L/H and G190S/A associated with resistance to nevirapine (NVP), efavirenz (EFV) and etravirin (ETR) The aim of this study was to use UDPS to investigate the The sensitivity for detection of rare variants is primarily determined by the number of virus templates that can be successfully extracted and amplified from plasma samples and by the error rate of PCR and UDPS Ethics application was approved by Regional Ethical Review board in Stockholm, Sweden (Dnr 52/2008-77). Patients participating in this study gave written informed consent according to the Declaration of Helsinki.A total of 40 plasma samples from six HIV-1 subtype-B-infected individuals were included in the study. Patients participating in this study gave written informed consent according to the Declaration of Helsinki. From each patient, longitudinally collected plasma samples that had been stored at −70°C or −20°C, were selected based on the patients' treatment history and plasma viral load . Information about the patients and the samples is summarized in et al. Considerable effort was invested in evaluating and comparing different approaches for RNA extraction, cDNA synthesis and PCR amplification, and substantial differences between methods were observed (data not shown). The aim of the protocol was to maximize the number of plasma HIV RNA molecules that were extracted, reverse transcribed, PCR amplified and finally subjected to UDPS. The final optimized protocol is presented below and a detailed workflow is outlined in The cDNA was used to amplify 261 nucleotides spanning amino acid positions 163 to 223  of the reverse transcriptase (RT) region of the pol gene with a nested PCR approach using the Fast Start High Fidelity System . The total 100 µl volume of cDNA was divided into parallel outer PCR reactions each containing 5 µl of cDNA. Next, the products from the outer PCR were pooled and 2.5 µl was used in two inner PCR reactions. Both PCRs were carried out as follows: one initial denaturation step of 95°C for 2 min followed by 30 cycles of denaturation for 20 s at 94°C, annealing for 20 s at 50°C, and extension for 90 s and a final 6-min extension at 72°C. The primers used were, outer sense primer JA269, outer antisense JA 272, inner sense JA329 and inner antisense JA331  and the DNA concentration and purity was determined using Nanodrop . In addition, the Agilent 2100 bioanalyzer  was used to verify the quality and length of the amplicons. After quality controls, PCR amplicons from eight samples were pooled in equimolar concentrations and sequenced in both forward and reverse direction on the 454 Life Science platform  according to the manufacturer's instructions.pol gene of all samples was also subjected to direct population Sanger sequencing (ABI Prism 3100) using Big Dye terminator cycle sequencing kit according to recommendations by the manufacturer . To identify possible contamination between specimens the population sequences were used to reconstruct neighbor-joining phylogenetic trees with the MEGA 4.0 software using the maximum composite likelihood model with gamma distributed rates across sites (α = 0.5) To facilitate the UDPS data cleaning processes and to verify the sample authenticity the To measure the accuracy of our UDPS protocol, the SG3Δenv plasmid was diluted to 1 copy, amplified using the optimized protocols described above and subjected to UDPS. The entire procedure from sample preparation to UDPS was repeated three times. The sequence of the plasmid clone was determined by Sanger sequencing and any difference from the Sanger sequence in the UDPS analysis was assumed to be a PCR or UDPS error. Based on these data we estimated the average frequency sequencing errors in the analyzed fragment as well as the frequency of sequencing errors at each nucleotide position. We calculated statistically derived cut-off values for detection of all possible mutations at each position.in vitro recombination during the PCR was evaluated by mixing two clones. The plasmid clones were generated from patient samples using TOPO TA cloning kit . Two plasmid clones, that contained 14 informative sites disbursed over the amplicon, were mixed in equal proportions and diluted to 10,000 templates and 100,000 templates before PCR amplification and UDPS.The frequency of et al., manuscript in preparation). The software was inspired by Tsibris et al. New bioinformatic software was written to manage, clean and analyze the UDPS data  for all positions were calculated using all reads in every position. The error rates were calculated by estimating the number of mismatches between all the UDPS reads generated from the SG3Δenv plasmid and the corresponding Sanger sequence.et al. manuscript in preparation). Based on these error rates and the number of reads from the clone data and the number of reads in each patient sample we calculated individual cut-off values  for all resistance mutations in all samples using a Chi-square test with correction for continuity.The error rates  were combined to one