title: Nonlinear mixed effects modeling of gametocyte carriage in patients with uncomplicated malaria.
abstract: BACKGROUND
  Gametocytes are the sexual form of the malaria parasite and the main agents of transmission. While there are several factors that influence host infectivity, the density of gametocytes appears to be the best single measure that is related to the human host's infectivity to mosquitoes. Despite the obviously important role that gametocytes play in the transmission of malaria and spread of anti-malarial resistance, it is common to estimate gametocyte carriage indirectly based on asexual parasite measurements. The objective of this research was to directly model observed gametocyte densities over time, during the primary infection.
  
  
  METHODS
  Of 447 patients enrolled in sulphadoxine-pyrimethamine therapeutic efficacy studies in South Africa and Mozambique, a subset of 103 patients who had no gametocytes pre-treatment and who had at least three non-zero gametocyte densities over the 42-day follow up period were included in this analysis.
  
  
  RESULTS
  A variety of different functions were examined. A modified version of the critical exponential function was selected for the final model given its robustness across different datasets and its flexibility in assuming a variety of different shapes. Age, site, initial asexual parasite density (logged to the base 10), and an empirical patient category were the co-variates that were found to improve the model.
  
  
  CONCLUSIONS
  A population nonlinear modeling approach seems promising and produced a flexible function whose estimates were stable across various different datasets. Surprisingly, dihydrofolate reductase and dihydropteroate synthetase mutation prevalence did not enter the model. This is probably related to a lack of power (quintuple mutations n = 12), and informative censoring; treatment failures were withdrawn from the study and given rescue treatment, usually prior to completion of follow up.
authors.affiliation: Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa. Greg.Distiller@uct.ac.za
authors.forename: Greg B
authors.initials: GB
authors.lastname: Distiller
authors.forename: Francesca
authors.initials: F
authors.lastname: Little
authors.forename: Karen I
authors.initials: KI
authors.lastname: Barnes
mesh_terms: D000818:Animals; D000962:Antimalarials / Q000627:therapeutic use; D002353:Carrier State / Q000469:parasitology / Q000635:transmission; D004338:Drug Combinations; D004351:Drug Resistance; D005500:Follow-Up Studies; D006790:Host-Parasite Interactions; D006801:Humans; D016778:Malaria, Falciparum / Q000188:drug therapy / Q000469:parasitology* / Q000635:transmission; D008954:Models, Biological; D009073:Mozambique; D010963:Plasmodium falciparum / Q000254:growth & development*; D011739:Pyrimethamine / Q000627:therapeutic use; D034101:Sporozoites / Q000254:growth & development*; D013413:Sulfadoxine / Q000627:therapeutic use; D013997:Time Factors
chemical_list: D000962:Antimalarials; D004338:Drug Combinations; C001205:fanasil, pyrimethamine drug combination; D013413:Sulfadoxine; D011739:Pyrimethamine