Frailty & Muscle Loss Increase Mortality & Are Common in HIV+

Subject: NATAP/CROI: Frailty/Muscle Loss in HIV Increases Mortality & is Common

NATAP http://natap.org/
_______________________________________________



Frailty & Muscle Loss Increase Mortality & Are Common in HIV+

from Jules Levin at CROI Live in Seattle. This poster session is a
breakthrough in that it is identifying that muscle loss & frailty are
fairly common in HIV+ persons & they increase mortality. AND HCV & HBV
contribute to frailty in one study below.read this:

"Frailty is a significant predictor of mortality among both HIV+ and
at-risk IDU....... Impaired functional capacity is strongly associated
with lower bone density and lower muscle mass in middle-aged HIV-1+
persons......Co-morbidity Is Predictive of Muscle Strength in HIV+
Veterans: Results from the VACS Index....
Overall, 40% of SUN study participants aged ≤50 years with
well-controlled HIV infection were pre-frail or frail. The significant
association of pre-frailty and frailty with a history of opportunistic
infection suggests earlier diagnosis of HIV infection and prevention of
opportunistic infections may reduce risk for frailty.......Prevalence
of low muscle mass increases with age. The highest prevalence was found
in the 41- to 50-year age group. Predictors of FFMi change appear to be
associated with age, lipoatrophy recovery, and time. FFMi is associated
with all-cause mortality in HIV+ patients, suggesting that this
biological entity can provide prognostic information, in HIV+
patients..........We have recently demonstrated that patients with
prior exposure to nucleoside analog ARV, which inhibit DNA
polymerase-γ, accumulate acquired mitochondrial DNA (mtDNA) mutations
in skeletal muscle, in an apparent acceleration of the process seen in
normal aging. Here we explore an in vivo functional correlate in aging
HIV+ patients. Abnormalities of resting muscle pH handling have been
associated with fatigue and may contribute to functional decline in
this patient group."



Frailty and Pre-frailty in a Contemporary Cohort of HIV+ Adults

Nur Onen*1, P Patel2, J Baker3, L Conley2, J Brooks2, T Bush2, M
Kojic4, J Hammer5, E Overton6, and SUN Study Investigators

1Washington Univ Sch of Med in St Louis, MO, US; 2CDC, Atlanta, GA, US;
3Hennepin County Med Ctr, Univ of Minnesota, Minneapolis, US; 4Miriam
Hosp, Providence, RI, US; 5Denver Infectious Disease Consultants, CO,
US; and 6Univ of Alabama at Birmingham, US

Background:  HIV+ persons can become prematurely pre-frail and frail;
however, pre-frailty prevalence and risk factors for both frail and
pre-frail states have not been fully elucidated.

Methods:  Using data from a contemporary prospective observational
cohort of HIV+ adults (SUN Study), we determined the percentages of
non-frail, pre-frail, and frail participants at the most recent study
visit by the respective presence of 0, 1 to 2, and ≥3 of 5 established
frailty criteria as shown in the table. We evaluated associations with
pre-frailty/frailty using logistic regression analysis.

Results:  Of 308 SUN Study participants assessed—79% men, 58%
non-Hispanic white, median age 47 years (interquartile range 41 to 53),
95% on combination ART, median CD4 cell count 650 cells/mm3 (IQR 467 to
799), and 93% HIV RNA <400 copies/mL—57% were non-frail, 38% pre-frail,
and 5% frail (61%, 36%, and 4%, respectively, among the 199 [65%]
participants aged ≤50 years). Prevalence of frailty criteria are
presented in the table; exhaustion and physical inactivity
predominated. In multivariate analysis, pre-frail/frail vs non-frail
participants were more likely of non-white race/ethnicity (54% vs 33%;
adjusted odds ratio 3.24; 95% confidence interval 1.78 to 5.91), to
have had an AIDS-defining opportunistic infection (35% vs 15%; aOR
2.55, 95%CI 1.29 to 5.02), to have poorer median perceived health
scores on the SF-12 health survey (1, IQR 1 to 2 vs 2, IQR 1 to 3; aOR
2.12, 95%CI 1.49 to 3.03), to have higher median PHQ-9 depression
scores (6, IQR 2 to 11 vs 3, IQR 0 to 5; aOR 1.11, 95%CI 1.04 to 1.18)
and to be older (median age 48 years, IQR 44 to 54 vs 46 years, IQR 40
to 52; aOR 1.04, 95%CI 1.01 to 1.07). Lower CD4 cell count nadir,
female sex, and unemployment were not independently associated with
pre-frailty/frailty.

Conclusions:  Overall, 40% of SUN study participants aged ≤50 years
with well-controlled HIV infection were pre-frail or frail. The
significant association of pre-frailty and frailty with a history of
opportunistic infection suggests earlier diagnosis of HIV infection and
prevention of opportunistic infections may reduce risk for frailty.
Racial disparities warrant further investigation.
-------------------

Low Muscle Mass in HIV+ Patients: Prevalence, Predictors, and Clinical
Implication

Giovanni Guaraldi*1, S Zona1, A Silva2, G Orlando1, F Carli1, A
Santoro1, N Crupi2, G Ligabue1, C Mussi1, and L Ferruci3

1Univ of Modena and Reggio Emilia, Italy; 2Hosp de Joaquim Urbano,
Porto, Portugal; and 3Natl Inst on Aging, NIH, Baltimore, MD, US

Background:  In HIV+ patients, muscle mass measured as fat free mass
index (FFMi = FFM/h2) in DXA has never been characterized in large
epidemiological cohorts. We aimed:  to describe the prevalence of low
muscle mass using t- and z-score, per age decades, defined as <–2 SD
from the mean FFMi for an Italian Caucasian population, respectively,
for the same age or in the age strata 30 to 39 years; to identify
predictors of FFMi change; and to assess the association between FFMi
and all-cause mortality in a large HIV+ cohort.

Methods:  This observational prospective study included all consecutive
patients from 2005 to 2011 who underwent at least 2 DXA scans,
performed 1 year apart. Univariate and multivariable longitudinal
linear regressions were built to evaluate FFMI change-associated
factors. Co-variates included in the models were:  age, sex, body mass
index (BMI), physical activity; change in leg fat percentage (assessed
with DXA), in visceral adipose tissue (VAT), and in total adipose
tissue of the abdomen (TAT) (assessed with abdominal CT); NRTI, NNRTI,
and PI cumulative exposure; CD4 nadir and recovery; vitamin D plasma
level; and time between DXA scans. A Cox model was built to predict the
impact of FFMi on all cause mortality after adjustment for age and sex.

