| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
 |
ABSTRACT |
TOP
ABSTRACT
INTRODUCTION
STUDY PARTICIPANTS AND METHODS
RESULTS
DISCUSSION
CONCLUSION
REFERENCES |
|---|
|
INTRODUCTION |
|
TOP
ABSTRACT
INTRODUCTION
STUDY PARTICIPANTS AND METHODS
RESULTS
DISCUSSION
CONCLUSION
REFERENCES |
|---|
Another important aspect of the potential interaction between HIV and malaria is the effect of HIV-associated immunosuppression on response to antimalarial therapy. Case series and retrospective reviews comparing the antimalarial drug efficacy among HIV-infected and HIV-uninfected patients have reported mixed results.4–7 Two recent clinical studies have been conducted in Africa to assess antimalarial efficacy in an HIV-infected population. In Zambia, treatment with sulfadoxine–pyrimethamine (SP) or artemether–lumefantrine was followed by a small increased risk of recurrent parasitemia in HIV-infected individuals with CD4 cell count < 300/µL compared with those with CD4 counts 
300/µL, when participants were followed for 45 days, but not after polymerase chain reaction (PCR) correction to exclude new infections.8 In Kenya, the risk of treatment failure after treatment with SP was 3.4-fold greater for HIV-infected adults with CD4 cell counts < 200/µL compared with HIV-uninfected adults, only in the presence of anemia.9 None of the previous studies considered the intrinsic resistance of the parasites to the study treatment.
The ability to clear drug-resistant parasites is a model for acquired immunity to malaria.10 As children get older and develop immunity, they have an improved ability to resolve parasitemia despite treatment with a drug to which the parasites are resistant. We hypothesized that if HIV-associated immunosuppression interferes with malaria immunity, then lower CD4 cell counts would be associated with an impaired ability of SP treatment to cure infections with SP-resistant parasites.
To identify both host and parasite factors that contribute to antimalarial drug efficacy, we studied HIV-infected adults and children enrolled in a longitudinal study in Blantyre, Malawi. When participants developed symptomatic malaria, they were treated with SP, according the Malawi national policy, and were followed for 28 days to assess the efficacy of the drug. Molecular analyses of infecting parasites were carried out to identify the presence of genetic mutations associated with resistance to SP.
|
STUDY PARTICIPANTS AND METHODS |
|
TOP
ABSTRACT
INTRODUCTION
STUDY PARTICIPANTS AND METHODS
RESULTS
DISCUSSION
CONCLUSION
REFERENCES |
|---|
Specimen collection. CD4 cell counts were measured at enrollment and every 4 months during participation in the study. Malaria smears and hemoglobin measurements were obtained at enrollment, at every scheduled 4-weekly visit regardless of symptoms, and at any sick visits when the participant had fever or any other signs or symptoms of malaria disease. Malaria thick smears were stained with Field stain, and parasites were counted against 200 white blood cells. Parasite density was calculated on the basis of an estimated white blood cell count of 8,000 cells/µL. For smears with parasite density too high to measure on a thick smear, thin smears were obtained to measure the percentage of parasitized red blood cells, and parasite density was calculated on the basis of the measured hemoglobin level.
Case definitions. A diagnosis of clinical malaria was made at the time of the clinic visit if any level of parasitemia was present, accompanied by symptoms associated with malaria. These symptoms included fever documented on physical examination or history of fever in the previous 48 hours, myalgia, weakness, pallor, or headache, and without signs or symptoms of severe malaria.12 Participants who had clinical or laboratory evidence of an acute bacterial infection were not included in the assessment of SP efficacy. However, 1 adult and 1 child with concurrent otitis media were included because the study physician determined that the clinical symptoms were most consistent with malaria. A second episode in 1 individual was only included if episodes were a minimum of 2 months apart with documentation of at least 1 negative malaria smear between episodes.
Malaria management.
