Personalization + prediction
Take, for example, breast cancer. It is an incredibly complex, heterogeneous disease that affects one in eight women. It is curable if detected early. Yet, one-third of women diagnosed with breast cancer eventually die of the disease. With multiple treatment strategies available, providing clinicians personalized information about a woman’s breast cancer may inform decision-making.
In the September issue of the Journal Nuclear Medicine, a group of South Korean researchers showed that pretreatment PET/CT imaging may shed light on a woman’s prognosis. Specifically, SUVmax offers a quantitative measure of lymph node involvement, a figure which, in turn, appears to correlate with a woman’s risk of recurrence.
The study is early but promising. Unlike other measures of lymph node metastasis, PET/CT is noninvasive, and it offers a high degree of accuracy. Ultimately, it could lead to personalized treatment strategies based on a woman’s individual disease.
In other scenarios, risk stratification can inform the use of screening tests that leverage advanced visualization tools.
Consider CT lung cancer screening, which is often a difficult decision. That’s partially because follow-up investigations of detected nodules can be invasive, which may be a dicey proposition for patients with lung conditions. In addition, serial CT screening and follow-up represents fairly significant costs.
The Liverpool Lung Project risk model provides an option to stratify high-risk candidates and predict a person’s five-year risk for lung cancer. When researchers tested the model and used a 5 percent threshold of absolute risk, the model achieved a higher proportion of true-positive classifications than a screen-all approach.
According to authors of the study published Aug. 21 in Annals of Internal Medicine, identification of persons at highest risk for lung cancer, and subsequent targeted application of CT lung cancer screening, will result in a more favorable benefit-harm ratio. An additional benefit is reduced screening costs.
How is your practice applying personalized tools to deliver better patient care? Please let us know.
Lisa Fratt, editor