Results:  A total of 1696 HIV+ patients (1046 men) were analyzed.
Median observation follow-up period was 3.5 years (IQR 2 to 5); 96% of
patients were on ART, and during the follow-up period 37 died. BMI
change and FFMI change appeared stable over time (ß = 0.001, p = 0.111;
ß = 0.001, p = 0.070, respectively). In men, the prevalence of low
muscle mass using t- and z-scores was 0.2% and 8.5%, respectively. In
women, the prevalence of low muscle mass using t- and z-scores was 0%
and 1.5%, respectively. The highest prevalence of low muscle mass was
detected in the 41- to 50-year age group strata (t-score 0.5% and
z-score 16%). Predictors of FFMi change were:  age (ß = –0.01, p =
0.002), change of leg fat percentage (as a surrogate for lipoatrophy
recovery) (ß = –0.05, p <0.001), and time between DXA scans (ß = 0.17,
p = 0.013). FFMi was associated with all-cause mortality (HR 0.87,
95%CI 0.78 to 0.98) after adjustment for age and sex.

Conclusions:  Prevalence of low muscle mass increases with age. The
highest prevalence was found in the 41- to 50-year age group.
Predictors of FFMi change appear to be associated with age, lipoatrophy
recovery, and time. FFMi is associated with all-cause mortality in HIV+
patients, suggesting that this biological entity can provide prognostic
information, in HIV+ patients.
---------------------

Frailty Predicts Mortality in a Cohort of HIV+ and At-risk IDU

Damani Piggott*, A Muzaale, S Mehta, T Brown, S Leng, and G Kirk

Johns Hopkins Univ, Baltimore, MD, US

Background:  Frailty, a syndrome of diminished physiologic reserve with
increased stressor vulnerability, predicts hospitalization, disability,
and mortality in older HIV– adults. We have previously observed a
significant association between frailty and HIV+, particularly advanced
HIV infection, among injection drug users (IDU). In this study, we
evaluated the impact of frailty on mortality in a cohort of aging HIV+
and at-risk IDU.

Methods:  Frailty was assessed biannually from 2005 to 2008 among
current and former IDU in the ALIVE cohorts and was defined by the
presence of ≥3 of 5 standard criteria:  weakness (grip strength), slow
gait speed, weight loss, low physical activity, and exhaustion. Cox
proportional hazards models with time-varying co-variates were used to
estimate the risk (hazard ratios with 95% confidence intervals) for
all-cause mortality among frail persons relative to their robust
counterparts (defined by the absence of any criteria) and to non-frail
persons.

Results:  For 1230 subjects at baseline, the median age was 48 years,
89% were African American, 418 (34%) were female, and 351 (29%) were
HIV+. The prevalence of frailty was 9%, while 31% met no frailty
criteria. In Cox multivariable analysis of 3365 person-visits,
increasing age and HIV status were associated with increased mortality
risk. Adjusting for age, race/ethnicity, gender, educational level, and
HIV status, frail persons had a 3.4-fold increased risk of death
relative to robust persons (HR 3.42, 95%CI 1.66 to 7.03). In stratified
analysis, increased mortality risk with frailty was observed among both
HIV– persons (HR 2.91, 95%CI 1.06 to 7.96) and HIV+ persons (HR 4.05,
95%CI 1.39 to 11.8). Controlling for advanced HIV infection (CD4 <350,
HIV RNA+), frailty remained a significant predictor of mortality (HR
3.13, 95%CI 1.25 to 7.82). In comparison to non-frail persons, similar
associations of frailty with mortality were observed.

Conclusions:  Frailty is a significant predictor of mortality among
both HIV+ and at-risk IDU. Frailty provides prognostic information even
when accounting for advanced HIV disease suggesting that standardized
assessment may inform prediction of significant clinical endpoints.
Further exploration of the biological mechanisms and clinical utility
of frailty may aid management of aging HIV+ persons.
------------------------

Mitochondrial Function in vivo in Aging HIV+ Patients

Brendan Payne*1,2, M Trenell2, K Hollingsworth2, J Baxter3, V Lee4, E
Wilkins3, A Price1, and P Chinnery2

1Royal Victoria Infirmary, Newcastle upon Tyne, UK; 2Newcastle Univ,
Newcastle upon Tyne, UK; 3Northern Manchester Gen Hosp, UK; and
4Manchester Royal Infirmary, UK

Background:  We have recently demonstrated that patients with prior
exposure to nucleoside analog ARV, which inhibit DNA polymerase-γ,
accumulate acquired mitochondrial DNA (mtDNA) mutations in skeletal
muscle, in an apparent acceleration of the process seen in normal
aging. Here we explore an in vivo functional correlate in aging HIV+
patients.

Methods:  We recruited older HIV+ patients in clinical care (n = 24;
age 48 to 74 years) and age-matched controls (HIV–). Phosphorus
magnetic resonance spectroscopy (31P-MRS) was performed using a 3-T
scanner. Spectra were obtained from gastrocnemius/soleus at rest and
during recovery from brief exercise. Key measures were:  adenosine
triphosphate (ATP) production during recovery (as Qmax (ADP), maximal
rate of adenosine diphosphate (ADP) clearance; τ1/2 (PCr), half-life of
phosphocreatine); and pH handling. In HIV+ subjects, comparison was
made with cellular mitochondrial function by COX (cytochrome c oxidase)
histochemistry of lower-limb muscle biopsy.

Results:  Basal parameters of ATP metabolism differed between subjects
groups:  ADP (mean ±SD) HIV+ 10.2±0.7 mM, HIV– 9.5±0.5 mM (p = 0.001);
PCr HIV+ 41.0±15.2 mM, HIV– 30.7±2.1 mM (p = 0.003). Furthermore, basal
ADP levels in HIV+ subjects correlated with biopsy COX defect (r =
0.45, p = 0.032). In contrast, dynamic measures of ATP production
during exercise recovery were similar in HIV+ and control subjects:
Qmax (ADP) (mean±SD) HIV+ 26.6±18.6 mM/min, HIV– 23.0±10.2 mM/min; τ1/2
(PCr) HIV+ 29.9±13.4 s, HIV– 27.5±8.3 s. There was more variance seen
in the HIV+ than the HIV– group, however no disease or treatment
variable was significantly correlated with ATP production rate, nor was
cellular COX defect. HIV+ subjects showed disordered pH handling
compared with HIV– controls as evidenced by higher basal pH (mean±SD,
7.07±0.03 vs 7.04±0.02, p = 0.001) and post-recovery pH (7.09±0.03 vs
7.06±0.02, p = 0.008) but similar exertional minimum pH (6.98±0.13 vs
7.00±0.03, ns). Resting pH correlated with COX defect (r = 0.42, p =
0.044).