average error rate and a 95% confidence interval was calculated. This was estimated for every drug resistance mutation  In this study we have used the UDPS technology to dissect the HIV-1 quasispecies evolution in longitudinally collected plasma samples from six HIV-1 infected individuals. The pre-UDPS protocols, i.e. the RNA extraction, cDNA synthesis and PCR, were carefully optimized for high recovery. The number of recovered cDNA molecules was quantified by limiting dilution PCR and compared to the HIV-1 RNA levels of the original plasma samples. These analyses showed that the number of cDNA molecules subjected to UDPS ranged from 2,300 to 570,000 and that the RNA extraction and cDNA synthesis methods had a combined efficiency that ranged from 1.3% to 100% . The lowin vitro recombination rates, calculate the sequencing depth and compute cut-off values for detection of resistance mutations and minority sequence variants.New technologies such as UDPS need to be validated. Therefore, we performed several control experiments. The results from these experiments were used to investigate UDPS sequencing errors, determine et al, manuscript in preparation). For this reason we calculated the UDPS error rates for each nucleotide position associated with drug resistance and used the upper limit of the 95% confidence interval as cut-off value for detection of mutations. The cut-off values for the resistance mutations relevant for this study are summarized in To measure the accuracy of the UDPS, we sequenced the SG3Δenv plasmid clone in three separate UDPS runs, which generated a total of 45,679 sequence reads (after data cleaning). From these data we estimated that the average error rate of UDPS after data cleaning was less than 0.05% errors per nucleotide compared to 0.54% before data cleaning. Thus, our cleaning strategy decreased the error rate approximately 10-fold. The error rate was not uniform across sites  at levels that ranged from 0.07% to 0.09% . The M18None of the five individuals had significant levels of Y181C/I/V, M184V, Y188C/L/H, G190S/A, L210W, T215Y/F and K219E before treatment . Thus, wFrom patients 2 and 5, we had samples taken three and four months after the start of 3TC containing therapy, respectively. At this time, the M184I mutation had increased from 0.08% to 0.27% in patient 2 and from 0.08% to 63% in patient 5 . HoweverDrug resistance mutations evolved during suboptimal treatment in all six patients. All patients developed the M184V mutation, four patients developed T215Y and three developed L210W. The M184V mutation increased in prevalence during failing 3TC-containing regimen in all patients and finally constituted between 99.5% and 99.9% of the viral quasispecies . In two Surprisingly, AZT/d4T-associated mutations did not develop in patients 2 and 4 despite failing AZT/d4T containing regimen, which could indicate that the adherence to AZT/d4T treatment was too low to drive development of resistance Five of the six patients were sampled during treatment interruption. In patient 6 the level of resistance was still high 2 weeks after treatment interruption when M184V and T215Y was found in 98.5% and 99.3% of the quasispecies, respectively , Fig. 1.in vitro recombination was rare with our experimental protocol. This allowed us to track individual HIV variants over time. Thus, we determined the number of variants in each sample to investigate the population dynamics of HIV-1 in our six patients. The number of variants ranged from 221 to 1729 in the six patients, but most variants were only represented by a small number of reads and their frequency did not exceed the statistically derived cut-off values for detection of high-confidence variants  . This suIn During maximum levels of resistance no wild-type variants were detected in plasma from five of the six patients. However, in patient 2 wild-type variants were detected in the first two samples during treatment . Since tIn four of the six patients  we were able to analyze the origin of the drug-sensitive variants that re-appeared during treatment interruption. For patient 1, 2 and 4 the reappearing drug-sensitive variants were identical to wild-type variants that were present before therapy was initiated . In patipol from six longitudinally followed patients. We optimized all pre-UDPS protocols and developed new data cleaning strategies. This allowed us to identify minority resistance mutations and viral variants that constituted as little as 0.05% of the viral quasispecies, enabling detailed studies of the viral dynamics during ART. We found no or very low levels of drug resistance before treatment, but during treatment failure resistant viruses effectively out-competed wild-type variants and constituted almost 100% of the viral population. When treatment was interrupted drug resistant viruses disappeared rapidly and were undetectable in plasma as early as after 3 months.In this study, we have used the UDPS technology to study the evolution of drug resistance and to detect minority