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Leveraging the power of pooled data for cancer outcomes research
Author(s) -
HughYeun Kiara,
Cheung Winson Y.
Publication year - 2016
Publication title -
cancer communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.119
H-Index - 53
ISSN - 2523-3548
DOI - 10.1186/s40880-016-0132-0
Subject(s) - medicine , clinical trial , nomogram , colorectal cancer , cancer , leverage (statistics) , oncology , clinical study design , informed consent , alternative medicine , pathology , statistics , mathematics
Background Clinical trials continue to be the gold standard for determining the efficacy of novel cancer treatments, but they may also expose participants to the potential risks of unpredictable or severe toxicities. The development of validated tools that better inform patients of the benefits and risks associated with clinical trial participation can facilitate the informed consent process. The design and validation of such instruments are strengthened when we leverage the power of pooled data analysis for cancer outcomes research. Main body In a recent study published in the Journal of Clinical Oncology entitled “Determinants of early mortality among 37,568 patients with colon cancer who participated in 25 clinical trials from the adjuvant colon cancer endpoints database,” using a large pooled analysis of over 30,000 study participants who were enrolled in clinical trials of adjuvant therapy for early‐stage colon cancer, we developed and validated a nomogram depicting the predictors of early cancer mortality. This database of pooled individual‐level data allowed for a comprehensive analysis of poor prognostic factors associated with early death; furthermore, it enabled the creation of a nomogram that was able to reliably capture and quantify the benefit‐to‐risk profile for patients who are considering clinical trial participation. This tool can facilitate treatment decision‐making discussions. Conclusion As China and other Asian countries continue to conduct oncology clinical trials, efforts to collate patient‐level information from these studies into a large data repository should be strongly considered since pooled data can increase future capacity for cancer outcomes research, which, in turn, can enhance patient‐physician discussions and optimize clinical care.

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