The possible differences in the clinical, immunological and virological features of HIV infection in men and women is a major point of concern. A number of articles dealing with this topic have been published, both before and after the introduction of HAART, with discrepant results as underscored in several reviews [1–5], varying from no differences between sexes to more favourable profiles for men or for women. To add further complexity, some authors found differences or not within the same series depending on the subgroup analysed [6–9] or reported variations over time of the initial pattern [1,10].
There are many important factors that could account for these discrepant results. Among them, studies differed greatly with regard to sample size, sex distribution, methodology, design, mode of collection of data, outcome variable studied, risk factors for HIV infection, access to medical care, length of follow-up, units of measurement and viral load assays, stages of HIV infection, ethnicity, geographic settings, demographics, proportion of drug-naive and drug-experienced patients, and treatment or not with HAART. Therefore, despite the many articles published on this topic, the issue has remained largely unsolved. Consequently, large series evaluating the full spectrum of HIV infection with similar characteristics in important aspects such as access to medical care and antiretroviral regimens are needed to elucidate the eventual differences that could exist between the sexes.
The aim of this study was to evaluate the comparative clinical, virological and immunological parameters of men and women, both at baseline and during HAART, in a well-characterized, nationwide, large database of patients collected prospectively, all of whom initiated a very similar, nelfinavir-based antiretroviral regimen at the time of entry into the study.
The data for this prospective, observational, multicentre, nationwide study were obtained from the Grupo Español para el Estudio Multifactorial de la Adherencia (GEEMA) cohort. This comprised a large number of non-selected patients recruited from 69 hospitals in Spain who had initiated treatment with nelfinavir, in combination with at least two other antiretroviral drugs, from January 1998 to December 1999. To be included in the present study, patients' records had to fulfil all of three criteria: (1) specification of the patients' sex; (2) a baseline determination, just before the onset of nelfinavir treatment, and at least one other measurement for both CD4 cell counts and viral load during follow-up; and (3) specification of the patient's drug history, whether naive or experienced for HAART. As the response to HAART was expected to be different in naive and experienced patients, these two groups were analysed separately.
The data collected included sociodemographic information, clinical parameters, treatment, adherence, development of significant side effects (but not the specific type of adverse effect), CD4 cell counts and viral load. All information was collected on a standardized form by each of the participating centres. All forms were gathered at each time point and were sent to a single institution to be introduced into a computer database. Patients were evaluated from a clinical and laboratory perspective at baseline and at 3, 6 and 12 months from starting nelfinavir therapy. CD4 cell counts were measured by flow cytometry and viral load by branched DNA and RNA polymerase chain reaction assays. The limit of detectability of viral load was 200 copies/ml. Data were analysed by intention-to-continue treatment, ignoring eventual changes in treatment during follow-up.
Adherence was estimated at month 3, 6 and 12 using a simplified medication adherence questionnaire, which was composed of six qualitative and quantitative items relative to the patients' intake of medication up to 3 months before the interview . According to that questionnaire, which was validated through its comparison with electronic adherence monitoring and virological outcomes, the patients were classified as adherents or non-adherents. It should be noted that medical care, analytical studies and antiretroviral therapy are provided free of charge to all HIV-infected patients in Spain. Therefore the reasons for not taking antiretroviral therapy are medical criteria or patient's refusal.
Categorical variables (sex, mode of acquisition of HIV infection, prior diagnosis of AIDS, undetectable viral load, viral load rebound, clinical progression/death, adverse events, prior antiretroviral or protease inhibitor therapy, use of nucleoside reverse transcriptase inhibitors and adherence) were compared using the χ2 test with the Yates correction for continuity. The comparison of continuous variables between two groups was assessed with the t-test or Mann–Whitney U test, as appropriate. The comparisons of sequential measurements of viral load, CD4 cell counts and rates of undetectable viral load were carried out with the paired t-test, the Wilcoxon matched-pairs signed-ranks test and the McNemar test, respectively. Stepwise multiple linear regressions were used to evaluate the independent association of different variables with CD4 cell counts and viral load at baseline and at the end of follow-up period. A Cox proportional hazards model was used to define the predictive value of baseline parameters on clinical progression or death during follow-up. A general linear model repeated measures procedure was performed to evaluate the comparative effects of HAART over time on the CD4 cell counts and viral load of both sexes. SPSS version 13.0 (SPSS, Chicago, Illinois, USA) was used for the statistical analysis. P < 0.05 for a two-sided test was considered to be statistically significant.
