Scientific Publications

Manuscripts

Using oncology real-world evidence for quality improvement and discovery: the case for ASCO's CancerLinQ

Future Medicine
Miller et al.

Patient Perspectives on the Ethical Implementation of a Rapid Learning System for Oncology Care

Journal of Oncology Practice
A rapid learning system (RLS) of health care harnesses data generated from routine patient care to create a virtuous cycle of data collection and…

Qualitative Study of Oncologists’ Views on the CancerLinQ Rapid Learning System

JCO Oncology Practice
Mayo et al.

Building a Rapid Learning Health Care System for Oncology: Why CancerLinQ Collects Identifiable Health Information to Achieve Its Vision

Journal of Clinical Oncology
Shah et al.

Building a Rapid Learning Health Care System for Oncology: The Regulatory Framework of CancerLinQ

Journal of Clinical Oncology
Schilsky et al.

Abstracts

Demographics, clinical characteristics, and treatment patterns for patients with BRCA mutated, HER2‐negative early stage breast cancer: a CancerLinQ®…

Miami Breast Cancer Conference 2021
Mokiou S et al.

Treatment patterns and outcomes of hepatocellular carcinoma (HCC) patients (pts) in the CancerLinQ Research Database (CLQ)

2021 Gastrointestinal Cancers Symposium
Kabadi et al

Demographics and clinical characteristics of metastatic colorectal cancer patients treated with bevacizumab-awwb in real-world oncology clinics

2021 Gastrointestinal Cancers Symposium
DeClue et al

Real-world clinical outcomes of patients with BRCA-mutated (BRCAm) HER2-negative metastatic breast cancer: A CancerLinQ® study

San Antonio Breast Cancer Symposium
Miller et al.

Disproportionate impact of COVID-19 disease among racial and ethnic minorities in the U.S. cancer population as seen in CancerLinQ Discovery data.

2020 ASCO Quality Care Symposium
Potter et al.

Impact of curated data on electronic quality eeasure capture rates within CancerLinQ

2020 ASCO Quality Care Symposium
Rios et al.

The relationship between treatment intensity and characteristics of patients with early stage breast cancer

2020 ASCO Quality Care Symposium
Franks et al.

Development of an artificial intelligence model to dynamically predict metastatic recurrence of early-stage breast cancer patients

2020 ASCO Virtual Scientific Program
Vaidya et al.

Identification of transgender people with cancer in electronic health records (EHR): Recommendations based on CancerLinQ observations

2020 ASCO Virtual Scientific Program
Alpert et al.