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Stimulant Medications and Cognition, Behavior and Quality of Life in Children and Youth with HIV

Sirois, Patricia A. PhD*; Aaron, Lisa MS†‡; Montepiedra, Grace PhD†‡; Pearson, Deborah A. PhD§; Kapetanovic, Suad MD; Williams, Paige L. PhD†‡; Garvie, Patricia A. PhD; Nozyce, Molly L. PhD**; Malee, Kathleen PhD††; Nichols, Sharon L. PhD‡‡; Kammerer, Betsy L. PhD§§; Mitchell, Wendy G. MD¶¶‖‖; Mintz, Mark MD***†††; Oleske, James M. MD‡‡‡ for the IMPAACTPACTG 219C Team

Author Information
The Pediatric Infectious Disease Journal: January 2016 - Volume 35 - Issue 1 - p e12-e18
doi: 10.1097/INF.0000000000000947

Abstract

Children and adolescents with perinatally acquired HIV (PHIV) infection may experience multiple risks to mental health and quality of life (QOL), including viral infection of the central nervous system, viral and drug exposure in utero, poverty, unstable housing, parental physical and mental health problems, and inadequate support networks.1,2 Recent data from US-based cohorts suggest that children and adolescents with PHIV perform within the low-average to average range of intellectual ability and show higher than expected rates of behavioral impairment.3–9 From infancy through adolescence, PHIV infection is associated with poorer QOL.10–13 Youth with PHIV are at risk for clinically significant behavioral problems such as overactivity, impulsivity and inattention,1,2 which may affect academic learning, social relationships and adherence to treatment regimens. Appropriate therapy for such symptoms is critical to their health care and development, and medications are frequently the first-line treatment choice.14–16

Stimulant medications are commonly prescribed for children with PHIV and other chronic illnesses for indications varying from treating attention-deficit/hyperactivity disorder (ADHD) and augmenting antidepressants to management of illness-related fatigue and decreased motivation to engage in medical care.1 A large study indicated that 19% of children with PHIV had been prescribed a stimulant medication.17 Although stimulants are known to be effective in treating the symptoms of hyperactivity and impulsivity associated with ADHD in children and adolescents across a wide range of cognitive ability,15,18–21 it is unclear whether this efficacy is generalizable to children with PHIV. There has been little empirical investigation into longitudinal changes in cognition, behavior or QOL in children with PHIV who take stimulants. The primary objective of this analysis was to examine the relationship between the use of commonly prescribed stimulants and changes in measures of cognition, behavior and QOL in children and adolescents with PHIV. We hypothesized that after adjustment for baseline levels of these measures, children with prescriptions for stimulants would show improvement in cognitive scores, parent-reported symptoms of hyperactivity and impulsivity and indices of QOL compared with their peers with PHIV without prescriptions for stimulants.

MATERIALS AND METHODS

Participants

This study included children and adolescents with PHIV, ages 3–19 years, with and without prescriptions for stimulant medications, who were enrolled in the Pediatric AIDS Clinical Trials Group (PACTG) 219C cohort study (P219C).22,23 Exposure to stimulants was defined as having a history of prescription for at least one of the methylphenidates or amphetamine salts. Among children prescribed at least one of these stimulants, we included those who started their first stimulant after enrollment into P219C, continued that medication for at least one month and had at least one outcome measurement obtained before (baseline measurement) and after the start of that first medication. Each participant with stimulant exposure was matched with 1–3 participants without stimulant exposure based on the following criteria: availability of outcome measurements, age at baseline measurement (within 1 year of each other) and CD4% category (<15%, 15–25%, >25% or missing) within 6 months of baseline measurement. With 3 outcomes of interest (cognition, behavior and QOL), each participant could have a maximum of 3 baseline measurements collected over a 3-year period (see the respective "Outcomes" sections for schedules of assessment). Each potential participant without stimulant exposure was required to match the participant with stimulant exposure on age, CD4% and availability of outcome data at all 3 baseline measurements.