The study group comprised 2620 patients, 71.9% of whom were men. Regarding previous HAART, 484 patients (18.5%) had no previous exposure and 2136 (81.5%) were experienced. Table 1 shows the baseline characteristics of the patients. Men were significantly older than the women, had lower CD4 cell counts and higher quantitative viral load, and they were more likely to have acquired the infection through injection drug use, to be in worse clinical and immunological stages [Centers for Disease Control and Prevention (CDC) staging] at the study inclusion, and to have received a prior diagnosis of AIDS. However, there were no significant differences between sexes regarding the rate of undetectable viral load, the proportion of drug-naive patients and the median time of prior antiretroviral therapy or prior exposure to protease inhibitors. The proportion of patients who for any reason (exclusion during the study, change of hospital, lack of laboratory determinations, death, etc.) did not have the 12 month clinical or laboratory evaluation was similar in men and women (29.5% versus 27.2%, respectively; P = 0.3). The characteristics of these patients were similar to those of patients who completed the 12 month evaluation for age, sex, risk factors, prior treatment, CDC stages, baseline CD4 cell counts and viral load, so there would not be significant bias in the final results owing to the missing cases. The proportion of patients who only received nucleoside reverse transcriptase inhibitors in addition to nelfinavir was also similar in men and women (75.9% versus 78.8%, respectively; P = 0.1).
Figure 1 shows the course of CD4 cell counts in patients naive and experienced for antiretroviral drugs. At baseline, CD4 cell counts were higher in women than in men: 14.5% higher in drug-naive women and 19.9% higher in drug-experienced women. CD4 cell counts increased throughout the follow-up period, although the highest increments were observed within the initial 3 months of therapy, particularly in drug-naive patients. The comparison of the course over time by the general linear model revealed that the response in CD4 cell count to HAART was higher in drug-naive women than in drug-naive men (P = 0.01). In drug-experienced patients, these differences were less marked (P = 0.06), although the slopes were also divergent during the first 3 months of treatment (P = 0.009).
Figure 2a depicts the rate of viral suppression over time according to sex. The course was parallel in both sexes, with two different patterns depending on the previous drug status of the patients: drug-experienced patients did not respond beyond the third month whereas additional responses were observed in drug-naive patients up to the sixth month, reaching a plateau thereafter. In fact, the obvious lower rate of viral suppression at baseline in drug-naive compared with drug-experienced patients (P < 0.001) was fully compensated at month 3 (P = 0.4), and significantly reversed at 6 and 12 months (P < 0.001 for each). Figure 2b depicts the course of viral load. Viral load at baseline was higher in men than in women: 25.2% higher in drug-naive subjects (2.0% if using a log base) and 73.1% higher (6.7% if using a log base) in the drug-experienced group. Similarly to the findings of viral load suppression, the highest responses were observed in drug-naive patients, who extended their virological response up to the sixth month. The curves of changes in men and women over time were also parallel, without differences in the slope between the sexes as a consequence of HAART in drug-naive (P = 0.6) and drug-experienced (P = 0.3) patients according to the general linear model. However, significant differences were observed only during the initial 3 months of therapy when all patients were considered altogether (P = 0.04). Men had higher viral load levels than women at all time points, which reached statistical significance only in experienced patients owing to the considerably lower sample size of drug-naive patients.
