What characterizes cancer family history collection tools? A critical literature review

Review Article

What characterizes cancer family history collection tools? A critical literature review


J.E. Cleophat, MD MSc*,, H. Nabi, PhD*,§, S. Pelletier, MSc*, K. Bouchard, MSc*, M. Dorval, PhD*,,


doi: http://dx.doi.org/10.3747/co.25.4042


ABSTRACT

Background

Many tools have been developed for the standardized collection of cancer family history (fh). However, it remains unclear which tools have the potential to help health professionals overcome traditional barriers to collecting such histories. In this review, we describe the characteristics, validation process, and performance of existing tools and appraise the extent to which those tools can support health professionals in identifying and managing at-risk individuals.

Methods

Studies were identified through searches of the medline, embase, and Cochrane central databases from October 2015 to September 2016. Articles were included if they described a cancer fh collection tool, its use, and its validation process.

Results

Based on seventy-nine articles published between February 1978 and September 2016, 62 tools were identified. Most of the tools were paper-based and designed to be self-administered by lay individuals. One quarter of the tools could automatically produce pedigrees, provide cancer-risk assessment, and deliver evidence-based recommendations. One third of the tools were validated against a standard reference for collected fh quality and cancer-risk assessment. Only 3 tools were integrated into an electronic health records system.

Conclusions

In the present review, we found no tool with characteristics that might make it an efficient clinical support for health care providers in cancer-risk identification and management. Adequately validated tools that are connected to electronic health records are needed to encourage the systematic identification of individuals at increased risk of cancer.

KEYWORDS: Family history, hereditary cancers, collection tools, screening, risk assessment, tools validation

INTRODUCTION

The role that heredity and familial exposure to nongenetic risk modifiers (lifestyle, environmental factors, health behaviours) play in cancer occurrence is well recognized1,2. With the development of genomic technologies, it has become easier to identify genetic mutations conferring an increased risk for developing malignancies. Eligibility for genetic testing is based on personal and familial health history criteria3,4. Collection of personal and family history (fh) is a noninvasive and relatively affordable way to perform a preliminary cancer-risk assessment and to identify individuals eligible for thorough genetic assessment5,6. Individuals found to be at increased risk might benefit from preventive and health promotion strategies7; those at average risk might be reassured8. Despite its essential role in cancer-risk prevention, fh is not systematically or adequately collected in clinical settings9,10. Hence, at-risk individuals remain unidentified11,12. Furthermore, when fh is collected, followed-up recommendations are not always provided13,14. Thus, at-risk individuals might not be referred to the appropriate resources9,15 or might be falsely reassured16.

Barriers to collecting fh in clinical settings include poor reimbursement, provider’s lack of time and expertise, lack of guidelines and adequate tools, and limited functionality of electronic health information systems to capture and interpret fh data17. The use of adapted fh collection tools could potentially alleviate some of those barriers and assist providers in collecting and interpreting fh. Many tools have been described in the literature, and several systematic reviews have attempted to group them according to analytic perspective10,1820. However, it is unclear which tools have the potential to help health professionals overcome traditional barriers to collecting cancer fh.

According to de Hoog et al.20 and Taylor et al.21, an ideal tool for collecting fh should be self-administered by patients, computerized, easy to use, and preferably linked or integrated into an electronic health record (ehr). An ideal tool should also allow for the fh to be easily updated over time. It should be designed to draw pedigrees, perform a criteria-based cancer-risk assessment, and deliver tailored, evidence-based management recommendations.

In the present review, we describe the characteristics, validation process, and performance of existing fh tools to determine which ones meet the criteria of the ideal tool and to assess the extent to which they can help clinicians in cancer-risk assessment and management. In contrast to prior works, our review focuses on cancer fh and considers all types of cancer in the adult population. It takes into account validated and non-validated tools to produce a broad picture of available tools used in both primary care and specialized clinics.