virus variants in HIV-1 et al, manuscript in preparation). These cut-off values were also dependent on the number of reads, but resistance mutations that represented on average 0.05% (range 0.014–0.29%) and viral variants that represented on average 0.11% (range 0.09–0.21%) were high-confidence, i.e. exceeded our statistically derived cut-off values. Thus, by using optimized pre-UDPS protocols and effective data cleaning strategies, we have been able to increase the sensitivity for detection of genuine virus variants so that variants within the HIV-1 quasispecies that are as rare as 1 in 1000 can be reliably detected. This has to our knowledge not been achieved before for HIV resistance studies. However, comparable detection limit was reported in one study of the HIV-1 envelope gene The sensitivity of UPDS depends on the number of viral templates that can be successfully extracted and amplified from a plasma sample −5 mutations per site and generation 105 times per day in an HIV-1 infected individual. However, it is not known at what frequency these mutations are present and if they in some situations may be of clinical relevance. In this study we found significant levels of M184I (4 of 5 patients), T215I and/or T215A (4 of 5 patients) ranging from 0.02%–0.12% in plasma samples obtained before treatment was initiated. In contrast, we did not find any significant pre-existence of the major drug resistance mutations M184V, Y181C, Y188C or T215Y/F. The presence of M184I, T215I and T215A in treatment naïve patients is somewhat expected since these drug resistance mutations only differ by one nucleotide from wild-type. For the same reason we would have expected to find M184V, Y181C and Y188C, but not T215Y/F since the latter are double mutants compared to wild-type. One explanation for the absence of significant levels of M184V, Y181C and Y188C could be that the cut-off values were higher at these positions (e.g. 0.15% for M184V compared to 0.07% for M184I) or that these mutations are associated with a higher fitness cost. However, Johnson et alMutations associated with drug resistance are expected to occur naturally within the HIV quasispecies, even if a patient has never received ART in vitro studies have shown that the mutation rate from wild-type to M184I is more than four times higher than that to M184V, while the enzymatic efficiency of a RT with M184I is approximately 50% lower than that of a RT with M184V It is interesting to note that we found significant levels of M184I, but not M184V, before treatment in 4 of 5 patients. This agrees with early data from 3TC mono-therapy studies where it was shown that M184I usually occurs transiently before being replaced by M184V, which is more fit in the presence of 3TC et al. reported significant levels (0.6 to 30%) of lamivudine-sensitive variants in viral population from patients with failing 3TC-containing therapy Our analyses of HIV-1 variants showed that different wild-type variants co-existed before initiation of therapy. Following start of therapy, virus variants with several different combinations of resistance mutations evolved and co-existed . Howeveret al. found low abundance mutations associated with AZT/d4T resistance 2 to 7 years after treatment with these drugs had been stopped. However, in contrast to our patients, the patients enrolled in their study continued therapy with other antiviral drugs. Thus, additional studies are needed to investigate the dynamics of drug resistant variants after treatment interruption. Since drug resistant variants can become established in long-term reservoirs Since many drug resistance mutations reduce replication fitness In conclusion, we have developed optimized UDPS protocols that have decreased the UDPS error rate and thereby increased the sensitivity for detection of minority HIV-1 resistance mutations and viral variants. With this technology we were able to identify and quantify variants that represented as little as 0.05% of the HIV-1 quasispecies. We have shown that the levels of preexisting drug resistance in plasma samples from treatment naïve patients is very low and that several important drug resistance mutations  were not detectable in pre-treatment samples, indicating that the natural occurrence of these mutations are below our detection limit. Furthermore, there was almost 100% replacement of wild-type and drug-resistant variants during treatment failure and treatment interruption, respectively. Thus, our study shows that UDPS can be used to gain new insights in HIV evolution and resistance and is relevant for the possible future clinical use of this technology.Figure S1Workflow over the optimized protocol.(3.00 MB TIF)Click here for additional data file.Table S1Primers used for PCR amplification.(0.03 MB DOC)Click here for additional data file.Table S2Tag sequences.(0.03 MB DOC)Click here for additional data file.Table S3Genetic diversity of the 10 most common variants at each sampling time point.(0.03 MB DOC)Click here for additional data file.