Table 2 shows the course over time of CD4 cell counts (assessed by the Wilcoxon matched-pairs signed-ranks test), viral suppression (McNemar test) and viral load (paired t-test) of each patient compared with himself or herself. Regarding viral load rebound after viral suppression, there were no significant differences at any time point in men compared with women in the patients as a whole (34.6% versus 33.6%; P = 0.8), in drug-experienced patients (38.4% versus 36.5%; P = 0.6) or in drug-naive patients (20.0% versus 21.6%, P = 0.9). From a clinical standpoint, men had higher rates of clinical progression or death than women among the patients as a whole (11.3% versus 7.1%; P = 0.008), and among drug-experienced (11.7% versus 7.4%; P = 0.01) and drug-naive (9.4% versus 5.7%; P = 0.3) patients. At the time of development of the event (clinical progression or death), women had lower CD4 cell counts (92.5 versus 147.5 cells/μl; P = 0.1) and similar viral load (3.96 versus 4.13 log copies/ml; P = 0.7) than men, considering the last measurement available. There was a non-significant trend towards a higher frequency of adverse events severe enough to change nelfinavir treatment in women compared with men (9.9% versus 7.9%, P = 0.09).
There were also no significant differences between genders in adherence, evaluated as a categorical variable, at any time point (P = 0.1 to P = 0.9), or within each of the two main risk factors for acquisition of the infection: injection drug use (P = 0.4) and homo/heterosexual route (P = 0.6). Regarding age, patients younger than 35 years had higher CD4 cell counts than older patients in men (280 versus 247 cells/μl; P < 0.001) and in women (321 versus 275 cells/μl; P = 0.06).
Table 3 shows the results of stepwise multivariate analyses that were carried out to evaluate the association of diverse baseline parameters (age, sex, mode of acquisition of HIV infection, history of previous HAART, immunological CDC stage, viral load and CD4 cell counts) with immunological and virological outcome variables. A Cox proportional hazards model using the same baseline parameters, as well as adherence as a time-dependent covariate, revealed that, after adjusting for the other variables, the significant predictors of clinical progression or death during follow up were CD4 cell count [hazard ratio (HR), 0.997; 95% confidence interval (CI), 0.995–0.998; P < 0.001], male sex (HR, 1.82; 95% CI, 1.14–2.92; P = 0.01) and age (HR, 0.974; 95% CI, 0.948–1.000; P = 0.049).
Our findings suggest that HIV-infected women had better clinical, immunological and virological parameters than men at entry to the study and during treatment. The absolute differences in immunological and virological parameters at each time point, although consistent, were minor in drug-naive patients and did not reach statistical significance because of the low sample size in this group. By comparison, the differences were more marked in drug-experienced patients, particularly in the CD4 cell responses. The effect of HAART, as measured by the slope of the change in CD4 cell count with time, was more marked in drug-naive women than in drug-naive men, as well as during the initial 3 months of therapy in drug-experienced patients. These findings indicate that women obtain additional benefits from HAART over men during the initial phases of treatment. Regarding viral load responses, the slope over time was relatively similar in both sexes.
Multivariate analysis revealed that, on average and after adjustment for other baseline variables, approximately one-half of the baseline and final CD4 cell counts can be predicted by the patient's immunological CDC category and initial CD4 cell counts, respectively. However, the power to predict viral load, although significant, was considerably poorer. Sex had a modest contribution in the prediction of virological and immunological parameters, but was more marked in the prediction of clinical outcome.
We found the highest responses in both viral load and CD4 cell counts during the first 3 months of therapy in both sexes, with higher responses and more marked slopes in drug-naive than in experienced patients. This difference between drug-naive and drug- experienced status was particularly remarkable, and clinically meaningful, in the viral load results, as the average drug-experienced patient did not improve beyond the third month of therapy, whereas drug-naive patients extended their virological response up to the sixth month.
