Incidence and nature of cognitive decline over 1 year among HIV-infected former plasma donors in China Lucette A. Cysiquea,g, Scott L. Letendreb, Christopher Akea, Hua Jina,d, Donald R. Franklina, Saurabh Guptaa, Chuan Shie, Xin Yue, Zunyou Wuf, Ian S. Abramsonc, Igor Granta, Robert K. Heatona, and the HIV Neurobehavioral Research Center group Objective: To quantify and characterize the nature of cognitive change over 1 year in a cohort of HIV-positive former plasma donors in rural China. Design: The present study is an observational cohort study. Methods: One hundred and ninety-two HIV-positive and 101 demographically comparable HIV-negative individuals, all former plasma donors, who lived in a rural part of China, received comprehensive medical and neuropsychological examinations. At study entry, 56% of HIV-positive group was on combination antiretroviral treatment and 60.9% at follow-up. Multiple regression change score approach was used with the HIV-negative sample to develop norms for change that would be then applied to the HIV-positive participants. Follow-up test scores adjusted for the control group practice effect. Results: Fifty-three HIV-positive individuals (27%) developed significant cognitive decline as compared with five (5%) HIV-negative individuals. Cognitive decline was predicted at baseline by AIDS status, lower nadir CD4, and worse processing speed; at follow-up, it was associated with lower current CD4 cell count and failure of viral suppression on combination antiretroviral treatment. Neuropsychological decline also was associated with decreased independence in activities of daily living. Using neuropsychological impairment scores that were corrected for ‘practice’ on repeated testing, we found that among the decliners, 41.5% (N ¼ 22) had incident impairment, whereas 38% (N ¼ 20) declined within the impaired range and another 20.7% (N ¼ 11) declined within the normal range. Conclusion: The present study demonstrates that despite ongoing combination antiretroviral treatment, cognitive decline in HIV-positive people is common over a 1-year follow-up. Regression-based norms for change on western neuropsychological tests can be used to detect disease-related cognitive decline in a developing country. ß 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins AIDS 2010, 24:983–990 Keywords: antiretroviral therapy, China, highly active, HIV/AIDS, incidence studies, longitudinal studies, neurocognitive disorders, neuropsychological tests a Department of Psychiatry, bDepartment of Medicine, cDepartment of Mathematics, and HIV Neurobehavioral Research Center (HNRC), University of California at San Diego, dVA San Diego Healthcare System, San Diego, California, USA, eInstitute of Mental Health, Peking University, fNational Center for AIDS/STD Control & Prevention (NCAIDS), Beijing, China, and gDepartment of Psychiatry, Brain Sciences, University of New South Wales, Sydney, Australia. Correspondence to Robert K. Heaton, Department of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603, La Jolla, CA 92093-0603, USA. Tel: +1 858 534 4044; fax: +1 858 534 9917; e-mail: rheaton@ucsd.edu Received: 26 July 2009; revised: 31 August 2009; accepted: 18 September 2009. DOI:10.1097/QAD.0b013e32833336c8 ISSN 0269-9370 Q 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. 983 984 AIDS 2010, Vol 24 No 7 Introduction Several recent studies have provided prevalence estimates of HIV-associated neurocognitive disorders (HAND) [1] in ‘nonwestern’ regions of the world such as sub-Saharan Africa [2,3], India [4], China [5,6], and south-east Asia [7]. Taken together, the findings of these studies have demonstrated that HAND can be validly assessed in resource-limited countries, when using appropriate control samples. HAND prevalence appears to be similar in these areas of the world to the estimates reported with western HIV-positive cohorts (i.e., 20–50%, depending upon disease stages and comorbid conditions [8]). Combination antiretroviral therapy (cART) has greatly decreased HIV-associated mortality and medical morbidity, including HIV-associated dementia (HAD), but the prevalence of milder forms of HAND remains high [8]. Several longitudinal cohort