To explore whether an assay change was responsible for an increasing proportion of patients with undetectable HIV viral loads at our urban HIV clinic, we selected highly stable patients, examining their viral loads before and after changing assays. We compared the proportion with detectable viremia during RT-PCR vs. bDNA periods.We selected patients with ≥1 viral loads assessed during both RT-PCR and bDNA periods. We included patients with stable CD4 counts, excluding patients with viral loads ≥1,000 copies/ml or any significant changes in therapy. Out of 4500 clinic patients, 419 patients  were included. 39% of viral loads were reported as detectable by RT-PCR vs. 5% reported as detectable by bDNA. The mean coefficient of variation was higher before vs. after assay change. We found an odds' ratio of 16.7 for having a viral load >75 copies/ml during the RT-PCR vs. bDNA periods.These data support previous reports, suggesting that bDNA may more reliably discriminate between viral suppression and low level viremia in stable patients on therapy. Low-level viremia, noted more with RT-PCR, may promote unneeded testing, while differences in viral load reliability may impact antiretroviral trial and quality assurance endpoints. Commonly used plasma separator tubes may differentially affect RT-PCR and bDNA results. The accurate and reliable quantification of HIV-1 RNA levels, or plasma viral load (pVL), has become a crucial tool in the management of HIV disease. Providers use pVL to determine a patient's viral set point prior to the initiation of antiretroviral therapy (ART), to help decide when to initiate therapy, to monitor response to treatment and to detect treatment failure Two assays employed clinically to measure HIV-1 pVL currently predominate in the U.S., the reverse transcription polymerase chain reaction assay (RT-PCR)  and the branched chain DNA assay . The current versions of these assays yield well correlated results throughout their dynamic ranges Peter and Blum report cumulative results for HIV-1 pVL testing done at a reference lab between January 2000 through December of 2001, with approximately 4000–7000 tests performed per month Differing rates of reliability near the LLOQ between the RT-PCR and bDNA may have important ramifications for individual patient care. Despite the clinically innocuous nature of intermittent viremia under 200 copies/ml, these “blips” in otherwise stable patients may promote both patient and practitioner anxiety, leading to more frequent office visits, more laboratory testing, and possibly unneeded changes or intensification of anti-retroviral regimens The John H. Stroger, Jr. Hospital (JSH) of Cook County lab, which performs HIV-1 pVL testing for the Ruth M. Rothstein CORE Center, Cook County Health and Hospital System ambulatory HIV clinic, changed from using a RT-PCR assay to a bDNA assay in February 2005. During the entire period under review samples were collected in Plasma Preparation Tubes (PPTs). Despite the adverse effect that use of PPTs may have on RT-PCR reliability, they are widely used since they allow phlebotomy technicians to do a simple centrifugation step before forwarding specimens to the molecular diagnostics lab. Following our lab's change in methodology, our clinic quality assurance surveillance detected an increase in the proportion of patients with viral suppression (pVL<75 copies/ml) We utilized a retrospective cohort study, selecting a group of immunologically stable patients, to determine if significant differences in the proportion of HIV pVLs reported as detectable existed between the RT-PCR versus bDNA assays.This research was approved by the Cook County Health and Hospital System's (CCHHS) Institutional Review Board. Since this research entailed the retrospective review of pre-existing data and because all personal identifying information has been permanently removed from the study database, the CCHHS IRB deemed that specific patient informed consent was not necessary.st, 2005. We conducted a review of the electronic medical record for the CORE Center's 4500+ patients. We included and compared all pVLs of patients who had ≥1 pVL assessed via RT-PCR  during eight months prior to assay change, and via bDNA  during six months after the change. In order