Integrating precision cancer medicine into healthcare-policy, practice, and research challenges

Development of a Value Assessment Framework for Pediatric Health Technologies Using Multicriteria Decision Analysis: Expanding the Value Lens for Funding Decision Making

OBJECTIVES

A health technology assessment (HTA) does not systematically account for the circumstances and needs of children and youth. To supplement HTA processes, we aimed to develop a child-tailored value assessment framework using a multicriteria decision analysis approach.

METHODS

We constructed a multicriteria-decision-analysis-based model in multiple phases to create the Comprehensive Assessment of Technologies for Child Health (CATCH) framework. Using a modified Delphi process with stakeholders having broad disciplinary and geographic variation (N = 23), we refined previously generated criteria and developed rank-based weights. We established a criterion-pertinent scoring rubric for assessing incremental benefits of new drugs. Three clinicians independently assessed comprehension by pilotscoring 9 drugs. We then validated CATCH for 2 childhood cancer therapies through structured deliberation with an expert panel (N = 10), obtaining individual scores, consensus scores, and verbal feedback. Analyses included descriptive statistics, thematic analysis, exploratory disagreement indices, and sensitivity analysis.

RESULTS

The modified Delphi process yielded 10 criteria, based on absolute importance/relevance and agreed importance (median disagreement indices = 0.34): Effectiveness, Child-specific Health-related Quality of Life, Disease Severity, Unmet Need, Therapeutic Safety, Equity, Family Impacts, Life-course Development, Rarity, and Fair Share of Life. Pilot scoring resulted in adjusted criteria definitions and more precise score-scaling guidelines. Validation panelists endorsed the framework's key modifiers of value. Modes of their individual prescores aligned closely with deliberative consensus scores.

CONCLUSIONS

We iteratively developed a value assessment framework that captures dimensions of child-specific health and nonhealth gains. CATCH could improve the richness and relevance of HTA decision making for children in Canada and comparable health systems.

How can we deliver on the promise of precision medicine in oncology and beyond? A practical roadmap for action

Background

Precision medicine (PM) is a form of personalized medicine that recognizes that individuals with the same condition may have different underlying factors and uses molecular information to provide tailored treatments. This approach can improve treatment outcomes and transform lives through favorable risk/benefit ratios, avoidance of ineffective interventions, and possible cost savings, as evidenced in the field of lung cancer and other oncology/therapeutic settings, including cardiac disease, diabetes, and rare diseases. However, the potential benefits of PM have yet to be fully realized.

Discussion

There are many barriers to the implementation of PM in clinical practice, including fragmentation of the PM landscape, siloed approaches to address shared challenges, unwarranted variation in availability and access to PM, lack of standardization, and limited understanding of patients' experience and needs throughout the PM pathway. We believe that a diverse, intersectoral multistakeholder collaboration, with three main pillars of activity: generation of data to demonstrate the benefit of PM, education to support informed decision-making, and addressing barriers across the patient pathway, is necessary to reach the shared goal of making PM an accessible and sustainable reality. Besides healthcare providers, researchers, policymakers/regulators/payers, and industry representatives, patients in particular must be equal partners and should be central to the PM approach-from early research through to clinical trials and approval of new treatments-to ensure it represents their entire experience and identifies barriers, solutions, and opportunities at the point of delivery.

Conclusion

We propose a practical and iterative roadmap to advance PM and call for all stakeholders across the healthcare system to employ a collaborative, cocreated, patient-centered methodology to close gaps and fully realize the potential of PM.

Pharmacogenetics of ABCB1, CDA, DCK, GSTT1, GSTM1 and outcomes in a cohort of pediatric acute myeloid leukemia patients from Colombia

BACKGROUND AND AIM

Different studies have shown pharmacogenetic variants related to drug toxicity in acute myeloid leukemia (AML) patients. Our aim was to identify the association between ABCB1, CDA, DCK, GSTT1, and GSTM1 variants with clinical outcomes and toxicity in pediatric patients with AML.

METHODS

Fifty-one confirmed de novo AML pediatric patients were included. A SNaPshot™ assay and conventional PCR were used to evaluate ABCB1, CDA, DCK, GSTT1, and GSTM1 variants. Clinical outcomes and toxicity associations were evaluated using odds ratios and Chi-square analysis.

