ArticlemedRxiv : the preprint server for health sciences2023
Combining Asian-European Genome-Wide Association Studies of Colorectal Cancer Improves Risk Prediction Across Race and Ethnicity.
Minta Thomas, Yu-Ru Su, Elisabeth A Rosenthal, Lori C Sakoda, Stephanie L Schmit, Maria N Timofeeva, Zhishan Chen, Ceres Fernandez-Rozadilla, Philip J Law, Neil Murphy and 119 more
Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02328677 (ColoCare Transdisciplinary Research in Colorectal Cancer Prognosis), which is not on this map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Statistical Methods for Integrative Genomics in CancerP01CA196569 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI David V Conti · 2016 to 2026
$25.5M
Data sharing: the Colon Cancer Family Registry CohortU01CA167551 · NCI · UNIVERSITY OF MELBOURNE · PI Daniel David BUCHANAN, Steven Gallinger · 2018 to 2026
$16.8M
Leveraging Prospective Cancer Epidemiology Cohorts and Novel Methods to Improve Polygenic Risk ScoresU01CA261339 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fei Chen, David V Conti · 2021 to 2026
$5.2M
Cancer Research UK 12076Cancer Research UK 18927Medical Research Council MC_PC_17228Medical Research Council MC_PC_U127527198Medical Research Council MC_U127527198Medical Research Council MC_UU_00007/1NCI NIH HHS P01 CA196569NCI NIH HHS U01 CA167551NCI NIH HHS U01 CA261339
6 · The paper itself
Abstract
Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expanded PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS were 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1,681-3,651 cases and 8,696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They were significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values<0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Combining Asian-European Genome-Wide Association Studies of Colorectal Cancer Improves Risk Prediction Across Race and Ethnicity. · full record | OpenQuestion