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Mahar, Alyson

https://orcid.org/0000-0002-6862-3760

Mayo Clinic

Queen's University

Citations 2

Personalizing prognosis in colorectal cancer: A systematic review of the quality and nature of clinical prognostic tools for survival outcomes
Mahar, Alyson , Compton, Carolyn C. , Halabi, Susan , Hess, Kenneth R. , Weiser, Martin R. , Groome, Patti A. , Mahar, Alyson L , Compton, Carolyn, Halabi, Susan

Journal of Surgical Oncology | August 2, 2017 | Volume: 116 | Issue: 8 | Pages: 969-982

10.1002/jso.24774 Get It

Integrating diverse types of prognostic information into accurate, individualized estimates of outcome in colorectal cancer is challenging. Significant heterogeneity in colorectal cancer prognostication tool quality exists. Methodology is incompletely or inadequately reported. Evaluations of the internal or external validity of the prognostic model are rarely performed. Prognostication tools are important devices for patient management, but tool reliability is compromised by poor quality. Guidance for future development of prognostication tools in colorectal cancer is needed.
American Joint Committee on Cancer acceptance criteria for inclusion of risk models for individualized prognosis in the practice of precision medicine
Kattan, Michael W. , Hess, Kenneth R. , Amin, Mahul B. , Lü, Ying , Moons, Karl G.M., Gershenwald, Jeffrey E. , Gimotty, Phyllis A. , Guinney, Justin , Halabi, Susan , Lazar, Alexander J. , Mahar, Alyson , Weiser, Martin R. , Compton, Carolyn C. , Core, members of the AJCC Precision Medicine, Compton, Carolyn, Patel, Tushar P , Sargent, Daniel J. , Core, members of the AJCC Precision Medicine, Mahar, Alyson L , Lazar, Alexander J , Halabi, Susan , Lu, Ying , Kattan, Michael W

CA: A Cancer Journal for Clinicians | January 19, 2016 | Volume: 66 | Issue: 5 | Pages: 370-374

10.3322/caac.21339 Get It

The American Joint Committee on Cancer (AJCC) has increasingly recognized the need for more personalized probabilistic predictions than those delivered by ordinal staging systems, particularly through the use of accurate risk models or calculators. However, judging the quality and acceptability of a risk model is complex. The AJCC Precision Medicine Core conducted a 2‐day meeting to discuss characteristics necessary for a quality risk model in cancer patients. More specifically, the committee established inclusion and exclusion criteria necessary for a risk model to potentially be endorsed by the AJCC. This committee reviewed and discussed relevant literature before creating a checklist unique to this need of AJCC risk model endorsement. The committee identified 13 inclusion and 3 exclusion criteria for AJCC risk model endorsement in cancer. The emphasis centered on performance metrics, implementation clarity, and clinical relevance. The facilitation of personalized probabilistic predictions for cancer patients holds tremendous promise, and these criteria will hopefully greatly accelerate this process. Moreover, these criteria might be useful for a general audience when trying to judge the potential applicability of a published risk model in any clinical domain. CA Cancer J Clin 2016;66:370–374. © 2016 American Cancer Society.