RESULTS

Patients carrying ABCB1 (1236C > T, rs1128503) GG genotype in had a 6.8 OR (CI 95% 1.08-42.73, p = .044) for cardiotoxicity as compared to patients carrying either AA or GA genotypes 0.14 OR (CI 95% 0.023-0.92, p = .044). For ABCB1 (1236G > A rs1128503/2677C > A/T rs2032582/3435G > A rs1045642) AA/AA/AA combined genotypes had a strong association with death after HSTC OR 13.73 (CI 95% 1.94-97.17, p = .009). Combined genotypes GG/CC/GG with CDA (79A > C, rs2072671) CA genotype or CDA (-451G > A, rs532545) CT genotype, had a 4.11 OR (CI 95% 2.32-725, p = .007) and 3.8 OR (CI 95% 2.23-6.47, p = .027) with MRD >0.1% after first chemotherapy cycle, respectively.

CONCLUSION

Our results highlight the importance of pharmacogenetic analysis in pediatric AML, particularly in populations with a high degree of admixture, and might be useful as a future tool for patient stratification for treatment.

A hybrid algorithm for clinical decision support in precision medicine based on machine learning

PURPOSE

The objective of the manuscript is to propose a hybrid algorithm combining the improved BM25 algorithm, k-means clustering, and BioBert model to better determine biomedical articles utilizing the PubMed database so, the number of retrieved biomedical articles whose content contains much similar information regarding a query of a specific disease could grow larger.

DESIGN/METHODOLOGY/APPROACH

In the paper, a two-stage information retrieval method is proposed to conduct an improved Text-Rank algorithm. The first stage consists of employing the improved BM25 algorithm to assign scores to biomedical articles in the database and identify the 1000 publications with the highest scores. The second stage is composed of employing a method called a cluster-based abstract extraction to reduce the number of article abstracts to match the input constraints of the BioBert model, and then the BioBert-based document similarity matching method is utilized to obtain the most similar search outcomes between the document and the retrieved morphemes. To realize reproducibility, the written code is made available on https://github.com/zzc1991/TREC_Precision_Medicine_Track .

FINDINGS

The experimental study is conducted based on the data sets of TREC2017 and TREC2018 to train the proposed model and the data of TREC2019 is used as a validation set confirming the effectiveness and practicability of the proposed algorithm that would be implemented for clinical decision support in precision medicine with a generalizability feature.

ORIGINALITY/VALUE

This research integrates multiple machine learning and text processing methods to devise a hybrid method applicable to domains of specific medical literature retrieval. The proposed algorithm provides a 3% increase of P@10 than that of the state-of-the-art algorithm in TREC 2019.

MMKP: A mind mapping knowledgebase prototyping tool for precision medicine

Background

With significant advancements in the area of precision medicine, the breadth and complexity of the relevant knowledge in the field has increased significantly. However, the difficulty associated with dynamic modelling and the disorganization of such knowledge hinders its rapid development potential.

Results

To overcome the difficulty in using the relational database model for dynamic modelling, and to aid in the organization of precision medicine knowledge, we developed the Mind Mapping Knowledgebase Prototyping (MMKP) tool. The MMKP implements a novel design that we call a “polymorphic foreign key”, which allows the establishment of a logical linkage between a single table field and a record from any table. This design has advantages in supporting dynamic changes to the structural relationships in precision medicine knowledge. Knowledge stored in MMKP is presented as a mind map to facilitate human interaction. When using this tool, medical experts may curate the structure and content of the precision knowledge in a flow that is similar to the human thinking process.

Conclusions

The design of polymorphic foreign keys natively supports knowledge modelling in the form of mind mapping, which avoids the hard-coding of medical logic into a rigid database schema and significantly reduces the workload that is required for adapting a relational data model to future changes to the medical logic. The MMKP tool provides a graphical user interface for both data management and knowledgebase prototyping. It supports the flexible customization of the data field constraints and annotations. MMKP is available as open-source code on GitHub: https://github.com/ZjuLiangsl/mmkp.

Ciência, Tecnologia e Inovações em Oncologia

A medicina genômica e a saúde de precisão deram seu primeiro grande passo no início dos anos 2000. O Projeto Genoma Humano (HGP, do inglês Human Genome Project), iniciado em 1990 e finalizado em 2003, não apenas impactou de forma significativa a compreensão sobre a arquitetura do genoma humano e a correlação deste com diferentes doenças, como também gerou uma revolução tecnológica multidisciplinar. Vinte anos depois, ainda são consideradas inovações em todo mundo, uma vez que sua implementação pelos sistemas de saúde não é simples, requerendo uma gama de ações e iniciativas complexas. Os rápidos avanços nos métodos de diagnóstico molecular, terapias avançadas e medicina de precisão enfatizam a necessidade da tradução desses conhecimentos para otimizar a aplicabilidade nos serviços de saúde da população. O Genomas Brasil apresenta uma prova de conceito que fornecerá dados importantes para a demonstração do valor da saúde de precisão para o SUS, subsidiando a futura tomada de decisão em relação à implementação, à projeção e ao escalonamento para o sistema de saúde público. O programa é fundamental para a transição adequada para um sistema de saúde baseado em saúde de precisão, etapa crítica para a adequação de estratégias, metodologias e protocolos e para o gerenciamento de riscos e potenciais obstáculos a serem enfrentados. Além disso, pretende iniciar uma revolução no SUS por meio do uso de estratégias de fronteira do conhecimento para fornecer o mais preciso e moderno cuidado à saúde à população brasileira, trazendo grandes transformações para a força de trabalho em saúde, para o avanço do conhecimento científico e para a indústria de saúde nacional.