METHODS

Data Sources and Inclusion Criteria

We searched the medline, embase, and Cochrane central databases using combinations of the words “family history,” “taking,” “collection,” “assessment,” “cancer risk,” “tools,” “cancer,” “questionnaire,” “instrument,” and “validation.” We applied the PubMed function “similar articles” to articles meeting our inclusion criteria and searched the lists thus generated by PubMed. We also manually searched bibliographic references of retrieved articles and systematic reviews. No time limit was applied to the search. The final literature search took place on 1 September 2016.

To be included in the analysis, articles had to meet these inclusion criteria: publication in English or French, description of a tool used to collect cancer fh in adults, primary focus on the collection of fh, and evaluation of the potential benefits and psychological impacts of a fh collection tool. Articles mentioning a fh collection tool as part of the methods without describing the instrument were excluded. Pertinent references were first identified by scanning titles. Index terms and available abstracts were subsequently reviewed to determine whether articles met the inclusion criteria. Final inclusion was based on a full-text review of selected articles. Relevant information was extracted from the articles retained at that final step.

Data Extraction and Analysis

A descriptive approach was used to summarize the features and validation process of the retained tools. The tools were described based on characteristics previously reported in three systematic reviews1820, but user experience was also included in our analysis. An Excel database (Microsoft Corporation, Redmond, WA, U.S.A.) containing 51 variables was created to describe study and tool characteristics, including tool name, first author name, year of publication, country, and setting in which the tool was tested or used. Properties and attributes of the tools were grouped to build the framework used to conduct our analyses and to present results. Components of that framework included diseases or cancers targeted, tool format, and the tool’s capacity to produce pedigrees, perform risk assessment and stratification, deliver recommendations. Data were processed and aggregated using the SAS software application (version 9.4: SAS Institute, Cary, NC, U.S.A.). Article screening, data extraction, and analysis were performed by the first author (JEC).

Analysis of Tool Performance

Two approaches were used to summarize and interpret tool performance. First, we combined papers in which tools were partly validated using the acce framework criteria (analytic validity; clinical validity; clinical utility; and ethical, legal, and social issues; Table i). The acce framework, commissioned by the U.S. Centers for Disease Control and Prevention, is dedicated to the assessment of the benefits and risks of genetic tests23,24. As proposed by Qureshi et al.22, the framework can be used to evaluate fh collection tools.

TABLE I Application of the ACCE frameworka to family history as a screening tool

 

Our second approach consisted in combining articles that had used performance indicators different from those suggested by the acce framework to evaluate the thoroughness of the fhs collected and the cancer-risk assessment ability of the tool. Concordance between tools and chosen references (for example, genetic counsellor, medical chart) was measured according to the various aspects of fh and cancer-risk assessment. Evaluation strategies and results were summarized in a table.

RESULTS

Tools Identified, Country and Setting of Use, and Target Users

Tables ii and iii present 62 fh collection tools that matched our criteria, identified from seventy-nine publications11,12,14,16,2599. Most were developed in the United States and the United Kingdom (73%), almost half were used in primary care settings (47%), and more than three quarters were devised to be self-administered by lay individuals (78%).

TABLE II Characteristics of 17 generic family history collection tools

 

TABLE III Characteristics of 45 cancer-specific family history collection tools



 

Types of Tools Based on the Diseases Targeted

The identified tools could be classified as generic or cancer-specific. Generic tools (n = 17) allow for the collection of fh for several medical conditions, including cancers (Table ii). Specific tools (n = 45) focus on the fh for one or several types of cancer or cancer syndromes (Table iii). Most frequently, fh is assessed for breast, ovarian, colon, and prostate cancers.

Format of the Identified Tools

Tools for fh collection could be divided into three categories: paper-based (n = 31), interview-based (n = 10), and electronic (n = 21). Paper-based questionnaires are intended to be completed at home or in the clinic. They consist of structured, open-ended, and closed-ended questions; tables28,33,53,65,78,79,82,84,85,96; organigrams66; or pedigrees26,27. Interview-based tools consist of automated telephone-based interviews55,75, structured computer-assisted telephone interviews87, and face-to-face interviews54,56,61,76,80,93,98. Non-automated telephone-based and face-to-face interviews are conducted with the support of structured questionnaires or pedigree information sheets54,56,61,76,80,87,98,93.

