The Journal of Infectious Diseases Comparison of modelling methods to determine liver-to-blood inocula and parasite multiplication rates during controlled human malaria infection --Manuscript Draft-Manuscript Number:
51292R1
Full Title:
Comparison of modelling methods to determine liver-to-blood inocula and parasite multiplication rates during controlled human malaria infection
Article Type:
Brief Report
Section/Category:
Parasites
Keywords:
Malaria; Plasmodium falciparum; vaccine; clinical trial; Modelling; qPCR
Corresponding Author:
Alexander Donald Douglas, BM BCh Jenner Institute, Oxford University Oxford, Oxfordshire UNITED KINGDOM
Corresponding Author Secondary Information: Corresponding Author's Institution:
Jenner Institute, Oxford University
Corresponding Author's Secondary Institution: First Author:
Alexander Donald Douglas, BM BCh
First Author Secondary Information: Order of Authors:
Alexander Donald Douglas, BM BCh Nick J Edwards Christopher J A Duncan Fiona M Thompson Susanne H Sheehy Geraldine A O'Hara Nicholas Anagnostou Michael Walther Daniel P Webster Susanna Dunachie David W Porter Laura Andrews Sarah C Gilbert Simon J Draper Adrian V S Hill Philip Bejon
Order of Authors Secondary Information: Manuscript Region of Origin:
UNITED KINGDOM
Abstract:
Controlled human malaria infection is used to measure efficacy of candidate malaria vaccines before field studies are undertaken. Mathematical modelling using data from quantitative PCR (qPCR) parasitemia monitoring can discriminate between vaccine effects upon the parasite's liver and blood stages. Uncertainty regarding the most appropriate modelling method hinders interpretation of such trials. Powered by Editorial Manager® and Preprint Manager® from Aries Systems Corporation
We used qPCR data from 274 Plasmodium falciparum-infected volunteers to compare linear, sine-wave, and normal-cumulative-density-function models. We find that the parameters estimated by these models are closely correlated, and their predictive accuracy for omitted data points was similar. We propose that future studies include the linear model. Suggested Reviewers:
Vasee Moorthy
[email protected] Technical Officer, WHO Initiative for Vaccine Research. Leader of initiative to standardise malaria vaccine - challenge clinical trial methodology. Thomas Richie
[email protected] Director, US Military Malaria Vaccine Program Carter Diggs
[email protected] Senior Technical Advisor, USAID Malaria Vaccine Development Program David Kaslow
[email protected] Director, PATH Malaria Vaccine Initiative. Patrick Duffy
[email protected] Chief, Malaria Vaccine Development Unit, NIAID/NIH
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Cover Letter Dr Alexander D. Douglas MA BM BCh, The Jenner Institute, University of Oxford Old Road Campus Research Building Roosevelt Drive Oxford, OX3 7DQ
T: 01865 617615 F: 01865 617608
[email protected]
30th December 2012
Dear Editor, Re: "Comparison of modelling methods to determine liver-to-blood inocula and parasite multiplication rates during controlled human malaria infection" Many thanks for your consideration of the above manuscript. We are very grateful to the reviewers for investing time in reading and commenting upon the paper, and were pleased to receive their largely positive comments. We have now revised the manuscript to take account of the points raised by reviewer #2. As well as the revised manuscript, we have prepared a point by point response the the reviewers' comments. We hope that you will feel we have fully addressed the points raised. Please do not hesitate to get in touch if you require any further information. Yours sincerely,
Dr Alexander Douglas, on behalf of all authors
*Response to Editor/Reviewer Comments
RESPONSE TO REVIEWERS' COMMENTS DOUGLAS et al- JID MS# 51292 "Comparison of modelling methods to determine liver-to-blood inocula and parasite multiplication rates during controlled human malaria infection"
REVIEWER #1 The most important conclusion from this paper is that the model used for analysis of CHMI data does not substantially affect its interpretation. The authors' recommendation to use the "linear" model going forward in the interest of simplicity and clarity is a major contribution to the field and will likely have a very significant impact on future practice. On the other hand, the result engenders more comfort with interpretations made through the use of other models in the past and when investigators elect to use other methods in future studies. The rather dramatic difference demonstrated in data variance in SybrGreen vs Taqman qPCR is another very useful contribution. The authors are to be commended for provision of crude data to enable independent analysis by other investigators.
We thank Reviewer #1 for the time taken to review the manuscript, and for these positive comments.
REVIEWER #2: This comparison of modeling methods for growth of subpatent malaria parasites is timely. Many groups are becoming involved in controlled human infections, but there is no agreement on how best to model these data and therefore to infer the impact of interventions such as vaccines on different stages of parasite development. There are, however, some key deficiencies in this manuscript that must be addressed: 1. Only data on parasite growth in non-immune individuals is presented from what I can see. Thus, there is no way to know how preerythrocytic or blood stage immunity affects the appearance and growth of malaria parasites in experimentally infected individuals. Please provide data from immunized and protected or partially protected individuals. Do the models really perform similarly when the data do not conform to the same pattern? The reviewer identifies an important issue. Individuals fully protected by pre-erythrocytic vaccines do not have PCR detectable parasitaemia at any point following challenge, and were therefore necessarily excluded from the current study. However, we include data from a number of subjects partly protected by pre-erythrocytic vaccines. In response to this reviewer's comment, we have now performed a secondary analysis of
the data displayed in figure 1, including only the subset of volunteers who were partially protected as defined above. This demonstrated that correlation between the parameter estimates from the different methods remained strong, and there was no significant difference in the predictive accuracy of the models. We have commented briefly on this in the revised manuscript text; a graphical depiction of this data is shown below.
Panel A: Parameter estimates from different models for partially protected volunteers (Upper = LBI estimates, lower = PMR estimates). Panel B: Comparison of forward-predictive accuracy of linear, sine and N-CDF models: fold error in prediction of time-of-diagnosis PCR for partially protected subjects. Panel C: Leave-one-out cross-validation. Fold-root mean square error (RMSE) for partially-protected subjects.
An alternative method of comparing the methods' likely performance for individuals partially protected by pre-erythrocytic vaccines would be to compare parameter estimates at the lower end of the range of LBI (partially protected volunteers will be those with the lowest LBI). It is apparent from inspection of figure 1A in the manuscript that the correlation of the LBI estimates produced from the different methods persists at low LBIs. We are therefore confident that the methods do indeed perform similarly in individuals partially protected by pre-erythrocytic vaccines. Regarding blood-stage immunity, there has unfortunately not yet been a convincing demonstration of even partial protection against experimental sporozoite challenge by vaccineinduced blood-stage immunity. However, there is considerably non-vaccine-induced natural variation in PMRs among different subjects. Inspection of figure 1A demonstrates that the PMR estimates produced by the different methods correlate across the full range of observed PMRs. More broadly, we do not rule out the possibility that one of the more complex models may perform favourably under certain circumstances. We have now addressed this point with the following additions to the manuscript, which can be found in the final sentences on pages 5, 8 and 9, and the penultimate sentence on page 11. Methods (Page 5): "To ensure that our conclusions remained valid for volunteers partially protected by pre-erythrocytic vaccines, we performed secondary analyses using the subset of volunteers who developed microscopically-patent parasitaemia later than all the non-vaccinated controls in the same challenge study." Results (Page 8): "Correlations between parameter estimates remained strong when considering volunteers partially protected by pre-erythrocytic vaccines (rS>0.75 and p
