Family health history: underused for actionable risk assessment

Aspects and outcomes of surveillance for individuals at high-risk of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related deaths and is associated with a poor prognosis. The majority of these cancers are detected at a late stage, contributing to the bad prognosis. This underscores the need for novel, enhanced early detection strategies to improve the outcomes. While population-based screening is not recommended due to the relatively low incidence of PDAC, surveillance is recommended for individuals at high risk for PDAC due to their increased incidence of the disease. However, the outcomes of pancreatic cancer surveillance in high-risk individuals are not sorted out yet. In this review, we will address the identification of individuals at high risk for PDAC, discuss the objectives and targets of surveillance, outline how surveillance programs are organized, summarize the outcomes of high-risk individuals undergoing pancreatic cancer surveillance, and conclude with a future perspective on pancreatic cancer surveillance and novel developments.

Leveraging Electronic Health Record Data to Understand Gaps Underlying the Underdiagnosis of Lynch Syndrome

Using the electronic health record to address the underdiagnosis of Lynch syndrome.

The Health History of First-Degree Relatives' Dyslipidemia Can Affect Preferences and Intentions following the Return of Genomic Results for Monogenic Familial Hypercholesterolemia

Genetic testing is key in modern healthcare, particularly for monogenic disorders such as familial hypercholesterolemia. This Tohoku Medical Megabank Project study explored the impact of first-degree relatives' dyslipidemia history on individual responses to familial hypercholesterolemia genomic results. Involving 214 participants and using Japan's 3.5KJPN genome reference panel, the study assessed preferences and intentions regarding familial hypercholesterolemia genetic testing results. The data revealed a significant inclination among participants with a family history of dyslipidemia to share their genetic test results, with more than 80% of participants intending to share positive results with their partners and children and 98.1% acknowledging the usefulness of positive results for personal health management. The study underscores the importance of family health history in genetic-testing perceptions, highlighting the need for family-centered approaches in genetic counseling and healthcare. Notable study limitations include the regional scope and reliance on questionnaire data. The study results emphasize the association between family health history and genetic-testing attitudes and decisions.

Barriers and facilitators to the implementation of family cancer history collection tools in oncology clinical practices

INTRODUCTION

This study aimed to identify barriers and facilitators to the implementation of family cancer history (FCH) collection tools in clinical practices and community settings by assessing clinicians' perceptions of implementing a chatbot interface to collect FCH information and provide personalized results to patients and providers.

OBJECTIVES

By identifying design and implementation features that facilitate tool adoption and integration into clinical workflows, this study can inform future FCH tool development and adoption in healthcare settings.

MATERIALS AND METHODS

Quantitative data were collected using survey to evaluate the implementation outcomes of acceptability, adoption, appropriateness, feasibility, and sustainability of the chatbot tool for collecting FCH. Semistructured interviews were conducted to gather qualitative data on respondents' experiences using the tool and recommendations for enhancements.

RESULTS

We completed data collection with 19 providers (n = 9, 47%), clinical staff (n = 5, 26%), administrators (n = 4, 21%), and other staff (n = 1, 5%) affiliated with the NCI Community Oncology Research Program. FCH was systematically collected using a wide range of tools at sites, with information being inserted into the patient's medical record. Participants found the chatbot tool to be highly acceptable, with the tool aligning with existing workflows, and were open to adopting the tool into their practice.

DISCUSSION AND CONCLUSIONS

We further the evidence base about the appropriateness of scripted chatbots to support FCH collection. Although the tool had strong support, the varying clinical workflows across clinic sites necessitate that future FCH tool development accommodates customizable implementation strategies. Implementation support is necessary to overcome technical and logistical barriers to enhance the uptake of FCH tools in clinical practices and community settings.

Does genetic testing offer utility as a supplement to traditional family health history intake for inherited disease risk?

CONTENT

This study examines the potential utility of genetic testing as a supplement to family health history to screen for increased risk of inherited disease. Medical conditions are often misreported or misunderstood, especially those related to different forms of cardiac disease (arrhythmias vs. structural heart disease vs. coronary artery disease), female organ cancers (uterine vs. ovarian vs. cervical), and type of cancer (differentiating primary cancer from metastases to other organs). While these nuances appear subtle, they can dramatically alter medical management. For example, different types of cardiac failure (structural, arrhythmia, and coronary artery disease) have inherited forms that are managed with vastly different approaches.

METHODS

Using a dataset of over 6,200 individuals who underwent genetic screening, we compared the ability of genetic testing and traditional family health history to identify increased risk of inherited disease. A further, in-depth qualitative study of individuals for whom risk identified through each method was discordant, explored whether this discordance could be addressed through changes in family health history intake.

FINDINGS

Of 90 individuals for whom genetic testing indicated significant increased risk for inherited disease, two-thirds (66%) had no corroborating family health history. Specifically, we identify cardiomyopathy, arrhythmia, and malignant hyperthermia as conditions for which discordance between genetic testing and traditional family health history was greatest, and familial hypercholesterolaemia, Lynch syndrome, and hereditary breast and ovarian cancer as conditions for which greater concordance existed.

CONCLUSION

We conclude that genetic testing offers utility as a supplement to traditional family health history intake over certain conditions.

Predicting personal cardiovascular disease risk based on family health history: Development of expert-based family criteria for the general population

In inherited and familial cardiovascular diseases (CVDs), relatives without current symptoms can still be at risk for early and preventable cardiovascular events. One way to help people evaluate their potential risk of CVD is through a risk-assessment tool based on family health history. However, family criteria including inherited CVD risk to be used by laypersons are non-existent. In this project, we employed a qualitative study design to develop expert-based family criteria for use in individual risk assessment. In the first phase of the project, we identified potential family criteria through an online focus group with physicians with expertise in monogenic and/or multifactorial CVDs. The family criteria from phase one were then used as input for a three-round Delphi procedure carried out in a larger group of expert physicians to reach consensus on appropriate criteria. This led to consensus on five family criteria that focus on cardiovascular events at young age (i.e., sudden death, any CVD, implantable cardioverter-defibrillator, aortic aneurysm) and/or an inherited CVD in one or more close relatives. We then applied these family criteria to a high-risk cohort from a clinical genetics department and demonstrated that they have substantial diagnostic accuracy. After further evaluation in a general population cohort, we decided to only use the family criteria for first-degree relatives. We plan to incorporate these family criteria into a digital tool for easy risk assessment by the public and, based on expert advice, will develop supporting information for general practitioners to act upon potential risks identified by the tool. Results from an expert focus group, a Delphi method in a larger group of experts, and evaluation in two cohorts were used to develop family criteria for assessing cardiovascular disease risk based on family health history for a digital risk-prediction tool for use by the general population. CVD Cardiovascular disease, ICD Implantable cardioverter defibrillator, TAA Thoracic aortic aneurysm, AAA Abdominal aortic aneurysm.

