Handling uncertainty using features from pathology: opportunities in primary care data for developing high risk cancer survival methods

12/17/2020
by   Goce Ristanoski, et al.
0

More than 144 000 Australians were diagnosed with cancer in 2019. The majority will first present to their GP symptomatically, even for cancer for which screening programs exist. Diagnosing cancer in primary care is challenging due to the non-specific nature of cancer symptoms and its low prevalence. Understanding the epidemiology of cancer symptoms and patterns of presentation in patient's medical history from primary care data could be important to improve earlier detection and cancer outcomes. As past medical data about a patient can be incomplete, irregular or missing, this creates additional challenges when attempting to use the patient's history for any new diagnosis. Our research aims to investigate the opportunities in a patient's pathology history available to a GP, initially focused on the results within the frequently ordered full blood count to determine relevance to a future high-risk cancer prognosis, and treatment outcome. We investigated how past pathology test results can lead to deriving features that can be used to predict cancer outcomes, with emphasis on patients at risk of not surviving the cancer within 2-year period. This initial work focuses on patients with lung cancer, although the methodology can be applied to other types of cancer and other data within the medical record. Our findings indicate that even in cases of incomplete or obscure patient history, hematological measures can be useful in generating features relevant for predicting cancer risk and survival. The results strongly indicate to add the use of pathology test data for potential high-risk cancer diagnosis, and the utilize additional pathology metrics or other primary care datasets even more for similar purposes.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/01/2021

Predicting erectile dysfunction after treatment for localized prostate cancer

While the 10-year survival rate for localized prostate cancer patients i...
research
08/06/2018

Improved survival of cancer patients admitted to the ICU between 2002 and 2011 at a U.S. teaching hospital

Over the past decades, both critical care and cancer care have improved ...
research
07/21/2023

A Deep Learning Approach for Overall Survival Prediction in Lung Cancer with Missing Values

One of the most challenging fields where Artificial Intelligence (AI) ca...
research
02/21/2018

Clinically verified pre-screening for cancer using web search queries: Initial results

Search engine queries have been demonstrated to be a useful signal for s...
research
10/27/2019

A novel high-power test for continuous outcomes truncated by death

Patient reported outcomes including quality of life (QoL) assessments ar...

Please sign up or login with your details

Forgot password? Click here to reset