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Issue 02

Winter 2018

The applied mathematician will see you now

Weang Kee Ho has no white coat and doesn’t own a stethoscope. But she does hold a doctorate in statistics and a passionate desire to fight breast cancer

Sadly, statistics tell us that pretty much everyone reading this magazine will have come up against cancer: either among their family and friends, or indeed personally.

But while, looking backwards, cancer statistics often give a grim message, Dr Ho wants to use statistics to focus on the future – and to engineer much happier outcomes.

From Nottingham’s Malaysia campus, she explains: “I’m a mathematician and a statistician, and I use statistics to answer important scientific questions. I’m working with scientists at Cancer Research Malaysia, Singapore and United Kingdom, to see whether we can give Malaysian women much better chances in the face of breast cancer.”

In short, the collaborative efforts aim to create a prediction tool that identifies women who are most at risk. “I’m hoping that the tool can give every Malaysian woman a personal score to accurately tell her how at risk she might be – and, if needed, to point her into the screening programme before the disease gets a chance to develop.” said Dr Ho.

I’m hoping that the tool can give every Malaysian woman a personal score to accurately tell her how at risk she might be.

Dr Weang Kee Ho

Breast cancer is a complex disease. Certain genes, such as BRCA1 and BRCA2 are known to increase the risk in affected women by up to 80%. But only a small percentage of patients come into this category. For the majority, it is believed that breast cancer is caused by a combination of smaller, much more common susceptibility variants, which go hand in hand with environmental factors such as lifestyle.

The good news is that Dr Ho is collaborating with a project that has already gathered a significant knowledge base of patient data. Established some years ago, it is the largest breast cancer study in Malaysia, led by Professor Teo Soo-Hwang OBE of Cancer Research Malaysia. Dr Ho says: “The search for a better breast cancer screening strategy for women would not be possible without the contribution from the participants of breast cancer studies as well as large team of doctors and scientists. Professor Soo-Hwang and her team are currently working on rare genetic mutation that may be associated with elevated risk.

“Taken together, with our collaborative project that aims to find the combination of common susceptibility variants that could pose the most risk for some women, this work could contribute to an understanding of whether we can target expensive mammography screening at women who are at highest risk of getting the disease.”

Historically, Malaysian women have a low rate of breast cancer compared to Caucasian women, but with a shift towards a more westernised lifestyle and diet, the disease is increasing at an alarming rate.

Yet health resources are stretched. Malaysia cannot afford to screen every woman, and while over 50s are encouraged to get a mammogram, almost half of breast cancer patients are under 50 when they are diagnosed. With this tool, the hope is that resources can be targeted much more effectively, by bringing a more tailored approach to screening.

Dr Ho adds: “I am very proud to be part of the global team that is working towards reducing the cancer burden in Malaysia. I hope that one day the fruits of our research will empower women to have better control of their health.”

Facts

  • In Malaysia, around 1 in 19 women will develop breast cancer 
  • In the next ten years, the incidence of breast cancer in Asia is projected to rise by 50%
  • In some Asian countries, five-year survival is just 49% due to late presentation, compared to 89% in Western countries
 

Weang Kee Ho

Dr Weang Kee Ho is a Lecturer and Researcher in Statistics. She joined the Department of Applied Mathematics at the University of Nottingham Malaysia in June 2013. Her research focuses on the area of statistical genetics, specifically in the application of statistical methods to genetic data for identifying and characterising genetic variants associated with disease.


Vision Nottingham Inspires The applied mathematician will see you now
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