to exclude patients with recent viral decay, patients had to have at least one undetectable pVL during the six months prior to entering the review period. To select patients with viremia related to assay reliability differences, rather than medication non-adherence or overt virologic failure, we excluded patients with any pVL measurement ≥1,000 copies/ml during the eight month RT-PCR period or the six month bDNA period. Also, we excluded patients if they had a decrease in absolute CD4 count of ≥15% during the 14 month review period. We performed chart reviews, excluding patients with significant changes in ART either during the 14 month review period, or three months prior to entering the review period. Decisions regarding whether to exclude or include patients with changes in ART were made independent of knowledge of their pVL results.We carried out a retrospective, two period review between May 2004 and August 2005, comparing HIV-1 pVL results for a cohort of highly stable patients. The JSH lab switched from the RT-PCR to the bDNA HIV pVL assay on February 1To assess the assays' clinical reliability near their LLOQ, as the primary analysis, we compared the proportion of pVLs reported as detectable during each of the two periods. Test reliability may be defined as the extent to which test results remain consistent over repeat measurements of the same subject under similar conditions. A test is reliable if it yields consistent results, given stable testing conditions. It is judged not to be reliable if repeat measurements, under the same conditions, give different results. For patients in this stable cohort, all of whom demonstrated previous virologic suppression, continued on stable ART and maintained steady CD4 counts, we characterized test reliability by the proportion of samples with suppressed vs. detectable viremia during the RT-PCR vs. bDNA periods, with more episodes of detectable, low-level viremia signifying less clinical reliability near the assays' LLOQ. To determine an odd's ratio describing the likelihood for detectable viremia during the RT-PCR vs. bDNA periods, we utilized a conditional, fixed-effects, logistic regression model that accounted for correlation between an individual patient's multiple samples . To account for RT-PCR's slightly lower LLOQ (down to pVL of 50) vs. bDNA (LLOQ down of 75), for analysis purposes, RT-PCR results between 50 and 75 copies/ml were considered undetectable. .As secondary endpoints, we compared censored mean pVLs and mean coefficients of variation (CV). In calculating censored means, we assign undetectable pVLs a value of 49 and 74 copies/ml for the RT-PCR and bDNA periods. As a sensitivity analysis we also calculated and report censored means using values of 49 copies/ml and 1 copy/ml for all undetectable pVLs, during both periods. Coefficients of variation (CV), representing the standard deviation divided by the mean, were calculated for each patient with more than one value per period. We report mean CVs using both censored values and actual values, after the exclusion of undetectable results. We do not report tests of statistical significance comparing censored mean pVLs, since the required left-sided censoring  is unlikely to reflect the true distribution of pVL values below the LLOQ. In order to assess utilization of pVL testing, we also compared mean duration between pVL measurements for the RT-PCR vs. bDNA periods.Out of 4500+ clinic patients, 454 patients met initial inclusion criteria. Following chart review, a total of 419 patients   pVL values were ≥75 copies/ml vs. 35/752 (5%) during the bDNA period (001) see . Figure The sensitivity analysis using different imputed values for undetectable viral loads demonstrates that using different values does not affect the finding that RT-PCR has a greater CV in these stable patients on invariant therapy who entered the observation period with undetectable pVL see . After eThese clinical data, drawn from a large group of immunologically stable, suppressed patients on established ART demonstrate that bDNA may more reliably discriminate between viral suppression and low level viremia in stable patients on therapy. Previous, similar reports comparing the assays' reliability lacked immunologic and treatment data to