Modelling gametocytes in the presence of interval-censoring - Takawira, Michaela Faro C (Department of Statistical Sciences, 2022)
Malaria is a parasitic disease that has afflicted many over the years, with Plasmodium falciparum malaria accounting for many deaths. Gametocytes are the sexual form of the parasite responsible for transmitting and spreading malaria from the human host to the mosquito vector. Most studies are designed to measure asexual parasites and hence the measurement intervals are not optimal for measuring gametocytes. The data analysed was obtained from a series of clinical trials conducted between 2002 and 2004 in Mpumalanga, South Africa and Mozambique. As part of the South-East African Combination Antimalarial Therapy (SEACAT) evaluation of the phased introduction of combination antimalarial drug under the Lubombo Spatial Development Initiative. Patients were observed on days 0, 3, 7, 14, 21, 28 and 42, where blood samples were collected and were analysed, providing gametocyte densities and other information. Due to the study design, observing gametocyte profiles was complex due to censoring. Censoring occurs when an event has not been observed, and hence the event time is only partially known. Censoring occurs for various reasons, which include the following. In some instances, a patient may enter a study with gametocytes circulating in their system before enrolling into the study. The time in which gametocytes have emerged is therefore unknown. Under such circumstances, this type of censoring is known as left censoring. Another example of censoring occurs when a patient is lost-to-follow-up or leaves the study before the end of the study period due to treatment failure leaving the gametocyte profile of the patient incomplete, resulting in right censoring. Lastly, besides left and right censoring, the gametocyte data has been affected by interval-censoring. Patients are observed and monitored on specific days; thus, the actual moment of observation of gametocyte emergence or clearance is estimated to have occurred between two observation days. The gametocyte data is thus also characterized by interval-censoring. Given these interesting characteristics of the gametocyte data, this research aims to directly model gametocytes while taking into account censoring.. Researchers often opt to assume the times to events of interest are at the moment of observation (right endpoint of an interval) or midpoint of the interval in which the event is assumed to have occurred. In this research, we also investigate and discuss the impact of ignoring the interval-censored mechanism present in the data and how parameter estimates based on these ad hoc approaches might differ from interval-censored results. Following the above discussion, the research will then apply interval-censored techniques to the data. Several survival analysis models were applied to the gametocyte data. These models included the Cox Proportional Hazards (PH) model, parametric PH model and accelerated failure time models, which were used to illustrate how results may differ based on whether intervalcensoring was taken into account or not. From the analysis, it was observed that the midpoint imputation was a better proxy for interval-censoring compared to the right-imputation method and that ignoring interval censoring had more of an impact on events that occurred during the wider intervals towards the latter part of the observation period. From the clinical perspective, it was found that younger patients who had high levels of baseline asexual parasitemia, quintuple mutations and used sulfadoxine-pyrimethamine were estimated to experience the most prolonged duration of gametocytemia. It was also found that age, treatment and baseline asexual parasitemia influenced whether a patient would develop gametocytes.