Conclusions:  The altered basal ATP metabolite levels in HIV+ subjects
coupled with preserved dynamic function, despite cellular mitochondrial
defects on biopsy, suggests functional compensation to an acquired
mtDNA defect, once therapy has been switched to a cleaner agent.
Abnormalities of resting muscle pH handling have been associated with
fatigue and may contribute to functional decline in this patient group.
-----------------------

Functional Impairment Is Associated with Low Bone and Muscle Mass in
Middle-aged HIV-1+ Persons

Kristine Erlandson*, A Allshouse, C Jankowski, S MaWhinney, W Kohrt,
and T Campbell
Univ of Colorado Denver, Aurora, US

Background:  Physical function impairment may be accelerated in the
presence of osteoporosis, obesity, or sarcopenia. HIV+ persons have
early physical impairment, but little is known about the contributions
of bone or body composition changes to impairment in persons aging with
HIV-1.

Methods:  We conducted a prospective study of 45- to 65-year-old HIV-1+
subjects who had been on ART >6 months and whose plasma HIV-1 RNA <48
copies/mL. Low functioning (LF) and high functioning (HF) subjects were
identified by deficits on both Fried’s frailty criteria and the Short
Physical Performance Battery and were matched by age, gender, and time
since HIV diagnosis. Bone, fat, and muscle were assessed by
densitometry. Osteoporosis was defined as T-score ≤–2.5, osteopenia as
T-score <–1 but >–2.5, sarcopenia as appendicular skeletal muscle index
(ASMI) <5.45 kg/m2 (female) and <7.26 kg/m2 (male). Insulin-like growth
factor (IGF)-1 and IGF-binding protein (BP)-3 were measured. Stratified
logistic regression for categorical variables and linear mixed effects
regression for continuous variables were estimated to account for
correlation within matched pairs. Body mass index (BMI), tobacco, and
nadir CD4+ T cells were adjusted in models of bone loss.

Results:  We identified 30 LF and matched them to 48 HF subjects; mean
age 52.7 years, CD4 T cell 598, 96% HIV-1 viral load <48 copies/mL, 18%
female, 77% white, 17% Hispanic. LF and HF were similar in age,
duration of ART, tenofovir use, and CD4 T- cells (all p >0.2). LF
subjects had significantly lower BMD and T scores at the hip and spine;
differences remained significant in multivariate analyses. Although all
persons with BMI <18.5 kg/m2 were LF, LF trended toward higher relative
body fat content. LF subjects had a greater prevalence of sarcopenia
(50% vs 25%, p = 0.04), lower lean mass, and lower IGF-1/IGFBP3.

Conclusions:  Impaired functional capacity is strongly associated with
lower bone density and lower muscle mass in middle-aged HIV-1+ persons. 
Whether bone or muscle loss is the result of disuse due to impairment,
or if low muscle or bone mass, mediated through effects of IGF-1, leads
to impairment by progressive weakness or inflammatory pathways remains
to be established. Further studies should investigate the role of
increased muscle/bone mass and increased IGF-1 on preserving functional
independence as persons with HIV age.
--------------------------

Co-morbidity Is Predictive of Muscle Strength in HIV+ Veterans: Results
from the VACS Index

Krisann Oursler*1, J Tate2, T Gill2, K Crothers3, T Brown4, S Crystal5,
J Womack2, D Leaf6, J Sorkin1, A Justice2, and Veterans Aging Cohort
Study Project Team

1Univ of Maryland Sch of Med and Publ Hlth and VA Maryland Hlthcare
System, Baltimore, US; 2Yale Univ Sch of Med and Publ Hlth and VA
Connecticut Hlthcare System, New Haven, US; 3Univ of Washington,
Seattle, US; 4Johns Hopkins Univ, Baltimore, MD, US; 5Rutgers Univ, New
Brunswick, NJ, US; and 6Univ of California, Los Angeles Sch of Med and
Greater Los Angeles VA Hlthcare System, US

Background:  Despite improved survival, HIV+ adults have increased risk
for physical disability due to muscle weakness, poor ambulatory
function, and low cardiorespiratory fitness. The objective of this
study was to determine whether the VACS Index, a comprehensive index of
generalized organ injury based on routine clinical laboratory data, is
associated with hand-grip and leg-strength, 6-minute walk distance, and
cardiorespiratory fitness (peak oxygen consumption, VO2 peak).

Methods:  HIV+ patients enrolled in the Veterans Aging Cohort Study
(VACS) participated in this cross-sectional study at the Baltimore VA
Medical Center from 2004 to 2007. The VACS Index was calculated
incorporating hemoglobin, FIB-4, eGFR, hepatitis C infection, CD4
count, HIV-1 viral load, and age; higher score reflected greater
co-morbidity. Analyses included nonparametric correlation (Spearman’s
rank) and linear regression models.

Results:  We included 2 women and 53 men:  91% African American race,
mean age of 52 (SD 7) years. The VACS Index was inversely correlated
with hand-grip strength (r = –0.36, p = 0.01) and lower extremity
strength (quadriceps, r = –0.45, p <0.01), but was not significantly
associated with 6-minute walk distance (r = –0.26, p = 0.07) or VO2
peak (r = –0.13, p = 0.3). A 20-point higher VACS Index score was
associated with a 10% lower leg strength (mean 76 newtons; 95%CI –124
to –29; p <0.001; see the figure), which remained significant after
adjustment for muscle cross-sectional area (p = 0.04). The VACS Index
explained 34% of the variance in specific leg strength. In contrast, an
index restricted to CD4 count, viral load, and age did not correlate
with any of these measures (p >0.08).

Conclusions:  In this sample of predominantly African American men
ranging in age from 31 to 72 years, the VACS Index was significantly
associated with upper and lower extremity strength. The VACS Index may
be valuable for identification of patients at high risk for disability
due to muscle weakness. Association of Leg Strength with the VACS Index.