Participants who were diagnosed with uncomplicated malaria were treated with SP. The dose for adults was 75 mg of pyrimethamine and 1500 mg of sulfadoxine, and for children the dose was 
1.25 mg/kg pyrimethamine and 25 mg/kg sulfadoxine. All participants who experienced treatment failure were treated with either halofantrine or quinine and followed to ensure resolution of symptoms and parasitemia.
Outcomes. Participants were followed according to the standard 28-day assessment of efficacy, with outcomes classified according to the WHO protocol.13 Participants returned for follow-up on days 1, 2, 3, 7, 14, and 28 and were also encouraged to return on other days if they were unwell. Early treatment failure could occur on days 0–3, and late clinical failure could occur on days 4–28. For participants who had parasitemia at day 28, but never had signs of severe disease or fever, the outcome was classified as late parasitological failure. Collectively, early treatment failure, late clinical failure, and late parasitological failure were classified as treatment failure.
Molecular analysis.
Drops of blood were collected on filter papers at every visit during the study. After DNA had been extracted from dried filter papers from the day of enrollment, nested PCR followed by mutation-specific restriction-endonuclease digestion was used to detect the molecular markers for SP resistance: dihydrofolate reductase (DHFR) Cys 
Arg at codon 59 and dihydropteroate synthetase (DHPS) Lys Glu at codon 540. We have previously demonstrated that these 2 mutations accurately predict the presence of the most SP-resistant parasites commonly found in Malawi, i.e., those containing DHFR mutations Ser Asn at codon 108, Asn Ile at codon 51, and Cys Arg at codon 59 and DHPS mutations Ala Gly at codon 437 and Lys Glu at codon 540.14 Infections in which only parasites containing mutations at DHFR 59 and DHPS 540 were detected were considered to be resistant infections. Genotyping for resistance mutations was performed on all infections in which the clinical outcome was known and on randomly selected infections for which the clinical outcomes were unknown.
Episodes of recurrent parasitemia from 14 to 28 days after therapy underwent analysis of the polymorphic region of merozoite surface protein-2 (MSP-2) from the original and the recurrent infection, according to established methods.15 Polymorphic fragments were considered the same if their measured molecular weights were within 15 base pairs. Recrudescent infection was defined as the presence of alleles in the recurrent episode that were also found in the original infection.
Data analysis. Information was entered into a database in Microsoft Access (Microsoft, Redmond, WA), and the data were analyzed in Stata 8.2 (StataCorp, College Station, TX). Participants < 16 years of age were considered children. Anemia was defined as hemoglobin < 10 g/dL. CD4 cell counts were used from the day of the diagnosis of malaria if they were available or within the prior 6 months. Frequencies were compared using Fisher’s exact test. Student’s t-test was used to compare normally distributed variables, and the Wilcoxon rank sum test was used for other continuous variables. The primary outcome measure was the cumulative treatment failure rate, with comparisons using Cox proportional hazards. The variables were tested to exclude colinearity. Huber–White robust estimates of variance were applied for multiple measurements from a single individual for all survival analyses. The role of each independent variable of interest was analyzed in both univariate and multivariate models. All variables were included in the final model because of their biologic interest. We explored the possibility of interactions between all combinations of CD4 cell count, hemoglobin, age, and resistant infections in the model. Kaplan–Meier survival curves were generated using the time to the first episode of recurrent parasitemia and compared using the log rank test.