studies in western countries have assessed cognitive decline and its potential contributing factors in the cART era [9–13]. Published studies, after varying follow-up periods, have found that between 22 and 63% of participants on cART demonstrated continuing impairment and at least 21% had incident impairment [12,13]. Variability in these estimates of cognitive impairment and change probably is related to methodological factors such as inclusion of appropriate normative standards for detecting these outcomes [14]. Just as it is important to define cross-sectional neuropsychological impairment in individual cases, rather than relying on group mean comparisons, longitudinal methods for classifying meaningful neuropsychological change in individuals also are needed. Advantages of reliably detecting cognitive change at the individual level include understanding factors responsible for variable manifestations and course of HAND, and alerting clinicians to consider changes in antiretroviral regimens early (e.g., to include agents with better central nervous system (CNS) penetration [15] or adjunctive treatments that may specifically benefit the CNS [16]). To our knowledge, the current study is the first to assess long-term neurocognitive outcomes in a large cohort of HIV-positive persons in China and in the cARTera. Our aim was to detect and quantify neuropsychological decline over a 1-year period in 192 individual HIVpositive former plasma donors (FPDs) in the Chinese province of Anhui. For this, we developed norms for change using longitudinal data of a fairly large sample (N ¼ 101) of demographically comparable HIV-negative individuals. The norms for change were derived using a regression change score approach [17,18]. Here we propose an extension of this method by introducing a battery approach to derive a normed summary change score for each individual. In addition, we propose an adaptation of the Global Deficit Score method [19,20] to estimate follow-up impairment rate corrected for practice effect. Methods Participants Details regarding participant recruitment procedures and baseline results were published in study by Heaton et al. [6]. Briefly, at baseline, 203 HIV-positive and 198 HIVnegative participants, virtually all of whom were farmers in the rural area of Anhui province, were enrolled into the study at a local hospital in Fuyang city. By design, at 12 months postbaseline, half of the baseline HIV-negative participants (N ¼ 101) were reassessed. In addition, all available HIV-positive participants were reassessed (N ¼ 192), yielding a 5.4% (11/203) attrition rate. The causes for dropout were one case of cerebral infarct; two cases of blindness and an additional case of substantial vision decline precluding valid neuropsychological testing; four moved away for work; and three deaths. The 101 HIVnegative participants had been randomly selected in order to compose a sample representative of the total baseline group with respect to demographic and baseline neuropsychological characteristics. This sample of HIV-negative participants was followed up at 1 year in order to develop normative standards for neuropsychological change (see also e-data analysis, http://links.lww.com/QAD/A35). At baseline, 106 (55.2%) of the 192 HIV-positive participants met CDC-1993 criteria for AIDS. Virtually, the same subgroup (N ¼ 107; 55.7%) was being prescribed cART at baseline consistent with prevailing antiretroviral initiation guidelines in China. HIV duration estimated from selfreport averaged 154 months (SD ¼ 42). When they were retested after 12 months, 20 additional HIV-positive participants had transitioned to AIDS and at that time, 60.9% of the total group was receiving cART. Procedure As in the baseline assessment, participants underwent comprehensive neurocognitive and neuromedical evaluations, and a structured psychiatric examination, as well as a self-report assessment of daily functioning. Examinations were performed by the same Chinese psychiatric staff who had conducted the baseline assessments the previous year. They had been trained and certified in the standardized testing procedures by the US research team (R.K.H., D.F., and H.J.). Prior to