There are remarkably discrepant results in the literature about the course of immunological, virological and clinical parameters according to sex. Some studies have found higher CD4 cell counts in women [8,12–15]; other found higher CD4 cell counts in men [9,16,17], and still others found similar values in both sexes [18–20]. It has also been reported that there are greater declines in CD4 cell counts in women  or no differences with men , as well as greater increases in CD4 cell counts following HAART in women  or no differences with men [13,14,22]. We found higher CD4 cell counts at baseline in women and at each of the time points in drug-naive and, particularly, in drug-experienced patients, findings that are in agreement with the higher CD4 cell counts observed in HIV-seronegative women compared with seronegative men [23,24].
Similar discrepancies have been described in the virological parameters. Some studies reported lower viral load in females [8–10,12,13,20,25], whereas others did not find sex differences [16–19,26]. Regarding the virological response to HAART, some authors found similar responses in men and women [8,13,14]; others found quicker and more sustained responses in women , and higher rates of viral rebound in women, although related to poorer adherence to HAART . We found similar viral load values in drug-naive patients of both sexes at presentation but, shortly after the onset of HAART, there was a trend towards lower viral load in women, which was most evident in the fully drug-experienced patients.
At first presentation seeking medical care as a consequence of HIV infection, woman have been reported to have similar , better [8,13] and poorer  clinical parameters compared with men in various studies. Similarly, the rate of clinical progression or death with or without HAART has been reported to be equivalent [3,7,13,14,20,25,28–30], higher [6,31] or lower [8,16,21,32,33] in females compared with males. In addition to the well-known, strongest predictive value of baseline CD4 cell count for progression , we found poorer clinical outcomes in men than in women after adjustment for other variables, in concordance with the poorer viroimmunological parameters of the former, both at baseline and during the follow-up period.
Some authors have reported that women progress to AIDS or death at appreciably higher CD4 cell counts  or lower viral load  than men, suggesting that the current treatment guidelines should be modified accordingly. Our results do not support these findings, because women had lower CD4 cell counts than men at the time of development of clinical progression or death. Remarkably, women had consistently higher CD4 cell counts than men at each time point in multiple comparisons and subgroup analyses; therefore, the same pattern would be expected in the subgroup of patients who progressed or died. However, we found the opposite trend in this particular subgroup: women had lower CD4 cell counts than men at the time of clinical progression or death. Although there was a trend towards statistical significance, it did not reach the P < 0.05 level, probably because the number of patients who progressed was small. However, the fact that CD4 cell counts in men did not simply exceed but were almost double those of women in the subgroup of patients who progressed (as opposed to the findings in other subgroups) suggests that there is a strong effect in this direction regardless of the statistical non-significance. Regarding viral load, we also found that women had somewhat lower viral load than men, but the difference [0.17 log copies/ml (4.3% lower expressed as log and 48.6% expressed as copies/ml)] was far from statistical significance (P = 0.7). In this regard, caution is required in interpreting virological parameters among different studies, as the results of statistical tests and, especially, the ratios among groups differ greatly depending on whether the units of measurement are expressed as copies/millilitre or as their logarithmic transformation.
We found a trend towards a higher rate of adverse effects in women compared with men. Other authors have reported similar findings with diverse antiretroviral regimens [4,22,31,33,35–37], which have been explained in terms of higher exposure to these drugs in women  or different expression and activities of drug transporters and metabolizing enzymes [4,35]. In fact, women seem to reach higher plasma concentrations with a number of antiretroviral drugs compared with men [4,36]. Consequently, it could be speculated that the superior results, as well as toxicity, observed in women in our series could be partially a result of higher drug exposure, because of their lower weight and/or pharmacokinetic characteristics. Regarding adherence to therapy, some studies [27,38,39], but not others [37,40], reported lower degrees of adherence in women. We did not find differences between sexes and so excluded a significant role for adherence in the different viroimmunological outcomes of men and women.
