Biostatistics

The biostatistics group has a pivotal role in sustaining and improving the quality of the quantitative research that is done at OUCRU. We give advice on study conception and design, as well as on data collection; we support the researchers in formulating the model that best answers their research question and in performing the analyses; and we give critical appraisal of how results are communicated and disseminated. We collaborate with all the other OUCRU research groups as well as with the clinical trials unit. Besides that, we enhance the statistical skills of our fellow researchers via both basic and advanced courses on statistical methods.

Our researchers

  • Lam Phung Khanh: post-doc, mostly working on dengue
  • Nhat Le Thanh Hoang: post-doc, general statistical advisor (CNS infections, dengue, enteric infections)
  • Thao Le Thi Phuong: PhD student, working on tuberculous meningitis
  • Van Cao Thao: research assistant, general statistical advisor
  • Vuong Nguyen Lam: research assistant, working on dengue
  • Ronald B. Geskus: group head

Some specific research projects

The construction and validation of models for diagnosis and prognosis.
We combine patient data with clinical and laboratory examinations in a model that helps diagnosing type of disease and/or predicting (clinical) outcomes. For example, using data from a large multi-center study, we want to improve early diagnosis of dengue, and we want to identify individuals with a high risk of progressing to severe dengue disease.  In another study we developed a model and wrote a program to predict mortality in patients with tuberculous meningitis.  Results from such models can be used to adapt clinical management to the individual patient.

The longitudinal development of markers of disease progression.
Often the primary interest is in a clinical outcome like disease, death or cure. Markers of disease progression provide important intermediate information. They may even serve as surrogate study outcome if the clinical outcome needs too long follow-up to observe. Examples of markers of disease progression are platelet counts in patients with dengue, fungal counts in patients with cryptococcal meningitis and plasma sodium level in patients with tuberculous meningitis. Because they reflect disease progression, such markers typically vary over time within individuals. We use statistical models for a proper description of their trajectories and their relation with the clinical outcome.

Modern trial design.
Randomized controlled trials (RCT) are the gold standard for evaluating the efficacy of clinical interventions. They are a fundamental component of OUCRU’s research programme with major ongoing trials in central nervous system infections, HIV opportunistic infections, typhoid fever, dengue, and hand, foot, and mouth disease. We are particularly interested in methods for adaptive clinical trials which may offer a more rational and efficient evaluation of interventions but have not yet been widely established in infectious or tropical diseases.

 –

Publications with important contributions from members of the
biostatistics group

Thao LTP, Heemskerk AD, Geskus RB, et al. (2017). Prognostic models for 9 month mortality in tuberculous meningitis. Clin Infect Dis, 2017.

Le T, Kinh NV, Cuc NTK, et al. (2017). A Trial of Itraconazole or Amphotericin B for HIV-Associated Talaromycosis. N Engl J Med.  Jun 15;376(24):2329-2340.

Carrington LB, Tran BCN, Le NTH, et al. (2018). Field- and clinically derived estimates of wolbachia mediated blocking of dengue virus transmission potential in aedes aegypti mosquitoes. Proc Natl Acad Sci USA. Jan 9;115(2):361-366.

Phung Khanh Lam, Tran Van Ngoc, Tran Thi Thu Thuy, et al. (2017). The value of daily platelet counts for predicting dengue shock syndrome: Results from a prospective observational study of 2301 Vietnamese  children with dengue. Plos Negl Trop Dis; 11(4).

Phung Khanh Lam, Dong Thi Hoai Tam, Nguyen Minh Dung, et al. (2015). A Prognostic Model for Development of Profound Shock among Children Presenting with Dengue Shock Syndrome. PLoS ONE; 10(5).