starting the second annual testing phase, the Chinese examiners participated in another training session in order to review and practice test administration and test scoring procedures. Details of the neuropsychological battery selection and adaptation for use in China are provided in studies by Cysique et al. [5] and Heaton et al. [6] (see also Table e-1 & e-2). Clinical significance of any neuropsychological impairment or change was examined with standard Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. Cognitive decline in HIV infection Cysique et al. instruments measuring participants’ experience of cognitive difficulties in everyday life (Patient’s Assessment of Own Functioning Inventory – PAOFI [21]) and decreases in degree of independence in activities of daily living [modified version of the Lawton & Brody Instrumental Activities of Daily Living (IADL) scale [22]]. Participants also completed the Beck Depression Inventory-II (BDI-II [23,24]). Data analysis To identify individuals who presented with overall neuropsychological change, we used a statistical methodology based on the multivariate regression change score approach (see [17,18] for review of this change score approach). The advantage of the regression-based change score approach is that it accounts for practice effect, regression toward the mean, and other factors that may influence normal test–retest variability in neurologically stable people (e.g., test–retest interval, demographics, and overall baseline neuropsychological competence [18]). Our detailed method is available in the supplemental file eData analysis, http://links.lww.com/QAD/A35. Briefly, to define neuropsychological decline in the HIV-positive sample, the 101 HIV-negative individuals were used as a reference sample to develop normative regression formulas. The final regression formulas were then applied to the HIV-positive sample providing a Z-score for each of 17 neuropsychological variables. These Z-scores reflect how well or poorly the person performed at follow-up, relative to normal expectation for someone with the same baseline neuropsychological and other relevant characteristics. The Z-scores were then summed to provide a summary regression change score (sRCS). We determined a 90% confidence interval (CI) on the sRCS to define ‘no change’ on the test battery. That is, the cut-off for the top 5% of the sRCS distribution of the HIV-negative controls defined the ‘improved’range and the cut-off for the bottom 5% defined the ‘decliners’ range. This was applied to the HIV-positive sample (Fig. 1). Secondary analyses were conducted to clarify the nature of both baseline predictors and follow-up correlates of 100 95% Overall X 2 (2) = 21.5; P < 0.0001 90 % Participants 80 72.4% 70 60 50 40 27.6% 30 20 5% 10 0 Stable HIV (n = 96) Declined HIV (n = 5) Stable HIV+ (n = 139) Declined HIV+ (n = 53) Fig. 1. Percentage of neuropsychological change as defined by the summary of regression change score in the HIVpositive and HIV-negative samples. cognitive decline in this population. The HIV-positive decliners and nondecliners (as defined by the sRCS) were compared on baseline and follow-up demographic, HIV disease-related laboratory measures, AIDS status, Global Deficit Score (GDS), and ability domain summary scores on the neuropsychological test battery, treatment-related variables, cognitive complaints, IADL, and BDI-II using t-test or x2 test as appropriate. We also conducted standard multivariate analyses to define which combination of baseline factors provided the most robust prediction of neuropsychological decline (defined by the sRCS). The GDS and ability domain T-scores at follow-up were corrected for the HIV-negative sample median practice effect (see also e-Data analysis, http://links.lww.com/ QAD/A35 [6,19,20]). Results The baseline demographic characteristics of the HIVnegative and HIV-positive persons who participated in the 12-month follow-up assessment are presented in Table 1. Test–retest correlations on the neuropsychological battery were robust for both groups [HIV-negative group’s mean scaled score rtt ¼ 0.85 and HIV-positive group’s mean scaled score rtt ¼ 0.84]. Incidence of neuropsychological