Impact of Communicating Familial Risk of Diabetes on Illness Perceptions and Self-Reported Behavioral Outcomes

Pijl, Miranda; Timmermans, Daniëlle R.M.; Claassen, Liesbeth; Janssens, A. Cecile J.W.; Nijpels, Giel; Dekker, Joost; Marteau, Theresa M.; Henneman, Lidewij

doi:10.2337/dc08-1049

Cited by 68 publications

(74 citation statements)

References 13 publications

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“…Of the five included studies (Table 1), two were randomized controlled trials, 13,18 and three were analog studies (Wright et al, unpublished study). [17][18][19] Two studies assessed perceived control over the development of obesity; a further two measured perceived control over multiple disease types, and one as- sessed perceived control over the development of diabetes.…”

Section: Characteristics Of Included Studiesmentioning

confidence: 99%

“…[17][18][19] Two studies assessed perceived control over the development of obesity; a further two measured perceived control over multiple disease types, and one as- sessed perceived control over the development of diabetes. The 5 included studies involved 1518 participants with a mean age of 42.2 years.…”

Section: Characteristics Of Included Studiesmentioning

confidence: 99%

“…Two studies 13,18 assessed the impact of personalized genetic risk information on perceived control of health problems in the short-term (Fig. 2).…”

Section: Clinical Studiesmentioning

confidence: 99%

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Impact of communicating personalized genetic risk information on perceived control over the risk: A systematic review

Collins

Wright

Marteau

2011

Genetics in Medicine

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Purpose: Much concern has been expressed that feedback of personalized genetic risk information may lead to fatalism, i.e., a lack of perceived control over the risk. This review aimed to assess the strength of evidence for such a view. Method: Electronic databases were searched to find eligible studies, which comprised randomized, controlled trials and analog studies, in which participants in one arm received either real or imagined personalized genetic risk information and assessed perceived control in relation to the treatability or preventability of the health problem. Results: Inspection of 1340 abstracts resulted in 5 studies meeting the inclusion criteria, involving the prediction of obesity, heart disease, depression, and diabetes. Meta-analyses of the clinical studies revealed no impact of personalized genetic risk information on perceived control in either the short term (pooled standardized mean difference 0.09, 95% confidence interval, Ϫ0.51 to 0.70) or longer term (pooled standardized mean difference 0.00, confidence interval, Ϫ0.20 to 0.21). Similarly, no impact on perceived control was evident in the three analog studies (pooled standardized mean difference 0.02, confidence interval, Ϫ0.17 to 0.20). Conclusion: Few studies have assessed empirically the impact of personalized genetic risk information on fatalism, assessed using perceptions of control over the risk. Limited evidence suggests feedback of genetic risk information may have little impact on such beliefs. Genet Med 2011: 13(4):273-277.

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Section: Characteristics Of Included Studiesmentioning

confidence: 99%

Section: Characteristics Of Included Studiesmentioning

confidence: 99%

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Impact of communicating personalized genetic risk information on perceived control over the risk: A systematic review

Collins

Wright

Marteau

2011

Genetics in Medicine

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“…18,19 Clinical utility conclusions. There is inadequate evidence of clinical utility for genomic profiles directly with T2D risk in the general or high-risk populations.…”

Section: Clinical Utilitymentioning

confidence: 99%

Recommendations from the EGAPP Working Group: does genomic profiling to assess type 2 diabetes risk improve health outcomes?