Reduced Limb Muscle, More Belly Fat Linked to Higher Mortality

http://www.hivandhepatitis.com/2011_conference/croi2011/docs/0322_2010b.html

A good reason to do resistance exercise, use nandrolone if needed, and manage lipodystrophy.

Mortality Down 94% in HIV Among Diagnosed

NATAP http://natap.org/
_______________________________________________



Changes in the Risk of Death After HIV Seroconversion Compared With Mortality in the General Population
Krishnan Bhaskaran, MSc; Osamah Hamouda, MD; Mette Sannes, MLabTech;Faroudy Boufassa, MD; Anne M. Johnson, MD; Paul C. Lambert, PhD; Kholoud Porter, PhD; for the CASCADE Collaboration


JAMA. July 2, 2008;300(1):51-59.

".....To our knowledge, no study to date has made a comparison of mortality among HIV-infected and uninfected individuals adjusted for duration of HIV infection, and our results provide estimates, hitherto unavailable, of the cumulative excess probability of death as duration of HIV infection increases.....we found that by 2004-2006, the risk of death in the first 5 years following seroconversion was similar to that of the generalpopulation, with the excess probability of death becoming apparent only later in the course of infection, particularly evident in those infected for 10 years or more....Our long-term cumulative mortality estimates for 2004-2006 include data from individuals infected in the mid-1990s or earlier who may have started antiretroviral treatment later in the course of infection and with regimensinferior to those currently available; thus, such estimates may be pessimistic in terms of the long-term outlook for more recently infected individuals.....Indeed, we found a lower uptake of HAART among those exposed through IDU compared with other groups, while lower therapy adherence among such individuals has been described in the literature.....Although we matched by age, sex, calendar time, and country, it is likely that HIV-infected individuals in our study differ from the general population in other ways. Rates of smoking have been shown to be high among some HIV-infected populations30; other risk behaviors, socioeconomic factors, and race/ethnicity are also likely to differ among HIV-infected persons. Those exposed through IDU in particular are likely to be at higher risk of mortality than the general population regardless of HIV infection, and we have presented our estimates of the cumulative excess mortality proportion excluding this group. Nonetheless, our results are interpretable as estimates of the excess mortality among HIV-infected individuals, who may differ from a general population not only in being infected with HIV but also in other factors......A second limitation is that HIV seroconverters are not representative of the total HIV-infected population; mortality estimates derived from seroconverters, by definition diagnosed and monitored from an early stage, are likely to be optimistic compared with the experience of the wider HIV-infected population....

......We found that the gap in mortality rates between HIV-infected individuals in our study and the general population narrowed in every calendar period from 1996 onward. Considering the first years following the widespread introduction of HAART, we haveestimated an 88% reduction in excess mortality in 2000-2001 compared with pre-1996, corresponding closely to the 87% reduction in the standardized mortality ratio in 1997-2001 compared with pre-1996, as reported by the Swiss HIV cohort.7 Our more recentdata show that reductions have continued to 2004-2006, with excess mortality in this period 94% lower than pre-1996 levels. Corresponding to these reductions, the uptake of HAART increased, and though this leveled off after 2001, there followed an increasing use of NNRTI-based HAART as the first-line treatment regimen and a substantial increase in the boosting of PI-based regimens......Despite the major reductions in excess mortality, a significantly increased risk of death remained among individuals of all ages in 2004-2006.....we aimed to evaluate changes over calendar time in the excess mortality of HIV-infected individuals comparedwith expected mortality in the general uninfected population, adjusting for duration of HIV infection. We further aimed to assess changes over calendar time in the effects of prognostic factors and in the overall and excess probability of death at various stages of HIV infection. We also report corresponding changes over time in the uptake and use of HAART in our population.....excess mortality decreased dramatically from 1996 onward. By 2004-2006, there was no evidence of any excess mortality to 5 years from seroconversion in any age group. However, in the longer term, some excess mortality was still evident, with the cumulative excess probability of death in the first 10 years from seroconversion estimated to be 4.8% (95% CI, 2.5%-8.6%) in those aged 15 to 24 years and 4.3% (95% CI, 0.0%-10.5%) in those 45 years or older at seroconversion....The median time from HIV seroconversion to starting HAART was 1.6 (IQR, 0.7-3.5) years in 1996-1997 and 1.4 (IQR, 0.6-3.4), 1.8 (IQR, 0.7-5.6), 2.4 (IQR, 0.8-6.7), and 2.2 (IQR, 1.0-4.8) years in 1998-1999, 2000-2001, 2002-2003, and 2004-2006, respectively..."

ABSTRACT



Context Mortality among human immunodeficiency virus (HIV)–infected individuals has decreased dramatically in countries with good access to treatment and may now be close to mortality in the general uninfected population.

Objective To evaluate changes in the mortality gap between HIV-infected individuals and the general uninfected population.

Design, Setting, and Population Mortality following HIV seroconversion in a large multinational collaboration of HIV seroconverter cohorts (CASCADE) was compared with expected mortality, calculated by applying general population death rates matched on demographic factors. A Poisson-based model adjusted for duration of infection was constructed to assess changes over calendar time in the excess mortality among HIV-infected individuals. Data pooled in September 2007 were analyzed in March 2008, covering years at risk 1981-2006.

Main Outcome Measure Excess mortality among HIV-infected individuals compared with that of the general uninfected population.

Results Of 16 534 individuals with median duration of follow-up of 6.3 years (range, 1 day to 23.8 years), 2571 died, compared with 235 deaths expected in an equivalent general population cohort. The excess mortality rate (per 1000 person-years) decreased from 40.8 (95% confidence interval [CI], 38.5-43.0; 1275.9 excess deaths in 31 302 person-years) before the introduction of highly active antiretroviral therapy (pre-1996)to 6.1 (95% CI, 4.8-7.4; 89.6 excess deaths in 14 703 person-years) in 2004-2006 (adjusted excess hazard ratio, 0.05 [95% CI, 0.03-0.09] for 2004-2006 vs pre-1996). By 2004-2006, no excess mortality was observed in the first 5 years following HIV seroconversion among those infected sexually, though a cumulative excess probability of death remained over the longer term (4.8% [95% CI, 2.5%-8.6%] in the first 10 years among those aged 15-24 years).

Conclusions Mortality rates for HIV-infected persons have become much closer to general mortality rates since the introduction of highly active antiretroviral therapy. In industrialized countries, persons infected sexually with HIV now appear to experience mortality rates similar to those of the general population in the first 5 years following infection, though a mortality excess remains as duration of HIV infection lengthens.