Our study has several advantages over others that would support the validity of our results. First, the influence of ethnic or racial factors on the results [5,9,24,41,42] would be minimal, as approximately 90% of the patients were white individuals from Spain. Second, patients were recruited from all the provinces of our country and the number of patients studied was very high, constituting one of the largest series on this topic published to date. Consequently, eventual biases that may occur in studies with a limited sample size from a single institution or reduced geographic area were minimized, and the results obtained reflect the real situation across Spain. Third, our study population was quite homogeneous for antiretroviral therapy, as the backbone of the antiretroviral regimen was the same for all patients: nelfinavir, in the vast majority combined only with two nucleoside reverse transcriptase inhibitors. In fact, to our knowledge, this is the first large report on this topic in which the antiretroviral treatment was reasonably homogeneous. In addition, patients were included at a time when the standard of care was to treat all patients regardless of their clinical or viroimmunological parameters, allowing the evaluation of the full spectrum of the disease. Another valuable characteristic of our study was that data were recorded prospectively rather than retrospective analysis of data not recorded systematically or homogeneously, as was the case in other large studies. Moreover, we analysed drug-naive and drug-experienced patients separately, because their response to HAART is different; this avoided the potential for misleading results that would occur in studies that mixed such patients. Finally, the free availability of medical care and antiretroviral drugs for all HIV-infected patients in our country prevents eventual biases derived from potentially poorer access to treatment or medical care for women, as has been reported in other countries [4,5,14,42–44]. In this regard, sex inequalities in the access to medical care and treatment for HIV-infected patients do not seem to be relevant in our country according to a large review on this topic . In fact, both the baseline and follow-up clinical and viroimmunological parameters were more favourable in women than in men in our study, an unexpected finding if such an imbalance had existed.
Limitations of our study include potential mistakes in the recording of information or missing data, both aspects common in large studies. However, these mistakes would have been evenly distributed between both sexes, minimizing their possible impact on the results. Another limitation is the different methods used for the determination of viral load. Nevertheless, the use of different assays has been found to be appropriate for application in multicentre studies . In addition, this shortcoming does not affect the immunological and clinical endpoints, and, once again, it would have involved male and female patients equally and, consequently, the results would not have changed. If our findings are extrapolated to other countries, then consideration should be given to the possible influence of race, ethnic diversity and unequal access to medical care between sexes. Also, current potent antiretroviral regimens could yield somewhat different responses than those observed in our study, although the differences between men and women would expect to be maintained. Finally, the limited follow-up period of our study does not allow the evaluation of possible variations in the immunological, virological or clinical parameters that could occur over the long-term, although this period was large enough to detect differences in clinical progression between sexes.
We conclude that HIV-infected women have more favourable profiles at any time point than men from a clinical, immunological and virological perspective, particularly in drug-experienced patients, which seems to be related to better conditions at presentation as well as to stronger immunological responses during the initial phases of treatment. Multivariate analyses also indicated that sex has a small, although significant, influence on the clinical, and viroimmunological outcomes of the patients. The highest responses in CD4 cells and viral load are observed during the first 3 months of therapy, especially in drug-naive patients. Beyond that point, no further virological benefit is expected in the average drug-experienced patient, although drug-naive patients may extend the response up to the sixth month.
Sponsorship: The GEEMA study was partially funded by Roche Farma, Spain, in their organizational aspects. The sponsor did not have any role in the study design, in the analysis or interpretation of data, in the writing of the report or in the decision to submit the paper for publication.