Acquisition of a Lexicon for Family History Information: Bidirectional Encoder Representations From Transformers-Assisted Sublanguage Analysis

BACKGROUND

A patient's family history (FH) information significantly influences downstream clinical care. Despite this importance, there is no standardized method to capture FH information in electronic health records and a substantial portion of FH information is frequently embedded in clinical notes. This renders FH information difficult to use in downstream data analytics or clinical decision support applications. To address this issue, a natural language processing system capable of extracting and normalizing FH information can be used.

OBJECTIVE

In this study, we aimed to construct an FH lexical resource for information extraction and normalization.

METHODS

We exploited a transformer-based method to construct an FH lexical resource leveraging a corpus consisting of clinical notes generated as part of primary care. The usability of the lexicon was demonstrated through the development of a rule-based FH system that extracts FH entities and relations as specified in previous FH challenges. We also experimented with a deep learning-based FH system for FH information extraction. Previous FH challenge data sets were used for evaluation.

RESULTS

The resulting lexicon contains 33,603 lexicon entries normalized to 6408 concept unique identifiers of the Unified Medical Language System and 15,126 codes of the Systematized Nomenclature of Medicine Clinical Terms, with an average number of 5.4 variants per concept. The performance evaluation demonstrated that the rule-based FH system achieved reasonable performance. The combination of the rule-based FH system with a state-of-the-art deep learning-based FH system can improve the recall of FH information evaluated using the BioCreative/N2C2 FH challenge data set, with the F1 score varied but comparable.

CONCLUSIONS

The resulting lexicon and rule-based FH system are freely available through the Open Health Natural Language Processing GitHub.

Returning integrated genomic risk and clinical recommendations: The eMERGE study

PURPOSE

Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.

METHODS

To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results.

RESULTS

GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.

CONCLUSION

Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Association between familial aggregation of chronic kidney disease and its incidence and progression

This study aimed to examine the association between familial aggregation of chronic kidney disease (CKD) and risk of CKD development and its progression. This nationwide family study comprised 881,453 cases with newly diagnosed CKD between 2004 and 2017 and 881,453 controls without CKD matched by age and sex, using data from the Korean National Health Insurance Service with linkage to the family tree database. The risks of CKD development and disease progression, defined as an incident end-stage renal disease (ESRD), were evaluated. The presence of any affected family member with CKD was associated with a significantly higher risk of CKD with adjusted ORs (95% CI) of 1.42 (1.38-1.45), 1.50 (1.46-1.55), 1.70 (1.64-1.77), and 1.30 (1.27-1.33) for individuals with affected parents, offspring, siblings, and spouses, respectively. In Cox models conducted on patients with predialysis CKD, risk of incident ESRD was significantly higher in those with affected family members with ESRD. The corresponding HRs (95% CI) were 1.10 (1.05-1.15), 1.38 (1.32-1.46), 1.57 (1.49-1.65), and 1.14 (1.08-1.19) for individuals listed above, respectively. Familial aggregation of CKD was strongly associated with a higher risk of CKD development and disease progression to ESRD.

Expanding Family Health History to Include Family Medication History

The collection of family health history (FHH) is an essential component of clinical practice and an important piece of data for patient risk assessment. However, family history data have generally been limited to diseases and have not included medication history. Family history was a key component of early pharmacogenetic research, confirming the role of genes in drug response. With the substantial number of known pharmacogenes, many affecting response to commonly prescribed medications, and the availability of clinical pharmacogenetic (PGx) tests and guidelines for interpretation, the collection of family medication history can inform testing decisions. This paper explores the roots of family-based pharmacogenetic studies to confirm the role of genes in these complex phenotypes and the benefits and challenges of collecting family medication history as part of family health history intake.

Implementation-effectiveness trial of systematic family health history based risk assessment and impact on clinical disease prevention and surveillance activities

BACKGROUND

Systematically assessing disease risk can improve population health by identifying those eligible for enhanced prevention/screening strategies. This study aims to determine the clinical impact of a systematic risk assessment in diverse primary care populations.

METHODS

Hybrid implementation-effectiveness trial of a family health history-based health risk assessment (HRA) tied to risk-based guideline recommendations enrolling from 2014-2017 with 12 months of post-intervention survey data and 24 months of electronic medical record (EMR) data capture.

SETTING

19 primary care clinics at four geographically and culturally diverse U.S. healthcare systems.

PARTICIPANTS

any English or Spanish-speaking adult with an upcoming appointment at an enrolling clinic.

METHODS

A personal and family health history based HRA with integrated guideline-based clinical decision support (CDS) was completed by each participant prior to their appointment. Risk reports were provided to patients and providers to discuss at their clinical encounter.

OUTCOMES

provider and patient discussion and provider uptake (i.e. ordering) and patient uptake (i.e. recommendation completion) of CDS recommendations.

MEASURES

patient and provider surveys and EMR data.

RESULTS

One thousand eight hundred twenty nine participants (mean age 56.2 [SD13.9], 69.6% female) completed the HRA and had EMR data available for analysis. 762 (41.6%) received a recommendation (29.7% for genetic counseling (GC); 15.2% for enhanced breast/colon cancer screening). Those with recommendations frequently discussed disease risk with their provider (8.7%-38.2% varied by recommendation, p-values ≤ 0.004). In the GC subgroup, provider discussions increased referrals to counseling (44.4% with vs. 5.9% without, P < 0.001). Recommendation uptake was highest for colon cancer screening (provider = 67.9%; patient = 86.8%) and lowest for breast cancer chemoprevention (0%).

CONCLUSIONS

Systematic health risk assessment revealed that almost half the population were at increased disease risk based on guidelines. Risk identification resulted in shared discussions between participants and providers but variable clinical action uptake depending upon the recommendation. Understanding the barriers and facilitators to uptake by both patients and providers will be essential for optimizing HRA tools and achieving their promise of improving population health.

TRIAL REGISTRATION

Clinicaltrials.gov number NCT01956773 , registered 10/8/2013.

Association of Disparities in Family History and Family Cancer History in the Electronic Health Record With Sex, Race, Hispanic or Latino Ethnicity, and Language Preference in 2 Large US Health Care Systems

IMPORTANCE

Clinical decision support (CDS) algorithms are increasingly being implemented in health care systems to identify patients for specialty care. However, systematic differences in missingness of electronic health record (EHR) data may lead to disparities in identification by CDS algorithms.

OBJECTIVE

To examine the availability and comprehensiveness of cancer family history information (FHI) in patients' EHRs by sex, race, Hispanic or Latino ethnicity, and language preference in 2 large health care systems in 2021.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective EHR quality improvement study used EHR data from 2 health care systems: University of Utah Health (UHealth) and NYU Langone Health (NYULH). Participants included patients aged 25 to 60 years who had a primary care appointment in the previous 3 years. Data were collected or abstracted from the EHR from December 10, 2020, to October 31, 2021, and analyzed from June 15 to October 31, 2021.

EXPOSURES

Prior collection of cancer FHI in primary care settings.

