Skip Navigation LinksHome > February 1, 2008 - Volume 47 - Issue 2 > Determinants of HIV Progression and Assessment of the Optima...
JAIDS Journal of Acquired Immune Deficiency Syndromes:
doi: 10.1097/QAI.0b013e31815ee282
Epidemiology and Social Science

Determinants of HIV Progression and Assessment of the Optimal Time to Initiate Highly Active Antiretroviral Therapy: PISCIS Cohort (Spain)

Jaén, Ángeles MD, PhD*∥∥; Esteve, Anna PhD*¶¶; Miró, Josep M MD, PhD†; Tural, Cristina MD, PhD‡; Montoliu, Alexandra BSc*¶¶; Ferrer, Elena MD§; Riera, Melcior MD, PhD∥; Segura, Ferran MD, PhD¶; Force, Lluis MD, PhD#; Sued, Omar MD, PhD†; Vilaró, Josep MD**; Garcia, Isabel MD††; Masabeu, Angels MD‡‡; Altès, Jordi MD§§; Clotet, Bonaventura MD, PhD‡; Podzamczer, Daniel MD, PhD§; Murillas, Javier MD, PhD∥; Navarro, Gemma MD, PhD¶; Gatell, Josep M MD, PhD†; Casabona, Jordi MD, MPH, PhD*¶¶##; the PISCIS Study Group

Free Access
Article Outline
Collapse Box

Author Information

From the *Centre d'Estudis Epidemiològics sobre ITS/VIH/SIDA de Catalunya, Badalona, Spain (CEEISCAT, coordinating center); †Hospital Clínic-Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; ‡Hospital Universitari Germans Trias i Pujol, Universitat Autònoma de Barcelona, Badalona, Spain; §Hospital Universitari de Bellvitge-Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), l'Hospitalet de Llobregat, Barcelona, Spain; ∥Hospital Son Dureta, Palma de Mallorca, Spain; ¶Corporació Sanitària Parc Taulí, Sabadell, Spain; #Hospital de Mataró, Mataró, Spain; **Hospital General de Vic, Vic, Spain; ††Hospital Creu Roja de L'Hospitalet, Hospitalet de Llobregat, Barcelona, Spain; ‡‡Hospital de Palamós, Palamós, Spain; §§Hospital Alt Penedès, Vilafranca, Spain; ∥∥Fundació Mútua de Terrassa per a la Docència i la Recerca Biomèdica i Social, Terrassa, Spain; ¶¶CIBER Epidemiología y Salud Pùblica (CIBERESP), Spain; and ##Preventive and Public Health Department, Autonomous University of Barcelona, Spain.

Received for publication May 4, 2007; accepted October 18, 2007.

Proyecto para la Informatización del Seguimiento Clínico epidemiológico de los pacientes con Infección por VIH/SIDA (PISCIS) Study Group (see members in the Appendix).

The PISCIS cohort is supported by the Fundación para la Investigación y Prevencion del Sida en España (FIPSE, Madrid Spain, National AIDS Plan Secretariat of the Spanish Ministry of Health), grants 3084/99, 36354/02, 36488/05 and the Department de Salut de la Generalitat de Catalunya, Barcelona, Catalunya, Spain. The study has also received support from the Fondo de Investigaciones Sanitarias (FIS), Spain, grant 1520/97; and by the Red Temática Cooperative de Grupos de Investigación en Sida, FIS.

J. M. Miró was a recipient of a Research Grant from the Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and the Conselleria de Salut de la Generalitat de Catalunya, Barcelona, Spain.

None of the authors have any potential conflicts of interest with this study.

Correspondence to: Ángeles Jaén, MD, PhD, Fundació Mútua de Terrassa per a la Docència i la Recerca Biomèdica i Social, Universitat de Barcelona, Plaça Dr. Robert, 5, 08221 Terrassa, Barcelona, Spain (e-mail: ajaen@mutuaterrassa.es).

Collapse Box

Abstract

Objective: We analyze the factors related to progression to AIDS or death in HIV-infected patients from the Proyecto para la Informatización del Seguimiento Clínico epidemiológico de los pacientes con Infección por VIH/SIDA (PISCIS) Cohort and we assess the optimal time to initiate highly active antiretroviral therapy (HAART) taking lead time into account.

Methods: We selected naive patients who were AIDS-free and initiated HAART after January 1998. Statistical analyses were performed using Cox proportional hazards models. Lead time was defined as the time it took the deferred group with an early disease stage to reach the later stage. The analysis accounting for lead time was performed using multiple imputation methods based on estimates from the pre-HAART period as described elsewhere.

Results: Multivariate analysis on 2035 patients (median follow-up = 34.3 months) showed significantly higher hazard ratios (HRs) for a CD4 count <200 cells/μL (HR = 3.79, 95% confidence interval [CI]: 2.18 to 6.57), HIV-1 RNA level >100,000 copies/mL (HR = 1.84, 95% CI: 1.26 to 2.69), and hepatitis C virus (HCV) coinfection (HR = 2.40, 95% CI: 1.65 to 3.49), whereas a lower risk was found for those who started HAART between January 2001 and June 2004 (HR = 0.55, 95% CI: 0.30 to 0.90). When lead time and unseen events were included, we found a higher risk of progression to AIDS among patients who deferred treatment when the CD4 count reached <200 cells/μL (HR = 2.97, 95% CI: 1.91 to 4.63) and 200 to 350 cells/μL (HR = 1.85, 95% CI: 1.03 to 3.33) compared with those who started treatment with CD4 counts from 200 to 350 cells/μL and >350 cells/μL, respectively.