Procedures

P219C was a longitudinal observational study of children and adolescents with PHIV exposure designed to examine long-term effects of exposure to antiretroviral (ARV) medications and complications of HIV infection. It was conducted from September 2000 to May 2007 at more than 80 participating sites in the US and Puerto Rico. Informed consent and assent were obtained according to local institutional review board guidelines. Participants’ medical records were abstracted at study entry and follow-up visits to obtain medical and treatment histories, including markers of immune functioning, neurologic and psychiatric diagnoses and ARV and concomitant medications, including stimulants. Follow-up visits included standardized assessment of verbal and nonverbal cognitive abilities, parent or primary caregiver (caregiver) report of child behavior and reports from caregivers and older children regarding the children’s QOL and current demographic and medical information. Respondents completed questionnaires independently or as interviews if they had difficulty reading. Medication start and stop dates were recorded as reported by caregivers and older participants or as documented in medical records. The baseline measure was defined as the measure completed at the visit preceding or on the same day as the visit at which the participant’s first prescription was recorded. The first available outcome measure after baseline was selected as the follow-up measure.

Cognitive Outcomes

Age-appropriate Wechsler scales24–29 were used to assess verbal and nonverbal intellectual functioning. These measures were administered according to standardized procedures at baseline and every 3 years after enrollment. Visits were scheduled around the children’s birthdays at ages 3, 6, 9, 12 and 15 years. The Wechsler tests have excellent psychometric properties and were updated as revised test versions were published. The Verbal Scale Intelligence Quotient (VIQ) and Performance Scale Intelligence Quotient (PIQ) were used in the analyses; these are age-normed standardized scores with mean (M) = 100 and standard deviation (SD) = 15. The Full Scale IQ, a summary score, was not used in order to examine potential differential effects of stimulant use on verbal and nonverbal intellectual abilities. Data were reviewed, and results were excluded if considered invalid because of a child’s sensory or physical impairment or insufficient proficiency in English.

Behavioral Outcomes

Conners’ Parent Rating Scales (CPRS-48)30 were administered to caregivers at baseline and every 3 years until their child was 15 years old. The CPRS-48 provides measures in 5 behavioral domains (labeled Conduct Problem, Learning Problem, Psychosomatic, Impulsive-Hyperactive, and Anxiety) and includes a Hyperactivity Index. Age-referenced T-scores (M = 50, SD = 10) were used in the analyses. Higher scores reflected greater frequency or intensity of problem behaviors.

QOL Outcomes

Standardized measures of QOL, previously validated for use with children and adolescents with PHIV,31 were administered to caregivers (for ages 6 months to 20 years) and study participants (ages 12–20 years) at baseline and every 6–12 months after enrollment. The General Health Perception, Health Care Utilization and Social/School Functioning domain scores were available for all participants; the Behavior Problem Index was available for those age 5–20 years. Domain composite scores (range = 0–100) were included in the analyses. Higher scores reflected better QOL.

Statistical Analysis

Characteristics of participants with and without exposure to stimulants were compared using Fisher exact tests, Mantel–Haenszel χ2 tests or Pearson χ2 tests, as appropriate. One-sample t tests were used to determine if the average changes in outcomes during follow-up were significantly different from 0. Unadjusted and adjusted generalized estimating equation models were used to evaluate the effect of stimulant exposure and other variables on change in each of the outcomes. All adjusted models included baseline level of the outcome, child’s sex and neurologic or psychiatric diagnosis (defined as ADHD/behavioral diagnosis, at least one other neurologic or psychiatric diagnosis or none). Variables considered as potential confounders in the model selection process included race/ethnicity (white non-Hispanic vs. other), HIV RNA (>400 copies/mL vs. ≤400 copies/mL), Centers for Disease Control and Prevention Class32,33 (Class C vs. other), caregiver (biological parent vs. other), caregiver’s education (high school or greater vs. other) and type of ARV treatment (ART) used at baseline. ART was modeled as a 4-category variable: highly active ART (HAART; defined as at least 3 drugs from at least 2 drug classes) with protease inhibitor, HAART without protease inhibitor, ART without HAART and no ART. All covariates with P < 0.25 in the univariate analysis were considered for inclusion. Covariates were removed using backward selection with a significance level of P < 0.10. Covariates significant for at least 1 outcome in a given analysis (cognitive, behavioral or QOL) were included in the multivariate model for all outcomes of that type.