decline in the HIVpositive group (27.6%) was significantly greater than that in our reference HIV-negative sample (5%) as defined by the sRCS approach [x2 (1) ¼ 21.4; P < 0.0001]. We found that 53 HIV-positive individuals were classified as having neuropsychological decline at the 12-month follow-up (i.e., they performed below the 5% cut-off reference range that defined the ‘decliners’ in the HIV-negative sample; CI of 95% one-tailed; see Fig. 1). When comparing the 53 HIV-positive participants who were classified as decliners at the 12-month follow-up with the 139 HIV-positive nondecliners, we found that decliners tended to be older (P < 0.08), were more likely to have AIDS at baseline (P < 0.03), and had lower nadir CD4 count (P < 0.05). At follow-up, they had lower current CD4 cell count (P < 0.03) and also were more likely to have detectable virus in plasma when on cART (P < 0.01; Table 2). To explore further the CD4 cell count finding at follow-up and take into account any cART effect, a two-way analysis of variance (ANOVA) was performed with the CD4 cell count at follow-up as the outcome variable, and the decliner status as well as the treatment status at baseline (whether receiving cART or not at baseline) as predictors, and their interaction. We found that the follow-up CD4 cell count still tended to differ between the decliners and nondecliners (P ¼ 0.06). No other findings approached statistical significance. Importantly, the decliner and nondecliner groups did not Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. 985 986 AIDS 2010, Vol 24 No 7 Table 1. Baseline characteristics of 101 HIV-negative and 192 HIV-positive participants at 1-year follow-up. Baseline Age (years) [mean (SD)] Education (years) [mean (SD)] Sex (%) male AIDS (%) Plasma HIV RNAa [median (IQR)] Plasma HIV RNA (%) undetectable On cART (%) Current CD4 cell count [median (IQR)] Nadir CD4 cell count [median (IQR)] HCV-positive (%) Follow-up New AIDS diagnosis (%) Plasma HIV RNAb [median (IQR)] Plasma HIV RNA (%) undetectable On cARTc (%) Current CD4 cell count [median (IQR)] HIV-negative (n ¼ 101) HIV-positive (n ¼ 192) P d 40.8 (6.7) 5.8 (2.1) 56% – – – – – 40.2 (6.3) 5.5 (2.3) 61% 55% 4.2 (3.5–4.7) 34% 56.3% (N ¼ 107) 346 (204–454) 200 (159–360) 92.7% 0.42 0.15 0.40 – – – – – – <0.0001 0.09 0.13 0.10 – – – – – – 0.46 10% (N ¼ 20) 4.2 (3.6–4.8) 39% 60.9% (N ¼ 117) 375 (11–1173) – – – – – – – – – – 67.3% – – – – ART, antiretroviral treatment; d, Cohen’s d; HCV, hepatitis C virus; IQR, interquartile range. (N ¼ 127 detectable). b (N ¼ 117 detectable). c At follow-up, among the participants on ART, all were on cART defined as a regimen composed of at least three antiretroviral drugs except for one patient who was on monotherapy. This is higher than baseline wherein, in this sample, 89% were on cART; 9% on dual therapy, and 2% on monotherapy. Most commonly prescribed ART drugs were stavudine (N ¼ 103); nevirapine (N ¼ 98); didanosine (N ¼ 77); and lamivudine (N ¼ 51). Other drugs prescribed less frequently were efavirenz (N ¼ 10); atazanavir (N ¼ 7); and zidovudine (N ¼ 8). The restricted range did not allow testing central nervous system (CNS) penetration effectiveness [15]. However, it should be noted that overall, the CNS penetration effectiveness ratings for ART regimens in this cohort are fairly low, suggesting that some individuals may be suboptimally treated for their CNS HIVrelated injury. a Table 2. Baseline and follow-up characteristics in HIV-positive persons who declined versus those who did not decline on the neuropsychological battery. Age [mean (SD)] Education [mean (SD)] Sex (%) Neuropsychologically impaired [baseline (%)] Neuropsychologically impaired [follow-up (correcteda) %] Global Deficit Score baseline [mean (SD)] Global Deficit Score follow-up [(correcteda) mean (SD)] HCV-positive (%) Estimated HIV duration [(months) mean (SD)] AIDS (%) baseline AIDS (%) follow-up New AIDS-defining illnesses (%) BDI-II baseline (% clinically depressed)b BDI-II follow-up (% clinically depressed)b On cART at baseline (Total N ¼ 107; 35 decliners, 72 nondecliners) (%) On cART at follow-up (Total N ¼ 117; 38 decliners, 79 nondecliners) (%) cART duration at follow-up [(months) mean (SD)] Current CD4 cell count at baseline [mean (SD)] Current CD4 cell count at follow-up [mean (SD)] CD4 nadir count [mean (SD)] CD4 nadir count <200% Percentage of undetectable VL at baseline (<50 copies/ml, total sample %) Percentage of undetectable VL at follow-up (<50 copies/ml, total sample %) Percentage of undetectable VL at baseline (<50 copies/ml, on cART at baseline %) Percentage of undetectable VL at follow-up (<50 copies/ml, on cART at follow-up %) Declined (N ¼ 53) Did not decline (N ¼ 139) P d 41.6 (6.6) 5.2 (2.4) 60.4% 37.7% 79.2% 0.52 (0.4) 0.91 (0.5) 94.3% 161 (36) 68.0% 71.1% 9.4% 26.4% 20.7% 66.0% 71.7% 139 (58) 324 (186) 352 (184) 233 (159) 62.3% 33.9% 32.1% 40% (14/35) 39.5% (15/38) 39.6 (6.2) 5.6 (2.2) 61.9% 36.7% 28.8% 0.49 (0.5) 0.40 (0.4) 92.1% 152 (44) 50.4% 63.8% 10.1% 25.2% 8.6% 52.5% 56.8% 124 (70) 365 (203) 422 (225) 268 (156) 46.0% 33.8% 41.2% 55.5% (40/72) 64.5% (51/79) <0.08 0.34 0.85 0.89 <0.0001 0.65 <0.0001 0.59 0.13 <0.03 0.30 0.89 0.86 0.02 0.09 0.06 0.22 0.19 <0.03 0.17 <0.05 0.98 0.22 0.13 <0.01 0.32 0.17 0.03 0.02 1.2 0.06 1.2 0.08 0.21 0.36 0.17 0.03 0.02 0.32 0.27 0.32 0.22 0.20 0.32 0.22 0.33 0.01 0.20 0.24 0.42 ART, antiretroviral treatment; d, Cohen’s d; HCV, hepatitis C virus; VL, viral load. Test–retest interval did not differ between the decliners and nondecliners (333
37 versus 331
45; P ¼ 0.79). Level of adherence was high in this sample and there were no significant differences between decliners and nondecliners at baseline: 100% of decliners on ART reported that they took their medication ‘Almost all of the time’ and 98.5% of nondecliners on ART reported that they took their medication ‘Almost all of the time’. At follow-up, 94.7% of decliners on ART reported that they took their medication ‘Almost all of the time’ and 98.8% of nondecliners on ART reported that they took their medication ‘Almost all of the time’. There were no significant differences in baseline demographics (age, P ¼ 0.44; education, P ¼ 0.86; sex, P ¼ 0.10) and baseline overall neuropsychological performance (P ¼ 0.35) between the five HIV-negative decliners and 96 HIV-nondecliners. a The Global Deficit Score was based on T-scores corrected for HIV-negative median practice effect. b BDI-II: Beck Depression Inventory-II; (a score  17 reflects threshold for clinical level of depressive complaints). Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. Cognitive decline in HIV infection Cysique et al. Table 3. Mean and domain T-scores in HIV-positive persons who declined versus those who did not decline. Declined (N ¼ 53) Mean T-score baseline [mean (SD)] Executive baseline [mean (SD)] Verbal baseline [mean (SD)] Attention/WM baseline [mean (SD)] Learning baseline [mean (SD)] Memory baseline [mean (SD)] Motor baseline [mean (SD)] SIP baseline [mean (SD)] Mean T-score follow-up a [mean (SD)] Executive follow-up a [mean (SD)] Verbal follow-up a [mean (SD)] Attention/WM follow-up a [mean (SD)] Learning follow-up a [mean (SD)] Memory follow-up a [mean (SD)] Motor follow-up a [mean (SD)] SIP follow-up a [mean (SD)] 44.5 45.1 46.3 45.1 45.2 44.2 46.5 42.5 40.2 40.6 42.3 42.4 39.4 37.2 42.4 38.6 (5.2) (8.8) (7.2) (7.3) (7.8) (7.2) (8.6) (5.7) (3.9) (8.2) (7.4) (6.0) (6.5) (7.1) (9.1) (5.0) Did not decline (N ¼ 139) 46.1 45.9 46.6 47.2 46.0 45.8 45.2 46.0 46.9 46.1 47.4 48.4 46.9 45.8 47.9 46.2 (6.1) (9.3) (8.1) (8.4) (8.9) (8.3) (10.3) (7.2) (5.4) (7.9) (8.1) (8.4) (8.4) (8.3) (9.4) (6.7) P d 0.08 0.57 0.81 0.09 0.52 0.18 0.37 0.0005 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.002 <0.0001 0.27 0.09 0.04 0.26 0.06 0.20 0.13 0.51 1.31 0.68 0.64 0.76 0.93 1.06 0.58 1.19 SIP, speed of information processing; WM, working memory. T-scores corrected for HIV-negative median practice effect. a differ in education and sex characteristics, or for prevalence of hepatitis C virus (HCV) infection or cART duration. They also did not differ in overall baseline neuropsychological performance (GDS) or prevalence of baseline neuropsychological impairment. estimates in the HIV-negative controls also dropped from an expected 14% to only 2% (P ¼ 0.0004). There is no known biological reason for such change; this result should, therefore, be