Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

The role of biostatisticians in clinical research is to contribute to trial design, by calculating sample size for example, and to help draw correct conclusions from the data, discriminating important information from noise. They are instrumental in the translation of a practical problem into a statistical model, and the translation of the result into practice.

My name is Ronald Geskus, I currently work at OUCRU in Ho Chi Minh City, Vietnam. We are a group of 6 biostatisticians and I am the head of that group. A biostatistician tries to prevent incorrect conclusions to be drawn from the data analysis. We are like the controllers of all of the quantitative analysis data done at OUCRU.

In a clinical trial we want to see whether some new treatment works better than the existing treatment, or maybe works better than no treatment at all, and it may be that the new treatment also has side effects or maybe it doesn’t work at all. Another thing is that a clinical trial in general is very expensive; there are lots of regulations around clinical trials, not without reason, but this requires a lot of logistics as well. So you don’t want to include too many patients, you want to include just enough patients to show that the effect works better. That is done in sample size calculation, finding out how many patients to include, and that is a typical job of a biostatistician.

Clinical trials are a basic example of an explanatory model; you want to explain the effect of the treatment. An observational study is different from a clinical trial: in general the sicker patients are more likely to receive a treatment. In both cases the purpose is explanation: what is the effect of the treatment? So explanation and effect or efficacy is basically the same. Whereas in a prediction model you want to find factors that help predict the outcome.

Research in biostatistics is important because nowadays so many data are collected, and it’s very important to do a proper analysis of these data, and this also holds for medical fields. Many more data are collected nowadays and this will generate a lot of noise. A lot of data is not relevant so it has become more important to find methods that are better to discriminate between signal - important information and noise.

As statisticians, we work at the basic part of the scientific research. We don’t work at bedside, but if you take translational medicine literally, it’s about translation of results into practice. Statisticians also play a role as they know very well the structure behind the model and they are in general very good at explaining results. In general what I like about doing biostatistical research is the translation of a practical problem into a statistical model, and then the translation of the result to practice.

Ronald Geskus

Professor Ronald Geskus heads the biostatistics group at OUCRU. His unit plays an important role in the design and analysis of clinical trials, and devise modern trial designs. Research interests include the construction and validation of models for diagnosis and prediction, models for the development of markers of disease progression, and complex time-to-event data.

More podcasts related to Global Health

Mike English: Health services that deliver for newborns

Global Health

Basic hospital care may be key to saving newborn lives. Professor Mike English outlines a multidisciplinary project engaging policy-makers and practitioners in Kenya. This project demonstrated poor coverage of Nairobi’s 4.25 million population if a sick newborn baby needs quality hospital care. Using novel research approaches the team also identified how severe shortages of nurses contribute to poor quality of care for patients and negatively affect nurses themselves.

Tran Hien: Infectious diseases in the tropics

Global Health

Although incidence of malaria has decreased in Vietnam, the burden of infectious diseases remains high and weighs heavily on the health care system. Clinical research aims to allow investments to go further: findings in the laboratory, tested in clinical trials and then applied to the community, help improve diagnosis and management.

Rogier Van Doorn: Research at OUCRU Hanoi

Global Health

Antibiotics are widely used in Vietnam, leading to widespread antimicrobial resistance. Monitoring antibiotic use helps inform the government to change treatment guidelines and implement antibiotic stewardship programmes. This may also prevent the transmission of resistant bacteria outside the country.

Heiman Wertheim: Clinical research in low and middle-income countries

Global Health

Drug resistant infections are a global crisis and we cannot focus on our own country only. Clinical trials in low and middle income countries where the burden is highest, as well as work with local communities and engagement with policy makers help influence public health policies.

Guy Thwaites: Tuberculosis meningitis

Global Health

Tuberculosis meningitis affects a fractions of TB patients but causes high levels of mortality and morbidity. A recent trial at OUCRU showed that aspirin can greatly improve outcomes. Such trial is typical of the work done in our Vietnam units, where all the research is focussed on improving the outcome for patients directly.

Motiur Rahman: OUCRU laboratory management

Global Health

OUCRU laboratories provide support to the unit’s extensive clinical research programme, from level 2 laboratory to SAPO 4 laboratory for high-risk pathogens responsible for zoonotic infections. Early diagnosis and detection of antimicrobial resistance helps prescribe the right medicine in time, contributing to better patient management.

Raph Hamers: Developing collaborative clinical trials in Indonesia

Global Health

Indonesia is a very populous country with a huge burden of infectious diseases such as TB, malaria, HIV and CNS infections. Running clinical trials requires high levels of expertise, currently developed and strengthened by institutions such as IOCRL (Universities of Indonesia and Oxford Clinical Research laboratory). Better collaborations will also help great ideas make a bigger impact.

Jeremy Day: Central nervous system and HIV infections in Vietnam

Global Health

Brain infections such as meningitis and encephalitis are highly debilitating diseases, and an accurate diagnostic is essential to give patients the best treatment available. For cryptococcal meningitis, clinical trials focus on prevention, for an early diagnosis, and novel ways to use existing treatments or repurpose old drugs.

Abhilasha Karkey: Connecting research with communities in Nepal

Global Health

Antimicrobial resistance is a huge burden in Nepal, particularly in hospitals where many nosocomial infections are caused by resistant pathogens. With limited resources, little infection controls and proper guidelines in place, finding out the main risk factors helps reduce infection rates within a hospital and better target vaccination campaigns.

Juan Carrique-Mas: Antimicrobial resistance in poultry production

Global Health

Many households in Vietnam raise animals for food production, particularly chickens, using large amounts of antimicrobials with no veterinary support, and those antimicrobials find their way into the food chain. The ViParc project conducts intervention trials similar to human clinical trials, to help farmers reduce the level of antimicrobials used when raising chickens.

Translational Medicine

From Bench to Bedside

Ultimately, medical research must translate into improved treatments for patients. At the Nuffield Department of Medicine, our researchers collaborate to develop better health care, improved quality of life, and enhanced preventative measures for all patients. Our findings in the laboratory are translated into changes in clinical practice, from bench to bedside.