Investigators of the GEEMA: Elisa Martínez-Alfaro (Albacete); Francisco Pasquau, José M. Cuadrado (Alicante); Luis Caminal, M. José Tuya, M. Luisa García-Alcalde, Teresa Vázquez, Victor Carcaba (Asturias); Daniel Podzamczer, David Dalmau, Enric Pedrol, Ester Dorca, Hernando Knobel, Isabel Gracia, Isabel Ruiz Camps, Jordi de Otero, Josep Vilaró, Luis Force, Manuel Cervantes, Pere Domingo (Barcelona); Juan F. Lorenzo (Burgos); Alberto Terrón, Antonio Vergara, Eugenio Perez (Cádiz); Jordi Usou (Castellón); José M. Kindelan (Córdoba); Ana Mariño, Elena Losada, Javier Juega (La Coruña); Paloma Geijo (Cuenca); Joan Colomer, Josep Cucurull (Gerona); Manuel Rodríguez-Zapata (Guadalajara); José A. Iribarren (Guipúzcoa); Ignacio Suárez (Huelva); Ramón Canet (Ibiza); José L. Mostaza (León); M. José Löpez-Alvarez (Lugo); Alberto Arranz, Carlos Barros, José L. Casado, Juan González, M. Victoria Gordillo, Teodoro Martin, Victor Roca (Madrid); José M. Antunez, Manuel Marquez (Málaga); Eduardo Rodríguez de Castro (Menorca); Alfredo Cano, Carlos Galera, José A. Garcia-Henarejos (Murcia); Raúl Rodríguez Pérez (Orense); Antonio Ocampo, Luis Morano, Manuel Camba, Rafael Ojea, Ricardo Rodríguez-Real (Pontevedra); Carmen Fariñas (Santander); Eva León, Miguel A. Colmenero, (Seville); Antonio Delegido, Ismael Piñas Forcadell, José J. Paraire (Tarragona); Fernando Cuadra, Fernando Marcos (Toledo); Carlos Tornero, José López-Aldeguer (Valencia); Joseba Portu (Vitoria); Julio Collazos (Vizcaya).
1. Gilad J, Walfisch A, Borer A, Schlaeffer F. Gender differences and sex-specific manifestations associated with human immunodeficiency virus infection in women. Eur J Obstet Gynecol Reprod Biol 2003; 109:199–205.
2. Napravnik S, Poole C, Thomas JC, Eron JJ Jr. Gender difference in HIV RNA levels: a meta-analysis of published studies. J Acquir Immune Defic Syndr 2002; 31:11–19.
3. Suligoi B. The natural history of human immunodeficiency virus infection among women as compared with men. Sex Transm Dis 1997; 24:77–83.
4. Umeh OC, Currier JS. Sex Differences in HIV: natural history, pharmacokinetics, and drug toxicity. Curr Infect Dis Rep 2005; 7:73–78.
5. Hessol NA, Palacio H. Gender, ethnicity and transmission category variation in HIV disease progression. AIDS 1996; 10(Suppl A):S69–S74.
6. Lemp GF, Hirozawa AM, Cohen JB, Derish PA, McKinney KC, Hernandez SR. Survival for women and men with AIDS. J Infect Dis 1992; 166:74–79.
7. Schmid M, Twisselmann W, Jacquat BJ, Ledergerber B, Battegay M, Egger M. Sex differences in disease course: analysis of the Swiss HIV cohort study. Schweiz Med Wochenschr 1996; 126:2234–2236.
8. Nicastri E, Angeletti C, Palmisano L, Sarmati L, Chiesi A, Geraci A, et al
. Gender differences in clinical progression of HIV-1-infected individuals during long-term highly active antiretroviral therapy. AIDS 2005; 19:577–583.
9. Anastos K, Gange SJ, Lau B, Weiser B, Detels R, Giorgi JV, et al
. Association of race and gender with HIV-1 RNA levels and immunologic progression. J Acquir Immune Defic Syndr 2000; 24:218–226.
10. Sterling TR, Lyles CM, Vlahov D, Astemborski J, Margolick JB, Quinn TC. Sex differences in longitudinal human immunodeficiency virus type 1 RNA levels among seroconverters. J Infect Dis 1999; 180:666–672.
11. Knobel H, Alonso J, Casado JL, Collazos J, González J, Ruiz I, et al
. Validation of a simplified medication adherence questionnaire in a large cohort of HIV-infected patients: the GEEMA study. AIDS 2002; 16:605–613.
