Statistical analysis plan for the LAKANA trial: a cluster-randomized, placebo-controlled, double-blinded, parallel group, three-arm clinical trial testing the effects of mass drug administration of azithromycin on mortality and other outcomes among 1–11-month-old infants in Mali

Juho Luoma, Laura Adubra, Dagmar Alber, Per Ashorn, Ulla Ashorn, Elaine Cloutman-Green, Fatoumata Diallo, Camilla Ducker, Riku Elovainio, Yue-Mei Fan, Lily Gates, Gwydion Gruffudd, Tiia Haapaniemi, Fadima Haidara, Lotta Hallamaa, Rikhard Ihamuotila, Nigel Klein, Owen Martell, Samba Sow, Taru VehmastoYin Bun Cheung

Tutkimustuotos: ArtikkeliScientificvertaisarvioitu

6 Lataukset (Pure)

Abstrakti

Background: The Large-scale Assessment of the Key health-promoting Activities of two New mass drug administration regimens with Azithromycin (LAKANA) trial in Mali aims to evaluate the efficacy and safety of azithromycin (AZI) mass drug administration (MDA) to 1–11-month-old infants as well as the impact of the intervention on antimicrobial resistance (AMR) and mechanisms of action of azithromycin. To improve the transparency and quality of this clinical trial, we prepared this statistical analysis plan (SAP). Methods/design: LAKANA is a cluster randomized trial that aims to address the mortality and health impacts of biannual and quarterly AZI MDA. AZI is given to 1–11-month-old infants in a high-mortality setting where a seasonal malaria chemoprevention (SMC) program is in place. The participating villages are randomly assigned to placebo (control), two-dose AZI (biannual azithromycin-MDA), and four-dose AZI (quarterly azithromycin-MDA) in a 3:4:2 ratio. The primary outcome of the study is mortality among the intention-to-treat population of 1–11-month-old infants. We will evaluate relative risk reduction between the study arms using a mixed-effects Poisson model with random intercepts for villages, using log link function with person-years as an offset variable. We will model outcomes related to secondary objectives of the study using generalized linear models with considerations on clustering. Conclusion: The SAP written prior to data collection completion will help avoid reporting bias and data-driven analysis for the primary and secondary aims of the trial. If there are deviations from the analysis methods described here, they will be described and justified in the publications of the trial results. Trial registration: ClinicalTrials.gov ID NCT04424511 . Registered on 11 June 2020.

AlkuperäiskieliEnglanti
Artikkeli733
JulkaisuTrials
Vuosikerta24
Numero1
DOI - pysyväislinkit
TilaJulkaistu - jouluk. 2023
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Julkaisufoorumi-taso

  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Pharmacology (medical)

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