RESULTS

Participants

Of the 2589 children with PHIV enrolled in P219C, 144 (5.6%) had a prescription for one or more stimulants (Table 1) and met inclusion criteria for this analysis. Of these, 134 (93%) had valid data for at least 1 of the 3 outcomes. Two of these participants were excluded because matching controls were unavailable. For the primary analyses, the 132 participants with prescriptions for stimulants [the prescription group (PG)] were matched with 1–3 participants who did not have prescriptions for stimulants [the comparison group (CG)], resulting in 392 matched controls, for a total sample of 524 participants. The analysis sets for the 3 outcomes were cognition, n = 212 (54 PG and 158 CG); behavior, n = 194 (49 PG and 145 CG); and QOL, n = 511 (131 PG and 380 CG). There were 122 participants (31 PG and 91 CG) with measurements for all 3 outcomes.

TABLE 1
TABLE 1:
Duration of Treatment with First-prescribed Stimulant Medication by Stimulant Group

The distribution of duration of treatment with the first-prescribed stimulant medication is shown in Table 1, overall and by stimulant group, and ranged from 1 to 75 months. Nineteen participants switched to at least 1 other stimulant medication during the follow-up period.

Table 2 presents the distribution of demographic and health characteristics of all participants included in the analyses. There were significant differences between the PG and CG by gender (62% vs. 43% male). A significantly higher proportion of the PG than CG were living with biologically unrelated adults (47% vs. 28%), and their caregivers had more years of formal education than the CG (77% vs. 67% with at least high school education). Participant characteristics were similar between the total sample and the samples for each outcome measure.

TABLE 2
TABLE 2:
Demographic and Health Characteristics of Study Participants* by Group

Medication Class and Psychiatric or Neurologic Diagnoses

Methylphenidates were the first medications prescribed for the majority (75%) of participants with prescriptions for stimulants (Table 1). The median duration of treatment was 13.2 months (14.0 months for methylphenidates; 9.6 months for amphetamines). The majority of the PG had one or more psychiatric or neurologic diagnoses recorded in the database (Table 2), and the prevalence of diagnoses was significantly higher than in the CG (55% vs. 28%; P < 0.001). A higher proportion of children in PG had a diagnosis of ADHD/other behavior disorder compared with CG (40% vs. 5%; P < 0.001); the groups did not differ in the prevalence of any psychiatric or neurologic diagnosis other than ADHD/other behavior disorder. There were no reported psychiatric or neurologic diagnoses for 45% of the PG. Diagnosis rates were similar between the total sample and the samples for each outcome measure.

Cognitive Outcomes

Unadjusted Wechsler mean VIQ and PIQ scores at baseline and mean changes from baseline are presented in Table 3. At baseline, mean VIQ and PIQ for both the PG and CG were in the low-average range relative to population norms, and the between-group differences were not significant. The mean retest interval for the cognitive outcomes was 31.5 months (SD = 12.4) and was higher for the PG (34.9 vs. 30.3 months for PG vs. CG, respectively; P = 0.02). After adjustment for baseline VIQ and PIQ and other relevant covariates, having a prescription for stimulants was not associated with changes from baseline in VIQ or PIQ (Table 4).

TABLE 3
TABLE 3:
Unadjusted Scores at Baseline and Change from Baseline by Outcome Measure for Participants With (PG) and Without (CG) Prescriptions for Stimulant Medications
TABLE 4
TABLE 4:
Estimated Effect of Stimulant Prescription Use on Change from Baseline in Cognitive, Behavioral and QOL Outcomes after Adjustment for Relevant Covariates

Behavioral Outcomes

At baseline, unadjusted mean CPRS-48 scores were significantly higher in the PG than the CG on the Hyperactivity Index (61.4 vs. 50.4) and Conduct Problem (56.4 vs. 49.1), Impulsive-Hyperactive (60.7 vs. 50.0) and Learning Problem (63.0 vs. 52.8) scales (Table 3). The mean retest interval for behavioral outcomes was 26.2 months (SD = 15.0) and was marginally higher for the PG (29.8 vs. 25.0 months for PG vs. CG, respectively; P = 0.06). After adjusting for baseline level of the outcome and other relevant covariates, having a prescription for stimulants was significantly associated with larger average changes on the Hyperactivity Index (7.7 points) and Impulsive-Hyperactive (5.4 points) and Learning Problem (11.4 points) scales (Table 4), indicating an increase in problem behaviors, per caregiver report, from baseline to follow-up for PG when compared with CG.