INTRODUCTION


Jump to Section
• Top
• Introduction
• Methods
• Results
• Comment
• Author information
• References





A number of studies have reported the dramatic decreases in mortality among individuals infected with human immunodeficiency virus (HIV) since the widespread introduction of highly active antiretroviral therapy (HAART) in industrialized countries.1-2 It is important to provide up-to-date and robust estimates of expected mortality as anti-HIV drugs and strategies continue to improve. Such estimates help policy makers and those planning health care to monitor the effectiveness of treatments at a population level and provide an indicator of the ongoing and likely future impact of HIV disease on health care needs.

With mortality among HIV-infected individuals decreasing to relatively low levels compared with the pre-HAART era and with patients living to older ages, it is also of increasing interest to assess how mortality rates of HIV-infected individuals compare with those of the general uninfected population, ie, the "excess mortality."3Overall mortality of HIV-infected individuals is likely to be increasingly influenced by deaths that would haveoccurred regardless of HIV infection, and mortality in the general uninfected population provides a natural reference point for taking this into account. This concept has been used in studies of other diseases in which successfully treated patients frequently live for many years, such as Hodgkin disease4 and thyroid5 and other6cancers.

A few studies have compared HIV-infected and uninfected populations in industrialized countries, reporting reductions in the standardized mortality ratio in the early years of HAART availability7 and estimating a reduced life expectancy of 17 years for HIV-infected individuals compared with that of the uninfected population.8 Two further studies specifically considering those with a good initial response to treatment found an increased mortality risk, even in this subgroup.9-10

These studies have not been able to adjust for duration of HIV infection, which is a key factor influencing mortality risk and could confound other relationships. Using a large data set of individuals with well-estimated HIV seroconversion dates—thus avoiding biases that can occur when duration of infection is unknown11—we aimed to evaluate changes over calendar time in the excess mortality of HIV-infected individuals comparedwith expected mortality in the general uninfected population, adjusting for duration of HIV infection. We further aimed to assess changes over calendar time in the effects of prognostic factors and in the overall and excess probability of death at various stages of HIV infection. We also report corresponding changes over time in the uptake and use of HAART in our population.


METHODS


Jump to Section
• Top
• Introduction
• Methods
• Results
• Comment
• Author information
• References





Data were used from CASCADE (Concerted Action on Seroconversion to AIDS and Death in Europe), which has been described elsewhere.12 It is currently a collaboration of 23 cohorts of individuals with well-estimated dates of HIV seroconversion from Europe (20 cohorts from Denmark [1], France [4], Germany [1], Greece [1], Italy [1], the Netherlands [2], Norway [2], Spain [4], Switzerland [1], and the United Kingdom [3]), Australia (2 cohorts), and Canada (1 cohort). All eligible individuals are recruited, both prospectively and retrospectively, to the constituent cohorts through the clinical centers where they receive their HIV care, and an enrollment date is recorded for each participant. Of the 23 cohorts, 3 regional and 6 national cohorts collect data on individuals from a number of HIV clinical centers across the region or country, through the abstraction of medical records for all participants from routine clinic visits. These data are recorded on clinic report forms and then entered into the individual cohort database. Data are then extracted according to an agreed-on standardized data exchange protocol and submitted to the CASCADE coordinating center (Medical Research Council Clinical Trials Unit, London, United Kingdom) on an annual basis,where they are pooled. The remaining 14 single-clinic cohorts abstract data directly from their clinic database according to the same standardized data exchange protocol and forward the data to the coordinating center. Enrollment averaged 317 individuals per year overall from 1985-1987 and increased to 801 per year over the 19-year period 1988-2006. Six cohorts included in the analysis had ceased recruitment of new seroconvertersin 1992, 1997 (2 cohorts), 2000, 2002, and 2004. These 6 cohorts make up 7.7% of data included in the analyses. A subgroup of participants represented by the UK cohort data presented herein were evaluated in a previous study estimating changes in survival over calendar time after HIV seroconversion in a UK setting.13

All cohorts received approval from their individual ethics review boards except for the Danish cohort, which received approval from the National Data Registry Surveillance Agency because Danish law allowed collection and pooling of anonymized clinical data with approval from this agency alone. Two ethics review boards deemed their cohort participants exempt from providing signed informed consent. Signed informed consent was obtained from all others. Approval was also given by all ethics review boards to pool anonymized data for analyses and dissemination.

Estimates of HIV seroconversion dates are accurate to within 18, 12, and 6 months for 100%, 87%, and 63% of individuals, respectively, and are based on documented evidence of seroconversion. In 95% of cases, this evidence comprised a documented negative HIV antibody test result, which must be dated fewer than 3 yearsbefore the first positive result, and seroconversion date is estimated as the midpoint between the last negative and first positive test results. For the remaining 5% of cases, alternative documented laboratory evidence of seroconversion is available (real-time polymerase chain reaction positivity in the absence of HIV antibodies, or antigen positivity with <4 bands on a Western blot).

We included all individuals 15 years or older at seroconversion who had sexual or injection drug use (IDU) exposure to HIV and at least 1 day of follow-up since enrollment into the cohort. Individuals infected through hemophilia treatment (n = 234) and occupational exposure (n = 156) were excluded, as were 547 with unknown exposure type. To avoid survivorship bias, late-entry methods were used so that, in cases in whichseroconversion was identified retrospectively, time since seroconversion was only considered "at risk" from the date of enrollment into the cohort. Data were pooled in September 2007 and analyzed in March 2008, with follow-up available from May 1981 to June 2007. Follow-up time was censored on the date at which mortalitydata were assumed to be complete for each contributing cohort; death registration is compulsory in all countries represented in CASCADE, and for 14 of the 21 cohorts represented in the final analysis there is active cross-checking with national death registers for individuals lost to follow-up. As a further measure to avoid underascertainment of death due to reporting delays, we applied additional right-censoring on December 31,2006.

