Cancer screening and genetics: a tale of two paradigms

Development of a novel measure of advanced cancer patients' perceived utility of secondary germline findings from tumor genomic profiling

Objective

Tumor genomic profiling (TGP) can inform advanced cancer patients' treatment decisions, and also reveal secondary germline findings-information about inherited risks for cancer and other disorders. We sought to develop a measure of patient perceptions of the clinical and personal utility of secondary germline findings.

Methods

We developed a draft survey based on literature and patient interview data (n=40). We evaluated and refined the survey through cognitive interviews with advanced cancer patients who received secondary germline findings from TGP (n=10). The survey was psychometrically validated with data from two independent samples of advanced cancer patients undergoing TGP (total n=349).

Results

Cognitive interviews offered opportunities for survey refinement and confirmation of its comprehensible nature. Exploratory and confirmatory factor analysis of the survey identified 16 items across three subscales with strong internal consistency (Cronbach's alpha ≥0.79): perceived utility for others, perceived utility for self and health, and confidence in secondary findings.

Conclusion

We developed a novel valid scale with promise for measuring advanced cancer patients' perceptions of the utility of secondary germline findings.

Innovation

We offer a new patient-derived measure of perceived utility of and confidence in secondary germline findings with potential applications for precision oncology research and clinical communication.

Quality of life drives patients' preferences for secondary findings from genomic sequencing

There is growing impetus to include measures of personal utility, the nonmedical value of information, in addition to clinical utility in health technology assessment (HTA) of genomic tests such as genomic sequencing (GS). However, personal utility and clinical utility are challenging to define and measure. This study aimed to explore what drives patients' preferences for hypothetically learning medically actionable and non-medically actionable secondary findings (SF), capturing clinical and personal utility; this may inform development of measures to evaluate patient outcomes following return of SF. Semi-structured interviews were conducted with adults with a personal or family cancer history participating in a trial of a decision aid for selection of SF from genomic sequencing (GS) ( www.GenomicsADvISER.com ). Interviews were analyzed thematically using constant comparison. Preserving health-related and non-health-related quality of life was an overarching motivator for both learning and not learning SF. Some participants perceived that learning SF would help them "have a good quality of life" through informing actions to maintain physical health or leading to psychological benefits such as emotional preparation for disease. Other participants preferred not to learn SF because results "could ruin your quality of life," such as by causing negative psychological impacts. Measuring health-related and non-health-related quality of life may capture outcomes related to clinical and personal utility of GS and SF, which have previously been challenging to measure. Without appropriate measures, generating and synthesizing evidence to evaluate genomic technologies such as GS will continue to be a challenge, and will undervalue potential benefits of GS and SF.

Evaluating the Integration of Genomics into Cancer Screening Programmes: Challenges and Opportunities

PURPOSE OF REVIEW

As the costs of genomic testing have fallen, and our understanding of genetic susceptibility to cancers has grown, there has been increasing interest in incorporating testing for cancer susceptibility genes, and polygenic risk estimates, into population cancer screening. A growing body of evidence suggests that this would be both clinically and cost-effective. In this article, we aim to explore the frameworks used to evaluate screening programmes, evaluate whether population screening for cancer susceptibility can be assessed using these standards, and consider additional issues and outcomes of importance in this context.

RECENT FINDINGS

There are tensions between traditional approaches of genetic testing (utilising tests with high sensitivity and specificity) and the principles of population screening (in which the screening test typically has low specificity), as well as the frameworks used to evaluate the two. Despite the existence of many screening guidelines, including consensus papers, these often do not align fully with broader considerations of genetic test evaluation. Population screening for genetic risk in cancer shifts the focus from diagnostics to prognostication and has wider implications for personal and familial health than existing screening programmes. In addition, understanding of the prevalence and penetrance of cancer susceptibility genes, required by many screening guidelines, may only be obtainable through population-level testing; prospective multi-disciplinary research alongside implementation will be essential.

SUMMARY

Appropriate evaluation of genetic screening for cancer risk will require modification of existing screening frameworks to incorporate additional complexity of outcomes and population values. As evidence supporting population screening for cancer susceptibility mounts, development of an appropriate evaluative framework, and expansion of public dialogue will be key to informing policy.