Precision Medicine Testing and Disparities in Health Care for Individuals With Non-Small Cell Lung Cancer: A Narrative Review

PROBLEM IDENTIFICATION

Precision medicine initiatives provide opportunities for optimal targeted therapy in individuals with non-small cell lung cancer. However, there are barriers to these initiatives that reflect social determinants of health.

LITERATURE SEARCH

MEDLINE®, CINAHL®, PsycINFO®, Embase®, and Google ScholarTM databases were searched for articles published in English in the United States from 2016 to 2020.

DATA EVALUATION

Data that were collected included individual demographic information, specific diagnosis, status of targeted genomic testing, and receipt of targeted therapy. All studies were retrospective and involved database review of insurance claims or medical records.

SYNTHESIS

Individuals with non-small cell lung cancer received less genetic testing and targeted therapy if they were of a lower socioeconomic status, had public health insurance or no health insurance, were Black, or lived in rural communities.

IMPLICATIONS FOR NURSING

Social determinants of health affect health equity, including in precision medicine initiatives for individuals with lung cancer. Gaining an understanding of this impact is the first step in mitigating inequities.

Applications and Biocompatibility of Mesoporous Silica Nanocarriers in the Field of Medicine

Mesoporous silica nanocarrier (MSN) preparations have a wide range of medical applications. Studying the biocompatibility of MSN is an important part of clinical transformation. Scientists have developed different types of mesoporous silica nanocarriers (MSNs) for different applications to realize the great potential of MSNs in the field of biomedicine, especially in tumor treatment. MSNs have achieved good results in diagnostic bioimaging, tissue engineering, cancer treatment, vaccine development, biomaterial application and diagnostics. MSNs can improve the therapeutic efficiency of drugs, introduce new drug delivery strategies, and provide advantages that traditional drugs lack. It is necessary not only to innovate MSNs but also to comprehensively understand their biological distribution. In this review, we summarize the various medical uses of MSN preparations and explore the factors that affect their distribution and biocompatibility in the body based on metabolism. Designing more reasonable therapeutic nanomedicine is an important task for the further development of the potential clinical applications of MSNs.

Implementing the FAIR Data Principles in precision oncology: review of supporting initiatives

Compelling research has recently shown that cancer is so heterogeneous that single research centres cannot produce enough data to fit prognostic and predictive models of sufficient accuracy. Data sharing in precision oncology is therefore of utmost importance. The Findable, Accessible, Interoperable and Reusable (FAIR) Data Principles have been developed to define good practices in data sharing. Motivated by the ambition of applying the FAIR Data Principles to our own clinical precision oncology implementations and research, we have performed a systematic literature review of potentially relevant initiatives. For clinical data, we suggest using the Genomic Data Commons model as a reference as it provides a field-tested and well-documented solution. Regarding classification of diagnosis, morphology and topography and drugs, we chose to follow the World Health Organization standards, i.e. ICD10, ICD-O-3 and Anatomical Therapeutic Chemical classifications, respectively. For the bioinformatics pipeline, the Genome Analysis ToolKit Best Practices using Docker containers offer a coherent solution and have therefore been selected. Regarding the naming of variants, we follow the Human Genome Variation Society's standard. For the IT infrastructure, we have built a centralized solution to participate in data sharing through federated solutions such as the Beacon Networks.