Statistical Analysis

Changes over time in the overall risk of death were calculated from a Cox model stratified by cohort and adjusted for age at seroconversion, sex, and HIV exposure category, with calendar period of follow-up as a time-updated covariate, categorized to represent the era before extensive availability of HAART (pre-1996) and at regular intervals thereafter (1996-1997, 1998-1999, 2000-2001, 2002-2003, and 2004-2006). We confirmed that there was no evidence against the proportional hazards assumption by a test based on the Schoenfeld residuals, where P < .05 would indicate problems with the assumption.14

For the analysis of excess mortality, the expected number of deaths was calculated by applying annual probability of death data from the general population to the study population, considering individuals to be at risk until their actual date of death or censoring.15 The general population mortality data were obtained from the Human Mortality Database in July 2007,16 stratified by age, sex, calendar year at risk, and country, and were matched to the study population on these factors. Race and ethnicity were not reported. The number of deaths among CASCADE individuals in each demographic stratum was then modeled using a Poisson process, offsetting the expected deaths. This is known as a relative survival model and provides adjustment for background mortality without the need for information on cause of death.3 Time since seroconversion was divided into 1-year intervals and included in the model as a categorical variable,17 thus effectively assuming a piecewise constant hazard of excess mortality in each 1-year interval following seroconversion. To check thesensitivity of our results to this assumption, we also repeated our analyses using 3-month and 6-month intervals in the first 2 years of infection, thus allowing the hazard function more flexibility close to seroconversion.

Within this relative survival model framework, we examined changes in the risk of excess mortality over calendar time of follow-up (time-updated), adjusting for age at seroconversion, sex, and HIV exposure category. The relative survival models provide estimates of excess hazard ratios (eHRs), the interpretation of which is similar to that of the familiar Cox hazard ratio. For example, an eHR of 1.5 for male/female would indicate that males have a 50% higher risk of dying compared with females, after accounting for expected background mortality. We then investigated the effects of age at seroconversion, sex, and HIV exposure category as potential prognostic factors for excess mortality. Interactions with calendar time were added to assess whether these effects had changed over calendar time. Two-sided P values for individual model parameters and interactions were produced using likelihood ratio tests of nested models, and for model-building purposes we considered P < .05 to indicate statistical significance.

Using subgroups based on the most important factors from the final model, we then calculated life-table estimates of the cumulative survival and relative survival function18 by duration of infection in each calendar period, by multiplying interval-specific probabilities. Hence the corresponding cumulative overall (1 – cumulative survival) and excess (1 – relative survival) probability of death at 5, 10, and 15 years of HIV infection duration were derived (as preplanned analyses). These intervals were chosen because we anticipated that reliable estimates could be derived up to 15 years from HIV seroconversion (in a prior report, stable estimates of overall survival to 10 years following HIV seroconversion were generated,1 and 5 additional years of follow-up data are now available), and we wished to describe changes in mortality patterns and allow comparison across subgroups at a small number of regular intervals of infection duration. Additional late entry and censoring were applied at the beginning and end, respectively, of the calendar period in question; thus,estimates for each period covered the entire duration of infection (incorporating short-term information from the recently diagnosed individuals and longer-term information from those diagnosed in the past). This approach is known as period analysis and has been commonly used in population-based studies.1, 19

Finally, in the same calendar periods, we described the time to starting HAART (defined as at least 3 antiretroviral drugs representing at least 2 drug classes or including abacavir or tenofovir20) using Kaplan-Meier methods and the proportion of time spent receiving HAART. The numerator for the latter was the amount of person-time spent receiving HAART as derived from the prescription start and stop dates recorded for individual drugs during routine clinical follow-up. Because therapy guidelines recommend the initiation of HAART before CD4 cell count decreases to 200 cells/µL and HAART is typically initiated at 200 to 350 cells/µL,20-21 we considered as the denominator only time at risk after the first CD4 cell count below 350 cells/µL or after HAART initiation, whichever came earlier.

All statistical analyses were performed using Stata version 10 (StataCorp, College Station, Texas).


RESULTS


Jump to Section
• Top
• Introduction
• Methods
• Results
• Comment
• Author information
• References





Participants

The analysis included 16 534 individuals (Table 1) with median age at HIV seroconversion of 29 years (interquartile range [IQR], 24-36 years). The reported exposure category was sex between males for 9465 individuals (57%), IDU for 3047 (18%), and sex between males and females for 4022 (24%). For year ofseroconversion, the median was 1994 (range, 1980-2006). The study observation time ranged from May 1981 to December 2006, and all but 1 cohort (representing 0.5% of the data) contributed data to every calendar period considered in the analysis. The median duration of follow-up was 6.3 years (range, 1 day to 23.8 years), with 16 344 individuals (99%) having more than 1 month of follow-up. There were 21 cohorts represented in the final included data (after excluding 2 with only hemophilia patients), with 16 143 individuals (98%) belonging to European cohorts. The median number of individuals included per cohort was 388 (range, 56-7000). For 2 contributing cohorts the reported exposure category was exclusively IDU and for 1 cohort was exclusively sex between males; however, most individuals (16 256 [98%]) were enrolled in cohorts covering all 3 exposure categories.




View this table:
[in this window]
[in a new window]
[as a PowerPoint slide]

Table 1. Characteristics of the Study Population






Changes Throughout Calendar Time in Excess Mortality Risk and Prognostic Factors

A total of 2571 individuals had died as of December 2006, compared with an estimated 235 deaths that would have been expected in a matched general population cohort (Table 2). The excess mortality rate per 1000 person-years was 40.8 (95% confidence interval [CI], 35.8-43.0; 1275.9 excess deaths in 31 302 person-years)pre-1996, decreasing in each subsequent calendar period to 6.1 (95% CI, 4.8-7.4; 89.6 excess deaths in 14 703 person-years) in 2004-2006.




View this table:
[in this window]
[in a new window]
[as a PowerPoint slide]

Table 2. Changes in Overall and Excess Mortality Rates






The overall adjusted hazard ratio of death compared with pre-1996 was 0.57 (95% CI, 0.51-0.64), 0.20 (95% CI, 0.18-0.24), 0.15 (95% CI, 0.12-0.17), 0.13 (95% CI, 0.11-0.15), and 0.09 (95% CI, 0.07-0.11) in 1996-1997, 1998-1999, 2000-2001, 2002-2003, and 2004-2006, respectively. In the relative survival model adjusted for background mortality, as well as duration of infection and prognostic factors, the eHR of death compared with pre-1996 was 0.54 (95% CI, 0.48-0.60), 0.17 (95% CI, 0.14-0.20), 0.12 (95% CI, 0.10-0.14), 0.10 (95% CI, 0.08-0.12), and 0.06 (95% CI, 0.05-0.08) in the same periods, respectively. Older age at seroconversion was associated with a higher risk of excess mortality (eHR, 2.54; 95% CI, 2.10-3.07 for age 45 years compared with age 15-24 years; P < .001), as was a reported exposure category of IDU (eHR, 1.52; 95% CI, 1.36-1.69 [P < .001] compared with sex between males). Females appeared to be at lower risk than males (eHR, 0.80; 95% CI, 0.70-0.91 [P = .001]).