Conclusions: Advanced HIV disease, HCV coinfection, and early HAART period were determinants of AIDS progression or death. Lead-time analysis in asymptomatic HIV-infected patients suggests that the best time to start HAART is before the CD4 count falls to lower than 350 cells/μL.

After the introduction of highly active antiretroviral therapy (HAART), the mortality and morbidity of HIV infection decreased dramatically, to the extent that it is now a chronic disease.1 HAART has some disadvantages, however, such as severe adverse effects, resistance to drugs, and its high cost. Furthermore, current regimens cannot eradicate infection, with the result that therapy is for life. Therefore, it is essential to define the determinants of progression to know exactly when to start therapy.

The most important factor affecting the prognosis of HIV infection is the CD4 cell count before starting therapy. Currently, one of the main controversies over when to initiate HAART concerns HIV-infected patients with an intermediate immunologic level (CD4 count of 200 to 350 cells/μL). Most studies have found a worse prognosis, with a higher risk of death or progression to AIDS, in patients who started HAART with a CD4 count <200 cells/μL compared with those who started with high CD4 cell levels.2-8 In those patients who started HAART with 200 to 350 cells/μL, however, studies differ in their results. Although some observational studies have found a higher risk of progression to AIDS or death,6,9 others have not found significant differences.2,3,8 In addition, some studies have found a different risk of disease progression depending on viral load (VL)10 or on whether an undetectable VL was reached.11 These authors recommend taking VL into account when deciding the optimal time to start treatment.

A major limitation of some of the reported differences is the lack of an adjustment for lead time, which results in biased risk estimates. Briefly, in an ideal hypothetic clinical trial designed to establish when to initiate HAART, HIV-positive AIDS-free patients would be randomly assigned to start or defer treatment and would be followed up from randomization to AIDS. Thus, to mimic such a trial using data from observational studies, previous survival time for individuals who started treatment at low immunologic levels (lead time) and previous events in those who initiate therapy later (the unseen fast progressors) should be taken into account so that a common origin for the time-to-event analysis can be determined.3,9,12,13

Since 1998, we have been conducting an observational study that includes HIV-infected patients from 9 hospitals within Catalonia and 1 from the Balearic Islands (PISCIS Cohort Study). Until December 2004, the study included 6922 patients with 17,766 person-years of follow-up. The PISCIS Cohort has provided us with information on clinical epidemiologic trends in the initial diagnosis of HIV and on the appropriate use of antiretroviral treatment.14

The aims of this study are to determine factors related to progression to AIDS or death in HIV-infected patients from the PISCIS Cohort Study and to assess the optimal time to initiate HAART on time to AIDS using methods that take lead time into account.

Back to Top | Article Outline

METHODS

PISCIS Cohort Study

The PISCIS Cohort Study was started in 1996 with the development of an informatics application to computerize the clinical records of HIV-infected patients. In 2000, after a feasibility study, information from the routine clinical follow-up of all newly attended patients (≥16 years of age) was retrospectively collected from 1998 to 2000, and prospectively thereafter. Detailed methods for the cohort have been described elsewhere.14

Back to Top | Article Outline
Quality Assessment

Quality was assessed by means of quality-control reports and quality-control visits for each center. To reduce the lack of information on patients lost to follow-up, hospitals periodically matched the data with other sources of information within the hospital (clinical records and other computerized records of death or hospital admissions from centers). Only a few centers performed active follow-up by telephone or mail when patients did not keep their appointment. The overall loss to follow-up of the PISCIS Cohort is 26%, and it is 18% for naive patients who started HAART.

Back to Top | Article Outline
Ethical Considerations

Confidentiality was ensured through nonpersonal identification. The study was approved by the ethics committees of the participating hospitals.

Back to Top | Article Outline
Laboratory Analysis

CD4 T lymphocytes were quantified by flow cytometry. HIV-1 RNA levels were quantified by reverse transcriptase (RT) polymerase chain reaction (PCR), branched DNA, or nucleic acid sequence-based amplification (NASBA) techniques.

Back to Top | Article Outline
Inclusion Criteria

We included treatment-naive HIV-infected patients who initiated HAART between January 1998 and June 2004, were AIDS-free before the treatment started, and were on HAART for at least 1 month.

Back to Top | Article Outline
Definitions

HAART was defined as the combination of at least 3 antiretroviral drugs, according to Spanish15 and international16 guidelines. This analysis included the following regimens: 1 or 2 protease inhibitors (PIs) with 2 nucleoside reverse transcriptase inhibitors (NRTIs), 1 nonnucleoside reverse transcriptase inhibitor (NNRTI) with 2 NRTIs, 3 NRTIs, or other combinations. AIDS-defining illnesses are based on the 1993 Centers for Disease Control and Prevention clinical case definition17 without considering a CD4 count <200 cells/μL as AIDS defining. All causes of mortality were considered. Patients were assigned to 1 of 3 groups based on their CD4 cell count at baseline, defined as the nearest CD4 cell determination before initiating HAART within a 6-month period (>350, 200 to 350, and <200 cells/μL). In addition, we considered VL at baseline as the nearest determination before initiating HAART within a 6-month period and assigned patients depending on whether they had a high VL (HIV-1 RNA ≥100,000 copies/mL) or low VL (HIV-1 RNA <100,000 copies/mL). Hepatitis B virus (HBV) and hepatitis C virus (HCV) were defined as the presence, before initiating HAART, of hepatitis B surface antigen (HBsAg) and HCV antibody, respectively. The period of initiation of HAART was categorized according to the availability of therapy: January 1998 through December 2000 (early HAART) or January 2001 through June 2004 (midterm HAART).

