Life insurance: genomic stratification and risk classification

With the development and increasing accessibility of new genomic tools such as next-generation sequencing, genome-wide association studies, and genomic stratification models, the debate on genetic discrimination in the context of life insurance became even more complex, requiring a review of current practices and the exploration of new scenarios. In this perspective, a multidisciplinary group of international experts representing different interests revisited the genetics and life insurance debate during a 2-day symposium ‘Life insurance: breast cancer research and genetic risk prediction seminar'' held in Quebec City, Canada on 24 and 25 September 2012. Having reviewed the current legal, social, and ethical issues on the use of genomic information in the context of life insurance, the Expert Group identified four main questions: (1) Have recent developments in genomics and related sciences changed the contours of the genetics and life insurance debate? (2) Are genomic results obtained in a research context relevant for life insurance underwriting? (3) Should predictive risk assessment and risk stratification models based on genomic data also be used for life insurance underwriting? (4) What positive actions could stakeholders in the debate take to alleviate concerns over the use of genomic information by life insurance underwriters? This paper presents a summary of the discussions and the specific action items recommended by the Expert Group.Access to genetic information by life insurers has been a topic of discussion for many years.¹ The possibility of using genetic data to underwrite an applicant''s insurance policy has given rise to concerns about the emergence of ‘genetic discrimination''. Genetic discrimination in the field of life insurance is not necessarily illegal in that in insurance underwriting questions about health, family history of disease, or genetic information may constitute legal exceptions to antidiscrimination legislation.^{2, 3} Nevertheless, the expression ‘genetic discrimination'' has acquired public notoriety⁴ and we will use more neutral language in this paper.Countries including Canada, the United States, Russia, and Japan⁵ have chosen not to adopt laws specifically prohibiting access to genetic data for underwriting by life insurers.⁶ In these countries, life insurance underwriters treat genetic data like other types of medical or lifestyle data. However, a growing number of countries such as Belgium, France, and Norway⁵ have chosen to adopt laws to prevent or limit insurers'' access to genetic data for life insurance underwriting. Other countries including Finland and the United Kingdom have developed voluntary arrangements with the industry (ie moratoria) with similar objectives.⁷Life insurance is a private contract between the policy-holder and the insurer. Its principal role is to provide financial security to the beneficiaries in the event of the insured''s death.⁸ Because of this important role, life insurance is often required, or strongly recommended for those seeking loans to acquire primary social goods, like housing or cars.⁹ In Europe, a consequence of the advent of the welfare state is that private insurance has increasingly played a complementary and supplementary role to social insurance by offering additional security and protection to the population. Thus, in this region, insurance is often considered as a social good that allows individuals to live a comfortable life and as a tool to promote social integration.¹⁰ In other regions of the world, this social role of life insurance is also recognized to a lesser extent. Given this social role, equitable access to life insurance is perceived as a sensitive issue and cases of denial looked upon negatively in popular media. Although documented incidents of denial or of increased premiums on the basis of genetic information have remained limited to the context of a few relatively well known, highly penetrant, familial, adult-onset, genetic conditions,¹¹ they have nevertheless generated significant public concern. Fear that insurers will have access to genetic information generated in a clinical or research setting for use in underwriting has been reported by several studies as a reason for non-participation in genetic research or recommended clinical genetic testing.^{12, 13, 14}The clinical utility of genetic testing for monogenic disorders such as Huntington disease, and hereditary forms of cancer are well established.¹⁵ However, genomic risk profiles based on the known common susceptibility variants have limited utility in risk prediction at the individual level, although they could be used for risk stratification in prevention programmes in populations.¹⁶ Today, a new era of genomic research has made it increasingly affordable to scan the entire genome of an individual. Researchers and physicians can interpret these data together with medical and lifestyle information in the form of sophisticated risk prediction models.¹⁷ Moreover, improvement in computing technologies coupled with the Internet make predictive information increasingly available, whether through direct-to-consumer marketing of genetic tests, genetic data sharing online communities, or international research database projects. Given these important technological and scientific changes, and their impact on various stakeholders. The term ‘stakeholders'' is used in this text to refer to the following groups of individuals: actuaries (person who computes insurance risk and premium rates based on statistical data), academic researchers, community representatives, ethics committees, genetic counsellors, genomic researchers, human rights experts, insurers, governmental representatives, non-governmental organisations, patient representatives, physicians, policy makers, popular media, reinsurers (company in charge of calculating the risk and premium amount for insuring a particular customer), research participants, and underwriters (company or person in charge of calculating the risk involved in providing insurance for a particular customer and to decide how much should be paid for the premium). This list is not meant to be exhaustive as relevant new groups may emerge as this topic further develops in the coming years. A multidisciplinary group of international experts representing different interests (hereinafter ‘the Expert Group'') revisited the genetics and life insurance debate. The following text presents a summary of the issues discussed and the ‘Action Items'' agreed upon by the Expert Group at the ‘Life Insurance, Risk Stratification, and Personalized Medicine Symposium''.     