Aggregate penetrance of genomic variants for actionable disorders in European and African Americans

In populations that have not been selected for family history of disease, it is unclear how commonly pathogenic variants (PVs) in disease-associated genes for rare Mendelian conditions are found and how often they are associated with clinical features of these conditions. We conducted independent, prospective analyses of participants in two community-based epidemiological studies to test the hypothesis that persons carrying PVs in any of 56 genes that lead to 24 dominantly inherited, actionable conditions are more likely to exhibit the clinical features of the corresponding diseases than those without PVs. Among 462 European American Framingham Heart Study (FHS) and 3223 African-American Jackson Heart Study (JHS) participants who were exome-sequenced, we identified and classified 642 and 4429 unique variants, respectively, in these 56 genes while blinded to clinical data. In the same participants, we ascertained related clinical features from the participants' clinical history of cancer and most recent echocardiograms, electrocardiograms, and lipid measurements, without knowledge of variant classification. PVs were found in 5 FHS (1.1%) and 31 JHS (1.0%) participants. Carriers of PVs were more likely than expected, on the basis of incidence in noncarriers, to have related clinical features in both FHS (80.0% versus 12.4%) and JHS (26.9% versus 5.4%), yielding standardized incidence ratios of 6.4 [95% confidence interval (CI), 1.7 to 16.5; P = 7 × 10^-4) in FHS and 4.7 (95% CI, 1.9 to 9.7; P = 3 × 10^-4) in JHS. Individuals unselected for family history who carry PVs in 56 genes for actionable conditions have an increased aggregated risk of developing clinical features associated with the corresponding diseases.

The hallmarks of premalignant conditions: a molecular basis for cancer prevention

The hallmarks of premalignant lesions were first described in the 1970s, a time when relatively little was known about the molecular underpinnings of cancer. Yet it was clear there must be opportunities to intervene early in carcinogenesis. A vast array of molecular information has since been uncovered, with much of this stemming from studies of existing cancer or cancer models. Here, examples of how an understanding of cancer biology has informed cancer prevention studies are highlighted and emerging areas that may have implications for the field of cancer prevention research are described. A note of caution accompanies these examples, in that while there are similarities, there are also fundamental differences between the biology of premalignant lesions or premalignant conditions and invasive cancer. These differences must be kept in mind, and indeed leveraged, when exploring potential cancer prevention measures.

Cancer prevention as part of precision medicine: 'plenty to be done'

Cancer burden worldwide is projected to rise from 14 million new cases in 2012 to 24 million in 2035. Although the greatest increases will be in developing countries, where cancer services are already hard pressed, even the richest nations will struggle to meet demands of increasing patient numbers and spiralling treatment costs. No country can treat its way out of the cancer problem. Consequently, cancer control must combine improvements in treatment with greater emphasis on prevention and early detection. Cancer prevention is founded on describing the burden of cancer, identifying the causes and evaluating and implementing preventive interventions. Around 40-50% of cancers could be prevented if current knowledge about risk factors was translated into effective public health strategies. The benefits of prevention are attested to by major successes, for example, in tobacco control, vaccination against oncogenic viruses, reduced exposure to environmental and occupational carcinogens, and screening. Progress is still needed in areas such as weight control and physical activity. Fresh impetus for prevention and early detection will come through interdisciplinary approaches, encompassing knowledge and tools from advances in cancer biology. Examples include mutation profiles giving clues about aetiology and biomarkers for early detection, to stratify individuals for screening or for prognosis. However, cancer prevention requires a broad perspective stretching from the submicroscopic to the macropolitical, recognizing the importance of molecular profiling and multisectoral engagement across urban planning, transport, environment, agriculture, economics, etc., and applying interventions that may just as easily rely on a legislative measure as on a molecule.

Threshold-free measures for assessing the performance of medical screening tests

Background

The area under the receiver operating characteristic curve (AUC) is frequently used as a performance measure for medical tests. It is a threshold-free measure that is independent of the disease prevalence rate. We evaluate the utility of the AUC against an alternate measure called the average positive predictive value (AP), in the setting of many medical screening programs where the disease has a low prevalence rate.

Methods

We define the two measures using a common notation system and show that both measures can be expressed as a weighted average of the density function of the diseased subjects. The weights for the AP include prevalence in some form, but those for the AUC do not. These measures are compared using two screening test examples under rare and common disease prevalence rates.

Results

The AP measures the predictive power of a test, which varies when the prevalence rate changes, unlike the AUC, which is prevalence independent. The relationship between the AP and the prevalence rate depends on the underlying screening/diagnostic test. Therefore, the AP provides relevant information to clinical researchers and regulators about how a test is likely to perform in a screening population.

Conclusion

The AP is an attractive alternative to the AUC for the evaluation and comparison of medical screening tests. It could improve the effectiveness of screening programs during the planning stage.