considered as evidence for error due to failure to correct for practice. About one quarter of both the decliners and nondecliners evidenced clinically significant level of depressive symptoms (BDI-II  17) at baseline (26.4 versus 25.2%). At follow-up, neither group showed an increase in rates of depression, but the nondecliners improved somewhat more (see Table 2). Decliners and nondecliners did not differ in their numbers of reported cognitive problems either at baseline (P ¼ 0.22) or follow-up (P ¼ 0.60), nor in the difference between baseline and follow-up (P ¼ 0.13). Results remain comparable when the BDI-II was entered as a covariate. However, decliners were more likely to have significant decrease in IADL independence at follow-up (9.4 versus 1.4%; P < 0.007; significant decrease in IADL was defined as decrease in dependence in at least two everyday functioning areas [22]). Although overall neuropsychological performance at baseline did not differ between decliners and nondecliners, we did find that speed of information processing (SIP) at baseline was significantly lower in the HIVpositive who would go on to decline as compared with the nondecliners (medium effect size, d ¼ 0.51 – see Table 3). At follow-up and using the practice effect corrected neuropsychological scores to derive demographically corrected ability domain T-scores, we found that the decliners demonstrated significantly lower performance in all domains when compared with the nondecliners, with the greatest difference found in learning, memory, and SIP (all large effect sizes; d > 0.8). Although neuropsychological impairment rates for the decliners and nondecliners were almost identical at baseline (37.7 versus 36.7%, respectively), not surprisingly, a much higher prevalence of impairment was seen in the decliners at follow-up (79.25 versus 28.78%; P < 0.0001). Overall impairment rate in the HIV-positive group at follow-up was 42.71% (82/192), which was just slightly higher than that at baseline (36.9%; 71/192). When using the follow-up scores that were uncorrected for practice effect, 51% of decliners and 15.1% of nondecliners would be classified neuropsychologically impaired at follow-up (and only 25% in the total HIVpositive group – see also Table e-2 e-Data analysis, http://links.lww.com/QAD/A35). Importantly, without correction for practice effect, impairment prevalence We found that among the 53 HIV-positive decliners, 22 (41.5%) showed incident impairment on the corrected GDS at follow-up. Eleven (20.7%) declined within the normal range and another 20 (38%) declined within the impaired range. These subgroups did not statistically differ on the sRCS. Finally, we tested predictors of cognitive change using a stagewise regression approach. First, in a multivariate model with the sRCS as the outcome and including the predictors that were found (P < 0.10) to be different between HIV-positive decliners and nondecliners at baseline (see Table 2), we found that SIP (P ¼ 0.004) and AIDS at baseline (trending at P ¼ 0.06) remained unique contributors to the model (R2 ¼ 0.10; P ¼ 0.007; baseline age did not uniquely predict change). Second, in a final two-covariate logistic regression model that predicted decliners’ status, baseline SIP mean T-score had an odds ratio of 1.07 (CI 1.03–1.13) for a one-unit decrease and Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. 987 988 AIDS 2010, Vol 24 No 7 baseline AIDS had an odds ratio of 1.94 (CI 0.98–3.84) relative to baseline non-AIDS. Discussion The present study demonstrated that performance on the neuropsychological tests originally developed in western regions of the world was quite reliable over time in both the infected and uninfected rural Chinese participants. Together with the earlier finding of greater baseline impairment associated with HIV and HCV infections and associations of neuropsychological impairment with both HIV disease severity and indications of decreases in everyday functioning [6], this suggests that neuropsychological tests standardized and widely used in western regions of the world (here historically and geographically defined as Europe, Australia, and North America) generalize to people having very