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AI Takes On Cancer
By Kiko Núñez  |  May 11, 2022
AI Takes On Cancer
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Existing prognostic tools such as nomograms have many advantages in predicting cancer patients’ chances of survival and ability to enjoy a good quality of life, but also tend toward inflexibility and inability to factor in new treatments, new data, and changes in patients’ conditions. AI, however, promises to remedy these shortcomings.

SEVILLE, SPAIN - ‘Doc, how much time do I have left?’ 

‘How will I feel during/after the cancer treatment?’

Oncologists must answer these questions (or similar ones) quite often in their daily routine whenever they communicate a new cancer diagnostic to patients. Those are tough questions indeed, and traditionally the only resources they have to answer them with are their own experience and, in some cases, generalist clinical calculators, also known as nomograms.1 

Before digging deeper into nomograms as a prognostic tool, a brief introduction to overall survival and quality of life concepts in cancer care is necessary. Overall survival is a prognostic factor commonly used in oncology to describe the chances a patient has to stay alive for a set number of years after a cancer diagnosis. There are slight variations of the term to consider different time periods (e.g., one, two, five, or 10 years), and also to consider not only survival, but the chances of remaining disease-free after that time too. 

Quality of life encompasses different aspects of health and wellness from both the physical and psychological standpoints. One of the most commonly used tools to assess patients’ quality of life is the EuroQoL family of questionnaires,2 which addresses the dimensions of mobility, self-care, normal activities, pain/discomfort, and anxiety/depression. Cancer treatment usually involves the prescription of aggressive therapies such as chemotherapy and/or radiotherapy and, depending on the drugs involved and the radiation regime, they have several associated side effects that may hinder a patient’s quality of life to differing degrees of severity. 

Nomograms can be used to predict the chances of a patient surviving beyond a given period of time, or of developing side effects as a result of a cance

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