Predicting cancer prognosis using interactive online tools: a systematic review and implications for cancer care providers
BA Rabin, B Gaglio, T Sanders, L Nekhlyudov… - … , biomarkers & prevention, 2013 - AACR
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 …
Prognostic tools have been developed to guide patient–physician communication and …
Dealing with prognostic uncertainty: the role of prognostic models and websites for patients with advanced cancer
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 …
and Palliative Care Dealing with prognostic uncertainty: the role of prognostic models and …
Variability in predictions from online tools: a demonstration using internet-based melanoma predictors
EC Zabor, D Coit, JE Gershenwald… - Annals of surgical …, 2018 - Springer
Background Prognostic models are increasingly being made available online, where they
can be publicly accessed by both patients and clinicians. These online tools are an …
can be publicly accessed by both patients and clinicians. These online tools are an …
Development and validation of a prognostic survival model with patient-reported outcomes for patients with cancer
H Seow, P Tanuseputro, L Barbera, C Earle… - JAMA Network …, 2020 - jamanetwork.com
Importance Existing prognostic cancer tools include biological and laboratory variables.
However, patients often do not know this information, preventing them from using the tools …
However, patients often do not know this information, preventing them from using the tools …
Clinician perspectives on machine learning prognostic algorithms in the routine care of patients with cancer: a qualitative study
Purpose Oncologists may overestimate prognosis for patients with cancer, leading to
delayed or missed conversations about patients' goals and subsequent low-quality end-of …
delayed or missed conversations about patients' goals and subsequent low-quality end-of …
InterPreT cancer survival: A dynamic web interactive prediction cancer survival tool for health-care professionals and cancer epidemiologists
Background There are a variety of ways for quantifying cancer survival with each measure
having advantages and disadvantages. Distinguishing these measures and how they …
having advantages and disadvantages. Distinguishing these measures and how they …
Communicating uncertainty in cancer prognosis: a review of web-based prognostic tools
Objective To review how web-based prognosis tools for cancer patients and clinicians
describe aleatory (risk estimates) and epistemic (imprecision in risk estimates) uncertainties …
describe aleatory (risk estimates) and epistemic (imprecision in risk estimates) uncertainties …
[HTML][HTML] Patient-reported outcomes as independent prognostic factors for survival in oncology: systematic review and meta-analysis
F Efficace, GS Collins, F Cottone, JM Giesinger… - Value in Health, 2021 - Elsevier
Objectives Assessment of patient-reported outcomes (PROs) in oncology is of critical
importance because it provides unique information that may also predict clinical outcomes …
importance because it provides unique information that may also predict clinical outcomes …
[HTML][HTML] Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved
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 …
using machine learning methods in the field of oncology. Study design and setting We …
[HTML][HTML] Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review
Background Describe and evaluate the methodological conduct of prognostic prediction
models developed using machine learning methods in oncology. Methods We conducted a …
models developed using machine learning methods in oncology. Methods We conducted a …