Cancer prognosis is of keen interest for patients with cancer, their caregivers, and providers.
Prognostic tools have been developed to guide patient–physician communication and …

Dealing with prognostic uncertainty: the role of prognostic... : Current Opinion in Supportive
and Palliative Care Dealing with prognostic uncertainty: the role of prognostic models and …

Importance Existing prognostic cancer tools include biological and laboratory variables.
However, patients often do not know this information, preventing them from using the tools …

Background There are a variety of ways for quantifying cancer survival with each measure
having advantages and disadvantages. Distinguishing these measures and how they …

Purpose Oncologists may overestimate prognosis for patients with cancer, leading to
delayed or missed conversations about patients' goals and subsequent low-quality end-of …

Objective To review how web-based prognosis tools for cancer patients and clinicians
describe aleatory (risk estimates) and epistemic (imprecision in risk estimates) uncertainties …

Objective Evaluate the completeness of reporting of prognostic prediction models developed
using machine learning methods in the field of oncology. Study design and setting We …

Objectives Assessment of patient-reported outcomes (PROs) in oncology is of critical
importance because it provides unique information that may also predict clinical outcomes …

Background Describe and evaluate the methodological conduct of prognostic prediction
models developed using machine learning methods in oncology. Methods We conducted a …

Importance Machine learning (ML) algorithms can identify patients with cancer at risk of
short-term mortality to inform treatment and advance care planning. However, no ML …