Berg

Campos‐Outcalt

Djulbegoviĉ

et al. 2013

Genetics in Medicine

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EGAPP REcommEndAtion stAtEmEnt summary of recommendations: The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (EWG) found insufficient evidence to recommend testing for predictive variants in 28 variants (listed in Table 1) to assess risk for type 2 diabetes in the general population, on the basis of studies in populations of northern European descent. The EWG found that the magnitude of net health benefit from the use of any of these tests alone or in combination is close to zero. The EWG discourages clinical use unless further evidence supports improved clinical outcomes.The EWG found insufficient evidence to recommend testing for the TCF7L2 gene to assess risk for type 2 diabetes in high-risk individuals. The EWG found that the magnitude of net health benefit from the use of this test is close to zero. The EWG discourages clinical use unless further evidence supports improved clinical outcomes.On the basis of the available evidence for both the scenarios, the overall certainty of net health benefit is deemed "low. "Rationale: It has been suggested that genomic profiling in the general population or in high-risk populations for type 2 diabetes might lead to management changes (e.g., earlier initiation or higher rates of medical interventions, or targeted recommendations for behavioral change) that improve type 2 diabetes outcomes or prevent type 2 diabetes. The EWG found no direct evidence to support this possibility; therefore, this review sought indirect evidence aimed at documenting the extent to which genomic profiling alters type 2 diabetes risk estimation, alone and in combination with traditional risk factors, and the extent to which risk classification improves health outcomes.Analytic validity: Assay-related evidence on available genomic profiling tests was deemed inadequate. However, on the basis of existing technologies that have been or may be used, the analytic sensitivity and specificity of tests for individual gene variants might be at least satisfactory.clinical validity: Twenty-eight candidate markers were evaluated in the general population. Evidence on clinical validity was rated inadequate for 24 of these associations (86%) and adequate for 4 (14%).Inadequate grades were based on limited evidence, poor replication, existence of possible biases, or combinations of these factors. Type 2 diabetes genomic profiling provided areas under the receiver operator characteristics curve of 55%-57%, with 4, 8, and 28 genes. Only TCF7L2 had convincing evidence of an association with type 2 diabetes with an odds ratio of 1.39 (95% confidence interval: 1.33-1.46).TCF7L2 was evaluated for high-risk populations, and the overall odds ratio was 1.66 (95% confidence interval: 1.22-2.27) for association with progression to type 2 diabetes.clinical utility: No studies were available to provide direct evidence on the balance of benefits and harms for genetic profiling for type 2 diabetes alone or in addition to traditional risk factors in the general population.Evidence for hig...

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“…For example, the presence of a first degree relative (parent or child) with T2D increases an individual's risk from an average of 3.2 % to 14.3 % in some populations and counselling on FHH risk increases the likelihood of initiating health behaviors aimed at T2D prevention. (Annis et al 2005;Hariri et al 2006;Pijl et al 2009). …”

Section: Introductionmentioning

confidence: 99%

Impact of Genetic Testing and Family Health History Based Risk Counseling on Behavior Change and Cognitive Precursors for Type 2 Diabetes

Myers

Hauser

et al. 2016

Journal of Genetic Counseling

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Family health history (FHH) in the context of risk assessment has been shown to positively impact risk perception and behavior change. The added value of genetic risk testing is less certain. The aim of this study was to determine the impact of Type 2 Diabetes (T2D) FHH and genetic risk counseling on behavior and its cognitive precursors. Subjects were non-diabetic patients randomized to counseling that included FHH +/− T2D genetic testing. Measurements included weight, BMI, fasting glucose at baseline and 12 months and behavioral and cognitive precursor (T2D risk perception and control over disease development) surveys at baseline, 3, and 12 months. 391 subjects enrolled of which 312 completed the study. Behavioral and clinical outcomes did not differ across FHH or genetic risk but cognitive precursors did. Higher FHH risk was associated with a stronger perceived T2D risk (p Kendall < 0.001) and with a perception of Bserious^risk (p Kendall < 0.001). Genetic risk did not influence risk perception, but was correlated with an increase in perception of Bserious^risk for moderate (p Kendall = 0.04) and average FHH risk subjects (p Kendall = 0.01), though not for the high FHH risk group. Perceived control over T2D risk was high and not affected by FHH or genetic risk. FHH appears to have a strong impact on cognitive precursors of behavior change, suggesting it could be leveraged to enhance risk counseling, particularly when lifestyle change is desirable. Genetic risk was able to alter perceptions about the seriousness of T2D risk in those with moderate and average FHH risk, suggesting that FHH could be used to selectively identify individuals who may benefit from genetic risk testing.

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Impact of Communicating Familial Risk of Diabetes on Illness Perceptions and Self-Reported Behavioral Outcomes

Cited by 68 publications

References 13 publications

Impact of communicating personalized genetic risk information on perceived control over the risk: A systematic review

Impact of communicating personalized genetic risk information on perceived control over the risk: A systematic review

Recommendations from the EGAPP Working Group: does genomic profiling to assess type 2 diabetes risk improve health outcomes?

Impact of Genetic Testing and Family Health History Based Risk Counseling on Behavior Change and Cognitive Precursors for Type 2 Diabetes

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