Electronic tools allow for interactive question-answering in a logical process that uses dialog boxes3032,63,64, drop-down windows62,81, or diagrams from which pedigrees can be built97. Three electronic tools display lists of possible or preformulated answers45,46,51,95. Three others have blank spaces49,81 or empty pedigrees40 that have to be completed. One electronic tool is a question prompter intended to be used by physicians during patient interviews74. Electronic questionnaires are available for use on a digital assistant74, a tablet51,86, a laptop47,86, or a computer in the clinic41,47,62,63,70,86. They can be made accessible through the Internet11,3032,34,39,4144,47,81,89,91,95,97, an online patient portal40,45,46,49, or an intranet71,72. Updates to the fh are possible with 3 of the electronic tools42,86,89. Another 3 tools are incorporated into or linked back to ehrs40,47,92.

Degree of Kinship Covered and Pedigree Production

Information about the degree of kinship covered was available for 53 tools (85%). Of those 53 tools, 13% ask respondents only about 1st-degree relatives; 87% and 49% include 2nd- and 3rd-degree relatives respectively. Almost half the tools (n = 29, 47%) are geared toward production of a pedigree, with 14 of them (23%) automatically producing a pedigree after the entry of fh data. Except for 1 automated telephone interview75, all of those tools are electronic. Another 15 tools (24%) allow for the detailed collection of fh in a way that a pedigree can subsequently be constructed. Nevertheless, 32 tools (52%) are disease-oriented, seeking only a positive fh of cancer among relatives.

Cancer-Risk Assessment and Recommendation Delivery

Of 20 tools (32%) that provide a preliminary cancer-risk assessment, 80% do so automatically, including 15 electronic tools and 1 automated telephone interview55. Of the paper-based tools, 4 allow for a preliminary cancer-risk assessment and communication to respondents66,79,84,85. Tools providing cancer-risk assessments are mostly cancer-specific (70%). Tailored follow-up recommendations for patients can be delivered by 15 tools (24%), with 9 of them offering advice on risk-reducing strategies (healthy lifestyle, cancer surveillance, preventive interventions). Six tools propose management recommendations to clinicians. When appropriate, 9 tools refer respondents to genetic counselling. Respondents are invited or prepared by 8 tools to talk about their cancer risk with their health care professionals. In 5 tools that include a cancer-risk assessment component49,66,74,84,85, no recommendations for follow-up are issued.

Respondent Experience and Appreciation of the Tools

User appreciation and experience were reported for 19 tools (31%). Overall, respondents expressed positive attitudes toward the tools, judging them as simple71,91,96, easy to use11,30,34,43,49,51,62,71,72,79,81,85,89,91, easy to understand11,43,47,79,91,96, worthy of recommendation to peers43,79, worthy of definitive incorporation into ehrs92, or highly acceptable75. Fair or negative appreciations were reported for only 4 tools. Respondents felt “fairly satisfied” about the cancer-risk information provided70, required assistance for completing the tool43, and at times, considered them too long49 or “brittle and clunky”81. The time required to complete the questionnaire was reported for 26 tools (42%). The completion time was 30 minutes or less for 20 tools. For 6 tools, completion time varied from 33 minutes to 120 hours.

Tool Evaluation and Performance Using the ACCE Framework

Analytic validity was measured for 5 tools and involved various fh parameters (Table iv). Analytic sensitivity varied from 33% to 100%, and specificity varied from 76% to 97%. Clinical validity was calculated for 6 tools (Table iv). Sensitivity for identifying increased risk varied from 0% to 100%; specificity, from 54% to 92%; positive predictive value, from 24% to 80%; and negative predictive value, from 92% to 100%.