Multiple strategies with the synergistic approach for addressing colorectal cancer

Cancer treatment is improving widely over time, but finding a proper defender to beat them seems like a distant dream. The quest for identification and discovery of drugs with an effective action is still a vital work. The role of a membrane protein called P-glycoprotein, which functions as garbage chute that efflux the waste, xenobiotics, and toxins out of the cancer cells acts as a major reason behind the therapeutic failure of most chemotherapeutic drugs. In this review, we mainly focused on a multiple strategies by employing 5-Fluorouracil, curcumin, and lipids in Nano formulation for the possible treatment of colorectal cancer and its metastasis. Eventually, multidrug resistance and angiogenesis can be altered and it would be helpful in colorectal cancer targeting.We have depicted the possible way for the depletion of colorectal cancer cells without disturbing the normal cells. The concept of focusing on multiple pathways for marking the colorectal cancer cells could help in activating one among the pathways if the other one fails. The activity of the 5-Fluorouracil can be enhanced with the help of curcumin which acts as a chemosensitizer, chemotherapeutic agent, and even for altering the resistance. As we eat to survive, so do the cancer cells. The cancer cells utilize the energy source to stay alive and survive. Fatty acids can be used as the energy source and this concept can be employed for targeting the colorectal cancer cells and also for altering the resistant part.

Trailblazing precision medicine in Europe: A joint view by Genomic Medicine Sweden and the Centers for Personalized Medicine, ZPM, in Germany

Over the last decades, rapid technological and scientific advances have led to a merge of molecular sciences and clinical medicine, resulting in a better understanding of disease mechanisms and the development of novel therapies that exploit specific molecular lesions or profiles driving disease. Precision oncology is here used as an example, illustrating the potential of precision/personalized medicine that also holds great promise in other medical fields. Real-world implementation can only be achieved by dedicated healthcare connected centers which amass and build up interdisciplinary expertise reflecting the complexity of precision medicine. Networks of such centers are ideally suited for a nation-wide outreach offering access to precision medicine to patients independent of their place of residence. Two of these multicentric initiatives, Genomic Medicine Sweden (GMS) and the Centers for Personalized Medicine (ZPM) initiative in Germany have teamed up to present and share their views on core concepts, potentials, challenges, and future developments in precision medicine. Together with other initiatives worldwide, GMS and ZPM aim at providing a robust and sustainable framework, covering all components from technology development to clinical trials, ethical and legal aspects as well as involvement of all relevant stakeholders, including patients and policymakers in the field.

Proteomic Interrogation in Cancer Biomarker

Biomarkers factor into the diagnosis and treatment of almost every patient with cancer. The innovation in proteomics follows improvement of mass spectrometry techniques and data processing strategy. Recently, proteomics and typical biological studies have been the answer for clinical applications. The clinical proteomics techniques are now actively adapted to protein identification in large patient cohort, biomarker development for more sensitive and specific screening based on quantitative data. And, it is important for clinical, translational researchers to be acutely aware of the issues surrounding appropriate biomarker development, in order to facilitate entry of clinically useful biomarkers into the clinic. Here, we discuss in detail include the case research for clinical proteomics. Furthermore, we give an overview on the current developments and novel findings in proteomics-based cancer biomarker research.

Governing Personalized Health: A Scoping Review

Genetic research is advancing rapidly. One important area for the application of the results from this work is personalized health. These are treatments and preventive interventions tailored to the genetic profile of specific groups or individuals. The inclusion of personalized health in existing health systems is a challenge for policymakers. In this article, we present the results of a thematic scoping review of the literature dealing with governance and policy of personalized health. Our analysis points to four governance challenges that decisionmakers face against the background of personalized health. First, researchers have highlighted the need to further extend and harmonize existing research infrastructures in order to combine different types of genetic data. Second, decisionmakers face the challenge to create trust in personalized health applications, such as genetic tests. Third, scholars have pointed to the importance of the regulation of data production and sharing to avoid discrimination of disadvantaged groups and to facilitate collaboration. Fourth, researchers have discussed the challenge to integrate personalized health into regulatory-, financing-, and service provision structures of existing health systems. Our findings summarize existing research and help to guide further policymaking and research in the field of personalized health governance.

Future of Health Services: The Role of Physicians in the Disruptive Era

This article aimed to address the role of physicians in future health in the disruptive era. Physicians in this disruptive era must increase their capability and knowledge to compensate for this development. Advances in technology increase the impact on health care and the significance of disruption. Disruptive innovation encompasses several fields, such as physics, digital, and biology. Big data as one of the most important parts in clinical aspects encompass high-throughput cellular and protein-binding assays toward chemoinformatic-driven databases. Health status can be modified by changing epigenetic factor, such as lifestyle and environment. As a result, they affect human genetics and provide the insight of pathophysiology of disease, clinical treatment, and early preventive action. Disruptive innovations in health-care align with the development of artificial intelligence, machine learning, robotics, Internet of things, digitalization, and genomics. New paradigm shifting in physician–patient relationships is relevant to consumer health informatics.