Back to Top | Article Outline
Statistical Analysis

For the descriptive analysis, quantitative characteristics were described using median values and interquartile ranges (IQRs) and qualitative characteristics using percentages. The Kruskal-Wallis test and Pearson χ2 test were used to compare the characteristics of the baseline CD4 cell count groups. Cumulative progression probabilities to AIDS/death were computed using the Kaplan-Meier estimator.

Cox proportional hazards models were used to assess the determinants of progression to AIDS or death after the initiation of HAART. The hazard ratios (HRs) and their 95% confidence intervals (95% CIs) were calculated. Multivariate models were adjusted by calendar period of treatment (early and midterm HAART), which was treated as a time-dependent variable. Potential confounding factors and variables with a significant unadjusted HR at the 0.20 level were included in the initial multivariate model. The best multivariate model was obtained by systematically comparing the deviance of the models. Patients included in the analysis not seen in the year preceding the censoring date were censored alive at the date of their last visit. Patients in active follow-up were administratively censored on December 31, 2004.

To estimate the impact of deferring the initiation of HAART on the progression of HIV infection to AIDS, we applied methodologies designed to mimic hypothetic randomized experiments as closely as possible.13 Briefly, when time to AIDS for patients who initiated HAART with a high CD4 count (eg, >350 cells/μL) was compared with that for patients who deferred HAART to lower levels (eg, 200 to 350 cells/μL), a common time-to-event analysis was performed by adding to the deferred group previous survival time (lead time) to progress from the early stage to the late stage, when therapy was initiated. Moreover, the survival time of patients who progressed to AIDS from a high CD4 cell count before reaching lower levels (unseen fast progressors) was added to the analysis. The procedure was performed analogously when those who initiated HAART at a CD4 count of 200 to 350 cells/μL were compared with those who deferred HAART until they reached a CD4 count <200 cells/μL.

Lead time for patients who transitioned to lower CD4 T-cell levels when HAART was initiated and lead time for the fast progressors were generated using the parametric cumulative models of progression reported by the Multicenter AIDS Cohort Study (MACS) with data from the pre-HAART era (Fig. 1),13 by taking advantage of the idea that therapies before December 1995 did not substantially alter the course of the disease. More specifically, we generated lead times to progress from a CD4 count >350 cells/μL to 200 to 350 cells/μL and from 200 to 350 cells/μL to <200 cells/μL, without AIDS, from the estimated log-normal cumulative probability distributions presented in Figure 1 (thick solid lines show cumulative incidence estimates of the time to the CD4 transition without AIDS). Additionally, fitted models for the number of fast progressors (unseen sample) and their survival times were used: the estimated proportion of fast progressors was 0.03 in the group with >350 cells/μL and 0.12 in the group with 200 to 350 cells/μL. Similarly, lead times to progression to AIDS from >350 cells/μL and 200 to 350 cells/μL without reaching a lower CD4 cell threshold were estimated using the log-normal cumulative probability distributions presented in Figure 1 (dashed lines show cumulative incidence estimates of the time to AIDS without CD4 cell transition).

Figure 1
Figure 1
Image Tools

Finally, the lead time and the unseen sample were multiply imputed (repeated 50 times), and the lead-time-adjusted HRs, which approximated the HRs obtained from a randomized deferral trial, were computed by combining the imputed survival times using multiple imputation techniques.18

The analyses were performed by intention to treat, ignoring treatment changes and interruptions.

Back to Top | Article Outline

RESULTS

A total of 3427 treatment-naive participants started HAART between January 1, 1998 and June 30, 2004. Of these, 2520 (73.53%) were AIDS-free before starting HAART, 2129 (84.48%) had had an available CD4 T-cell count within 6 months before initiating HAART, and 2035 (95.58%) were on HAART for at least 30 days.

The clinical and epidemiologic characteristics of the study population by baseline CD4 cell count groups are shown in Table 1. Of the 2035 patients included, 760 were in the group with <200 cells/μL at baseline, 650 were in the group with 200 to 350 cells/μL, and 625 were in the group with >350 cells/μL. The median age of the patients was 35.5 years, and 75.4% were men.

Table 1
Table 1
Image Tools
Back to Top | Article Outline
Determinants of HIV Disease Progression or Death

A total of 148 patients (7.3%) progressed to AIDS or death after a median follow-up of 34.3 months. Univariate and multivariate Cox models for risk progression are shown in Table 2. We found a higher risk for the group with a CD4 count <200 cells/μL (HR = 4.22, 95% CI: 2.63 to 6.78) than for the group with a CD4 count >350 cells/μL. We also found a higher risk of disease progression in older patients, men, injection drug users (IDUs), patients with HCV at baseline, those who initiated treatment with a PI-containing HAART regimen, and those with a high VL. In those patients who initiated HAART between January 2001 and June 2004, the risk was reduced by half. In the multivariate analysis, after adjusting by the effect of the calendar period, only a CD4 count <200 cells/μL, a high VL before starting HAART, HCV at baseline, and early HAART period remained significant.

Table 2
Table 2
Image Tools

A hypothesis on the linear trend in the risk of progression to AIDS or death according to the different levels of CD4 cell counts and VLs at HAART initiation was assessed using a combined variable (Fig. 2). We observed a higher risk of progression to AIDS or death in patients with a CD4 count <200 cells/μL and high and low VLs (HRs = 5.88 and 3.39, respectively).