There was strong evidence for a change over calendar time in the effects of age at seroconversion (P = .002), exposure category (P < .001), and sex (P < .001) when these interactions were added individually to our model, although when all 3 were added, only the exposure category interaction remained statistically significant (Table 3). There was no overall effect of exposure category in the pre-1996 period (P = .29). In each subsequent calendar period, exposure category was strongly predictive of excess mortality (P < .001 in each period), with those exposed through IDU at significantly higher risk than those exposed through sex between males (eHR, 3.71; 95% CI, 2.05-6.73 in 2004-2006). Those exposed via sex between males and females had a risk of excess mortality similar to that of those exposed via sex between males in every periodexcept 2000-2001, when they were at higher risk (eHR, 2.02; 95% CI, 1.18-3.45).




View this table:
[in this window]
[in a new window]
[as a PowerPoint slide]

Table 3. Excess Hazard Ratios (eHRs) Obtained Using a Multivariate Model for Excess Mortalitya






For age at seroconversion and sex there was no evidence of variation over calendar time in the final model (P = .40 and P = .45, respectively, for interaction). Over all calendar periods there was a clear gradient of increasing risk of excess mortality with increasing age at seroconversion. Females were at consistently lower risk than males.

All estimates were very similar in 2 sensitivity analyses in which time since seroconversion was split into smaller intervals (3 and 6 months) for the first 2 years of infection.

Estimated Excess Mortality by Duration of Infection

Considering those in the sexual HIV exposure groups, mortality among HIV-infected individuals decreased toward background mortality levels between pre-1996 and 2004-2006 (Figure). Because individuals in the IDU exposure category are likely to be at higher risk of mortality than the general population regardless of HIV infection, this category was initially excluded from estimates of the cumulative excess mortality. Comparing the cumulative overall and excess probability of death, we found that prior to 1996, excess mortality above that expected in the general population accounted for the vast majority of total observed mortality in CASCADE in all age groups and at all stages of infection (Table 4). However, excess mortality decreased dramatically from 1996 onward. By 2004-2006, there was no evidence of any excess mortality to 5 years from seroconversion in any age group. However, in the longer term, some excess mortality was still evident, with the cumulative excess probability of death in the first 10 years from seroconversion estimated to be 4.8% (95% CI, 2.5%-8.6%) in those aged 15 to 24 years and 4.3% (95% CI, 0.0%-10.5%) in those 45 years or older at seroconversion, though in the latter age group this excess mortality represented less than half of the total 10-year mortality of 12.2%.





View larger version (42K):
[in this window]
[in a new window]
[as a PowerPoint slide]

Figure. Reduction in All-Cause Mortality pre-1996 to 2006 and Comparison With That of the General Population, by Age Group
The general population curve for 2004-2006 was generated by applying general population mortality rates in each 1-year interval since seroconversion to a hypothetical cohort matched to the study population on age, sex, and country. HIV indicates human immunodeficiency virus.






View this table:
[in this window]
[in a new window]
[as a PowerPoint slide]

Table 4. Estimated Cumulative Overall Probability of Death by Duration of HIV Infection Among Sexual Exposure Groups in CASCADE and Cumulative Excess Probability of Death Compared With That of the General Populationa







Among individuals exposed through IDU, in contrast, mortality in 2004-2006 was higher than background levels, even early in infection (estimated cumulative excess probability of death in the first 5 and 10 years, 4.8% [95% CI, 1.4%-13.6%] and 6.2% [95% CI, 2.2%-14.3%], respectively, among those exposed throughIDU who were younger than 45 years at seroconversion).

To further explore the differences between HIV exposure groups, we considered causes of death in 2004-2006. Of the 127 individuals who died in this period, 95 had known cause of death (as recorded in clinic records or death certificates), the most common being AIDS for 27 individuals (28%), non-AIDS malignancy for 14 (15%),and suicide or intentional harm for 13 (14%). The pattern of causes of death among those exposed through IDU differed from that of other groups: no non-AIDS malignancies were reported, and there was a higher proportion of reported liver-related causes (7/22 [32%], compared with 2/73 [3%] among sexual exposure groups). The proportion of deaths reported as suicide among those exposed through IDU was only slightly higher than among those with reported exposure category of sex between males (4/22 [18%] vs 8/51 [16%]).

Uptake of HAART

The median time from HIV seroconversion to starting HAART was 1.6 (IQR, 0.7-3.5) years in 1996-1997 and 1.4 (IQR, 0.6-3.4), 1.8 (IQR, 0.7-5.6), 2.4 (IQR, 0.8-6.7), and 2.2 (IQR, 1.0-4.8) years in 1998-1999, 2000-2001, 2002-2003, and 2004-2006, respectively. After excluding time at risk when HAART would not be indicated, the proportion of person-time spent receiving HAART increased from 17% in 1996-1997 to 54%, 66%, 69%, and 73% in the same calendar periods, respectively. As expected, the use of nonnucleoside reverse transcriptase inhibitor (NNRTI)–based regimens increased over time and by 2004-2006, the proportion of person-time receiving NNRTI-based HAART was approximately equal to that spent receiving protease inhibitor (PI)–based HAART (40% and 42% of person-time on HAART, respectively, compared with 18% and 71%, respectively, in 1998-1999, when the first NNRTIs were available). Ritonavir boosting of PI regimens also increased from 7.0% of person-time receiving PI-based HAART in 1996-1997 to 10.7%, 32%, 63%, and 79% in 1998-1999, 2000-2001, 2002-2003, and 2004-2006, respectively.


COMMENT


Jump to Section
• Top
• Introduction
• Methods
• Results
• Comment
• Author information
• References





We found that the gap in mortality rates between HIV-infected individuals in our study and the general population narrowed in every calendar period from 1996 onward. Considering the first years following the widespread introduction of HAART, we haveestimated an 88% reduction in excess mortality in 2000-2001 compared with pre-1996, corresponding closely to the 87% reduction in the standardized mortality ratio in 1997-2001 compared with pre-1996, as reported by the Swiss HIV cohort.7 Our more recentdata show that reductions have continued to 2004-2006, with excess mortality in this period 94% lower than pre-1996 levels. Corresponding to these reductions, the uptake of HAART increased, and though this leveled off after 2001, there followed an increasing use of NNRTI-based HAART as the first-line treatment regimen and a substantial increase in the boosting of PI-based regimens.