QOL Outcomes

At baseline, unadjusted mean QOL scores for the PG and CG were virtually equivalent in the Health Care Utilization and Social/School Functioning domains, but the PG obtained significantly lower mean scores the General Health Perception domain (79.4 vs. 84.8) and Behavior Problem Index (69.1 vs. 82.9) (Table 3). The mean retest interval for the QOL outcomes was 10.9 months (SD = 7.3) and was comparable between the 2 groups (11.3 vs. 10.7 months for PG vs. CG, respectively; P = 0.39). After adjustment for the baseline level of the outcome and other relevant covariates (Table 4), having a prescription for stimulants was significantly associated with decreases in the General Health Perception domain (−6.7 points) and Behavior Problem Index (−5.4 points), indicating that respondents in the PG reported changes toward poorer QOL from baseline to follow-up compared with respondents in the CG.

DISCUSSION

We hypothesized that children with PHIV and prescriptions for stimulants, compared with those without prescriptions, would show improvements over time in cognition, behavior and QOL. Study findings contradicted these hypotheses. After adjustment for baseline levels of the outcomes and other relevant covariates, having a prescription for stimulants was associated with worsening symptoms of hyperactivity, impulsivity and learning problems and worsening of perceived health status in school-age children with PHIV. Participants’ performance on measures of verbal and nonverbal intellectual ability, both at baseline and follow-up, was consistent with recent studies of school-age children with PHIV regardless of stimulant exposure,2–6 and there were no significant changes from baseline in VIQ or PIQ among children with PHIV, with or without prescriptions for stimulants.

At baseline, QOL domain scores assessing general health perception, behavior problems and social/school functioning in both groups were consistent with a previous study of QOL in the P219C cohort.13 Compared with population norms for the CPRS-48,30 the CG did not demonstrate significant behavior or learning problems, according to caregiver ratings. As expected, children in the PG demonstrated more frequent signs of hyperactivity, impulsivity and learning problems than their peers in the general population and in the CG. The PG also showed more frequent signs of conduct problems than the CG. Findings for the PG, but not the CG, were consistent with the literature showing higher risks for behavior and learning problems among children with PHIV,1,2,7–9 possibly because of the relatively higher prevalence of ADHD and other behavior disorders in the PG. PHIV, per se, might not be the primary mechanism for these difficulties.2,34 More than half (55%) of the PG had at least one psychiatric or neurologic diagnosis recorded in the database, the majority being ADHD or another behavior disorder, yet a fairly large proportion of children in this group (45%) had no reported diagnosis. Differences in access to medical and psychiatric records17 or differences in clinical services offered across sites may have affected the availability of psychiatric and neurologic diagnoses for P219C. Thus, the present results may not accurately reflect the true frequency of psychiatric diagnoses in children with PHIV.

Children in the PG did not improve over time on measures of cognition, behavior or QOL, consistent with an emerging literature regarding long-term efficacy of stimulant medications in the general pediatric population.15,16,35–37 There are plausible explanations for this finding. We have little knowledge about the synergistic relationships among stimulants, ARVs and other medications the children may be taking. Children and adolescents with PHIV and comorbid ADHD, compared with their uninfected peers, may require higher doses of stimulants to achieve the same therapeutic benefit because of the altered metabolism that may be associated with HIV disease and its treatments.38 Stimulant treatments must be maintained to preserve initial benefits,35 yet parents and older youth in the general population may use stimulants intermittently or discontinue treatment entirely for a variety of reasons, including lack of perceived benefit, medication side effects (including loss of appetite and the potential for decreased physical growth), financial costs, philosophical concerns about medicating children and inadequate access to qualified health care professionals willing to provide medication management for ADHD.39,40 Family decisions over the use of stimulant treatments are further complicated by the presence of HIV infection, a chronic illness that typically requires ongoing treatment with ARVs and frequent medical monitoring and, in addition, may put children at risk for comorbid conditions such as language disorders, learning disabilities, and behavioral or emotional disorders. It is possible that one or more of these factors influenced the findings in this study.

This study was limited by reliance on subjective reports from caregivers without collateral reports from sources such as teachers or health care providers. For the PG, there was a lack of information concerning stimulant dosing and medication adherence. For example, children in the PG may have performed more poorly than those in the CG because they were not adherent to their stimulant treatment regimens, a possibility consistent with recent literature on medical treatment of children and adults with ADHD.41 Follow-up intervals were linked to children’s ages and dates of enrollment into P219C, not to medication start and stop dates, and there was wide variability in treatment duration, with some participants continuing their first prescription for as little as 1 month. Such variability limits the interpretation of study findings. Children who entered P219C with prescriptions for stimulants were not included in the study, limiting the generalizability of the findings. Information was lacking concerning important life events during the lengthy retest intervals as well as nonmedical therapies that may have been provided to families, for example, behavior therapy, parent training and general educational and psychosocial supports. The imbalance in some covariates and lack of data on potentially important confounding variables suggests that the use of an alternative research design, such as propensity score matching, should be explored in future studies. Although the age range was wide, and analyses were not stratified by age, the outcome measures were standardized and appropriate for use with children and adolescents across the age range included in the study.