TABLE IV Analytic and clinical validity among the retrieved family history (FH) collection tools

 

A formal evaluation of the clinical utility of the tool was not performed in any publication. However, based on study results, we identified potential benefits for respondents and their relatives. Assessment of fh helped to identify cancer patients for whom a referral to a genetics clinic would be warranted because of the pattern of cancer occurrence in their family12,68,80,94,96,99. The tool allowed for increased and improved-quality referrals to genetics clinics12,69,71,72,90,92; for fh-based decision-making in primary care41,43,44,47; and for efficient26,28,45,46,49,88,92, efficacious11,3944,51,54,6264,68,73,75,7678,81,82, and exhaustive25 collection of fh and updates41,86,89. Increased compliance with cancer screening55,61 and changes in health behaviours34 were also noted. By collecting the fh before clinical appointments, clinicians had more time to assess and discuss cancer risk, resulting in enhanced-quality counselling and improved individual management49,91.

The fourth component of the acce framework—ethics, legal, and social issues—were not discussed in the retained publications, except for psychological effects. After fh documentation and cancer-risk assessment, psychological evaluations for respondents showed scores for distress and depressive symptoms that were, on average, within normal limits29,65,70,77.

Tool Performance According to Indicators Other Than the ACCE Framework

The performance of 30 cancer fh collection tools was assessed using indicators different from those proposed in the acce framework. Table v summarizes the strategies and comparators used by the research teams to assess the thoroughness of the fh collected and the appropriateness of risk stratifications and referrals to genetics clinics. Validation outcomes were reported as narratives supplemented with quantitative data, simple frequencies or proportions (or both) not related to intrinsic validity, correlation coefficients, concordance scores, and percentages of agreement. Sensitivities, specificities, and odds ratios were calculated to assess the appropriateness of referrals to genetics clinics. Overall, those tools found a good level of concordance for fh collection and risk assessment with their respective comparators. The tools outperformed medical charts in fh collection.

TABLE V Validation of collected family history (FH), risk stratification, and referral decisions



 

DISCUSSION

In the present review, we identified 17 generic and 45 cancer-specific tools developed for cancer fh collection. Most of the retrieved tools were paper-based and designed to be self-administered by patients and family members. One third of the tools identified were available electronically, and one quarter were able to automatically produce a pedigree, provide cancer-risk assessment, and deliver evidence-based recommendations. The validation process showed that the performance of the tools varied depending on the disease or diseases being investigated, the fh parameters, and the comparators considered. One third of the tools were partly validated against a standard reference.

To our knowledge, our review is the first to focus on fh collection tools developed to report on all types of cancer in the adult population. It is also the first to assess the strategies used to validate tools according to the acce framework. It represents an important update concerning the progress made over time in developing fh collection tools. Our findings about the greater number of cancer-specific tools, the preference for paper-based and self-administered instruments, the inconsistent validation, and the lack of functionality, are similar to those in earlier reviews1820.

We did not find any tool that met all the characteristics of an ideal tool to support clinicians in decision-making and cancer-risk management effectively, but 6 were considered promising: grace70, MeTree42, Health Heritage11, Hughes Risk App86, Cancer in the Family89, and CancerGene Connect91. All 6 tools are electronic and self-administered; all draw pedigrees and provide cancer-risk assessment and management recommendations. However, updates to the fh are possible in only 3 of them (MeTree, Hughes Risk App, Cancer in the Family)42,86,89. Only 2 (Health Heritage, MeTree)11,42 were evaluated for fh accuracy and completeness, and risk-assessment accuracy or compliance with proposed genetics referral guidelines. Moreover, only 3 were deemed easy to use (Health Heritage, CancerGene Connect, Cancer in the Family)11,89,91. More importantly, none are embedded into an ehr system. Hickey et al.100 and Feero et al.101 made a case for integrating, into ehrs, a common fh core dataset that would allow for the standardized collection and exchange of fh throughout health information systems, ensuring a continuum of patient care. Although none of these 6 proposed tools are “ideal” cancer fh questionnaires, they can still help health care providers to identify at-risk individuals and families. They could be used in medical clinics to screen patients requiring a genetic counselling referral or in genetics clinics to document fh and to conduct a preliminary risk assessment before a formal genetic counselling interview.