Despite the major reductions in excess mortality, a significantly increased risk of death remained among individuals of all ages in 2004-2006. A number of other studies comparing mortality in HIV-infected and uninfected populations have also found a significant remaining excess mortality,10 though we found a relatively low level of excess mortality among those 45 years or older compared with 1 study8; however, since that study considered time-updated acquired age rather than age at HIV seroconversion, it is likely that those contributing to the 45 years or older age groups had longer duration of infection, which was unknown in that study.

To our knowledge, no study to date has made a comparison of mortality among HIV-infected and uninfected individuals adjusted for duration of HIV infection, and our results provide estimates, hitherto unavailable, of the cumulative excess probability of death as duration of HIV infection increases. Interestingly, we found that by 2004-2006, the risk of death in the first 5 years following seroconversion was similar to that of the generalpopulation, with the excess probability of death becoming apparent only later in the course of infection. Our long-term cumulative mortality estimates for 2004-2006 include data from individuals infected in the mid-1990s or earlier who may have started antiretroviral treatment later in the course of infection and with regimensinferior to those currently available; thus, such estimates may be pessimistic in terms of the long-term outlook for more recently infected individuals. Nevertheless, it is likely that even with current standards of HIV management, some long-term excess mortality would remain because problems of toxicity, resistance, and therapy adherence are likely to increase with time receiving HAART.

We found that older age was highly predictive of excess mortality prior to 1996, and this effect broadly continued in later calendar periods, despite suggestions in the literature that increasing age is associated with better adherence to HAART.22 Another large study23 found an association between older age and overallmortality following HAART initiation. It is of interest that the effect persisted in our analysis adjusted for natural aging, which appeared to account for more than half of the total mortality in individuals 45 years or older in 2004-2006. Some studies have found that older individuals experience slower immune recoveryfollowing HAART initiation,24-25 which could reflect the state of thymic function and may in part account for their continuing excess risk of death.26

Individuals exposed through IDU had a higher excess risk of death throughout the HAART era, with a 4-fold higher risk compared with the reported exposure category of sex between males in 2004-2006. It is unlikely that HIV infection is the only factor leading to increased mortality rates among those exposed through IDU, who, as well as accounting for the direct risks of substance abuse, may be more likely to be diagnosed with mental health–related illnesses27 and coinfections,28 the effects of which may have been masked prior to 1997 by the mortality burden of HIV disease itself. On the other hand, the increasing separation of those exposed through IDU since 1997 as a group with higher excess mortality may point to differences in access and adherence to therapy. Indeed, we found a lower uptake of HAART among those exposed through IDU compared with other groups, while lower therapy adherence among such individuals has been described in the literature.29

Our study has some limitations. Ideally we would like to quantify the excess mortality associated with HIV infection. To this end, we have compared mortality in CASCADE with that in the general population. Although we matched by age, sex, calendar time, and country, it is likely that HIV-infected individuals in our study differ from the general population in other ways. Rates of smoking have been shown to be high among some HIV-infected populations30; other risk behaviors, socioeconomic factors, and race/ethnicity are also likely to differ among HIV-infected persons. Those exposed through IDU in particular are likely to be at higher risk of mortality than the general population regardless of HIV infection, and we have presented our estimates of the cumulative excess mortality proportion excluding this group. Nonetheless, our results are interpretable as estimates of the excess mortality among HIV-infected individuals, who may differ from a general population not only in being infected with HIV but also in other factors.

A second limitation is that HIV seroconverters are not representative of the total HIV-infected population; mortality estimates derived from seroconverters, by definition diagnosed and monitored from an early stage, are likely to be optimistic compared with the experience of the wider HIV-infected population. In particular,further research will be needed before our finding of no excess mortality in the first 5 years of infection in 2004-2006 can be generalized beyond those diagnosed early in infection.

Despite these limitations, seroconverters provide a unique opportunity to study and adjust for the effect of duration of HIV infection on mortality and excess mortality. Our results show the progress in reducing mortality among HIV-infected individuals toward the levels experienced by the general uninfected population. However, there is continuing excess mortality, particularly evident in those infected for 10 years or more. Ongoing monitoring of excess mortality will be important as new treatment advances are implemented in an attempt to further reduce mortality rates among HIV-infected individuals.


AUTHOR INFORMATION


Jump to Section
• Top
• Introduction
• Methods
• Results
• Comment
• Author information
• References





Corresponding Author: Kholoud Porter, PhD, MRC Clinical Trials Unit, 222 Euston Rd, London NW1 2DA, United Kingdom (kp@ctu.mrc.ac.uk).

Author Contributions: Mr Bhaskaran had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Bhaskaran, Johnson, Porter.

Acquisition of data: Bhaskaran, Hamouda, Sannes, Boufassa.

Analysis and interpretation of data: Bhaskaran, Lambert, Porter.

Drafting of the manuscript: Bhaskaran, Sannes, Porter.

Critical revision of the manuscript for important intellectual content: Hamouda, Boufassa, Johnson, Lambert, Porter.

Statistical analysis: Bhaskaran, Lambert.

Obtained funding: Porter.

Administrative, technical, or material support: Hamouda, Sannes, Boufassa, Porter.

Study supervision: Bhaskaran, Johnson, Porter.

Financial Disclosures: None reported.

Funding/Support: The CASCADE collaboration has been funded through grants BMH4-CT97-2550, QLK2-2000-01431, QLRT-2001-01708, and LSHP-CT-2006-018949 from the European Union.

Role of the Sponsor: The European Union had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; or the preparation, review, or approval of the manuscript.


--------------------------------------------------------------------------------
Get the Moviefone Toolbar. Showtimes, theaters, movie news, & more!


_______________________________________________
NATAP nataphcvhiv mailing list -- nataphcvhiv@natap.org

This is an annoucement-only mailing list. Do not reply.

To unsubscribe: send a blank email to nataphcvhiv-request@natap.org with a subject of unsubscribe.


For more information, see http://seven.pairlist.net/mailman/listinfo/nataphcvhiv

_______________________________________________