Should individuals be able to directly access their genetic information without physician involvement? Jeff Gulcher MD PhD Chief Scientific Officer and.

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Presentation transcript:

Should individuals be able to directly access their genetic information without physician involvement? Jeff Gulcher MD PhD Chief Scientific Officer and co-Founder deCODE Genetics March 8, 2011

Key issues with DTC genetics for common diseases  Traditional requirements for any genetic test (no different for DTC):  Analytical Validation % accurate based on inheritance checks; bidirectional sequencing confirmation  Clinical Validation  Consistent replication and effect of each marker used (tens of thousands of patients and controls across populations typically reported)  Standard multiplicative model  At clinically significant levels of risk (greater than 1.5 to 2.0 fold), multiple companies agree; most assessments have compared insignificant risk levels ( 0.80) in a handful of individuals (GAO, Venter)  If differences exist, then usually due to variable number of markers annotated;  This problem is not unique to DTC of common diseases:  CF testing (initially 6 mutations vs 25 mutations vs full sequencing to define all 1000 rare variants) can result in dramatic differences in CF results in a patient  Proficiency testing – this is required by CMS, CAP

Key issues with DTC genetics for common diseases  Unique issues  Communication of results in layman’s terms  Intended use is a risk test, not a determinative diagnostic test  Measures genetic risk that is independent of immediate family history  Emphasizes other risk factors to consider with physician  Communication of results to healthcare provider  Transparency of what is measured and periodic updating of profiles  Informational risk without physician involvement  No different than if test ordered through a physician  Consumer cannot receive an invasive treatment without interaction with the healthcare profession

Risk to patient of DTC genetics for common diseases is comparable to that of other risk tools or web-based information offered direct to patients  Risk that patient will have inappropriate prophylactic surgeries or medical therapy  No invasive procedure can be done on the patient without involvement of health care system  No drug can be prescribed without physician involvement  Possible risk that patient may change his/her drug dose without consulting with physician (e.g. warfarin sensitivity)  deCODE only offers pharmacogenomic tests through physician prescription

Risk to consumer of DTC genetics for common diseases is comparable to that of other risk tools or web-based information offered direct to patients  Possible risk that patients with lower genetic risk leads to lower compliance with mammography or prostate screening  Direct to patient websites at major medical centers, at AHA (Framingham score for MI risk), ADA (type 2 diabetes), NCI (Gail score for breast cancer risk) – same risk for misinterpretation? Who regulates these sites?

Without a physician, a women can assess her 5 year and lifetime risk for breast cancer at NCI website. Absolute risk is reported and compared to average risk of women at same age.

Outcome studies of DTC genetic testing have not found any evidence for psychological harms or excessive use of healthcare resources  Robert Green and REVEAL study on ApoE4-based Alzheimer risk showed no increase in clinically meaningful distress: positive vs negative vs non-disclosure (used genetic counselors)  NHGRI DTC study (Multiplex Initiative) – no increase in psychological distress; no increased use of healthcare resources; participants showed an understanding of the difference between a risk test and a determinative test.  David Kaufman – Johns Hopkins DTC study on 23andme, Navigenics, deCODE customers -Large portion reported increased motivation to improve diet and exercise;  Scripps/Navigenics DTC study showed no increase in short-term psychological distress, no increased use of healthcare resources

Prostate cancer risk across the population – 25 SNP markers Upper 5 percentile has 2.8 fold risk, Upper 15% has 2.1 fold Lower 35 percentile has 0.5 fold risk

Prostate Cancer – testing multiplicative model in discovery and replication cohorts Left panel : Iceland Right Panel :US, Netherlands, Spain and Romania Dashed line to 95% distribution interval for the predicted value within each bin

High Risk 5% 15% of the population are reclassified from average risk to 2-fold risk with prostate genetic risk profile Family History & 25 common SNP markers Family History Alone Average Risk 95% 20% High Risk account for 40% of prostate cancers 15%

Inclusive model (Gail & 10-SNP Genetic) performed best at all levels of the ROC curve (AUC 61.8%) Genetic model on its own performed better than Gail model in all except highest risk levels of the ROC curve (59.7% vs 58%) Inclusive model almost doubles incremental increase in AUC vs Gail (8.4% vs 4.6%) Substantially more individuals who developed breast cancer were classified as “High Risk” (in the top risk quintile) by the Inclusive model (27.7%) than by the Gail model (18.9%). Wacholder et al. (NEJM 2010) showed that the genetic risk profile for breast cancer outperformed Gail score

Example of a higher risk patient  48 year old male without family history of early prostate cancer  Family history of late onset prostate cancer  Genetic risk by deCODEme = 1.88 (estimated lifetime risk 30% vs baseline 16%)  PSA measured by primary care (2.0 ng/ml)  Referred to urology- Different FDA approved test for PSA  Biopsy performed – 3 out 12 cores positive for intermediate grade (Gleason 6) cancer; bilateral  Resected – high grade cancer (Gleason 7)  Early detection before spread beyond the capsule

 The medical community has encouraged individuals to be aware of their risk factors and to take personal responsibility for healthcare  A person who knows the risk he has of developing a disease is more likely to seek help to mitigate the risk. And isn’t the right of the individual to have access to this risk information?  If the analytical and clinical validation of DTC genetic tests are cleared by the FDA, CMS or CAP, they pose no more risk to individuals than disease risk scales and advice now widely available to consumers on websites from NIH, professional societies, and academia.  If using a risk-based approach to regulation or access, need to make sure that the harm due to delaying a new test does not outweigh the benefit of the regulation. Does the risk of DTC genetic tests really exceed the informational risk of prescription tests or publicly available risk scales?