Assessment of Family History Information in Case-Control Cancer Studies

1991 ◽  
Vol 133 (8) ◽  
pp. 757-765 ◽  
Author(s):  
Pamela H. Phillips ◽  
Martha S. Linet ◽  
Emily L. Harris
Keyword(s):  
Family History ◽  
Case Control ◽  
Family History Information ◽  
History Information ◽  
Cancer Studies

scholarly journals Leveraging Family History in Case-Control Analyses of Rare Variation

2019 ◽  
Author(s):  
Claudia R. Solis-Lemus ◽  
S. Taylor Fischer ◽  
Andrei Todor ◽  
Cuining Liu ◽  
Elizabeth J. Leslie ◽  
...  
Keyword(s):  
Family History ◽  
Rare Variant ◽  
Cleft Lip And Palate ◽  
Association Studies ◽  
Case Control ◽  
Outcome Variable ◽  
Family History Information ◽  
Rare Variant Association ◽  
Rare Variation ◽  
History Information

AbstractStandard methods for case-control association studies of rare variation often treat disease outcome as a dichotomous phenotype. However, both theoretical and experimental studies have demonstrated that subjects with a family history of disease can be enriched for risk variation relative to subjects without such history. Assuming family history information is available, this observation motivates the idea of replacing the standard dichotomous outcome variable used in case-control studies with a more informative ordinal outcome variable that distinguishes controls (0), sporadic cases (1), and cases with a family history (2), with the expectation that we should observe increasing number of risk variants with increasing category of the ordinal variable. To leverage this expectation, we propose a novel rare-variant association test that incorporates family history information based on our previous GAMuT framework (Broadaway et al., 2016) for rare-variant association testing of multivariate phenotypes. We use simulated data to show that, when family history information is available, our new method outperforms standard rare-variant association methods like burden and SKAT tests that ignore family history. We further illustrate our method using a rare-variant study of cleft lip and palate.

scholarly journals Leveraging Family History in Case-Control Analyses of Rare Variation

Genetics ◽  
2019 ◽  
Vol 214 (2) ◽  
pp. 295-303
Author(s):  
Claudia R. Solis-Lemus ◽  
S. Taylor Fischer ◽  
Andrei Todor ◽  
Cuining Liu ◽  
Elizabeth J. Leslie ◽  
...  
Keyword(s):  
Family History ◽  
Rare Variant ◽  
Cleft Lip And Palate ◽  
Association Studies ◽  
Case Control ◽  
Outcome Variable ◽  
Family History Information ◽  
Rare Variant Association ◽  
Rare Variation ◽  
History Information

Standard methods for case-control association studies of rare variation often treat disease outcome as a dichotomous phenotype. However, both theoretical and experimental studies have demonstrated that subjects with a family history of disease can be enriched for risk variation relative to subjects without such history. Assuming family history information is available, this observation motivates the idea of replacing the standard dichotomous outcome variable used in case-control studies with a more informative ordinal outcome variable that distinguishes controls (0), sporadic cases (1), and cases with a family history (2), with the expectation that we should observe increasing number of risk variants with increasing category of the ordinal variable. To leverage this expectation, we propose a novel rare-variant association test that incorporates family history information based on our previous GAMuT framework for rare-variant association testing of multivariate phenotypes. We use simulated data to show that, when family history information is available, our new method outperforms standard rare-variant association methods, like burden and SKAT tests, that ignore family history. We further illustrate our method using a rare-variant study of cleft lip and palate.

Use of Family History Information for Neural Tube Defect Prevention

2011 ◽  
Vol 42 (5) ◽  
pp. 296-308
Author(s):  
Ridgely Fisk Green ◽  
Joan Ehrhardt ◽  
Margaret F. Ruttenber ◽  
Richard S. Olney
Keyword(s):  
Family History ◽  
Neural Tube ◽  
Neural Tube Defect ◽  
Family History Information ◽  
History Information ◽  
Defect Prevention

Identification and Referral of Families at High Risk for Cancer Susceptibility

2002 ◽  
Vol 20 (2) ◽  
pp. 528-537 ◽  
Author(s):  
Kevin M. Sweet ◽  
Terry L. Bradley ◽  
Judith A. Westman
Keyword(s):  
Risk Assessment ◽  
Family History ◽  
High Risk ◽  
Computer Program ◽  
Medical Record ◽  
Comprehensive Cancer Center ◽  
Family History Information ◽  
Cancer History ◽  
History Information ◽  
Family Cancer History

PURPOSE: Obtainment of family history and accurate assessment is essential for the identification of families at risk for hereditary cancer. Our study compared the extent to which the family cancer history in the physician medical record reflected that entered by patients directly into a touch-screen family history computer program. PATIENTS AND METHODS: The study cohort consisted of 362 patients seen at a comprehensive cancer center ambulatory clinic over a 1-year period who voluntarily used the computer program and were a mixture of new and return patients. The computer entry was assessed by genetics staff and then compared with the medical record for corroboration of family history information and appropriate physician risk assessment. RESULTS: Family history information from the medical record was available for comparison to the computer entry in 69%. It was most often completed on new patients only and not routinely updated. Of the 362 computer entries, 101 were assigned to a high-risk category. Evidence in the records confirmed 69 high-risk individuals. Documentation of physician risk assessment (ie, notation of significant family cancer history or hereditary risk) was found in only 14 of the high-risk charts. Only seven high-risk individuals (6.9%) had evidence of referral for genetic consultation. CONCLUSION: This study demonstrates the need to collect family history information on all new and established patients in order to perform adequate cancer risk assessment. The lack of identification of patients at highest risk seems to be directly correlated with insufficient data collection, risk assessment, and documentation by medical staff.

scholarly journals Family history information extraction via deep joint learning

2019 ◽  
Vol 19 (S10) ◽  
Author(s):  
Xue Shi ◽  
Dehuan Jiang ◽  
Yuanhang Huang ◽  
Xiaolong Wang ◽  
Qingcai Chen ◽  
...  
Keyword(s):  
Family History ◽  
Language Processing ◽  
Family Members ◽  
Decision Making Process ◽  
Family History Information ◽  
Health Records ◽  
Joint Learning ◽  
Clinical Text ◽  
History Information ◽  
Entity Identification

Abstract Background Family history (FH) information, including family members, side of family of family members (i.e., maternal or paternal), living status of family members, observations (diseases) of family members, etc., is very important in the decision-making process of disorder diagnosis and treatment. However FH information cannot be used directly by computers as it is always embedded in unstructured text in electronic health records (EHRs). In order to extract FH information form clinical text, there is a need of natural language processing (NLP). In the BioCreative/OHNLP2018 challenge, there is a task regarding FH extraction (i.e., task1), including two subtasks: (1) entity identification, identifying family members and their observations (diseases) mentioned in clinical text; (2) family history extraction, extracting side of family of family members, living status of family members, and observations of family members. For this task, we propose a system based on deep joint learning methods to extract FH information. Our system achieves the highest F1- scores of 0.8901 on subtask1 and 0.6359 on subtask2, respectively.

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