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Predictive Models of Survival in Patients with Advanced Cancer

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Author(s): Eman Al Duhaiby | Jocelyn Pang | Sheldon Kwok | Edward Chow

Journal: The Asia-Pacific Journal of Oncology & Hematology
ISSN 1759-6637

Volume: 2;
Issue: 1;
Start page: 121;
Date: 2010;
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Keywords: prognostic models | prediction models | prognostic factors | survival probability

ABSTRACT
Accurate prognosis is necessary for terminally ill patients and their families to plan remaining time realistically and use available end-of-life resources effectively. Physicians also value this information in determining appropriate treatment plans. Nonetheless, predicting life expectancy is a difficult task. Clinical prediction of survival (CPS) has been extensively studied in recent decades and is found to be inaccurately optimistic. The actuarial estimation of survival employs prognostic factors of survival probability. These prognostic variables, which may sometimes include CPS, can be evaluated to develop prediction models for different populations and settings. This article gives an overview of the current issues of CPS as well as what the literature recognizes as important prognostic factors in cancer patients: symptoms, performance status, quality of life, and laboratory measures. It also provides details regarding the possible concerns and useful applications of several well-validated prediction models, both cancer specific and non-cancer specific. As prognostic models of survival have proven themselves in the literature to successfully aid in prognosis formulation, we suggest that health care providers familiarize themselves with existing models that may be specific to certain patient groups and clinical environments.

Tango Rapperswil
Tango Rapperswil

    
RPA Switzerland

Robotic Process Automation Switzerland