12. Loupa CV, Rodriguez B, McComsey G, Gripshover B, Salata RA, Valdez H, et al
. Gender differences in human immunodeficiency virus (HIV) RNA and CD4 cell counts among new entrants to HIV care. Clin Microbiol Infect 2006; 12:389–391.
13. Moore AL, Kirk O, Johnson AM, Katlama C, Blaxhult A, Dietrich M, et al
. Virologic, immunologic, and clinical response to highly active antiretroviral therapy: the gender issue revisited. J Acquir Immune Defic Syndr 2003; 32:452–461.
14. Mocroft A, Gill MJ, Davidson W, Phillips AN. Are there gender differences in starting protease inhibitors, HAART, and disease progression despite equal access to care? J Acquir Immune Defic Syndr 2000; 24:475–482.
15. Delmas MC, Jadand C, De Vincenzi I, Deveau C, Persoz A, Sobel A, et al
. Gender difference in CD4+ cell counts persist after HIV-1 infection. SEROCO Study Group. AIDS 1997; 11:1071–1073.
16. Moore AL, Sabin CA, Johnson MA, Phillips AN. Gender and clinical outcomes after starting highly active antiretroviral treatment: a cohort study. J Acquir Immune Defic Syndr 2002; 29:197–202.
17. Moore AL, Mocroft A, Madge S, Devereux H, Wilson D, Phillips AN, et al
. Gender differences in virologic response to treatment in an HIV-positive population: a cohort study. J Acquir Immune Defic Syndr 2001; 26:159–163.
18. Finkel DG, John G, Holland B, Slim J, Smith SM. Women have a greater immunological response to effective virological HIV-1 therapy. AIDS 2003; 17:2009–2011.
19. Savès M, Morlat P, Chêne G, Dumon B, Peuchant E. Sex differences in HIV-1 viral load and TNF-alpha plasmatic level? AIDS 1999; 13:1414–1415.
20. Sterling TR, Vlahov D, Astemborski J, Hoover DR, Margolick JB, Quinn TC. Initial plasma HIV-1 RNA levels and progression to AIDS in women and men. N Engl J Med 2001; 344:720–725.
21. Prins M, Robertson JR, Brettle RP, Aguado IH, Broers B, Boufassa F, et al
. Do gender differences in CD4 cell counts matter? AIDS 1999; 13:2361–2364.
22. Clark RA, Squires KE. Gender-specific considerations in the antiretroviral management of HIV-infected women. Expert Rev Anti-infect Ther 2005; 3:213–227.
23. Uppal SS, Verma S, Dhot PS. Normal values of CD4 and CD8 lymphocyte subsets in healthy indian adults and the effects of sex, age, ethnicity, and smoking. Cytometry B Clin Cytom 2003; 52:32–36.
24. Tollerud DJ, Clark JW, Brown LM, Neuland CY, Mann DL, Pankiw-Trost LK, et al
. The effects of cigarette smoking on T cell subsets. A population-based survey of healthy caucasians. Am Rev Respir Dis 1989; 139:1446–1451.
25. Farzadegan H, Hoover DR, Astemborski J, Lyles CM, Margolick JB, Markham RB, et al
. Sex differences in HIV-1 viral load and progression to AIDS. Lancet 1998; 352:1510–1514.
26. Bush CE, Donovan RM, Markowitz N, Baxa D, Kvale P, Saravolatz LD. Gender is not a factor in serum human immunodeficiency virus type 1 RNA levels in patients with viremia. J Clin Microbiol 1996; 34:970–972.
27. Kuyper LM, Wood E, Montaner JS, Yip B, O'Connell JM, Hogg RS. Gender differences in HIV-1 RNA rebound attributed to incomplete antiretroviral adherence among HIV-infected patients in a population-based cohort. J Acquir Immune Defic Syndr 2004; 37:1470–1476.
28. Junghans C, Low N, Chan P, Witschi A, Vernazza P, Egger M. Uniform risk of clinical progression despite differences in utilization of highly active antiretroviral therapy: Swiss HIV Cohort study. AIDS 1999; 13:2547–2554.
