Efficacy of RTS,S malaria vaccines: individual-participant pooled analysis of phase 2 data.

BACKGROUND: The efficacy of RTS,S/AS01 as a vaccine for malaria is being tested in a phase 3 clinical trial. Early results show significant, albeit partial, protection against clinical malaria and severe malaria. To ascertain variations in vaccine efficacy according to covariates such as transmission intensity, choice of adjuvant, age at vaccination, and bednet use, we did an individual-participant pooled analysis of phase 2 clinical data. METHODS: We analysed data from 11 different sites in Africa, including 4453 participants. We measured heterogeneity in vaccine efficacy by estimating the interactions between covariates and vaccination in pooled multivariable Cox regression and Poisson regression analyses. Endpoints for measurement of vaccine efficacy were infection, clinical malaria, severe malaria, and death. We defined transmission intensity levels according to the estimated local parasite prevalence in children aged 2-10 years (PrP₂₋₁₀), ranging from 5% to 80%. Choice of adjuvant was either AS01 or AS02. FINDINGS: Vaccine efficacy against all episodes of clinical malaria varied by transmission intensity (p=0·001). At low transmission (PrP₂₋₁₀ 10%) vaccine efficacy was 60% (95% CI 54 to 67), at moderate transmission (PrP₂₋₁₀ 20%) it was 41% (21 to 57), and at high transmission (PrP₂₋₁₀ 70%) the efficacy was 4% (-10 to 22). Vaccine efficacy also varied by adjuvant choice (p<0·0001)--eg, at low transmission (PrP₂₋₁₀ 10%), efficacy varied from 60% (95% CI 54 to 67) for AS01 to 47% (14 to 75) for AS02. Variations in efficacy by age at vaccination were of borderline significance (p=0·038), and bednet use and sex were not significant covariates. Vaccine efficacy (pooled across adjuvant choice and transmission intensity) varied significantly (p<0·0001) according to time since vaccination, from 36% efficacy (95% CI 24 to 45) at time of vaccination to 0% (-38 to 38) after 3 years. INTERPRETATION: Vaccine efficacy against clinical disease was of limited duration and was not detectable 3 years after vaccination. Furthermore, efficacy fell with increasing transmission intensity. Outcomes after vaccination cannot be gauged accurately on the basis of one pooled efficacy figure. However, predictions of public-health outcomes of vaccination will need to take account of variations in efficacy by transmission intensity and by time since vaccination. FUNDING: Medical Research Council (UK); Bill & Melinda Gates Foundation Vaccine Modelling Initiative; Wellcome Trust

Comparison of PfHRP-2/pLDH ELISA, qPCR and microscopy for the detection of Plasmodium events and prediction of sick visits during a malaria vaccine study.

BACKGROUND: Compared to expert malaria microscopy, malaria biomarkers such as Plasmodium falciparum histidine rich protein-2 (PfHRP-2), and PCR provide superior analytical sensitivity and specificity for quantifying malaria parasites infections. This study reports on parasite prevalence, sick visits parasite density and species composition by different diagnostic methods during a phase-I malaria vaccine trial. METHODS: Blood samples for microscopy, PfHRP-2 and Plasmodium lactate dehydrogenase (pLDH) ELISAs and real time quantitative PCR (qPCR) were collected during scheduled (n = 298) or sick visits (n = 38) from 30 adults participating in a 112-day vaccine trial. The four methods were used to assess parasite prevalence, as well as parasite density over a 42-day period for patients with clinical episodes. RESULTS: During scheduled visits, qPCR (39.9%, N = 119) and PfHRP-2 ELISA (36.9%, N = 110) detected higher parasite prevalence than pLDH ELISA (16.8%, N = 50) and all methods were more sensitive than microscopy (13.4%, N = 40). All microscopically detected infections contained P. falciparum, as mono-infections (95%) or with P. malariae (5%). By qPCR, 102/119 infections were speciated. P. falciparum predominated either as monoinfections (71.6%), with P. malariae (8.8%), P. ovale (4.9%) or both (3.9%). P. malariae (6.9%) and P. ovale (1.0%) also occurred as co-infections (2.9%). As expected, higher prevalences were detected during sick visits, with prevalences of 65.8% (qPCR), 60.5% (PfHRP-2 ELISA), 21.1% (pLDH ELISA) and 31.6% (microscopy). PfHRP-2 showed biomass build-up that climaxed (1813±3410 ng/mL SD) at clinical episodes. CONCLUSION: PfHRP-2 ELISA and qPCR may be needed for accurately quantifying the malaria parasite burden. In addition, qPCR improves parasite speciation, whilst PfHRP-2 ELISA is a potential predictor for clinical disease caused by P. falciparum. TRIAL REGISTRATION: ClinicalTrials.gov NCT00666380

Trends in malaria prevalence by diagnostic method among the study participants that did not develop clinical malaria during the 112-day study.

<p>At every visit, malaria prevalences are highest when detected by <i>Pf</i>HRP-2 ELISA and qRT-PCR methods and lowest when measured with microscopy and <i>p</i>LDH ELISA.</p

Species-specific primers and probes for detecting <i>Plasmodium</i> parasites.

<p>Species-specific primers and probes for detecting <i>Plasmodium</i> parasites.</p

Pair-wise Comparison of malaria diagnostic methods using Generalized Estimating Equations (GEE).

<p>Pair-wise Comparison of malaria diagnostic methods using Generalized Estimating Equations (GEE).</p

Utility of microscopy, qPCR, PfHRP-2 and pLDH ELISAs in predicting clinical episodes.

<p>Parasite dynamics before clinical malaria attack (<b>day 0</b>) as measured by (A) <i>Pf</i>HRP-2, (B) <i>p</i>LDH (C) Microscopy and (D) qPCR, for the 12 participants with microscopically confirmed clinical malaria. Parasite dynamics after clinical attack are also presented for <i>Pf</i>HRP-2 (A). Error bars represent standard error of mean of the parasitemia values at each time point. The arrows indicate the day of treatment. Microscopy, <i>p</i>LDH and qPCR did not detect malaria parasites after the treatment.</p

Comparison of routine microscopy, <i>p</i>LDH/<i>Pf</i>HRP-2 ELISA and qPCR for a group of study participants who had acute blood smears prepared at sick visits.

<p>Each column (1–38) represents one blood sample with the corresponding microscopy, <i>p</i>LDH/<i>Pf</i>HRP-2 ELISA and qRT-PCR results, ordered by parasite density as determined by microscopy (top graph) and antigen levels (<i>p</i>LDH/<i>Pf</i>HRP-2) or Ct values (qPCR). As the levels of parasitemia decreases, the concordance between the different methods also decreases. <i>Pf</i>HRP-2 and qPCR detect parasites densities way beyond the detection limit of microscopy.</p

The number and percentage of <i>Plasmodium</i> parasite species detected by microscopy and qPCR.

<p>Key: Pf = <i>P. falciparum</i>, Pm = <i>P. malariae</i>, Po = <i>P. ovale</i>.</p