MAIN OUTCOMES AND MEASURES

Availability was defined as having any FHI and any cancer FHI in the EHR and was examined at the patient level. Comprehensiveness was defined as whether a cancer family history observation in the EHR specified the type of cancer diagnosed in a family member, the relationship of the family member to the patient, and the age at onset for the family member and was examined at the observation level.

RESULTS

Among 144 484 patients in the UHealth system, 53.6% were women; 74.4% were non-Hispanic or non-Latino and 67.6% were White; and 83.0% had an English language preference. Among 377 621 patients in the NYULH system, 55.3% were women; 63.2% were non-Hispanic or non-Latino, and 55.3% were White; and 89.9% had an English language preference. Patients from historically medically undeserved groups-specifically, Black vs White patients (UHealth: 17.3% [95% CI, 16.1%-18.6%] vs 42.8% [95% CI, 42.5%-43.1%]; NYULH: 24.4% [95% CI, 24.0%-24.8%] vs 33.8% [95% CI, 33.6%-34.0%]), Hispanic or Latino vs non-Hispanic or non-Latino patients (UHealth: 27.2% [95% CI, 26.5%-27.8%] vs 40.2% [95% CI, 39.9%-40.5%]; NYULH: 24.4% [95% CI, 24.1%-24.7%] vs 31.6% [95% CI, 31.4%-31.8%]), Spanish-speaking vs English-speaking patients (UHealth: 18.4% [95% CI, 17.2%-19.1%] vs 40.0% [95% CI, 39.7%-40.3%]; NYULH: 15.1% [95% CI, 14.6%-15.6%] vs 31.1% [95% CI, 30.9%-31.2%), and men vs women (UHealth: 30.8% [95% CI, 30.4%-31.2%] vs 43.0% [95% CI, 42.6%-43.3%]; NYULH: 23.1% [95% CI, 22.9%-23.3%] vs 34.9% [95% CI, 34.7%-35.1%])-had significantly lower availability and comprehensiveness of cancer FHI (P < .001).

CONCLUSIONS AND RELEVANCE

These findings suggest that systematic differences in the availability and comprehensiveness of FHI in the EHR may introduce informative presence bias as inputs to CDS algorithms. The observed differences may also exacerbate disparities for medically underserved groups. System-, clinician-, and patient-level efforts are needed to improve the collection of FHI.

FHH Quick App Review: How Can a Quality Review Process Assist Primary Care Providers in Choosing a Family Health History App for Patient Care?

Family health history (FHH) is a data type serving risk assessment, diagnosis, research, and preventive health. Despite technological leaps in genomic variant detection, FHH remains the most accessible, least expensive, and most practical assessment tool for assessing risks attributable to genetic inheritance. The purpose of this manuscript is to outline a process to assist primary care professionals in choosing FHH digital tools for patient care based on the new ISO/TS 82304-2 Technical Specification (TS), which is a recently developed method to determine eHealth app quality. With a focus on eHealth in primary care, we applied the quality label concept to FHH, and how a primary care physician can quickly review the quality and reliability of an FHH app. Based on our review of the ISO TS’s 81 questions, we compiled a list of 25 questions that are recommended to be more succinct as an initial review. We call this process the FHH Quick App Review. Our ‘informative-only’ 25 questions do not produce a quality score, but a guide to complete an initial review of FHH apps. Most of the questions are straight from the ISO TS, some are modified or de novo. We believe the 25 questions are not only relevant to FHH app reviews but could also serve to aid app development and clinical implementation.

Family history tools for primary care: A systematic review

Background

Many medical family history (FH) tools are available for various settings. Although FH tools can be a powerful health screening tool in primary care (PC), they are currently underused.

Objectives

This review explores the FH tools currently available for PC and evaluates their clinical performance.

Methods

Five databases were systematically searched until May 2021. Identified tools were evaluated on the following criteria: time-to-complete, integration with electronic health record (EMR) systems, patient administration, risk-assessment ability, evidence-based management recommendations, analytical and clinical validity and clinical utility.

Results

We identified 26 PC FH tools. Analytical and clinical validity was poorly reported and agreement between FH and gold standard was commonly inadequately reported and assessed. Sensitivity was acceptable; specificity was found in half of the reviewed tools to be poor. Most reviewed tools showed a capacity to successfully identify individuals with increased risk of disease (6.2–84.6% of high and/or moderate or increased risk individuals).

Conclusion

Despite the potential of FH tools to improve risk stratification of patients in PC, clinical performance of current tools remains limited as well as their integration in EMR systems. Twenty-one FH tools are designed to be self-administered by patients.

A Family and a Genome-Wide Polygenic Risk Score Are Independently Associated With Stroke in a Population-Based Study

BACKGROUND

Positive family history and genetic risk scores have been shown to independently capture those individuals with high risk for stroke. The aim of our study was to evaluate the amount of shared information between family history and genetic risk and to investigate their combined effect on the association with prevalent and incident stroke cases.

METHODS

We obtained a family risk score (FamRS), weighted for disease onset and family size as well as genome-wide polygenic risk score (PGS) including over 3.2 million single-nucleotide polymorphisms in the population-based prospective KORA F3 (Cooperative Health Research in the Region of Augsburg) study (n=3071) from Southern Germany. FamRS and PGS were evaluated separately and combined. The measures were once treated as continuous variables but also divided in the highest 20%, 10%, 5%, and 1% percentiles. Odds ratios via logistic regression and hazard ratios via Cox regression were estimated. A stroke event was defined as a hospitalization for stroke that was self-reported in a standardized interview by certified and supervised personnel.

RESULTS

The FamRS outperformed other simplified family measures such as affected parents or number of affected family members. FamRS and PGS were not correlated, and no individuals were observed with both very high FamRS and very high PGS (top 1% percentile). In a combined model, both FamRS and PGS were independently from each other associated with risk of stroke, also independent of other traditional risk factors (p [FamRS]=0.02, p [PGS]=0.005). Individuals in the top 1% of either FamRS or PGS were found to have >5-fold risk for stroke (odds ratios, 5.82 [95% CI, 2.08-14]; P=0.0002). The results for incident stroke events showed the same trend but were not significant.

CONCLUSIONS

Our study shows that a family risk score and PGS capture different information concerning individual stroke risk. Combining the risk measures FamRS and PGS increases predictive power, as demonstrated in a population-based study.

Clustering of lung diseases in the family of interstitial lung disease patients

Background

The presence of familial interstitial lung disease (ILD) has been found to predict development of progressive pulmonary fibrosis. However, the role of non-ILD lung diseases in ILD patients’ families has not yet been investigated. We aimed to identify associations between ILDs and non-ILD lung diseases from ILD patients’ self-reported family health history.

Methods

We analysed questionnaires on family health history of 1164 ILD patients for the occurrence of ILD and non-ILD lung disease in relatives. Logistic regression analysis was used to study associations with diagnosis groups.