Opportunities for the use of health information technology to support research

In the last decade, expanding use of health information technology (IT) across the United States has created opportunities for use of electronic health data for health services and biomedical research, but efforts may be hampered by limited data access, data quality, and system functionality. We identify five opportunities to advance the use of health IT for health services and biomedical research, which informed a federal government-led, collaborative effort to develop a relevant policy and development agenda. In particular, the health IT infrastructure should more effectively support the use of electronic health data for research; provide adaptable technologies; incorporate relevant research-related functionality; support patient and caregiver engagement in research; and support effective integration of knowledge into practice. While not exhaustive, these represent important opportunities that the biomedical and health informatics communities can pursue to better leverage health IT and electronic health data for research.

Novel biomimetic dual-mode nanodroplets as ultrasound contrast agents with potential ability of precise detection and photothermal ablation of tumors

PURPOSE

Molecule-targeted ultrasound imaging has attracted extensive attention for precise diagnosis and targeted therapy of tumors. The aim of this research is to prepare novel biomimetic dual-mode nanoscale ultrasound contrast agents (UCAs), which can not only evade the immune clearance of reticuloendothelial system, but also have the potential ability of precise detection and photothermal ablation of tumors.

METHODS

In this study, for the first time, the novel biomimetic UCAs were prepared by encapsulating liquid perfluorohexanes with red blood cell membranes carrying IR-780 iodide and named IR780-RBCM@NDs. The characteristics of that were verified through the particle size analyzer, scanning electron microscopy, transmission electron microscopy and laser scanning confocal microscopy. The stability of IR780-RBCM@NDs at 37 °C was explored. The abilities of immune escape, dual-mode imaging and photothermal effect for IR780-RBCM@NDs were verified via in vitro experiments.

RESULTS

The novel prepared nanodroplets have good characteristics such as mean diameter, zeta potential, and relatively stability. Importantly, the integrin-associated protein expressed on the surface of RBCMs was detected on IR780-RBCM@NDs. Then, compared with control groups, IR780-RBCM@NDs performed excellent immune escape function away from macrophages in vitro. Furthermore, the IR-780 iodide was observed on the new nanodroplets and that was able to perform the dual-mode imaging with near-infrared fluorescence imaging and contrast-enhanced ultrasound imaging after the phase change. Finally, the effective photothermal ablation ability of IR780-RBCM@NDs was verified in tumor cells.

CONCLUSION

The newly prepared biomimetic IR780-RBCM@NDs provided novel ideas for evading immune clearance, performing precise diagnosis and photothermal ablation of tumor cells.

Being Precise About Precision Medicine: What Should Value Frameworks Incorporate to Address Precision Medicine? A Report of the Personalized Precision Medicine Special Interest Group

Precision medicine is a dynamic area embracing a diverse and increasing type of approaches that allow the targeting of new medicines, screening programs or preventive healthcare strategies, which include the use of biologic markers or complex tests driven by algorithms also potentially taking account of patient preferences. The International Society for Pharmacoeconomics and Outcome Research expanded its current work around precision medicine to (1) describe the evolving paradigm of precision medicine with examples of current and evolving applications, (2) describe key stakeholders perspectives on the value of precision medicine in their respective domains, and (3) define the core factors that should be considered in a value assessment framework for precision medicine. With the ultimate goal of improving health of well-defined patient groups, precision medicine will affect all stakeholders in the healthcare system at multiple levels spanning the individual perspective to the societal perspective. For an efficient, timely and practical precision medicine value assessment framework, it will be important to address these multiple perspectives through building consensus among the stakeholders for robust procedures and measures of value aspects, including performance of precision mechanism; aligned reimbursement processes of precision mechanism and subsequent treatment; transparent expectations for evidence requirements and study designs adequately matched to the intended use of the precision mechanism and to the smaller target patient populations; recognizing the potential range of value-generation such as ruling-in and ruling-out decisions.

DNA methylation-based profiling for paediatric CNS tumour diagnosis and treatment: a population-based study

BACKGROUND

Marked variation exists in the use of genomic data in tumour diagnosis, and optimal integration with conventional diagnostic technology remains uncertain despite several studies reporting improved diagnostic accuracy, selection for targeted treatments, and stratification for trials. Our aim was to assess the added value of molecular profiling in routine clinical practice and the impact on conventional and experimental treatments.

METHODS

This population-based study assessed the diagnostic and clinical use of DNA methylation-based profiling in childhood CNS tumours using two large national cohorts in the UK. In the diagnostic cohort-which included routinely diagnosed CNS tumours between Sept 1, 2016, and Sept 1, 2018-we assessed how the methylation profile altered or refined diagnosis in routine clinical practice and estimated how this would affect standard patient management. For the archival cohort of diagnostically difficult cases, we established how many cases could be solved using modern standard pathology, how many could only be solved using the methylation profile, and how many remained unsolvable.