Nevertheless, non-electronic tools still have their place in cancer fh collection, given that not every clinical setting is equipped with an ehr system and not every health care provider has access to and can make use of the Internet and electronic devices. Validated paper-based questionnaires, automated telephone interviews, and telephone and face-to-face interviews can play a significant role in identifying at-risk individuals if they can guide health care providers in assessing risk and managing decisions, and if the data can be easily retrieved and updated. Otherwise, their contribution will remain partial and will continue to require additional human resources.

Lu et al.17, on behalf of the American Society of Clinical Oncology, advocated for the use of a minimum cancer fh, including 1st- and 2nd-degree relatives in both the maternal and paternal lineages. For nearly 70% of retrieved tools, cancer fh was collected up to 2nd-degree relatives. However, it remains unclear how that minimum fh affects cancer-risk assessment. It would be worthwhile to compare the performance of the tools according to the degree of kinship covered and the perspective taken (pedigree-oriented vs. disease-oriented). Cost-effectiveness analyses should also be undertaken to determine whether an evidenced-based benefit accrues to the use of one type of tool over another.

Automatic production of pedigrees by an electronic or an automated collection tool can be beneficial for health care providers. Three-generation pedigrees allow for an appreciation of family size, a determination of the pattern of medical condition inheritance within the family, and easier identification of at-risk individuals102. Of the 23 electronic or automated fh collection tools identified in this review, only 14 were able to generate a pedigree automatically. Thus, improvements are needed in this regard.

Tools for fh collection that estimate individual risk of cancer and propose management strategies would be valuable to health care providers and would facilitate provider–patient risk communication. Only one third of the tools identified here can provide risk assessment, and one quarter can issue management recommendations. Indeed, we identified 5 tools that provide a preliminary risk assessment, but none issue follow-up recommendations49,66,74,84,85. The lack of follow-up represents a missed opportunity to empower respondents with choices concerning their health and providers with the ability to manage at-risk individuals.

Health care providers often state that lack of time precludes them from routinely collecting fh. However, the fact that 81% of the identified tools can be self-administered by lay individuals has the potential to help overcome that barrier. The tools allow patients and family members to provide fh information without lengthening in-office consultations. Moreover, answering the questionnaires at home offers patients the opportunity to contact family members for more precise information102.

Tool completion time was not reported for more than half the tools. Unfortunately, the reasons for that non-reporting were not provided. Given the importance of completion time to the acceptability and usability of the tools, authors should document that aspect more thoroughly. Also, researchers should try to balance fh comprehensiveness and ease of questionnaire completion when developing new tools.

Systematic validation of fh collection tools is needed; 33% of the tools identified in our review did not benefit from validation against any comparator. The acce framework, the first publicly available analytic process for the evaluation of the risks and benefits of genetic testing, constitutes an important resource for validating cancer fh tools103, and both Qureshi et al.22 and Valdez et al.6 advocated for its use. Few of the identified tools were validated in a way that complies with some components of the framework, which, when considered in its entirety, has the potential to allow for a standardized, comprehensive, and in-depth assessment of a tool’s performance and effects. Wider use of the acce or an equivalent framework104 should be encouraged when tools are being developed, especially if evidence-based recommendations are to be delivered to lay individuals and health professionals.