Results

Familial pulmonary fibrosis was reported by 20% of patients with idiopathic pulmonary fibrosis (IPF; OR 9.2, 95% CI 4.7–17.9), and 15% of patients with unclassifiable pulmonary fibrosis (OR 4.1, 95% CI 2.0–8.2). Familial occurrence was reported by 14% of patients with sarcoidosis (OR 3.3, 95% CI 1.9–5.8). Regarding non-ILD lung disease, significantly more patients with IPF (36%) reported lung cancer in their family (OR 2.3, 95% CI 1.4–3.5), and patients with hypersensitivity pneumonitis (18%) mostly reported COPD (OR 2.3, 95% CI 1.3–4.2). Comparison of sporadic and familial ILD patients’ reports showed that emphysema (OR 4.6, 95% CI 1.8–11.6), and lung cancer (OR 2.4, 95% CI 1.2–4.9) were predictive for familial pulmonary fibrosis, particularly when reported both in a family (OR 16.7, 95% CI 3.2–86.6; p < 0.001).

Conclusions

Our findings provide evidence for clustering of ILD and non-ILD lung diseases in families and show that self-reported emphysema and lung cancer of relatives in this population predicts familial pulmonary fibrosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01927-x.

Establishing a process to improve the collection of family health history

ABSTRACT

Knowledge of a person's potential to inherit certain diseases has rapidly become a valuable part of the discussion between provider and patient. Knowing the risk of hereditary disorders allows providers to include screening and diagnostic tests in a timely way. The family heath history is an easy and important tool for identification of risk for genetic diseases, including cancers. A project, which incorporated patient education and technology, was developed to improve the collection of family health history and identify high-risk patients for genetic cancers and/or diseases.

PREDICTION OF HEREDITARY CANCERS USING NEURAL NETWORKS

Family history is a major risk factor for many types of cancer. Mendelian risk prediction models translate family histories into cancer risk predictions, based on knowledge of cancer susceptibility genes. These models are widely used in clinical practice to help identify high-risk individuals. Mendelian models leverage the entire family history, but they rely on many assumptions about cancer susceptibility genes that are either unrealistic or challenging to validate, due to low mutation prevalence. Training more flexible models, such as neural networks, on large databases of pedigrees can potentially lead to accuracy gains. In this paper we develop a framework to apply neural networks to family history data and investigate their ability to learn inherited susceptibility to cancer. While there is an extensive literature on neural networks and their state-of-the-art performance in many tasks, there is little work applying them to family history data. We propose adaptations of fully-connected neural networks and convolutional neural networks to pedigrees. In data simulated under Mendelian inheritance, we demonstrate that our proposed neural network models are able to achieve nearly optimal prediction performance. Moreover, when the observed family history includes misreported cancer diagnoses, neural networks are able to outperform the Mendelian BRCAPRO model embedding the correct inheritance laws. Using a large dataset of over 200,000 family histories, the Risk Service cohort, we train prediction models for future risk of breast cancer. We validate the models using data from the Cancer Genetics Network.

Multigenerational health research using population-based linked databases: an international review

Family health history is a well-established risk factor for many health conditions but the systematic collection of health histories, particularly for multiple generations and multiple family members, can be challenging. Routinely-collected electronic databases in a select number of sites worldwide offer a powerful tool to conduct multigenerational health research for entire populations. At these sites, administrative and healthcare records are used to construct familial relationships and objectively-measured health histories. We review and synthesize published literature to compare the attributes of routinely-collected, linked databases for three European sites (Denmark, Norway, Sweden) and three non-European sites (Canadian province of Manitoba, Taiwan, Australian state of Western Australia) with the capability to conduct population-based multigenerational health research. Our review found that European sites primarily identified family structures using population registries, whereas non-European sites used health insurance registries (Manitoba and Taiwan) or linked data from multiple sources (Western Australia). Information on familial status was reported to be available as early as 1947 (Sweden); Taiwan had the fewest years of data available (1995 onwards). All centres reported near complete coverage of familial relationships for their population catchment regions. Challenges in working with these data include differentiating biological and legal relationships, establishing accurate familial linkages over time, and accurately identifying health conditions. This review provides important insights about the benefits and challenges of using routinely-collected, population-based linked databases for conducting population-based multigenerational health research, and identifies opportunities for future research within and across the data-intensive environments at these six sites.

Potential of polygenic risk scores for improving population estimates of women's breast cancer genetic risks

PURPOSE

Breast cancer risk has conventionally been assessed using family history (FH) and rare high/moderate penetrance pathogenic variants (PVs), notably in BRCA1/2, and more recently PALB2, CHEK2, and ATM. In addition to these PVs, it is now possible to use increasingly predictive polygenic risk scores (PRS) as well. The comparative population-level predictive capability of these three different indicators of genetic risk for risk stratification is, however, unknown.

METHODS

The Canadian heritable breast cancer risk distribution was estimated using a novel genetic mixing model (GMM). A realistically representative sample of women was synthesized based on empirically observed demographic patterns for appropriately correlated family history, inheritance of rare PVs, PRS, and residual risk from an unknown polygenotype. Risk assessment was simulated using the BOADICEA risk algorithm for 10-year absolute breast cancer incidence, and compared to heritable risks as if the overall polygene, including its measured PRS component, and PV risks were fully known.

RESULTS

Generally, the PRS was most predictive for identifying women at high risk, while family history was the weakest. Only the PRS identified any women at low risk of breast cancer.

CONCLUSION

PRS information would be the most important advance in enabling effective risk stratification for population-wide breast cancer screening.

Experience and Perceptions of a Family Health History Risk Assessment Tool among Multi-Ethnic Asian Breast Cancer Patients

A family health history-based risk assessment is particularly valuable for guiding cancer screening and treatment strategies, yet an optimal implementation depends upon end-users' values and needs. This is not only true prior to disease development, but also for those already affected. The aim of this study is to explore perceptions of the value of knowing one's family health history (FHH)-based risk, experience using a patient-facing FHH tool and the potential of the tool for wider implementation. Twenty multi-ethnic Asian patients undergoing breast cancer treatment in Singapore completed an FHH-based risk assessment. Semi-structured one-on-one interviews were conducted and data were thematically analyzed. All participants were female and slightly more than half were Chinese. The acceptance and usage of an FHH risk assessment tool for cancers and its broader implementation was affected by a perceived importance of personal control over early detection, patient concerns of anxiety for themselves and their families due to risk results, concerns for genetic discrimination, adequacy of follow-up care plans and Asian cultural beliefs toward disease and dying. This study uniquely sheds light on the factors affecting Asian breast cancer patients' perceptions about undergoing an FHH-based risk assessment, which should inform steps for a broader implementation in Asian healthcare systems.

How is family health history discussed in routine primary healthcare? A qualitative study of archived family doctor consultations

OBJECTIVES

Family health history underpins genetic medicine. Our study aimed to explore language and patterns of communication relating to family health history observed in interactions between general practitioners (GPs) and their patients within routine primary care consultations.