Ethical review. This study was approved by the University of Malawi College of Medicine Research and Ethics Committee, as well as the institutional review boards of the University of Maryland and Michigan State University. Informed consent was obtained from all participants prior to enrollment in the cohort study.
|
RESULTS |
|
TOP
ABSTRACT
INTRODUCTION
STUDY PARTICIPANTS AND METHODS
RESULTS
DISCUSSION
CONCLUSION
REFERENCES |
|---|
).
|
, the failure rate was not statistically different for episodes occurring in individuals with CD4 cell counts < 200/µL compared with 200/µL, but children had a much higher failure rate than adults (71.4% compared with 20.9%, P < 0.001). No episodes of severe malaria developed during the study. Recurrent parasitemia in cases of late clinical or parasitological failure was due to recrudescent infection in 10/12 (83%) cases in which MSP-2 genotypes were known.
|
200 cells/µL (56% versus 48%, P = 0.5). Eleven infections were wild type with respect to at least one of the codons of interest, and the remaining 51 infections contained a mixture of SP-susceptible and resistant parasites.
Univariate analysis.
In the analysis of host and parasite risk factors, children had a 3-fold increased risk of treatment failure compared with adults, and anemia was associated with a 2-fold increase relative risk of failure. The log-transformed parasite density at the initial infection was not associated with a change in risk (hazards ratio 1.1, CI 0.8–1.6, P = 0.6). Neither CD4 cell count nor infection with resistant parasites was associated with increased risk of treatment failure (Table 2
). We examined early treatment failure and late clinical and parasitological failure separately. The relative risk for early treatment failure comparing malaria episodes in individuals with CD4 count < 200 cells/µL to 200 cells/µL was 0.5 (CI 0.2–1.6, P = 0.2), and for late clinical and parasitological failure the relative risk was 0.9 (CI 0.4–2.0, P = 0.7). Results were similar when age and CD4 count were included as continuous variables and when a CD4 cell count cutoff of 300/µL was used instead of 200/µL (data not shown).
Multivariate analysis. We detected an interaction between age and infection with resistant parasites (P = 0.04), but we found no interaction between CD4 cell count and infection with resistant parasites, CD4 count and anemia, or anemia and infection with resistant parasites on the outcome of treatment failure. Age and categorization of child or adult were both included in the multivariate model to fulfill the assumptions of proportional hazards. The variables were not colin-ear.
Because age modified the effect of resistant infections on treatment outcome, we analyzed adults and children separately (Table 3). In the pediatric population, increasing age was protective against treatment failure. Anemia and infection with resistant parasites were associated with 2-fold and 11-fold increased risk of treatment failure, respectively (Table 3). Among adults, none of the proposed factors was associated with risk of treatment failure. We conducted the same analysis but restricted it to cases in which the parasite density was > 2,000/µL, which is a more specific case definition and is also the population recommended for study in the WHO protocol for assessing antimalarial therapeutic efficacy.13 The results were similar except for a statistically significant increased risk of treatment failure with higher parasite density of the initial infection.
|
These analyses were repeated, classifying infections that contained only SP-resistant parasites as well as those with a mixture of both SP-resistant and susceptible parasites as "SP-resistant infection." Relationships between the risk factors of interest and treatment failure were similar (data not shown).
Time to first recurrent parasitemia.
Figure 1 shows the relative risk of recurrent parasitemia for the lower versus higher CD4 count groups and for children versus adults. The difference between CD4 cell count groups was not statistically significant (P = 0.1), but between adults and children the curves differed (P = 0.003).
|
|
DISCUSSION |
|
TOP
ABSTRACT
INTRODUCTION
STUDY PARTICIPANTS AND METHODS
RESULTS
DISCUSSION
CONCLUSION
REFERENCES |
|---|
A small effect of CD4 count may have been undetected due to the sample size. Malaria infection is becoming less frequent among individuals identified as being HIV-infected due to trimethoprim–sulfamethoxazole prophylaxis. Large clinical studies of the interaction between the 2 infections are therefore unlikely to be possible in the future. The point estimates of the risk of treatment failure among adults suggest an increased risk of treatment failure in the group with the higher CD4 cell count, although the confidence intervals were overlapping. It has been suggested that malaria may transiently decrease CD4 cell counts in adults with HIV infection.16 We and others have demonstrated associations between low CD4 cell count and increased susceptibility to malaria based on CD4 cell counts that were measured both during and prior to the episode of malaria, as was done in the present study, so it is unlikely that the timing of the CD4 cell count measurements obscured an important association between immunosuppression and treatment outcome in this study. Incomplete follow-up of some participants that inevitably occurs in this mobile, urban population may have obscured significant differences. However, the individuals who did not complete the study had similar demographic, parasitological, and immunologic characteristics to those who did reach a study endpoint.