Interpretation of the results of the present review should be considered in light of several potential limitations. First, our search was limited to reports published in French and English, which might have resulted in publication bias. However, we did not find additional relevant articles in other languages. Second, only 1 reviewer analyzed the papers and extracted the data. However, the latter limitation was mitigated through data cross-checking and repeated readings of relevant article sections. Third, the literature search might have missed papers of interest given that it ended in September 2016. In that regard, we conducted an overview of the literature spanning 1 October 2016 through 3 January 2018. We found four additional relevant papers105108, but none reported any particular innovative tool characteristics. Including those papers in the present review would not have significantly changed the main results. Fourth, we could have used more precise search terms such as “pedigree production,” “tablet and smartphone apps,” and “laptop,” which could have enriched the present work. Finally, ranking the tools by score could have been more insightful for readers. However, that approach would have required a purpose-designed and validated scale. To our knowledge, such a scale does not yet exist—but it is needed.

CONCLUSION AND PERSPECTIVES

Currently, there is no standard cancer fh collection tool. The tools identified here can help health professionals in the systematic collection of fh. They can facilitate the identification of individuals at increased risk of cancer while also saving time for the health care provider. However, most of the identified tools do not produce pedigrees, perform cancer-risk assessment, or deliver management recommendations, and few are integrated into ehrs, which limits the support that they provide to health care providers. Those areas are the ones that require improvement. Notably, information technology developments are needed to integrate electronic cancer fh collection tools into ehrs to promote secure sharing of health information.

Developing and making available multifaceted cancer fh collection tools is important. However, increasing the capability and willingness of health care providers to use the outcomes of fh assessment for preventive and, sometimes, therapeutic purposes is a challenge14. Research and new strategies are necessary to address that challenge. In the meantime, continuous effort should be made to upgrade the functionality of existing tools that will improve the ability of health professionals to identify and manage high-risk individuals. As has already occurred for hereditary cancer identification and genetic counselling referral guidelines in a pediatric population109, smartphone and tablet applications are other avenues that can be explored to document fh in adults. Because of their widespread use and popularity, such devices have the potential to streamline fh information-sharing between patients, family members, and health care providers. Several Web-based initiatives for collecting cancer fh have also been reported22,110. However, those initiatives still have to be evaluated in scientific studies to gain acceptance.

The emerging role of the genetic counselling assistant in the field of genetic counselling111 holds much promise and could potentially increase the efficiency of certified genetic counsellors and expand their patient volume. The effect on genetic counselling accessibility and uptake attributable to the use by genetic assistants of the tools recommended in the present review represents an interesting perspective for further research.

More studies of cancer fh collection tools—their validation, utility, social impacts, implementation, utilization, and user experience—are needed. Comparative studies evaluating the efficacy of generic and cancer-specific tools in collecting cancer fh are also needed. Cohort studies with populations of individuals at increased risk might also offer the possibility to assess, in real-world conditions, the clinical validity of cancer fh collection tools.

ACKNOWLEDGMENTS

JEC is a recipient of scholarships from the Fonds d’enseignement et de recherche (Faculty of Pharmacy, Université Laval) and the Centre de recherche sur le cancer–Université Laval. We thank Sue-Ling Chang for linguistic editing of the manuscript.

CONFLICT OF INTEREST DISCLOSURES

We have read and understood Current Oncology’s policy on disclosing conflicts of interest, and we declare that we have none.

AUTHOR AFFILIATIONS

*Centre de recherche du chu de Québec, Axe Oncologie, Quebec City, QC;,
Université Laval, Faculté de pharmacie, Quebec City, QC;,
Centre de recherche sur le cancer, Quebec City, QC;,
§inserm, U1018, Centre de recherche en épidémiologie et santé des populations, Villejuif, France;,
Centre de recherche du cisss Chaudière–Appalaches, Lévis, QC..

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Correspondence to: Michel Dorval, Centre de recherche du CHU de Québec, Université Laval, Hôpital du Saint-Sacrement, 1050 chemin Sainte-Foy, Québec (Québec) G1S 4L8. E-mail: michel.dorval@crchudequebec.ulaval.ca

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Current Oncology, VOLUME 25, NUMBER 4, August 2018








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ISSN: 1198-0052 (Print) ISSN: 1718-7729 (Online)