Figure 2
Figure 2
Image Tools
Back to Top | Article Outline
When to Initiate HAART

In an unadjusted Cox regression analysis, we found a higher risk among patients who deferred treatment with <200 cells/μL (HR = 2.81, 95% CI: 1.79 to 4.40) than among those starting treatment with 200 to 350 cells/μL. Moreover, a higher risk of progression was found among those patients who deferred HAART until they had 200 to 350 cells/μL compared with those who started with >350 cells/μL, although this was not statistically significant (HR = 1.56, 95% CI: 0.84 to 2.90). When methodologies taking lead time into account were applied, the risk of progression to AIDS was higher for patients who initiated treatment with <200 cells/μL (HR = 2.97, 95% CI: 1.91 to 4.63) and for those who initiated treatment with 200 to 350 cells/μL (HR = 1.85, 95% CI: 1.03 to 3.33), compared with those who started treatment with 200 to 350 cells/μL and >350 cells/μL, respectively (Fig. 3).

Figure 3
Figure 3
Image Tools
Back to Top | Article Outline

DISCUSSION

The PISCIS Cohort is an observational prospective study that includes 70% of all new HIV infections reported in Catalonia and the Balearic Islands. We assessed the progression of HIV infection in 2035 asymptomatic naive patients on HAART with a median follow-up of 34 months. We found a higher risk of progression to AIDS or death in those patients who started HAART with a CD4 count <200 cells/μL. In addition, VL, HCV coinfection, and period of initiation of HAART were independent risk factors. After accounting for lead time and unseen events, a statistically significant risk of progression to AIDS was found in patients who delayed HAART initiation until they had a CD4 count of 200 to 350 cells/μL compared with those who initiated therapy with more than 350 cells/μL.

Back to Top | Article Outline
Determinants of HIV Disease Progression or Death

We observed a higher risk of progression to AIDS or death in patients who started HAART with <200 cells/μL, and this agrees with previous findings.2-9 Recently, some authors19 have found that the CD4 percentage (CD4%) could be important when deciding on the optimal time to start therapy, particularly in patients with a CD4 count of 200 to 350 cells/μL. In our study, however, the relative hazards of progression to AIDS or death for each CD4 cell count group were unaffected by adjustment for the CD4% (data not shown).

VL is also an important factor affecting the progression of HIV infection. In the MACS, Mellors et al20 estimated a different risk of long-term progression to AIDS according to a combination of CD4 cell count and VL groups. The Concerted Action on SeroConversion to AIDS and Death in Europe (CASCADE) Collaboration21 analyzed 3226 patients to determine short-term risk at 6 months of progression to AIDS according to CD4 cell count and VL and the risk increased with higher VL for a given CD4 cell count. As in other studies,7,20-22 we observed an increased risk of progression in each CD4 cell count group with a higher VL (see Fig. 2). In addition, an independent effect of VL on progression to AIDS or death was also found after adjusting for other covariates, including CD4 cell count.

Moreover, we found a higher risk of progression to AIDS or death with increased age. This agrees with other observational studies, which found an increased probability of progression in older subjects with the same CD4 cell count and VL.7,21 There are no established gender differences in response to HAART, although some studies reported lower progression to AIDS and death in women.23,24 We found a greater risk of progression in men, although this did not reach statistical significance in the multivariate analysis.

Although it is well known that patients with HIV-HCV coinfection have increased morbidity and mortality,25,26 the question of whether HCV infection affects progression of HIV infection is more controversial. Some authors did not find a higher risk of mortality or AIDS-defining events,27,28 whereas others did find a higher risk of disease progression to AIDS or death in naive patients on HAART,29,30 in specific HCV genotypes,31 or in coinfected patients during the HAART era.32 Interestingly, we found a higher risk (HR = 2.40, 95% CI: 1.65 to 3.49) of disease progression to AIDS or death in HCV-positive patients. Our study had 642 HCV-positive patients from a total of 2035 HIV-infected patients. To our knowledge, the PISCIS Cohort Study is one of the largest studies (also see the article by De Luca et al29) to assess the influence of HCV on the progression of HIV infection. The risk of progression remains even if we account for other variables in the multivariate analysis, including IDU transmission group. A possible interaction effect between both variables was assessed performing separate analyses for the IDU and non-IDU groups, and we found that coinfection by HCV was an independent risk factor for progression to AIDS or death, even among the non-IDU group (data not shown).

Other treatment-related factors, such as HAART regimen or period in which HAART was initiated, could influence prognosis. Although we found a lower risk of progression to AIDS or death in patients who initiated treatment with NNRTI combinations in the univariate analysis, the association disappeared after adjusting for other factors. Conversely, we did find an important association between the risk of progression and the period of HAART initiation. Those patients who initiated treatment between January 2001 and June 2004 had half the risk of progressing to AIDS or death. These results are in accordance with recent studies that have found an increase in survival in HIV-infected patients during the period from 2000 to 200533 and a lower risk for development of AIDS over calendar years.34 Several factors, such as greater efficacy of new antiretroviral drugs, together with simplified dosing and less drug toxicity, which increases adherence, could lead to increased survival in HIV-infected patients treated during the late period.

