Skip to main content
. 2010 Jan 19;7(1):e1000218. doi: 10.1371/journal.pmed.1000218

Table 3. Proposed guidelines of the reporting of Malaria Immuno-epidemiology Observational Studies (MIOS guidelines).

Report Section Topics Recommended Inclusions
Title and abstract Indicate the study design and the study population
Provide in the abstract an informative and balanced summary of what was done and the main findings. Indicate immune response measured, antigens used, and all Plasmodium and clinical end-points examined. Present key estimates of associations with measures of variability.
Introduction Explain the scientific background and rationale for the antigens and Plasmodium end-points chosen.
State objectives, including any prespecified hypotheses (i.e., protection, no effect).
State how the current study will add to the malaria immuno-epidemiology literature and briefly state how it compares to previous studies.
Methods Epidemiological study A description of the setting, including location, Plasmodium spp. found in the area, rate of malaria transmission, dates of transmission. Mention any recent changes in endemicity.
Study design, describe exactly how and when immune response, Plasmodium and clinical data collection took place. For longitudinal studies discriminate between serial cross-sectional studies and longitudinal cohort studies.
Relevant dates such as participant recruitment, measurement of immune responses, follow-up, and Plasmodium and clinical data collection.
Eligibility criteria and sources and methods of selection of participants. Justification of criteria.
Methods of follow-up and data collection. Indicate intervals for ACD and the appropriateness of the use of PCD in the setting. Indicate how presumptive malaria diagnosis was dealt with in data collection.
A description of any efforts to address potential sources of bias.
Sample size calculations. Include the level of precision and power, the expected size of differences to be measured (e.g., in antibody levels, risk/odds of malaria), and the minimum difference you wish to detect.
Variables Definitions of all Plasmodium outcomes (i.e., parasitaemia, symptomatic malaria), detail parasitological cut-offs and fever definitions. State whether Plasmodium speciation was done and how this was incorporated into definitions. Mention the sensitivity and specificity of malaria definitions in the population. Indicate how “unexposed” individuals were defined, if relevant.
Definitions of all immunological variables. Explain how responders and nonresponders were defined. Explain how continuous variables were handled in the analyses such as the use of transformations and groupings. Describe which groupings were chosen and why, and state the cut-offs used for each group and the category mean or median values. For each antigen indicate the allele, amino acid position, expression system, and tag. Provide gene accession numbers.
A list of all potential confounders and effect modifiers that were considered with justification. These should at least include age, Plasmodium status at baseline, and variables that represent level of transmission/exposure (e.g., spatial confounders).
Statistical analysis Rationale for statistical approach considering study design and distribution of immunological and Plasmodium data. Make particular note of any collinearity issues with immunological data.
Description of all statistical methods, including those used to control for confounding, examine subgroups and interactions (particularly with age) and any sensitivity analyses. Explain how missing data were addressed if relevant.
Details and justification of all data transformations explored during analysis. State any assumptions of linearity in immunological data. State whether categories generated from continuous antibody variables were used as a nominal or ordinal variable (i.e., classified into unordered or ordered qualitative categories).
Results Study participants The numbers of individuals at each stage of the study and any groups excluded from analysis.
The demographic and clinical characteristics of the participants and information on exposures and potential confounders. Indicate the number of participants with missing data for each variable of interest. Summarize follow-up times if applicable and mention changes in incidence of Plasmodium over follow-up. Consider presenting clinical and immunology data according to age group to give the reader a sense of the acquisition of immunity in the study population or by immunological response categories so they can be related to confounders.
Immunological responses and malaria measures Mean (standard deviation) or median (percentiles/range) of values to describe measures of central tendency and the spread of data measured in the study. Do not use inferential measures such as standard errors or confidence intervals.
Details of any quantification of antibody or other concentrations (i.e., titres in µg/ml).
Counts of cases, controls, person-time at risk, risk etc. for each immune response category in addition to effect-measure estimates and results of model fitting.
Risk estimates Unadjusted and adjusted estimates of risk and their precision, e.g., 95% CIs. This will allow the reader to judge by how much, and in what direction, they changed. Make clear which confounders were adjusted for and why they were included. Provide risk estimates for all immunology variables investigated (i.e., responders versus nonresponders and any dose-dependent variables).
Separate estimates for each immune response. Also assess joint effects and interactions between immune responses. Consider both additive and multiplicative scales (i.e., does the combined effect of response A and B add (a+b)% or (a×b)% to risk?). This will help assess the relative contribution of each immune response to protection.
Separate estimates for different lengths of follow-up. E.g., 1, 3, 6, 9, 12 mo.
Report all other analyses done such as subgroups, interactions, and sensitivity analysis.
Discussion Summarise key results in relation to study objectives
Provide limitations of your study.
Give a balanced interpretation of the results considering limitations. Discuss both direction and magnitude of effects and pay particular attention to evidence of no effect versus no evidence of an effect. Outline possible methodological reasons for why the current results may differ from other studies.
Discuss the generalisability of results to other malaria endemic areas.

Items should be addressed in the main body of the manuscript and/or supplementary material. This table has been adapted from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement, which contains a checklist of items that should be addressed in reports of observational studies [74]. The STROBE statement and explanation [73],[74] should also be consulted.