To our knowledge, this study is one of the first to examine the association of stimulant prescription use with changes in important indicators of well being in children and adolescents with PHIV. Despite its limitations, the results of the study are intriguing and support a growing consensus42–45 that expectations of parents, teachers and medical providers may not be well aligned with the long-term effects of these medications on children’s behavior, academics and QOL. This study provides preliminary, exploratory data concerning the associations between stimulant prescription use and the selected outcomes. It is important to pursue this research to gain a fuller understanding of the most appropriate, evidence-informed treatments for children with PHIV and symptoms of ADHD and other behavior disorders.

ACKNOWLEDGMENTS

We thank the children and families for their participation in PACTG 219C and the individuals and institutions involved in the conduct of 219C as well as the leadership and participants of the P219/219C protocol team. We are grateful for the contributions of Joyce Kraimer, Barbara Heckman, Shirley Traite and Nathan Tryon.

D.A.P. has received travel reimbursement and research support from the Forest Research Institute and from Curemark LLC; she has also served as a consultant to Curemark LLC and to United BioSource Corporation (now Bracket). M.M. has no direct financial or nonfinancial relationships that are directly related to the content of this manuscript. Other financial and other relationships that might be perceived as a potential conflict requiring disclosure include the following: In the past 36 months, M.M. has functioned as Principal Investigator for research contracted through the Clinical Research Center of New Jersey, LLC (CRCNJ) sponsored by the following companies: UCB Pharma, Sunovion, Pfizer, Eisai Inc., and Allergan. CRCNJ receives funding to conduct the clinical trial. M.M. is the principle investigator for research funded by the State of New Jersey, through the Governor’s Council for Medical Research and Treatment of Autism. The other authors have no conflicts of interest to disclose.

Overall support for the International Maternal Pediatric Adolescent AIDS Clinical Trials Group (IMPAACT) was provided by the National Institute of Allergy and Infectious Diseases (U01 AI068632) and the NICHD International and Domestic Pediatric and Maternal HIV Clinical Trials Network supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (contract N01-3-3345 and HHSN267200800001C). This research was supported in part by the Intramural Research Program of the NIMH.

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Allergy and Infectious Diseases or the National Institutes of Health.

This work was supported by the Statistical and Data Analysis Center at Harvard School of Public Health, under the National Institute of Allergy and Infectious Diseases cooperative agreement #5 U01 AI41110 with the Pediatric AIDS Clinical Trials Group (PACTG) and #1 U01 AI068616 with the IMPAACT Group.

We also thank the protocol 219 and 219C leadership and team members and the individual staff members and sites who have participated in the conduct of this study, as provided in Appendix (Supplemental Digital Content 1, https://links.lww.com/INF/C298).