Back to Top | Article Outline
When to Initiate HAART

In the absence of a randomized clinical trial to answer the question about when to initiate HAART, unadjusted HRs obtained from observational data are biased because of (1) confounding factors associated with early initiation of AIDS and (2) an inappropriate origin for the time scale. In our study, more accurate results for the relative hazards of disease progression were obtained after adjusting the survival curve by adding the lead time and including the unseen events (fast progressors). We found an HR of progression to AIDS of 2.97 in patients who deferred treatment with <200 cells/μL compared with those starting with 200 to 350 cells/μL. A more important finding was that the higher HR of progression to AIDS among patients who delayed initiating HAART until they reached 200 to 350 cells/μL achieved statistical significance compared with those who initiated therapy at >350 cells/μL. In view of these results, and if they could be confirmed by further collaborative studies, it would be advisable to revise the current guidelines that recommend not starting HAART with a CD4 count >350 cells/μL.

Our study has several limitations. First, this is an intention-to-treat study and we do not take into account adherence to treatment. Because this is a limitation for all 3 CD4 cell count strata, however, we do not expect there to be differences in adherence between groups. In addition, other factors related to lower adherence (eg, IDU transmission group, gender, age) were included in the multivariate analysis.

Second, estimations of the lead time were based on data from the MACS on AIDS-free HIV-infected individuals who were followed up during the pre-HAART period. Because our main assumption was that, up to December 1995, therapies did not considerably change the course of the natural history of HIV infection, in the absence of data such as those of the PISCIS Cohort, the use of external estimates was justified. Moreover, estimates of the probability of CD4 cell count transition reported by the MACS were based on patients with <500 cells/μL. Nevertheless, in our study, the lead-time-adjusted HR of patients with 200 to 350 cells/μL was obtained, thus allowing patients with >350 cells/μL to be included in the comparison.

Third, if external data from the pre-HAART period were available, more accurate estimates of progression might be obtained from CD4 cell count transition models according to combinations of different biomarkers (eg, CD4 cell count, VL) and other clinical endpoints (eg, death).

Finally, although clinical trials are the “gold standard” for assessing treatment efficacy, observational studies have provided valuable estimates of treatment effects in the general population using appropriate statistical methodologies.35-37 In this context, we could consider alternative methods that adjust appropriately for time-dependent confounders allowing causal inferences from prevalent cohort data.37,38 Given that these methodologies need a sufficient sample size to obtain stable estimates, however, it would be necessary to pool different cohorts to improve the analysis with regard to the question of when to initiate HAART.

In conclusion, this study shows that, apart from a low CD4 T-cell count and high VL, HCV coinfection is an important determinant of higher HIV disease progression or death, whereas the midterm HAART period was associated with higher survival. Our results reinforce the appropriateness of initiating HAART earlier in asymptomatic HIV-infected patients. Lead-time analysis suggested that the optimal time to start HAART is before the CD4 T-cell count falls to lower than 350 cells/μL. These results provide valuable information for clinical decisions about when to start HAART, particularly now that we have better antiretroviral drugs and more comfortable regimens.

Back to Top | Article Outline

ACKNOWLEDGMENTS

The authors are indebted to Thomas O'Boyle for his assistance with the English version of the manuscript. They are grateful to D. A. Muñoz and S. Cole for their helpful comments and suggestions on the lead-time analysis. They are also grateful to all their patients and the health care providers involved in the PISCIS Cohort.

Back to Top | Article Outline

AUTHOR CONTRIBUTIONS

A. Jaén and A. Esteve conceived the study and wrote the first draft of the report. All authors contributed to the final draft. A. Esteve and A. Montoliu performed the statistical analyses with assistance and data interpretation from A. Jaén. J. M. Miró contributed to data interpretation. J. Casabona conceived the PISCIS Cohort. J. Casabona and A. Jaén were responsible for the scientific and technical coordination of the PISCIS Cohort.

Back to Top | Article Outline

REFERENCES

1. Palella FJ Jr, Delaney KM, Moorman AC, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV Outpatient Study Investigators. N Engl J Med. 1998;338:853-860.

2. Sterling TR, Chaisson RE, Moore RD. HIV-1 RNA, CD4 T-lymphocytes, and clinical response to highly active antiretroviral therapy. AIDS. 2001;15:2251-2257.

3. Ahdieh-Grant L, Yamashita TE, Phair JP, et al. When to initiate highly active antiretroviral therapy: a cohort approach. Am J Epidemiol. 2003;157:738-746.

4. Hogg RS, Yip B, Chan KJ, et al. Rates of disease progression by baseline CD4 cell count and viral load after initiating triple-drug therapy. JAMA. 2001;286:2568-2577.

5. Chan KC, Yip B, Hogg RS, et al. Survival rates after the initiation of antiretroviral therapy stratified by CD4 cell counts in two cohorts in Canada and the United States. AIDS. 2002;16:1693-1695.

6. Kaplan JE, Hanson DL, Cohn DL, et al. When to begin highly active antiretroviral therapy? Evidence supporting initiation of therapy at CD4+ lymphocyte counts <350 cells/μL. Clin Infect Dis. 2003;37:951-958.

7. Egger M, May M, Chene G, et al. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet. 2002;360:119-129.

8. Jacobson LP, Li R, Phair J, et al. Evaluation of the effectiveness of highly active antiretroviral therapy in persons with human immunodeficiency virus using biomarker-based equivalence of disease progression. Am J Epidemiol. 2002;155:760-770.

9. Palella FJ Jr, Deloria-Knoll M, Chmiel JS, et al. Survival benefit of initiating antiretroviral therapy in HIV-infected persons in different CD4+ cell strata. Ann Intern Med. 2003;138:620-626.