different cultural, linguistic, and educational backgrounds. It may be, therefore, that the abilities assessed by most or all of these tests capture some universal features of cognition. Moreover, using the regression change score approach that has been validated mainly in non-HIV populations in the United States, we found that we could detect cognitive decline in 27.6% of the HIV-positive participants after a 1-year interval. This greatly exceeded the expected 5% normative cut-off of the HIV-negative sample. Even though our infected sample remained relatively healthy from a general medical point of view (average immune status improved and few participants had new AIDS-defining illnesses) and reported excellent adherence to their cART (Table 2), many evidenced worsening of their neurocognitive status and slightly fewer than expected showed any improvement. Thus, though cART has dramatically improved the mortality and medical morbidity associated with HIV disease, such treatment appears less effective in alleviating or reversing CNS compromise that has been observed since the beginning of the HIV epidemic [25]. The minimal 12-month dropout rate (5%) for our HIV-positive FPDs is remarkable and reflects high levels of cooperation and dedication of the Chinese participants and examiners. Of the 11 baseline HIV-positive patients who could not be retested, seven were presumed to be due to HIV disease phenomena (three deaths, one stroke, three with recent severe visual impairment), so their loss to follow-up may have slightly underestimated rates of HIV-related neuropsychological decline. Similar to prior longitudinal neuropsychological findings in western studies [26–29], test–retest interval in our rural Chinese population was not a significant predictor of variability in cognitive performance. Still, the variation in retest interval was restricted by design (actual range 237– 494 days) and it is possible that more discrepant test–retest intervals may have yielded different results. Also similar to results in western studies, we found that the most robust predictors of follow-up neuropsychological scores were baseline scores on the same tests, as well as overall neuropsychological competence at baseline [18,27,28, 30,31], and to a lesser extent age [27] (see also e-Data analysis, http://links.lww.com/QAD/A35). Supporting the current method for classifying change is the fact that neuropsychological decline was associated with markers of advanced HIV disease such as AIDS at baseline and lower nadir CD4 count. The same diseaserelated predictors were associated with neuropsychological impairment at baseline [6]. Worse immune recovery, as reflected by lower current CD4 cell counts at followup, also was associated with cognitive decline. Even though both groups’ CD4 cell counts improved at followup, immune recovery was slightly worse for the decliners. Although cART use and duration did not differ between the groups, the cARTof the decliners was less likely to be effective (they were more likely to have detectable viral loads at follow-up, suggesting more treatment failure in the decliner group). Altogether, our findings would imply that current virological response to cART and past immune injury are important factors for HAND prognosis. Lower nadir CD4 cell counts may reflect prior HIV-related brain injury, representing a neuropathogenic process that may persist despite partial immune recovery, whereas current viral load detection would reflect ineffective cART. In any event, our results regarding long-lasting effects of earlier immunosuppression are consistent with several reports in western regions [10,13,32–34] as are findings suggesting that successful cART is an important factor for maintaining stable cognitive functions [9]. Together, these findings strengthen the hypothesis that effective cART initiated earlier in HIV disease may be more efficient at preventing HAND [35]. As has been noted in relation to studies of NeuroAIDS in the west, the precise timing and nature of the neuropathological mechanisms occurring in Chinese HIV-positive persons with stable or incident HAND are not well understood [36]. Coinfection with HCV, though associated with