DESIGN

Secondary analysis of patient and GP routine consultation data (n=252).

PARTICIPANTS

Consultations that included 'family health history' were eligible for inclusion (n=58).

PRIMARY OUTCOMES

A qualitative inductive analysis of the interactions from consultation transcripts.

RESULTS

46/58 conversations about family health history were initiated by the GP. Most discussions around family history lasted for between approximately 1 to 2 min. Patients were invited to share family health history through one of two ways: non-specific enquiry (eg, by asking the patient about 'anything that runs in the family'); or specific enquiry where they were asked if they had a 'strong family history' in relation to a particular condition, for example, breast cancer. Patients often responded to either approach with a simple no, but fuller negative responses also occurred regularly and typically included an account of some kind (eg, explaining family relationships/dynamics which impeded or prevented the accessibility of information).

CONCLUSIONS

Family health history is regarded as a genetic test and is embedded in the sociocultural norms of the patient from whom information is being sought. Our findings highlight that it is more complex than asking simply if 'anything' runs in the family. As the collection of family health history is expected to be more routine, it will be important to also consider it from sociocultural perspectives in order to help mitigate any inequities in how family history is collected, and therefore used (or not) in a person's healthcare. Orientating an enquiry away from 'anything' and asking more specific details about particular conditions may help facilitate the dialogue.

Mapping Users' Experience of a Family History and Genetic Risk Algorithm Tool in Primary Care

INTRODUCTION

The development of a family history (FH) questionnaire (FHQ) provides an insight into a patient's familiarity of a trait and helps to identify individuals at increased risk of disease. A critical aspect of developing a new tool is exploring users' experience.

OBJECTIVE

The objective of this study was to examine users' experience, obstacles and challenges, and their views and concerns in the applicability of a new tool for determining genetic risk in Slovenia's primary care.

METHODS

We used a qualitative approach. The participants completed a risk assessment software questionnaire that calculates users' likelihood of developing familial diseases. Audio-taped semi-structured telephone interviews were conducted to evaluate their experience. There were 21 participants, and analyses using the constant comparative method were employed.

RESULTS

We identified 3 main themes: obstacles/key issues, suggestions for improvements, and coping. The participants were poorly satisfied with the clarity of instructions, technical usability problems, and issues with the entry of relatives' data. They expressed satisfaction with some of the characteristics of the FHQ (e.g., straightforward and friendly format, easy entry, and comprehension). They suggested simpler language, that the disease risk should be targeted toward the disease, that the FHQ should include patient-specific recommendations, and that it should be part of the electronic medical records. When discussing what would they do with the results of the FHQ, the participants used different coping strategies: active (e.g., seeking information) or passive (e.g., avoidance).

DISCUSSION/CONCLUSION

User experience was shown to be a synthesis of obstacles, overcoming them with suggestions for improvements, and exploration of various coping mechanisms that may emerge from dealing with the stressor of "being at risk."

Risk of prostate cancer in relatives of prostate cancer patients in Sweden: A nationwide cohort study

BACKGROUND

Evidence-based guidance for starting ages of screening for first-degree relatives (FDRs) of patients with prostate cancer (PCa) to prevent stage III/IV or fatal PCa is lacking in current PCa screening guidelines. We aimed to provide evidence for risk-adapted starting age of screening for relatives of patients with PCa.

METHODS AND FINDINGS

In this register-based nationwide cohort study, all men (aged 0 to 96 years at baseline) residing in Sweden who were born after 1931 along with their fathers were included. During the follow-up (1958 to 2015) of 6,343,727 men, 88,999 were diagnosed with stage III/IV PCa or died of PCa. The outcomes were defined as the diagnosis of stage III/IV PCa or death due to PCa, stratified by age at diagnosis. Using 10-year cumulative risk curves, we calculated risk-adapted starting ages of screening for men with different constellations of family history of PCa. The 10-year cumulative risk of stage III/IV or fatal PCa in men at age 50 in the general population (a common recommended starting age of screening) was 0.2%. Men with ≥2 FDRs diagnosed with PCa reached this screening level at age 41 (95% confidence interval (CI): 39 to 44), i.e., 9 years earlier, when the youngest one was diagnosed before age 60; at age 43 (41 to 47), i.e., 7 years earlier, when ≥2 FDRs were diagnosed after age 59, which was similar to that of men with 1 FDR diagnosed before age 60 (41 to 45); and at age 45 (44 to 46), when 1 FDR was diagnosed at age 60 to 69 and 47 (46 to 47), when 1 FDR was diagnosed after age 69. We also calculated risk-adapted starting ages for other benchmark screening ages, such as 45, 55, and 60 years, and compared our findings with those in the guidelines. Study limitations include the lack of genetic data, information on lifestyle, and external validation.

CONCLUSIONS

Our study provides practical information for risk-tailored starting ages of PCa screening based on nationwide cancer data with valid genealogical information. Our clinically relevant findings could be used for evidence-based personalized PCa screening guidance and supplement current PCa screening guidelines for relatives of patients with PCa.

Modernizing family health history: achievable strategies to reduce implementation gaps

Family health history (FHH) is a valuable yet underused healthcare tool for assessing health risks for both prevalent disorders like diabetes, cancer, and cardiovascular diseases, and for rare, monogenic disorders. Full implementation of FHH collection and analysis in healthcare could improve both primary and secondary disease prevention for individuals and, through cascade testing, make at risk family members eligible for pre-symptomatic testing and preventative interventions. In addition to risk assessment in the clinic, FHH is increasingly important for interpreting clinical genetic testing results and for research connecting health risks to genomic variation. Despite this value, diverse implementation gaps in clinical settings undermine its potential clinical value and limit the quality of connected health and genomic data. The NHGRI Family Health History Group, an open-membership, US-based group with international members, believes that integrating FHH in healthcare and research is more important than ever, and that achievable implementation advances, including education, are urgently needed to boost the pace of translational utility in genomic medicine. An inventory of implementation gaps and proposed achievable strategies to address them, representing a consensus developed in meetings from 2019-2020, is presented here. The proposed measures are diverse, interdisciplinary, and are guided by experience and ongoing implementation and research efforts.

Effects of family health history-based colorectal cancer prevention education among non-adherent Chinese Americans to colorectal cancer screening guidelines

OBJECTIVE

This study examined the effects of the first family health history (FHH)-based colorectal cancer (CRC) prevention education on 1) FHH of CRC communication with family members and primary care physicians (PCPs), 2) fecal occult blood test (FOBT) uptake, and 3) CRC preventive lifestyle modifications among 50- to 75-year-old Chinese Americans non-adherent to CRC screening guidelines.

METHODS

Using a community-based participatory research approach, we developed and implemented 62 culturally and linguistically appropriate, theory-driven, FHH-based CRC prevention educational workshops across Texas for 344 Chinese Americans (mostly with low education/income) aged 50-75 years who were non-adherent to CRC screening guidelines.