10. Phair JP, Mellors JW, Detels R, et al. Virologic and immunologic values allowing safe deferral of antiretroviral therapy. AIDS. 2002;16:2455-2459.

11. Sterling TR, Chaisson RE, Keruly J, et al. Improved outcomes with earlier initiation of highly active antiretroviral therapy among human immunodeficiency virus-infected patients who achieve durable virologic suppression: longer follow-up of an observational cohort study. J Infect Dis. 2003;188:1659-1665.

12. Opravil M, Ledergerber B, Furrer H, et al. Clinical efficacy of early initiation of HAART in patients with asymptomatic HIV infection and CD4 cell count >350 × 10(6)/l. AIDS. 2002;16:1371-1381.

13. Cole SR, Li R, Anastos K, et al. Accounting for leadtime in cohort studies: evaluating when to initiate HIV therapies. Stat Med. 2004;23:3351-3363.

14. Jaen A, Casabona J, Esteve A, et al. Clinical-epidemiological characteristics and antiretroviral treatment trends in a cohort of HIV infected patients. The PISCIS Project. Med Clin (Barc). 2005;124:525-531.

15. Iribarren JA, Labarga P, Rubio R, et al. Spanish GESIDA/national AIDS plan recommendations for antiretroviral therapy in HIV-infected adults (October 2004). Enferm Infecc Microbiol Clin. 2004;22:564-642.

16. US Department of Health and Human Services (DHHS). Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Available at: http://AIDSinfo.nih.gov. Accessed October 10, 2006.

17 Centers for Disease Control and Prevention. 1993 Revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR Recomm Rep. 1992;41(RR-17):1-19.

18. Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York: Wiley; 1987.

19. Moore DM, Hogg RS, Yip B, et al. CD4 percentage is an independent predictor of survival in patients starting antiretroviral therapy with absolute CD4 cell counts between 200 and 350 cells/μL. HIV Med. 2006;7:383-388.

20. Mellors JW, Munoz A, Giorgi JV, et al. Plasma viral load and CD4+ lymphocytes as prognostic markers of HIV-1 infection. Ann Intern Med. 1997;126:946-954.

21. Phillips A, Collaboration CASCADE. Short-term risk of AIDS according to current CD4 cell count and viral load in antiretroviral drug-naive individuals and those treated in the monotherapy era. AIDS. 2004;18:51-58.

22. Thiebaut R, Chene G, Jacqmin-Gadda H, et al. Time-updated CD4+ T-lymphocyte count and HIV RNA as major markers of disease progression in naive HIV-1-infected patients treated with a highly active antiretroviral therapy: the Aquitaine Cohort, 1996-2001. J Acquir Immune Defic Syndr. 2003;33:380-386.

23. Nicastri E, Angeletti C, Palmisano L, et al. Gender differences in clinical progression of HIV-1-infected individuals during long-term highly active antiretroviral therapy. AIDS. 2005;19:577-583.

24. Garcia de la Hera M, Ferreros I, del Amo J, et al. Gender differences in progression to AIDS and death from HIV seroconversion in a cohort of injecting drug users from 1986 to 2001. J Epidemiol Community Health 2004;58:944-950.

25. Martin-Carbonero L, Soriano V, Valencia E, et al. Increasing impact of chronic viral hepatitis on hospital admissions and mortality among HIV-infected patients. AIDS Res Hum Retroviruses. 2001;17:1467-1471.

26. Graham CS, Baden LR, Yu E, et al. Influence of human immunodeficiency virus infection on the course of hepatitis C virus infection: a meta-analysis. Clin Infect Dis. 2001;33:562-569.

27. Tedaldi EM, Baker RK, Moorman AC, et al. Influence of coinfection with hepatitis C virus on morbidity and mortality due to human immunodeficiency virus infection in the era of highly active antiretroviral therapy. Clin Infect Dis. 2003;36:363-367.

28. Rockstroh JK, Mocroft A, Soriano V, et al. Influence of hepatitis C virus infection on HIV-1 disease progression and response to highly active antiretroviral therapy. J Infect Dis. 2005;192:992-1002.

29. De Luca A, Bugarini R, Lepri AC, et al. Coinfection with hepatitis viruses and outcome of initial antiretroviral regimens in previously naive HIV-infected subjects. Arch Intern Med. 2002;162:2125-2132.

30. Greub G, Ledergerber B, Battegay M, et al. Clinical progression, survival, and immune recovery during antiretroviral therapy in patients with HIV-1 and hepatitis C virus coinfection: the Swiss HIV Cohort Study. Lancet. 2000;356:1800-1805.

31. Yoo TW, Donfield S, Lail A, et al. Hemophilia Growth and Development Study. Effect of hepatitis C virus (HCV) genotype on HCV and HIV-1 disease. J Infect Dis. 2005;191:4-10.

32. Dorrucci M, Valdarchi C, Suligoi B, et al. The effect of hepatitis C on progression to AIDS before and after highly active antiretroviral therapy. AIDS. 2004;18:2313-2318.

33. Lohse N, Hansen A, Pedersen G, et al. Survival of persons with and without HIV infection in Denmark, 1995-2005. Ann Intern Med. 2007;146:87-95.

34. The Antiretroviral Therapy (ART) Cohort Collaboration. HIV treatment response and prognosis in Europe and North America in the first decade of highly active antiretroviral therapy: a collaborative analysis. Lancet. 2006;368:451-458.