29. Cozzi Lepri A, Pezzotti P, Dorrucci M, Phillips AN, Rezza G. HIV disease progression in 854 women and men infected through injecting drug use and heterosexual sex and followed for up to nine years from seroconversion. Italian Seroconversion Study. Br Med J 1994; 309:1537–1542.
30. Rezza G. Determinants of progression to AIDS in HIV-infected individuals: an update from the Italian Seroconversion Study. J Acquir Immune Defic Syndr Hum Retrovirol 1998; 17(Suppl 1):S13–S16.
31. Hewitt RG, Parsa N, Gugino L. Women's health. The role of gender in HIV progression. AIDS Read 2001; 11:29–33.
32. Garcia de la Hera M, Ferreros I, del Amo J, Garcia de Olalla P, Perez Hoyos S, Muga R, 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.
33. Currier JS, Spino C, Grimes J, Wofsy CB, Katzenstein DA, Hughes MD, et al
. Differences between women and men in adverse events and CD4+ responses to nucleoside analogue therapy for HIV infection. The AIDS Clinical Trials Group 175 Team. J Acquir Immune Defic Syndr 2000; 24:316–324.
34. Egger M, May M, Chene G, Phillips AN, Ledergerber B, Dabis F, et al
. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet 2002; 360:119–129.
35. Ofotokun I. Sex differences in the pharmacologic effects of antiretroviral drugs: potential roles of drug transporters and phase 1 and 2 metabolizing enzymes. Top HIV Med 2005; 13:79–83.
36. Gandhi M, Aweeka F, Greenblatt RM, Blaschke TF. Sex differences in pharmacokinetics and pharmacodynamics. Annu Rev Pharmacol Toxicol 2004; 44:499–523.
37. Haug NA, Sorensen JL, Lollo ND, Gruber VA, Delucci KL, Hall SM. Gender differences among HIV-positive methadone maintenance patients enrolled in a medication adherence trial. AIDS Care 2005; 17:1022–1029.
38. Godin G, Cote J, Naccache H, Lambert LD, Trottier S. Prediction of adherence to antiretroviral therapy: a one year longitudinal study. AIDS Care 2005; 17:493–504.
39. Berg KM, Demas PA, Howard AA, Schoenbaum EE, Gourevitch MN, Arnsten JH. Gender differences in factors associated with adherence to antiretroviral therapy. J Gen Intern Med 2004; 19:1111–1117.
40. Iliyasu Z, Kabir M, Abubakar IS, Babashani M, Zubair ZA. Compliance to antiretroviral therapy among AIDS patients in Aminu Kano Teaching hospital, Kano, Nigeria. Niger J Med 2005; 14:290–294.
41. Hellinger FJ, Fleishman JA. Location, race, and hospital care for AIDS patients: an analysis of 10 states. Inquiry 2001; 38:319–330.
42. Fleishman JA, Gebo KA, Reilly ED, Conviser R, Mathews CW, Todd KP, et al
. Hospital and outpatient health services utilization among HIV-infected adults in care 2000–2002. Med Care 2005; 43(Suppl 9):III40–III52.
43. Davidson AJ, Bertram SL, Lezotte DC, Marine WM, Rietmeijer CA, Hagglund BB, et al
. Comparison of health status, socioeconomic characteristics, and knowledge and use of HIV-related resources between HIV-infected women and men. Med Care 1998; 36:1676–1684.
44. Hellinger FJ. The use of health services by women with HIV infection. Health Serv Res 1993; 28:543–561.
45. Garcia-Sanchez I. Gender differences in HIV/AIDS. Gac Sanit 2004; 18(Suppl 2):47–54.
46. Schuurman R, Descamps D, Weverling GJ, Kaye S, Tijnagel J, Williams I, et al
. Multicenter comparison of three commercial methods for quantification of human immunodeficiency virus type 1 RNA in plasma. J Clin Microbiol 1996; 34:3016–3022.