RESULTS

Linear mixed modeling analyses showed that participants' FHH of CRC communication with PCPs and family members significantly increased two-week post-workshop compared to pre-workshop data (ps<0.001). Moreover, at two-weeks post-workshop, 91.9 % of participants underwent FOBT. Nevertheless, no significant changes were found in participants' lifestyles.

CONCLUSION

Our educational workshops successfully increased Chinese Americans' FHH of CRC communication and FOBT uptake. Personalized education with longer follow-ups may be needed in future studies to promote lifestyle changes among Chinese Americans.

PRACTICE IMPLICATIONS

Health and public health professionals may adopt our workshop educational materials to provide patient and public CRC prevention education for Chinese Americans.

Utility of a virtual counselor (VICKY) to collect family health histories among vulnerable patient populations: A randomized controlled trial

OBJECTIVES

This study is a randomized controlled trial comparing the efficacy of a virtual counselor (VICKY) to the My Family Health Portrait (MFHP) tool for collecting family health history (FHx).

METHODS

A total of 279 participants were recruited from a large safety-net hospital and block randomized by health literacy to use one of the digital FHx tools, followed by a genetic counselor interview. A final sample of 273 participants were included for analyses of primary study aims pertaining to tool concordance, which assessed agreement between tool and genetic counselor.

RESULTS

Tool completion differed significantly between tools (VICKY = 97%, MFHP = 51%; p < .0001). Concordance between tool and genetic counselor was significantly greater for participants randomized to VICKY compared to MFHP for ascertaining first- and second-degree relatives (ps<.0001), and most health conditions examined. There was significant interaction by health literacy, with greater differences in concordance observed between tools among those with limited literacy.

CONCLUSIONS

A virtual counselor overcomes many of the literacy-related barriers to using traditional digital tools and highlights an approach that may be important to consider when collecting health histories from vulnerable populations.

PRACTICE IMPLICATIONS

The usability of digital health history tools will have important implications for the quality of the data collected and its downstream clinical utility.

Utility and Diversity: Challenges for Genomic Medicine

Genomic information is poised to play an increasing role in clinical care, extending beyond highly penetrant genetic conditions to less penetrant genotypes and common disorders. But with this shift, the question of clinical utility becomes a major challenge. A collaborative effort is necessary to determine the information needed to evaluate different uses of genomic information and then acquire that information. Another challenge must also be addressed if that process is to provide equitable benefits: the lack of diversity of genomic data. Current genomic knowledge comes primarily from populations of European descent, which poses the risk that most of the human population will be shortchanged when health benefits of genomics emerge. These two challenges have defined my career as a geneticist and have taught me that solutions must start with dialogue across disciplinary and social divides.

Cases in Precision Medicine: Genetic Testing to Predict Future Risk for Disease in a Healthy Patient

Genetic testing is performed more routinely in clinical practice, and direct-to-consumer tests are widely available. It has obvious appeal as a preventive health measure. Clinicians and their healthy patients increasingly inquire about genetic testing as a tool for predicting diseases, such as cancer, heart disease, or dementia. Despite demonstrated utility for diagnosis in the setting of many diseases, genetic testing still has many limitations as a predictive tool for healthy persons. This article uses a hypothetical case to review key considerations for predictive genetic testing.

Clinical implementation of an oncology-specific family health history risk assessment tool

BACKGROUND

The presence of hereditary cancer syndromes in cancer patients can have an impact on current clinical care and post-treatment prevention and surveillance measures. Several barriers inhibit identification of hereditary cancer syndromes in routine practice. This paper describes the impact of using a patient-facing family health history risk assessment platform on the identification and referral of breast cancer patients to genetic counselling services.

METHODS

This was a hybrid implementation-effectiveness study completed in breast cancer clinics. English-literate patients not previously referred for genetic counselling and/or gone through genetic testing were offered enrollment. Consented participants were provided educational materials on family health history collection, entered their family health history into the platform and completed a satisfaction survey. Upon completion, participants and their clinicians were given personalized risk reports. Chart abstraction was done to identify actions taken by patients, providers and genetic counsellors.

RESULTS

Of 195 patients approached, 102 consented and completed the study (mean age 55.7, 100 % women). Sixty-six (65 %) met guideline criteria for genetic counseling of which 24 (36 %) were referred for genetic counseling. Of those referred, 13 (54 %) participants attended and eight (33 %) completed genetic testing. On multivariate logistic regression, referral was not associated with age, cancer stage, or race but was associated with clinical provider (p = 0.041). Most providers (71 %) had higher referral rates during the study compared to prior. The majority of participants found the experience useful (84 %), were more aware of their health risks (83 %), and were likely to recommend using a patient-facing platform to others (69 %).

CONCLUSIONS

65 % of patients attending breast cancer clinics in this study are at-risk for hereditary conditions based on current guidelines. Using a patient-facing risk assessment platform enhances the ability to identify these patients systematically and with widespread acceptability and recognized value by patients. As only a third of at-risk participants received referrals for genetic counseling, further understanding barriers to referral is needed to optimize hereditary risk assessment in oncology practices.

TRIAL REGISTRATION

NIH Clinical Trials registry, NCT04639934 . Registered Nov 23, 2020 -- Retrospectively registered.

Comparison of family health history in surveys vs electronic health record data mapped to the observational medical outcomes partnership data model in the All of Us Research Program

OBJECTIVE

Family health history is important to clinical care and precision medicine. Prior studies show gaps in data collected from patient surveys and electronic health records (EHRs). The All of Us Research Program collects family history from participants via surveys and EHRs. This Demonstration Project aims to evaluate availability of family health history information within the publicly available data from All of Us and to characterize the data from both sources.

MATERIALS AND METHODS

Surveys were completed by participants on an electronic portal. EHR data was mapped to the Observational Medical Outcomes Partnership data model. We used descriptive statistics to perform exploratory analysis of the data, including evaluating a list of medically actionable genetic disorders. We performed a subanalysis on participants who had both survey and EHR data.

RESULTS

There were 54 872 participants with family history data. Of those, 26% had EHR data only, 63% had survey only, and 10.5% had data from both sources. There were 35 217 participants with reported family history of a medically actionable genetic disorder (9% from EHR only, 89% from surveys, and 2% from both). In the subanalysis, we found inconsistencies between the surveys and EHRs. More details came from surveys. When both mentioned a similar disease, the source of truth was unclear.

CONCLUSIONS

Compiling data from both surveys and EHR can provide a more comprehensive source for family health history, but informatics challenges and opportunities exist. Access to more complete understanding of a person's family health history may provide opportunities for precision medicine.