35. Detels R, Munoz A, McFarlane G, et al. Effectiveness of potent antiretroviral therapy on time to AIDS and death in men with known HIV infection duration. Multicenter AIDS Cohort Study Investigators. JAMA. 1998;280:1497-1503.

36. Tarwater PM, Mellors J, Gore ME, et al. Methods to assess population effectiveness of therapies in human immunodeficiency virus incident and prevalent cohorts. Am J Epidemiol. 2001;154:675-681.

37. Cole SR, Hernan MA, Robins JM, et al. Effect of highly active antiretroviral therapy on time to acquired immunodeficiency syndrome or death using marginal structural models. Am J Epidemiol. 2003;158:687-694.

38. Sterne JAC, Hernan MA, Ledergerber B, et al. Long-term effectiveness of potent antiretroviral therapy in preventing AIDS and death: a prospective cohort study. Lancet. 2005;366:378-384.

Back to Top | Article Outline
APPENDIX
PISCIS Study Group

Steering Committee: J. Casabona, A. Esteve, A. Jaén, and M. Granell from the Centre d'Estudis Epidemiològics sobre ITS/VIH/SIDA de Catalunya, Badalona, Spain (CEEISCAT); J. M. Gatell and J. M. Miró from Hospital Clínic, Barcelona; J. Murillas and S. Riera from Hospital Son Dureta, Palma de Mallorca; D. Podzamcer and E. Ferrer from Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona; B. Clotet and C. Tural from Hospital Universitari Germans Trias i Pujol, Badalona; F. Segura and G. Navarro from Hospital Parc Taulí, Sabadell; L. Force from Hospital Mataró, Barcelona; J. Vilaró from Hospital General Vic, Vic; A. Masabeu from Hospital Palamós, Girona; I. García from Hospital Creu Roja, Hospitalet de Llobregat, Barcelona; and J. Altés from Hospital Alt Penedès, Vilafranca, Barcelona.

Data Manager and Computer Support: E. Puchol, Y. Alvaro, and A. Montoliu (CEEISCAT, Badalona); and Modesto Sánchez (Hospital Clínic-IDIBAPS, Universitat de Barcelona, Barcelona)

Clinical Staff: L. Zamora, F. Aguero, O. Sued, J. L. Blanco, F. García-Alcaide, E. Martínez, and J. Mallolas (Hospital Clínic-IDIBAPS, Universitat de Barcelona, Barcelona); G. Sirera, J. Romeu, A. Bonjoch, A. Jou, A. Ballesteros, E. Negredo, D. Fuster, and J. C. Martínez (Hospital Universitari Germans Trias i Pujol, Universitat Autónoma de Barcelona, Badalona); M. Santin, M. J. Barbera, M. Olmo, P. Robres, F. Bolao, J. Carratala, C. Cabellos, and C. Peña (Hospital de Bellvitge-IDIBELL, Universitat de Barcelona, Hospitalet de Llobregat, Barcelona); P. Barrufet (Hospital de Mataró, Barcelona); M. Guadarrama (Hospital Alt Penedès, Vilafranca, Barcelona); and M. J. Amengual, M. Sala, M. Cervantes, and E. Penelo (Corporació Sanitària Parc Taulí, Sabadell)

Cited By:

This article has been cited 17 time(s).