verify the clinical stability of patients with low-level viremia Several factors other than differences in assay reliability may have led to more detectable viremia during the RT-PCR period. RT-PCR has a lower reported LLOQ and 16% of the detectable pVLs during the RT-PCR period fell into the 50–75 copies/ml range. These values were considered undetectable for purposes of our primary analysis, thereby eliminating any difference mediated by this disparity in LLOQ. It should also be noted calculating censored mean pVL levels allowed for the reporting of mean CVs for the two periods, but it is unlikely that censoring of undetectable pVLs to an arbitrary, set value reflects the true distribution of pVLs below the LLOQ. Because of this, the secondary endpoint of difference in mean CV derived via use of the censored means should be cautiously interpreted.Seasonal or time period bias may have contributed to differences noted in the two assays. Since we included over 400 patients on stable therapy and close to 1600 observations such effects are unlikely to have resulted in the magnitude of difference we demonstrated. Also, because loss of virologic control tends to increase with time, if anything, time period effects would have led to more detectable viremia during the chronologically later bDNA period.The wide use of PPTs, rather than ethylenediaminetetraacetic acid (EDTA) tubes for collection of pVL specimens has been linked with false-positive, detectable values, especially when used with RT-PCR Since we used PPTs during the entire RT-PCR and bDNA periods, collection tube effects likely influenced RT-PCR and bDNA assays differently, contributing to the observed differences in assay reliability near the LLOQ. Because PPTs require less specimen processing (e.g. no need to remove plasma from cellular components of sample), their use may improve lab technician safety and efficiency. Furthermore, clinicians may be unaware of these collection tube effects or of which collection tube their lab utilizes. The need to use EDTA tubes for RT-PCR rather than the more convenient PPTs may, therefore, present an additional barrier to effective HIV treatment monitoring. The data presented here demonstrate that bDNA presents a more clinically reliable option for quantifying HIV pVL versus RT-PCR in settings which use PPTs.The difference we observed in clinical reliability at the lower end of the assays' dynamic ranges may have patient-care, quality assurance, and clinical research implications. While intermittent viremia of less than 200 copies/ml has been shown to be innocuous, sustained low-level viremia has been associated with the emergence of drug resistance Proportions of patients with undetectable viral loads are important benchmarks in clinical science and quality assurance. Since antiretroviral registrational trials utilize the TLOVR endpoint, RT-PCR's inferior reliability near the LLOQ, especially when using PPTs, may both inflate virologic failure rates and confound efforts to compare failure rates between trials


We investigated whether this is due to modulation of T cell activation and inflammation.Maraviroc treatment for HIV-1 infected patients results in larger CD4+ T cell changes. Maraviroc treatment tended to result in more rapid decreases in CD38 expression on CD4+ T cells and in plasma D-dimer concentrations than did treatment with efavirenz. The proportion of patients with high-sensitivity C-reactive protein >2 µg/mL increased from 45% to 66% in the efavirenz arm, but remained constant in the maraviroc arm (P = 0.033). Decreases in CD38 expression on CD8+ T cells were correlated with CD4+ T cell rises for maraviroc treatment , but not for treatment with efavirenz.Thirty maraviroc-treated patients from the Maraviroc versus Efavirenz Regimens as Initial Therapy (MERIT) study were randomly selected from among those who had CCR5-tropic (R5) HIV on screening and achieved undetectable HIV RNA (<50 copies/mL) by Week 48. Efavirenz-treated controls were matched for baseline characteristics to the maraviroc-treated patients selected for this substudy. Changes in immune activation and inflammation markers were examined for associations with CD4+ T cell gains.Maraviroc-treated patients had earlier, modest decreases in certain