REFERENCES

1. Donenberg GR, Pao M.. Youths and HIV/AIDS: psychiatry’s role in a changing epidemic. J Am Acad Child Adolesc Psychiatry. 2005;44:728–747
2. Smith R, Wilkins M.. Perinatally acquired HIV infection: long-term neuropsychological consequences and challenges ahead. Child Neuropsychol. 2015;21:234–268
3. Jeremy RJ, Kim S, Nozyce M, et al.Pediatric AIDS Clinical Trials Group (PACTG) 338 & 377 Study Teams. Neuropsychological functioning and viral load in stable antiretroviral therapy-experienced HIV-infected children. Pediatrics. 2005;115:380–387
4. Nozyce ML, Lee SS, Wiznia A, et al. A behavioral and cognitive profile of clinically stable HIV-infected children. Pediatrics. 2006;117:763–770
5. Malee K, Williams PL, Montepiedra G, et al.PACTG 219C Team. The role of cognitive functioning in medication adherence of children and adolescents with HIV infection. J Pediatr Psychol. 2009;34:164–175
6. Smith R, Chernoff M, Williams PL, et al.Pediatric HIV/AIDS Cohort Study (PHACS) Team. Impact of HIV severity on cognitive and adaptive functioning during childhood and adolescence. Pediatr Infect Dis J. 2012;31:592–598
7. Malee K, Williams P, Montepiedra G, et al.PACTG 219C Team. Medication adherence in children and adolescents with HIV infection: associations with behavioral impairment. AIDS Patient Care STDS. 2011;25:191–200
8. Mellins CA, Tassiopoulos K, Malee K, et al.Pediatric HIV/AIDS Cohort Study. Behavioral health risks in perinatally HIV-exposed youth: co-occurrence of sexual and drug use behavior, mental health problems, and nonadherence to antiretroviral treatment. AIDS Patient Care STDS. 2011;25:413–422
9. Garvie PA, Zeldow B, Malee K, et al.Pediatric HIVAIDS Cohort Study (PHACS). Discordance of cognitive and academic achievement outcomes in youth with perinatal HIV exposure. Pediatr Infect Dis J. 2014;33:e232–e238
10. Lee GM, Gortmaker SL, McIntosh K, et al.Pediatric AIDS Clinical Trials Group Protocol 219C Team. Quality of life for children and adolescents: impact of HIV infection and antiretroviral treatment. Pediatrics. 2006;117:273–283
11. Lyon ME, Williams PL, Woods ER, et al. Do-not-resuscitate orders and/or hospice care, psychological health, and quality of life among children/adolescents with acquired immune deficiency syndrome. J Palliat Med. 2008;11:459–469
12. Butler AM, Williams PL, Howland LC, et al.Pediatric AIDS Clinical Trials Group 219C Study Team. Impact of disclosure of HIV infection on health-related quality of life among children and adolescents with HIV infection. Pediatrics. 2009;123:935–943
13. Storm DS, Boland MG, Gortmaker SL, et al.Pediatric AIDS Clinical Trials Group Protocol 219 Study Team. Protease inhibitor combination therapy, severity of illness, and quality of life among children with perinatally acquired HIV-1 infection. Pediatrics. 2005;115:e173–e182
14. Faraone SV.. Using meta-analysis to compare the efficacy of medications for attention-deficit/hyperactivity disorder in youths. P&T. 2009;34:678–694
15. Charach A, Dashti B, Carson P, et al. Attention Deficit Hyperactivity Disorder: Effectiveness of Treatment in At-Risk Preschoolers; Long-Term Effectiveness in All Ages; and Variability in Prevalence, Diagnosis, and Treatment. Comparative Effectiveness Review No. 44. AHRQ Publication No. 12-EHC003-EF. 2011 Rockville, MD Agency for Healthcare Research and Quality Available at: www.effectivehealthcare.ahrq.gov/reports/final.cfm. Accessed December 7, 2014.
16. Palli SR, Kamble PS, Chen H, et al. Persistence of stimulants in children and adolescents with attention-deficit/hyperactivity disorder. J Child Adolesc Psychopharmacol. 2012;22:139–148
17. Sirois PA, Montepiedra G, Kapetanovic S, et al.IMPAACT/PACTG 219C Team. Impact of medications prescribed for treatment of attention-deficit hyperactivity disorder on physical growth in children and adolescents with HIV. J Dev Behav Pediatr. 2009;30:403–412
18. Pliszka SR, Greenhill LL, Crismon ML, et al. The Texas children’s medication algorithm project: report of the Texas consensus conference panel on medication treatment of childhood attention-deficit/hyperactivity disorder. Part I. J Am Acad Child Adolesc Psychiatry. 2000;39:908–919
19. Pliszka SR, Greenhill LL, Crismon ML, et al. The Texas children’s medication algorithm project: report of the Texas consensus conference panel on medication treatment of childhood attention-deficit/hyperactivity disorder. Part II: tactics. J Am Acad Child Adolesc Psychiatry. 2000;39:920–927