AIDS Research and Therapy
Clinical, demographic and laboratory parameters at HAART initiation associated with decreased post-HAART survival in a US military prospective HIV cohort
Lifson, AR; Krantz, EM; Grambsch, PL; Macalino, GE; Crum-Cianflone, NF; Ganesan, A; Okulicz, JF; Eaton, A; Powers, JH; Eberly, LE; Agan, BK
AIDS Research and Therapy, 9(): -.
ARTN 4
CrossRef
International Journal of Std & AIDS
Initiating antiretroviral treatment in a resource-constrained setting: does clinical staging effectively identify patients in need?
Torpey, K; Lartey, M; Amenyah, R; Addo, NA; Obeng-Baah, J; Rahman, Y; Suzuki, C; Mukadi, YD; Colebunders, R
International Journal of Std & AIDS, 20(6): 395-398.
10.1258/ijsa.2008.008333
CrossRef
Lancet
Timing of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studies
Sterne, JAC; May, M; Costagliola, D; de Wolf, F; Phillips, AN; Harris, R; Funk, MJ; Geskus, RB; Gill, J; Dabis, F; Miro, JM; Justice, AC; Ledergerber, B; Fatkenheuer, G; Hogg, RS; Monforte, AD; Saag, M; Smith, C; Staszewski, S; Egger, M; Cole, SR
Lancet, 373(): 1352-1363.
10.1016/S0140-6736(09)60612-7
CrossRef
Enfermedades Infecciosas Y Microbiologia Clinica
Recommendations from the GESIDA/Spanish AIDS Plan regarding antiretroviral treatment in adults with human immunodeficiency virus infection (update February 2009)
[Anon]
Enfermedades Infecciosas Y Microbiologia Clinica, 27(4): 222-235.
10.1016/j.eimc.2008.11.002
CrossRef
Infection
Surgical Site Infections in HIV-infected Patients: Results from an Italian Prospective Multicenter Observational Study
Drapeau, CMJ; Pan, A; Bellacosa, C; Cassola, G; Crisalli, MP; De Gennaro, M; Di Cesare, S; Dodi, F; Gattuso, G; Irato, L; Maggi, P; Pantaleoni, M; Piselli, P; Soavi, L; Rastrelli, E; Tacconelli, E; Petrosillo, N
Infection, 37(5): 455-460.
10.1007/s15010-009-8225-1
CrossRef
New England Journal of Medicine
Effect of Early versus Deferred Antiretroviral Therapy for HIV on Survival
Kitahata, MM; Gange, SJ; Abraham, AG; Merriman, B; Saag, MS; Justice, AC; Hogg, RS; Deeks, SG; Eron, JJ; Brooks, JT; Rourke, SB; Gill, MJ; Bosch, RJ; Martin, JN; Klein, MB; Jacobson, LP; Rodriguez, B; Sterling, TR; Kirk, GD; Napravnik, S; Rachlis, AR; Calzavara, LM; Horberg, MA; Silverberg, MJ; Gebo, KA; Goedert, JJ; Benson, CA; Collier, AC; Van Rompaey, SE; Crane, HM; McKaig, RG; Lau, B; Freeman, AM; Moore, RD
New England Journal of Medicine, 360(): 1815-1826.
10.1056/NEJMoa0807252
CrossRef
Clinical Infectious Diseases
Meta-Analysis: Increased Mortality Associated with Hepatitis C in HIV-Infected Persons Is Unrelated to HIV Disease Progression
Chen, TY; Ding, EL; Seage, GR; Kim, AY
Clinical Infectious Diseases, 49(): 1605-1615.
10.1086/644771
CrossRef
Sexually Transmitted Infections
Recently acquired HIV infection in Spain (2003-2005): introduction of the serological testing algorithm for recent HIV seroconversion
Romero, A; Gonzalez, V; Granell, M; Matas, L; Esteve, A; Martro, E; Rodrigo, I; Pumarola, T; Miro, JM; Casanova, A; Ferrer, E; Tural, C; del Romero, J; Rodriguez, C; Caballero, E; Ribera, E; Casabona, J
Sexually Transmitted Infections, 85(2): 106-110.
10.1136/sti.2008.031864
CrossRef
Jama-Journal of the American Medical Association
Antiretroviral treatment of adult HIV infection - 2008 recommendations of the International AIDS Society USA panel
Hammer, SM; Eron, JJ; Reiss, P; Schooley, RT; Thompson, MA; Walmsley, S; Cahn, P; Fischl, MA; Gatell, JM; Hirsch, MS; Jacobsen, DM; Montaner, JSG; Richman, DD; Yeni, PG; Volberding, PA
Jama-Journal of the American Medical Association, 300(5): 555-570.

Clinical Infectious Diseases
Coinfection with Hepatitis C Virus and HIV: More than Double Trouble
Piroth, L
Clinical Infectious Diseases, 49(4): 623-625.
10.1086/603558
CrossRef
Journal of Virology
Antiretroviral Therapy in the Clinic
Tsibris, AMN; Hirsch, MS
Journal of Virology, 84(): 5458-5464.
10.1128/JVI.02524-09
CrossRef
Clinical Microbiology and Infection
Optimal timing for initiation of highly active antiretroviral therapy in treatment-naive human immunodeficiency virus-1-infected individuals presenting with AIDS-defining diseases: the experience of the PISCIS Cohort
Manzardo, C; Esteve, A; Ortega, N; Podzamczer, D; Murillas, J; Segura, F; Force, L; Tural, C; Vilaro, J; Masabeu, A; Garcia, I; Guadarrama, M; Ferrer, E; Riera, M; Navarro, G; Clotet, B; Gatell, JM; Casabona, J; Miro, JM
Clinical Microbiology and Infection, 19(7): 646-653.
10.1111/j.1469-0691.2012.03991.x
CrossRef
Bmc Infectious Diseases
Incidence and determinants of new AIDS-defining illnesses after HAART initiation in a Senegalese cohort
De Beaudrap, P; Etard, JF; Diouf, A; Ndiaye, I; Ndeye, GFN; Sow, PS; Ndeye, KCT; Ecochard, R; Delaporte, E
Bmc Infectious Diseases, 10(): -.
ARTN 179
CrossRef
Current Opinion in Infectious Diseases
Should HIV therapy be started at a CD4 cell count above 350 cells/μl in asymptomatic HIV-1-infected patients?
Sabin, CA; Phillips, AN
Current Opinion in Infectious Diseases, 22(2): 191-197.
10.1097/QCO.0b013e328326cd34
PDF (119) | CrossRef
AIDS
Prognosis of patients treated with cART from 36 months after initiation, according to current and previous CD4 cell count and plasma HIV-1 RNA measurements
The antiretroviral therapy cohort collaboration (ART-CC),
AIDS, 23(16): 2199-2208.
10.1097/QAD.0b013e3283305a00
PDF (490) | CrossRef
Current Opinion in Infectious Diseases
Cohort studies: to what extent can they inform treatment guidelines?
Sabin, CA
Current Opinion in Infectious Diseases, 23(1): 15-20.
10.1097/QCO.0b013e32833521b4
PDF (318) | CrossRef
AIDS
The effect of combined antiretroviral therapy on the overall mortality of HIV-infected individuals
The HIV-CAUSAL Collaboration,
AIDS, 24(1): 123-137.
10.1097/QAD.0b013e3283324283
PDF (638) | CrossRef
Back to Top | Article Outline
Keywords:

CD4 T-cell count; hepatitis C virus; highly active antiretroviral therapy; HIV disease progression; lead time; PISCIS cohort; when to start highly active antiretroviral therapy

© 2008 Lippincott Williams & Wilkins, Inc.

Login

Search for Similar Articles
You may search for similar articles that contain these same keywords or you may modify the keyword list to augment your search.