The poor efficacy of SP in the HIV-infected pediatric population was expected based on the gradual increase in parasitological resistance that occurred at this site from 1998 to 2002.17 In a recent study from 2005, we found a cumulative treatment failure rate of 79% among children of unknown HIV status with uncomplicated malaria who were treated with SP.18 Antimalarial drug efficacy is not usually assessed in the adult population in areas of intense malaria transmission where acquired immunity aids parasite clearance. Because of SP’s loss of efficacy, Malawi is changing its first-line therapy to an artemisinin-based combination therapy.
These results are consistent with a recent study from Uganda in which no association between the presence of HIV infection and PCR-adjusted treatment failure was found in a retrospective analysis of specimens from > 3,000 participants from drug efficacy trials from 2002 to 2004.7 Similarly, in a prospective trial in Zambia, a trend was noted toward an increased risk of treatment failure among individuals with CD4 counts < 300/µL compared with those with CD4 counts 300/µL, but this difference did not achieve statistical significance.8 Both of these studies found increased rates of reinfection in participants with HIV-associated immunosuppression, but we found too few cases of re-infection to conduct such a subgroup analysis in this study. The finding that recurrent infection was almost always due to recrudescence is probably a result of the post-treatment prophylactic effect provided by the very long action of SP compared with some of the artemisinin-based combination therapies used in the previous studies.7,8
The study of SP efficacy conducted by Shah and colleagues in Kenya was the most analogous to ours, as only a single therapy was studied in the setting of high levels of parasite resistance. An increased risk of treatment failure among adults with low CD4 cell counts was detected only among those with anemia. Although anemia at the onset of the malaria episode was an important risk factor for treatment failure among children, we did not find an interaction between CD4 cell count and anemia in this study. Only a small number of participants in the Kenyan study reported the use of anti-folate drugs in the preceding week (S. Shah, personal communication). Because the investigators did not provide comprehensive care for the participants in this study, the authors admit that their ability to accurately determine previous exposure to SP and antibacterials with antimalarial activity was limited.9 The distribution of resistant parasites may have been uneven in the lower and high CD4 count strata.
A key feature that distinguishes our study from previous studies is that all study participants in this report were enrolled in a longitudinal cohort study and subjected to close follow-up. Seeking treatment of febrile illness in the informal sector is common in Africa.20,21 It is possible that patients who are sick with HIV infection are more frequently exposed to drugs with antimalarial properties and are more likely to harbor resistant parasites selected by these drugs.19 Our study team provided all the medical care for the participants, so we were reasonably confident that none was recently exposed to antimalarial medication or antimicrobials that may have antimalarial activity.
Common HIV-related opportunistic infections, such as bacteremia, may present with symptoms that meet the case definition of clinical malaria. If individuals with parasites found on blood smear and a second acute illness are treated only for malaria, they are likely to be classified as "treatment failure" because the fever and symptoms are likely to persist or recur. The findings we report were derived from a longitudinal cohort study with extensive evaluation of every illness episode. Although we could not exclude some causes of fever such as viral co-infection, we were confident that the individuals enrolled in the drug-efficacy study did not have concomitant febrile conditions, such as bacteremia, pneumonia, meningitis, enteritis, or urinary tract infection. Among the most immunosuppressed people living with HIV infection, up to 10% of those with a positive malaria smear may also have a clinically significant additional illness.3 To our knowledge, none of the previous studies that examined the relationship between HIV and malaria treatment outcomes so thoroughly evaluated the nonmalarial etiologies of illness. It is possible that the lack of association found between CD4 cell count and treatment failure was due to our ability to identify the concomitant morbidities that occur more frequently among more immunosuppressed patients and thus avoid misclassification of treatment episodes.