20. Pearson DA, Santos CW, Roache JD, et al. Treatment effects of methylphenidate on behavioral adjustment in children with mental retardation and ADHD. J Am Acad Child Adolesc Psychiatry. 2003;42:209–216
21. American Academy of Child and Adolescent Psychiatry. . Practice parameter for the assessment and treatment of children and adolescents with attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2007;46:894–921
22. Brogly SB, Ylitalo N, Mofenson LM, et al. In utero nucleoside reverse transcriptase inhibitor exposure and signs of possible mitochondrial dysfunction in HIV-uninfected children. AIDS. 2007;21:929–938
23. Brady MT, Oleske JM, Williams PL, et al.Pediatric AIDS Clinical Trials Group219/219C Team. Declines in mortality rates and changes in causes of death in HIV-1-infected children during the HAART era. J Acquir Immune Defic Syndr. 2010;53:86–94
24. Wechsler D. Wechsler Preschool and Primary Scales of Intelligence. 1989Revised San Antonio The Psychological Corporation
25. Wechsler D. Wechsler Preschool and Primary Scales of Intelligence. 20023rd ed San Antonio The Psychological Corporation
26. Wechsler D. Wechsler Intelligence Scales for Children. 1974Revised San Antonio The Psychological Corporation
27. Wechsler D. Wechsler Intelligence Scales for Children. 19913rd ed San Antonio The Psychological Corporation
28. Wechsler D. Wechsler Adult Intelligence Scale. 1981Revised San Antonio The Psychological Corporation
29. Wechsler D. Wechsler Adult Intelligence Scale. 19973rd ed San Antonio The Psychological Corporation
30. Conners CK. Conners Rating Scales: Technical Manual. 1989Revised North Tonawanda, NY Multi-Health Systems
31. Gortmaker SL, Lenderking WR, Clark C, et al.Drotar D Development and use of a pediatric quality of life questionnaire in AIDS clinical trials: reliability and validity of the general health assessment for children. Assessing Pediatric Health-Related Quality of Life and Functional Status: Implications for Research, Practice, and Policy. 1998 Mahwah, NJ Laurence Erlbaum Associates:219–235
32. . 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. 1992;41(RR-17):1–19
33. Centers for Disease Control and Prevention. . 1994 revised classification system for human immunodeficiency virus infection in children less than 13 years of age. MMWR. 1994;43(RR-12):1–10
34. Mellins CA, Malee KM.. Understanding the mental health of youth living with perinatal HIV infection: lessons learned and current challenges. J Int AIDS Soc. 2013;16:1–19
35. MTA Cooperative Group. . National Institute of Mental Health Multimodal Treatment Study of ADHD follow-up: changes in effectiveness and growth after the end of treatment. Pediatrics. 2004;113:762–769
36. Jensen PS, Arnold LE, Swanson J, et al. Follow-up of the NIMH MTA study at 36 months after randomization. J Am Acad Child Adolesc Psychiatry. 2007;46:988–1001
37. Molina BS, Hinshaw SP, Swanson JM, et al.MTA Cooperative Group. The MTA at 8 years: prospective follow-up of children treated for combined-type ADHD in a multisite study. J Am Acad Child Adolesc Psychiatry. 2009;48:484–500
38. Best B, Farhad M, Rossi R, et al.IMPAACT P1080. Methylphenidate concentrations and dose requirements in HIV-infected and uninfected children, adolescents, and young adults. 20th Conference on Retroviruses and Opportunistic Infections (CROI)March 2013Atlanta GA
39. Brinkman WB, Sherman SN, Zmitrovich AR, et al. Parental angst making and revisiting decisions about treatment of attention-deficit/hyperactivity disorder. Pediatrics. 2009;124:580–589
40. Garfield CF, Dorsey ER, Zhu S, et al. Trends in attention deficit hyperactivity disorder ambulatory diagnosis and medical treatment in the United States, 2000–2010. Acad Pediatr. 2012;12:110–116
41. Gajria K, Lu M, Sikirica V, et al. Adherence, persistence, and medication discontinuation in patients with attention-deficit/hyperactivity disorder—a systematic literature review. Neuropsychiatr Dis Treat. 2014;10:1543–1569
42. Sharpe K.. Medication: the smart-pill oversell. Nature. 2014;506:146–148
43. Graf WD, Miller G, Nagel SK.. Addressing the problem of ADHD medication as neuroenhancements. Expert Rev Neurother. 2014;14:569–581
44. Thomas R, Mitchell GK, Batstra L.. Attention-deficit/hyperactivity disorder: are we helping or harming? BMJ. 2013;347:f6172
45. Riddle MA, Yershova K, Lazzaretto D, et al. The Preschool Attention-Deficit/Hyperactivity Disorder Treatment Study (PATS) 6-year follow-up. J Am Acad Child Adolesc Psychiatry. 2013;52:264–278.e2
Keywords:

HIV/AIDS; children; adolescents; ADHD; stimulants

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