somewhat increased risk of neuropsychological impairment in this population at baseline, was unrelated to further cognitive decline over the next year. One explanation for this observation is that any brain injury that was previously linked to HCV had already occurred and was static and nonprogressive. Another is that some individuals who tested positive for HCV antibodies at baseline no longer had active HCV viral replication, though this hypothesis was not tested in this study. Future longitudinal research with coinfected (and HCV-monoinfected) samples should determine Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited. Cognitive decline in HIV infection Cysique et al. whether detectable HCV in plasma confers an increased risk for neuropsychological decline over time. Another confirmatory finding with the previous literature in NeuroAIDS is that lower SIP performance was predictive of future neuropsychological decline [37]. Impairment of this ability appears to be a common and possibly early feature of both HAND and HAND progression. If so, the presence of even fairly isolated deficiencies in information processing speed may suggest the possibility of an evolving process. Studies in other countries should be undertaken to see whether this is a generalizable feature of HAND, independently of the cultural context. We showed that our estimate of cognitive decline was associated with decreased independence in activities of daily living, but not change in cognitive complaints or depressive symptoms. Independence in everyday life serves as an important benchmark to distinguish asymptomatic from symptomatic forms of HAND [1]. We had previously demonstrated that neuropsychological criteria for HAND could be effectively adapted to the Chinese rural context cross-sectionally [6] and that neuropsychological impairment was associated with reported decrease in performance of IADL. This longitudinal finding is the first to be reported in a Chinese HIV-positive cohort and supports our definition of neuropsychological change and its clinical meaningfulness. In conclusion, this study demonstrates that despite ongoing cART, cognitive decline in HIV-positive people is common over a 1-year follow-up. Regression-based norms for change on western neuropsychological tests can be used to detect disease-related cognitive decline in a developing country. Acknowledgements The present study was supported by the NIMH grant 5 R01 MH073433-04 (R.K.H., PI). The HIV Neurobehavioral Research Center (HNRC) is supported by Center award MH 62512 from NIMH. The authors would like to thank Fuyang city CDC and Psychiatric Hospital for providing staff support and the examiners for the study. The San Diego HIV Neurobehavioral Research Center (HNRC) group is affiliated with the University of California, San Diego, the Naval Hospital, San Diego, and the Veterans Affairs San Diego Healthcare System, and includes the following members: Director: Igor Grant, MD; Co-Directors: J. Hampton Atkinson, MD, Ronald J. Ellis, MD, PhD, and J. Allen McCutchan, MD; Center Manager: Thomas D. Marcotte, PhD; Naval Hospital San Diego: Braden R. Hale, MD, MPH (PI); Neuromedical Component: Ronald J. Ellis, MD, PhD (PI), J. Allen McCutchan, MD, Scott Letendre, MD, Edmund Capparelli, Pharm D, Rachel Schrier, PhD; Neurobehavioral Component: Robert K. Heaton, PhD (PI), Mariana Cherner, PhD, Steven Paul Woods, Psy D; Neuroimaging Component: Terry Jernigan, PhD (PI), Christine Fennema-Notestine, PhD, Sarah L., Archibald, M.A., John Hesselink, MD, Jacopo Annese, PhD, Michael J. Taylor, PhD, Neurobiology Component: Eliezer Masliah, MD (PI), Ian Everall, FRCPsych., FRCPath., PhD,Cristian Achim, MD, PhD; Neurovirology Component: Douglas Richman, MD, (PI), David M. Smith, MD; International Component: J. Allen McCutchan, MD, (PI); Developmental Component: Ian Everall, FRCPsych., FRCPath., PhD (PI), Stuart Lipton, MD, PhD; Clinical Trials Component: J. Allen McCutchan, MD, J. Hampton Atkinson, MD, Ronald J. Ellis, MD, PhD, Scott Letendre, MD; Participant Accrual and Retention Unit: J. Hampton Atkinson, MD (PI), Rodney von Jaeger, MPH; Data Management Unit: Anthony C. 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