FINDINGS

Of 484 patients younger than 20 years with CNS tumours, 306 had DNA methylation arrays requested by the neuropathologist and were included in the diagnostic cohort. Molecular profiling added a unique contribution to clinical diagnosis in 107 (35%; 95% CI 30-40) of 306 cases in routine diagnostic practice-providing additional molecular subtyping data in 99 cases, amended the final diagnosis in five cases, and making potentially significant predictions in three cases. We estimated that it could change conventional management in 11 (4%; 95% CI 2-6) of 306 patients. Among 195 historically difficult-to-diagnose tumours in the archival cohort, 99 (51%) could be diagnosed using standard methods, with the addition of methylation profiling solving a further 34 (17%) cases. The remaining 62 (32%) cases were unresolved despite specialist pathology and methylation profiling.

INTERPRETATION

Together, these data provide estimates of the impact that could be expected from routine implementation of genomic profiling into clinical practice, and indicate limitations where additional techniques will be required. We conclude that DNA methylation arrays are a useful diagnostic adjunct for childhood CNS tumours.

FUNDING

The Brain Tumour Charity, Children with Cancer UK, Great Ormond Street Hospital Children's Charity, Olivia Hodson Cancer Fund, Cancer Research UK, and the National Institute of Health Research.

High-Throughput Architecture for Discovering Combination Cancer Therapeutics

PURPOSE

The amount of available next-generation sequencing data of tumors, in combination with relevant molecular and clinical data, has significantly increased in the last decade and transformed translational cancer research. Even with the progress made through data-sharing initiatives, there is a clear unmet need for easily accessible analyses tools. These include capabilities to efficiently process large sequencing database projects to present them in a straightforward and accurate way. Another urgent challenge in cancer research is to identify more effective combination therapies.

METHODS

We have created a software architecture that allows the user to integrate and analyze large-scale sequencing, clinical, and other datasets for efficient prediction of potential combination drug targets. This architecture permits predictions for all genes pairs; however, Food and Drug Administration-approved agents are currently lacking for most of the identified gene targets.

RESULTS

By applying this approach, we performed a comprehensive study and analyzed all possible combination partners and identified potentially synergistic target pairs for 38 approved targets currently in clinical use. We further showed which genes could be synergistic prediction markers and potential targets with MAPK/ERK inhibitors for the treatment of melanoma. Moreover, we integrated a graph analytics technique in this architecture to identify pathways that could be targeted synergistically to enhance the efficacy of certain therapeutics in cancer.

CONCLUSION

The architecture and the results presented provide a foundation for discovering effective combination therapeutics.

Counting Oceanians of Non-European, Non-Asian Descent (ONENA) in the South Pacific to Make Them Count in Global Health

Several diseases and vulnerabilities associated with genetic or microbial factors are more frequent among populations of Oceanian, Non-European, Non-Asian descent (ONENA). ONENA are specific and have long been isolated geographically. To our knowledge, there are no published official, quantitative, aggregated data on the populations impacted by these excess vulnerabilities in Oceania. We searched official census reports for updated estimates of the total population for each of the Pacific Island Countries and Territories (including Australia) and the US State of Hawaii, privileging local official statistical or censual sources. We multiplied the most recent total population estimate by the cumulative percentage of the ONENA population as determined in official reports. Including Australia and the US State of Hawaii, Oceania counts 27 countries and territories, populated in 2016 by approximately 41 M inhabitants (17 M not counting Australia) among which approximately 12.5 M (11.6 M not counting Australia) consider themselves of entire or partial ONENA ancestry. Specific genetic and microbiome traits of ONENA may be unique and need further investigation to adjust risk estimates, risk prevention, diagnostic and therapeutic strategies, to the benefit of populations in the Pacific and beyond.

A Review of the Challenges of Using Biomedical Big Data for Economic Evaluations of Precision Medicine

There is potential value in incorporating biomedical big data (BBD)-observational real-world patient-level genomic and clinical data in multiple sub-populations-into economic evaluations of precision medicine. However, health economists face practical and methodological challenges when using BBD in this context. We conducted a literature review to identify and summarise these challenges. Relevant articles were identified in MEDLINE, EMBASE, EconLit, University of York Centre for Reviews and Dissemination and Cochrane Library from 2000 to 2018. Articles were included if they studied issues relevant to the interconnectedness of biomedical big data, precision medicine, and health economic evaluation. Nineteen articles were included in the review. Challenges identified related to data management, data quality and data analysis. The availability of large volumes of data from multiple sources, the need to conduct data linkages within an environment of opaque data access and sharing procedures, and other data management challenges are primarily practical and may not be long-term obstacles if procedures for data sharing and access are improved. However, the existence of missing data across linked datasets, the need to accommodate dynamic data, and other data quality and analysis challenges may require an evolution in economic evaluation methods. Health economists face challenges when using BBD in economic evaluations of technologies that facilitate precision medicine. Potential solutions to some of these challenges do, however, exist. Going forward, health economists who present work that uses BBD should document challenges and the solutions they have applied to the challenges to support future researcher endeavours.

Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review

BACKGROUND

Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges.

OBJECTIVES

The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting.

METHODS

This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted.

RESULTS

A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures).

CONCLUSIONS

The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.

Beyond the Helix: Ethical, Legal, and Social Implications in Genomics

OBJECTIVE

To review ethical, legal, and social implications of genomics, a ground-breaking science that when applied improves cancer care outcomes.

DATA SOURCES

PubMed, Cumulative Index to Nursing and Allied Health (CINAHL), Cochrane Library, consensus statements, and professional guidelines.

CONCLUSION

Ethical, legal, and social domains of genomics are not fully delineated. Areas needing further discussion and policies include return of findings, informed consent, electronic health records, and data resources and sharing.

IMPLICATIONS FOR NURSING PRACTICE

All nurses need a basic understanding of the ethical, legal, and social implications of genomics.

Sharing longitudinal, non-biological birth cohort data: a cross-sectional analysis of parent consent preferences

BACKGROUND

Mandates abound to share publicly-funded research data for reuse, while data platforms continue to emerge to facilitate such reuse. Birth cohorts (BC) involve longitudinal designs, significant sample sizes and rich and deep datasets. Data sharing benefits include more analyses, greater research complexity, increased opportunities for collaboration, amplification of public contributions, and reduced respondent burdens. Sharing BC data involves significant challenges including consent, privacy, access policies, communication, and vulnerability of the child. Research on these issues is available for biological data, but these findings may not extend to BC data. We lack consensus on how best to approach these challenges in consent, privacy, communication and autonomy when sharing BC data. We require more stakeholder engagement to understand perspectives and generate consensus.

METHODS

Parents participating in longitudinal birth cohorts completed a web-based survey investigating consent preferences for sharing their, and their child's, non-biological research data. Results from a previous qualitative inquiry informed survey development, and cognitive interviewing methods (n = 9) were used to improve the question quality and comprehension. Recruitment was via personalized email, with email and phone reminders during the 14-day window for survey completion.

RESULTS

Three hundred and forty-six of 569 parents completed the survey in September 2014 (60.8%). Participants preferred consent processes for data sharing in future independent research that were less-active (i.e. no consent or opt-out). Parents' consent preferences are associated with their communication preferences. Twenty percent (20.2%) of parents generally agreed that their child should provide consent to continue participating in research at age 12, while 25.6% felt decision-making on sharing non-biological research data should begin at age 18.

CONCLUSIONS

These finding reflect the parenting population's preference for less project-specific permission when research data is non-biological and de-identified and when governance practices are highly detailed and rigourous. Parents recognize that children should become involved in consent for secondary data use, but there is variability regarding when and how involvement occurs. These findings emphasize governance processes and participant notification rather than project-specific consent for secondary use of de-identified, non-biological data. Ultimately, parents prefer general consent processes for sharing de-identified, non-biological research data with ultimate involvement of the child.

Clinical exome sequencing in France and Quebec: what are the challenges? What does the future hold?

BACKGROUND

The decreasing cost of next-generation sequencing technologies (NGS) has resulted in their increased use in research, and in the clinic. However, France and Quebec have not yet implemented nation-wide personalized medicine programs using NGS. To produce policies on the large-scale implementation of NGS, decision makers could benefit from a detailed understanding of how these technologies are currently used, their limitations, and the benefits they could bring to patients.

OBJECTIVES

We aimed at answering two research questions: How are patients' NGS data currently managed in healthcare institutions in Quebec and in France? What issues do technology users identify which should be solved in order to implement clinical genomics at the national level?

METHOD

Through a multiple case study method, we analysed interviews and documentation from four teams that use whole-exome sequencing in hybrid clinical research projects focusing on cancer and rare diseases.

RESULTS

Interviewees detailed numerous challenges linked with managing the complexity of the process of collecting and interpreting data in a relevant manner for patients, and described how obtaining buy-in from multiple stakeholders was necessary.

CONCLUSION

A strong political will is essential for personalized medicine to be implemented efficiently in France and Quebec.