markers of immune activation and inflammation, although in this small study, many of the differences were not statistically significant. Levels of high-sensitivity C-reactive protein remained constant in the maraviroc arm and increased in the efavirenz arm. Decreases in immune activation correlated with increased CD4NCT00098293ClinicalTrials.gov  When analyzing the inflammatory marker hsCRP, we selected 2.0 µg/mL as a threshold level based on results of the JUPITER study that suggested a clinical benefit to reducing inflammation for individuals with hsCRP >2.0 µg/mL.In the phase 3 MERIT study comparing the CCR5 antagonist maraviroc (MVC) to the non-nucleoside reverse transcriptase inhibitor efavirenz (EFV), patients who received MVC had significantly greater increases in blood CD4+ cell count, and baseline HIV RNA. Each patient sample was assigned a numerical code, and the laboratory personnel performing all assays were blinded to the treatment arm from which each sample was collected.As described elsewhere + or CD8+ T lymphocytes were then analyzed for expression of CD38 with a phycoerythrin (PE)-labeled antibody. CD38 expression is reported as antibodies bound per cell. Appropriately conjugated murine monoclonal isotype control antibodies were used for gating. All antibodies were purchased from BD Bioscience, San Diego, CA. Cells were stained for 10 min at room temperature, washed in phosphate buffered saline with 1% bovine serum albumin and 0.1% sodium azide, then fixed in 1% formaldehyde and analyzed using a dual-laser flow cytometer  and CellQuest software (BD Bioscience). Plasma was prepared by centrifugation of whole blood collected into EDTA-containing tubes at 1500–2000×g for 10–15 minutes and was stored at −80°C until analysis. Plasma samples were thawed and analyzed in batch. Levels of D-dimers , tumor necrosis factor receptor I (TNFRI) , TNFRII , Neopterin , IL-6 (R&D Systems), and hsCRP , were measured by ELISA.Frozen PBMCs were thawed in batch and T cells were identified by size, granularity, and by positive staining with Peridinin-chlorophyll-protein Complex (PerCP)-labeled murine monoclonal antibody to CD3 and either allophycocyanin (APC)-labeled antibody to CD4, or fluorescein isothiocyanate (FITC)-labeled antibody to CD8. Electronically gated CD4+ cell count using Pearson's correlation. The statistical analysis plan was developed and specified prior to any execution of the study. We did not consider adjustment for multiple comparisons in this exploratory, hypothesis-generating set of analyses.Immune activation markers were assayed over time and changes reported as median and interquartile range. Differences in percent change from baseline to week 24 and 48 between the two arms were analyzed using a Wilcoxon Rank Sum test. A Cochran-Mantel-Haenszel test was used to compare the treatment arms with respect to a number exceeding threshold at week 48 while adjusting for baseline status. Changes from baseline to week 48 of each marker were analyzed for association with change from baseline to week 48 in CD4+ T cell count, and baseline HIV RNA levels. All patients selected for this sub-study had reached undetectable (<50 copies/mL) viral levels in plasma between weeks 24 and 48. Complete data sets were available for 28 MVC-treated and 29 EFV-treated patients. Most patients were male  and the median age of each group was 36. At baseline, HIV RNA levels were 4.9 log10 copies/mL and CD4+ lymphocyte counts were 274 cells/µL in both treatment groups. Baseline levels of immune activation and inflammation markers were similar across the two groups  on CD4+ cells at week 24 versus a 0.29% increase in CD38 levels in the EFV arm .At week 48, MVC-treated patients had a mean change in CD4P = 0.177 at Week 24; P = 0.033). Levels of plasma IL-6 fell more quickly in the EFV arm, but this difference did not approach significance . Declines in plasma levels of soluble TNFRI, soluble TNFR II, and neopterin were similar for the MVC-treated and EFV-treated groups (data not shown).Plasma levels of D-dimers also tended to fall more rapidly among patients treated with MVC, although the difference between the arms was not significant Click here for additional data file.Protocol S1(0.57 MB DOC)Click here for additional data file.