Reconsideration of the genetic risk assessment for ethylene oxide exposures

1995 ◽  
Vol 26 (3) ◽  
pp. 189-202 ◽  
Author(s):  
R. Julian Preston ◽  
Timothy R. Fennell ◽  
A. Philip Leber ◽  
Robert L. Sielken ◽  
James A. Swenberg
Keyword(s):  
Risk Assessment ◽  
Ethylene Oxide ◽  
Genetic Risk ◽  
Genetic Risk Assessment

Genetic risk assessment for hereditary renal cell carcinoma: Clinical consensus statement

Cancer ◽  
2021 ◽  
Author(s):  
Gennady Bratslavsky ◽  
Neil Mendhiratta ◽  
Michael Daneshvar ◽  
James Brugarolas ◽  
Mark W. Ball ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Genetic Risk ◽  
Renal Cell ◽  
Consensus Statement ◽  
Genetic Risk Assessment

Genetic Risk Assessment Coping Evaluation

2010 ◽  
Author(s):  
C. Phelps ◽  
P. Bennett ◽  
H. Jones ◽  
K. Hood ◽  
K. Brain ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Genetic Risk ◽  
Genetic Risk Assessment

Evaluation of cohort diversity in development and validation studies of hereditary cancer genetic risk assessment models.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10600-10600
Author(s):  
Amanda Gammon ◽  
Ambreen Khan ◽  
Joanne M. Jeter
Keyword(s):  
Risk Assessment ◽  
Validation Studies ◽  
Genetic Risk ◽  
External Validation ◽  
Ashkenazi Jewish ◽  
Genetic Risk Assessment ◽  
Internal Validation ◽  
Risk Assessment Models ◽  
Race Ethnicity ◽  
Development And Validation

10600 Background: Multiple models estimate a person’s chance of harboring a pathogenic variant increasing cancer risk. Some pathogenic variants are more common in individuals from specific ancestries, such as the BRCA1 and BRCA2 founder variants in Ashkenazi Jews. Yet data remains limited on the larger variant spectrum seen among people of different ancestral backgrounds and whether or not the pathogenic variant frequency differs in many populations. Due to this, it is important that genetic risk assessment models be validated in a diverse cohort including Black, Indigenous, People of Color (BIPOC). Methods: A literature search was conducted to identify published development and validation studies for the following genetic risk assessment models: BRCAPRO, MMRPRO, CanRisk/BOADICEA, Tyrer-Cuzick, and PREMM. Validation studies that only evaluated the cancer risk prediction capabilities of the models (and not the genetic variant risk prediction) were excluded. The following participant information was abstracted from each study: total number of participants, gender, race, and ethnicity. Authors were contacted to obtain missing information (if available). Results: 12 development and 12 validation studies of the genetic risk assessment models BRCAPRO, MMRPRO, CanRisk/BOADICEA, Tyrer-Cuzick, and PREMM were abstracted. Of the validation studies, five were internal validation studies conducted by the model developers, and seven were external validation studies. Four external validation studies compared multiple models. 75% (18/24) of papers did not include reporting of participant race or ethnicity information in their published reports. External validation studies (4/7, 57%) more often reported participant race/ethnicity than development (0/12, 0%) or internal validation (2/5, 40%) studies. The external validation studies for BRCAPRO reporting race/ethnicity information involved cohorts that ranged from 50-51% non-Ashkenazi Jewish white, 28% African American, 1% Asian, 2-49% Hispanic, and 19-42% Ashkenazi Jewish. The external validation studies for MMRPRO and PREMM reporting race/ethnicity information involved cohort that ranged from 0-82% white, 4-100% Asian, 7% Black, and 7% Hispanic. Conclusions: Increased reporting of participant ancestry and ethnicity is needed in the development and validation studies of genetic risk assessment models. BRCAPRO’s validation cohorts have included a higher percentage of Hispanic and Black/African American participants, while MMRPRO and PREMM have been validated in a higher percentage of Asian participants. As debate continues about the utility of currently used racial categories in genetics research, it will be important to determine how best to report on participant diversity. These findings highlight the continued need for genetics researchers to engage BIPOC and identify ways to diversify their participant cohorts.

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