Hospitalizations and Costs Incurred at the Facility Level after Scale-up of Malaria Control: Pre-Post Comparisons from Two Hospitals in Zambia

There is little evidence on the impact of malaria control on the health system, particularly at the facility level. Using retrospective, longitudinal facility-level and patient record data from two hospitals in Zambia, we report a pre-post comparison of hospital admissions and outpatient visits for malaria and estimated costs incurred for malaria admissions before and after malaria control scale-up. The results show a substantial reduction in inpatient admissions and outpatient visits for malaria at both hospitals after the scale-up, and malaria cases accounted for a smaller proportion of total hospital visits over time. Hospital spending on malaria admissions also decreased. In one hospital, malaria accounted for 11% of total hospital spending before large-scale malaria control compared with < 1% after malaria control. The findings demonstrate that facility-level resources are freed up as malaria is controlled, potentially making these resources available for other diseases and conditions.     

Interactions between killer immunoglobulin-like receptors and their human leucocyte antigen Class I ligands influence the outcome of unrelated haematopoietic stem cell transplantation for thalassaemia: a novel predictive algorithm

In a study conducted on 114 patients undergoing unrelated donor haematopoietic stem cell transplantation (HSCT) for thalassaemia, we observed that the lack of activating killer immunoglobulin-like receptors (KIRs) on donor natural killer (NK) cells significantly increased the risk of graft-versus-host disease (GvHD) [hazard risk (HR) 4.2, 95% confidence interval (CI) 1.7-10.1, P = 0.002] and transplantation-related mortality (HR 4.7, 95% CI 1.6-14.2, P = 0.01). The risk of GvHD furthermore increased when recipients heterozygous for HLA-C KIR ligand groups (C1/C2) were transplanted from donors completely lacking activating KIRs (HR 6.1, 95% CI 1.9-19.2, P = 0.002). We also found that the risk of rejection was highest when the recipient was homozygous for the C2 HLA-KIR ligand group and the donor carried two or more activating KIRs (HR 6.8, 95% CI 1.9-24.4, P = 0.005). By interpolating the number of donor activating KIRs with recipient HLA-C KIR ligands, we created an algorithm capable of stratifying patients according to the immunogenetic risk of complications following unrelated HSCT. In clinical practice, this predictive tool could serve as an important supplement to clinical judgement and decision-making.     

Phase II study of sorafenib in patients with relapsed or refractory lymphoma

The safety and activity of the multikinase inhibitor sorafenib were investigated in patients with relapsed or refractory lymphoproliferative disorders who received sorafenib (400 mg) twice daily until disease progression or appearance of significant clinical toxicity. The primary endpoint was overall response rate (ORR). Biomarkers of sorafenib activity were analysed at baseline and during treatment. Thirty patients (median age, 61 years; range, 18-74) received a median of 4 months of therapy. Grade 3-4 toxicities included hand/foot skin reactions (20%), infections (12%), neutropenia (20%) and thrombocytopenia (14%). Two patients achieved complete remission (CR), and two achieved partial remission (PR) for an ORR of 13%. Stable disease (SD) and progressive disease (PD) was observed in 15 (50%) and 11 patients (37%), respectively. The median overall survival (OS) for all patients was 16 months. For patients who achieved CR, PR and SD, the median time to progression and OS was 5 and 24 months, respectively. Compared with patients with PD, responsive patients had significantly higher baseline levels of extracellular signal-regulated kinase phosphorylation and autophagy and presented a significant reduction of these parameters after 1 month of therapy. Sorafenib was well tolerated and had a clinical activity that warrants development of combination regimens.