Secondary leukemia in patients with germline transcription factor mutations (RUNX1, GATA2, CEBPA)

Recognition that germline mutations can predispose individuals to blood cancers, often presenting as secondary leukemias, has largely been driven in the last 20 years by studies of families with inherited mutations in the myeloid transcription factors (TFs) RUNX1, GATA2, and CEBPA. As a result, in 2016, classification of myeloid neoplasms with germline predisposition for each of these and other genes was added to the World Health Organization guidelines. The incidence of germline mutation carriers in the general population or in various clinically presenting patient groups remains poorly defined for reasons including that somatic mutations in these genes are common in blood cancers, and our ability to distinguish germline (inherited or de novo) and somatic mutations is often limited by the laboratory analyses. Knowledge of the regulation of these TFs and their mutant alleles, their interaction with other genes and proteins and the environment, and how these alter the clinical presentation of patients and their leukemias is also incomplete. Outstanding questions that remain for patients with these germline mutations or their treating clinicians include: What is the natural course of the disease? What other symptoms may I develop and when? Can you predict them? Can I prevent them? and What is the best treatment? The resolution of many of the remaining clinical and biological questions and effective evidence-based treatment of patients with these inherited mutations will depend on worldwide partnerships among patients, clinicians, diagnosticians, and researchers to aggregate sufficient longitudinal clinical and laboratory data and integrate these data with model systems.

Family history assessment significantly enhances delivery of precision medicine in the genomics era

BACKGROUND

Family history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs rendering the value of family history unknown. We evaluated the utility of incorporating family history information for genomic sequencing selection.

METHODS

To ascertain the relationship between family histories on such population-level initiatives, we analysed whole genome sequences of 1750 research participants with no known pre-existing conditions, of which half received comprehensive family history assessment of up to four generations, focusing on 95 cancer genes.

RESULTS

Amongst the 1750 participants, 866 (49.5%) had high-quality standardised family history available. Within this group, 73 (8.4%) participants had an increased family history risk of cancer (increased FH risk cohort) and 1 in 7 participants (n = 10/73) carried a clinically actionable variant inferring a sixfold increase compared with 1 in 47 participants (n = 17/793) assessed at average family history cancer risk (average FH risk cohort) (p = 0.00001) and a sevenfold increase compared to 1 in 52 participants (n = 17/884) where family history was not available (FH not available cohort) (p = 0.00001). The enrichment was further pronounced (up to 18-fold) when assessing only the 25 cancer genes in the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes. Furthermore, 63 (7.3%) participants had an increased family history cancer risk in the absence of an apparent clinically actionable variant.

CONCLUSIONS

These findings demonstrate that the collection and analysis of comprehensive family history and genomic data are complementary and in combination can prioritise individuals for genomic analysis. Thus, family history remains a critical component of health risk assessment, providing important actionable data when implementing genomics screening programs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02791152 . Retrospectively registered on May 31, 2016.

The Biobehavioral Family Model: An Evidence-Based Approach to Biopsychosocial Research, Residency Training, and Patient Care

Engel's biopsychosocial model, based in systems theory, assumes the reciprocal influence of biological, psychological, and social factors on one another and on mental and physical health. However, the model's application to scientific study is limited by its lack of specificity, thus constraining its implementation in training and healthcare environments. The Biobehavioral Family Model (BBFM) is one model that can facilitate specification and integration of biopsychosocial conceptualization and treatment of illness. The model identifies specific pathways by which family relationships (i.e., family emotional climate) impact disease activity, through psychobiological mechanisms (i.e., biobehavioral reactivity). Furthermore, it is capable of identifying positive and negative effects of family process in the same model, and can be applied across cultural contexts. The BBFM has been applied to the study of child health outcomes, including pediatric asthma, and adult health, including for underserved primary care patients, minoritized samples, and persons with chronic pain, for example. The BBFM also serves as a guide for training and clinical practice; two such applications are presented, including the use of the BBFM in family medicine residency and child and adolescent psychiatry fellowship programs. Specific teaching and clinical approaches derived from the BBFM are described in both contexts, including the use of didactic lecture, patient interview guides, assessment protocol, and family-oriented care. Future directions for the application of the BBFM include incorporating temporal dynamics and developmental trajectories in the model, extending testable theory of family and individual resilience, examining causes of health disparities, and developing family-based prevention and intervention efforts to ameliorate contributing factors to disease. Ultimately, research and successful applications of the BBFM could inform policy to improve the lives of families, and provide additional support for the value of a biopsychosocial approach to medicine.

An efficient machine learning-based approach for screening individuals at risk of hereditary haemochromatosis

Hereditary haemochromatosis (HH) is an autosomal recessive disease, where HFE C282Y homozygosity accounts for 80–85% of clinical cases among the Caucasian population. HH is characterised by the accumulation of iron, which, if untreated, can lead to the development of liver cirrhosis and liver cancer. Since iron overload is preventable and treatable if diagnosed early, high-risk individuals can be identified through effective screening employing artificial intelligence-based approaches. However, such tools expose novel challenges associated with the handling and integration of large heterogeneous datasets. We have developed an efficient computational model to screen individuals for HH using the family study data of the Hemochromatosis and Iron Overload Screening (HEIRS) cohort. This dataset, consisting of 254 cases and 701 controls, contains variables extracted from questionnaires and laboratory blood tests. The final model was trained on an extreme gradient boosting classifier using the most relevant risk factors: HFE C282Y homozygosity, age, mean corpuscular volume, iron level, serum ferritin level, transferrin saturation, and unsaturated iron-binding capacity. Hyperparameter optimisation was carried out with multiple runs, resulting in 0.94 ± 0.02 area under the receiving operating characteristic curve (AUCROC) for tenfold stratified cross-validation, demonstrating its outperformance when compared to the iron overload screening (IRON) tool.

The Importance of Cancer Screening

The burden of cancer in the United States is substantial, providing important opportunity and obligation for primary care clinicians to promote cancer prevention and early detection. Without a system of organized screening to support reminders and follow-up of cancer screening, primary care clinicians face challenges in addressing risk assessment, informed/shared decision making, reminders for screening, and tracking adherence to screening recommendations. Tools exist for collecting information about family history, tracking screening adherence, and reminding patients when they are due for screening, and strategies exist for making cancer prevention and early detection an office policy and delegating roles and responsibilities to office staff.

Gender differences in self-reported family history of cancer: A review and secondary data analysis

Background

Assessment of family history of cancer (FHC) mostly relies on self‐report. Our goal was to find out whether there is a systematic gender difference in self‐reported FHC.

Methods

We identified nine population‐based studies which provided statistics of FHC in men and women (N₁ = 404 541). Furthermore, we analyzed data (N₂ = 167 154) from several iterations of the US‐based Health Information National Trends Survey (HINTS) and the National Health Interview Survey (NHIS). We calculated the proportion of positive FHC, odds ratios (OR M/F), 95% confidence intervals, and aggregated statistics. We additionally analyzed in‐depth questions about FHC from HINTS 5 Cycle 2.