This study has key public-health implications. As African countries that grapple with both HIV and malaria infection begin to adopt new antimalarial treatment, efficacy trials can focus on HIV-infected individuals in general and do not require stratification based on CD4 cell count. What may appear to be treatment failure among adults with advanced immunosuppression may actually be infection with opportunistic pathogens in this population rather than failure to respond to malaria treatment. The study of malaria treatment in the context of HIV co-infection provides an opportunity to better understand the development and maintenance of the immune response to malaria.
|
CONCLUSION |
|
TOP
ABSTRACT
INTRODUCTION
STUDY PARTICIPANTS AND METHODS
RESULTS
DISCUSSION
CONCLUSION
REFERENCES |
|---|
Received April 26, 2007. Accepted for publication June 11, 2007.
Acknowledgments: We are grateful to the Blantyre Malaria Project Ndirande Clinic team led by Mr. Feston Thumba and the study participants, with whom it has been a privilege to work. We also thank Drs. Grant Dorsey and Philip Rosenthal and Chris Dokomajilar for sharing the protocols for MSP-2 genotyping and assistance with interpretation of results.
Financial support: This study was funded by the National Institutes of Health (UO1 AI47858 and K25 AI59316).
* Address correspondence to Miriam K. Laufer, Center for Vaccine Development, University of Maryland School of Medicine, Baltimore, MD 21201. E-mail: mlaufer{at}medicine.umaryland.edu 
Authors’ addresses: Miriam K. Laufer, Teresa Hsi, Lorraine Beraho, and Christopher V. Plowe, University of Maryland School of Medicine, 685 W. Baltimore St., HSF-1 Room 480, Baltimore, MD 21201, Telephone: +1 (410) 706-2491, Fax: +1 (410) 706-1204, E-mails: mlaufer{at}medicine.umaryland.edu, thsi{at}medicine.umaryland.edu, lberaho1{at}gmail.com, and cplowe{at}medicine.umaryland.edu. Joep J.G. van Oosterhout, University of Malawi College of Medicine, Department of Medicine, Private Bag 360, Blantyre, Malawi, Telephone: +265-1-870-202, E-mail: vanoosterhout{at}malawi.net. Phillip C. Thesing and Fraction K. Dzinjalamala, Blantyre Malaria Project, P.O. Box 32256, Blantyre 3, Malawi, Telephone: +265-1-675-021, Fax: +265-1-870-542, E-mails: fpthesing{at}medicine.umaryland.edu and fdzinjalamala{at}bmp.medcol.mw. Stephen M. Graham, Malawi–Liverpool–Wellcome Trust Programme of Clinical Tropical Research, P.O. Box 30096, Blantyre 3, Malawi, Telephone: +265-9-836-625, Fax: +265-1-875-774, E-mail: sgraham{at}mlw.medcol.mw. Terrie E.Taylor, Michigan State University, B309-B W. Fee Hall, Department of Internal Medicine, College of Osteopathic Medicine, East Lansing, MI 48824, Telephone: +1 (517) 353-8975, Fax: +1 (517) 432-1062, E-mail: taylort{at}msu.edu.
Reprint requests: Miriam K. Laufer, Center for Vaccine Development, University of Maryland School of Medicine, 685 W. Baltimore St., HSF-1 Room 480, Baltimore, MD 21201, Telephone: +1 (410) 706-5333, Fax: +1 (410) 706-1204, E-mail: mlaufer{at}medicine.umaryland.edu.
|
REFERENCES |
|
TOP
ABSTRACT
INTRODUCTION
STUDY PARTICIPANTS AND METHODS
RESULTS
DISCUSSION
CONCLUSION
REFERENCES |
|---|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