Results

In the reviewed studies the odds of men reporting a FHC were lower compared with the odds of women with an average OR of 0.84 [0.71; 1.00] across all studies and an OR of 0.75 [0.70; 0.80] for the six studies from the US and Europe. The gender gap was replicated in our own analyses of HINTS and NHIS with an average OR of 0.75 [0.71; 0.79]. In HINTS 5 Cycle 2 men described themselves as less familiar with their FHC and less confident answering questions regarding FHC. They were also less likely to discuss FHC with family members.

Conclusions

Men— at least in the US and Europe—were consistently less likely to report FHC compared with women. Future research should investigate how the assessment of FHC can be improved to reduce these differences. Health care professionals should also consider the potential for biased reporting by gender when assessing FHC.

Challenge-comet assay, a functional and genomic biomarker for precision risk assessment and disease prevention among exposed workers

Advancements in genomic technologies have ushered application of innovative changes into biomedical sciences and clinical medicine. Consequently, these changes have created enormous opportunities to implement precision population/occupational disease prevention and target-specific disease intervention (or personalized medicine). To capture the opportunities, however, it is necessary is to develop novel, especially genomic-based, biomarkers which can provide precise and individualized health risk assessment. In this review, development of the Challenge-comet assay is used as an example to demonstrate how assays need to be validated for its sensitivity, specificity, and functional and quantitative features, and how assays can be used to provide individualized health risk assessment for precision prevention and intervention. Other examples of genomic-based novel biomarkers will also be discussed. Furthermore, no biomarkers can be used alone therefore their integrated usage with other biomarkers and with personal data bases will be discussed.

Family health history collected by virtual conversational agents: An empirical study to investigate the efficacy of this approach

Family health history (FHx) is one of the simplest and most cost-effective and efficient ways to collect health information that could help diagnose and treat genetic diseases at an early stage. This study evaluated the efficacy of collecting such family health histories through a virtual conversational agent (VCA) interface, a new method for collecting this information. Standard and VCA interfaces for FHx collection were investigated with 50 participants, recruited via email and word of mouth, using a within-subject experimental design with the order of the interfaces randomized and counterbalanced. Interface workload, usability, preference, and satisfaction were assessed using the NASA Task Load Index workload instrument, the IBM Computer System Usability Questionnaire, and a brief questionnaire derived from the Technology Acceptance Model. The researchers also recorded the number of errors and the total task completion time. It was found that the completion times for 2 of the 5 tasks were shorter for the VCA interface than for the standard one, but the overall completion time was longer (17 min 44 s vs. 16 min 51 s, p = .019). We also found the overall workload to be significantly lower (34.32 vs. 42.64, p = .003) for the VCA interface, and usability metrics including overall satisfaction (5.62 vs. 4.72, p < .001), system usefulness (5.76 vs. 4.84, p = .001), information quality (5.43 vs. 4.62, p < .001), and interface quality (5.66 vs. 4.64, p < .001) to be significantly higher for this interface as well. Approximately 3 out of 4 participants preferred the VCA interface to the standard one. Although the overall time taken was slightly longer than with standard interface, the VCA interface was rated significantly better across all other measures and was preferred by the participants. These findings demonstrate the advantages of an innovative VCA interface for collecting FHx, validating the efficacy of using VCAs to collect complex patient-specific data in health care.

Primary care physician experiences utilizing a family health history tool with electronic health record-integrated clinical decision support: an implementation process assessment

Family health history (FHH) screening plays a key role in disease risk identification and tailored disease prevention strategies. Primary care physicians (PCPs) are in a frontline position to provide personalized medicine recommendations identified through FHH screening; however, adoption of FHH screening tools has been slow and inconsistent in practice. Information is also lacking on PCP facilitators and barriers of utilizing family history tools with clinical decision support (CDS) embedded in the electronic health record (EHR). This study reports on PCPs' initial experiences with the Genetic and Wellness Assessment (GWA), a patient-administered FHH screening tool utilizing the EHR and CDS. Semi-structured interviews were conducted with 24 PCPs who use the GWA in a network of community-based practices. Four main themes regarding GWA implementation emerged: benefits to clinical care, challenges in practice, CDS-specific issues, and physician-recommended improvements. Sub-themes included value in improving patient access to genetic services, inadequate time to discuss GWA recommendations, lack of patient follow-through with recommendations, and alert fatigue. While PCPs valued the GWA's clinical utility, a number of challenges were identified in the administration and use of the GWA in practice. Based on participants' recommendations, iterative changes have been made to the GWA and workflow to increase efficiency, upgrade the CDS process, and provide additional education to PCPs and patients. Future studies are needed to assess a diverse sample of physicians' and patients' perspectives on the utility of FHH screening utilizing EHR-based genomics recommendations.

Management of patients with increased risk for familial pancreatic cancer: updated recommendations from the International Cancer of the Pancreas Screening (CAPS) Consortium

BACKGROUND AND AIM

The International Cancer of the Pancreas Screening Consortium met in 2018 to update its consensus recommendations for the management of individuals with increased risk of pancreatic cancer based on family history or germline mutation status (high-risk individuals).

METHODS

A modified Delphi approach was employed to reach consensus among a multidisciplinary group of experts who voted on consensus statements. Consensus was considered reached if ≥75% agreed or disagreed.

RESULTS

Consensus was reached on 55 statements. The main goals of surveillance (to identify high-grade dysplastic precursor lesions and T1N0M0 pancreatic cancer) remained unchanged. Experts agreed that for those with familial risk, surveillance should start no earlier than age 50 or 10 years earlier than the youngest relative with pancreatic cancer, but were split on whether to start at age 50 or 55. Germline ATM mutation carriers with one affected first-degree relative are now considered eligible for surveillance. Experts agreed that preferred surveillance tests are endoscopic ultrasound and MRI/magnetic retrograde cholangiopancreatography, but no consensus was reached on how to alternate these modalities. Annual surveillance is recommended in the absence of concerning lesions. Main areas of disagreement included if and how surveillance should be performed for hereditary pancreatitis, and the management of indeterminate lesions.

CONCLUSIONS

Pancreatic surveillance is recommended for selected high-risk individuals to detect early pancreatic cancer and its high-grade precursors, but should be performed in a research setting by multidisciplinary teams in centres with appropriate expertise. Until more evidence supporting these recommendations is available, the benefits, risks and costs of surveillance of pancreatic surveillance need additional evaluation.

Opportunities, resources, and techniques for implementing genomics in clinical care

Advances in technologies for assessing genomic variation and an increasing understanding of the effects of genomic variants on health and disease are driving the transition of genomics from the research laboratory into clinical care. Genomic medicine, or the use of an individual's genomic information as part of their clinical care, is increasingly gaining acceptance in routine practice, including in assessing disease risk in individuals and their families, diagnosing rare and undiagnosed diseases, and improving drug safety and efficacy. We describe the major types and measurement tools of genomic variation that are currently of clinical importance, review approaches to interpreting genomic sequence variants, identify publicly available tools and resources for genomic test interpretation, and discuss several key barriers in using genomic information in routine clinical practice.