Analyzing the clinical actionability of germline pharmacogenomic findings in oncology

BACKGROUND

Germline and tumor pharmacogenomics impact drug responses, but germline markers less commonly guide oncology prescribing. The authors hypothesized that a critical number of clinically actionable germline pharmacogenomic associations exist, representing clinical implementation opportunities.

METHODS

In total, 125 oncology drugs were analyzed for positive germline pharmacogenomic associations in journals with impact factors ≥5. Studies were assessed for design and genotyping quality, clinically relevant outcomes, statistical rigor, and evidence of drug-gene effects. Associations from studies of high methodologic quality were deemed potentially clinically actionable, and translational summaries were written as point-of-care clinical decision support (CDS) tools and formally evaluated using the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument.

RESULTS

The authors identified germline pharmacogenomic results for 56 of 125 oncology drugs (45%) across 173 publications. Actionable associations were detected for 12 drugs, including 6 that had germline pharmacogenomic information within US Food and Drug Administration labels or published guidelines (capecitabine/fluorouracil/dihydropyrimidine dehydrogenase [DPYD], irinotecan/uridine diphosphate glucuronosyltransferase family 1 member A1 [UGT1A1], mercaptopurine/thioguanine/thiopurine S-methyltransferase [TPMT], tamoxifen/cytochrome P450 [CYP] family 2 subfamily D member 6 [CYP2D6]), and 6 others were novel (asparaginase/nuclear factor of activated T-cells 2 [NFATC2]/human leukocyte antigen D-related β1 [HLA-DRB1], cisplatin/acylphosphatase 2 [ACYP2], doxorubicin/adenosine triphosphate-binding cassette subfamily C member 2/Rac family small guanosine triphosphatase 2/neutrophil cytosolic factor 4 [ABCC2/RAC2/NCF4], lapatinib/human leukocyte antigen DQ α1 [HLA-DQA1], sunitinib/cytochrome P450 family 3 subfamily A member 5 [CYP3A5], vincristine/centrosomal protein 72 [CEP72]). By using AGREE II, the developed CDS summaries had high mean ± standard deviation scores (maximum score, 100) for scope and purpose (92.7 ± 5.1) and rigour of development (87.6 ± 7.4) and moderate yet robust scores for clarity of presentation (58.6 ± 25.1) and applicability (55.9 ± 24.6). The overall mean guideline quality score was 5.2 ± 1.0 (maximum score, 7). Germline pharmacogenomic CDS summaries for these 12 drugs were recommended for implementation.

CONCLUSIONS

Several oncology drugs have actionable germline pharmacogenomic information, justifying their delivery through institutional pharmacogenomic implementations to determine clinical utility. Cancer 2018;124:3052-65. © 2018 American Cancer Society.

Pharmacogenetics: An Important Part of Drug Development with A Focus on Its Application

Since the human genome project in 2003, the view of personalized medicine to improve diagnosis and cure diseases at the molecular level became more real. Sequencing the human genome brought some benefits in medicine such as early detection of diseases with a genetic predisposition, treating patients with rare diseases, the design of gene therapy and the understanding of pharmacogenetics in the metabolism of drugs. This review explains the concepts of pharmacogenetics, polymorphisms, mutations, variations, and alleles, and how this information has helped us better understand the metabolism of drugs. Multiple resources are presented to promote reducing the gap between scientists, physicians, and patients in understanding the use and benefits of pharmacogenetics. Some of the most common clinical examples of genetic variants and how pharmacogenetics was used to determine treatment options for patients having these variants were discussed. Finally, we evaluated some of the challenges of implementing pharmacogenetics in a clinical setting and proposed actions to be taken to make pharmacogenetics a standard diagnostic tool in personalized medicine.

Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein-protein interaction, and pharmacogenomics data, are indispensable to glean into the cancer genome and proteome and these approaches have generated multidimensional universal studies of genes and proteins (OMICS) data which has the potential to facilitate precision medicine. However, due to slow progress in computational technologies, the translation of big omics data into their clinical aspects have been slow. In this review, attempts have been made to describe the role of high-throughput genomic and proteomic technologies in identifying a panel of biomarkers which could be used for the early diagnosis and prognosis of cancer.

Unsolved challenges in pediatric whole-exome sequencing: A literature analysis

Whole-exome sequencing (WES) has been instrumental in the discovery of novel genes and mechanisms causing Mendelian diseases. While this technology is now being successfully applied in a number of clinics, particularly to diagnose patients with rare diseases, it also raises a number of ethical, legal and social issues. In order to identify what challenges were directly foreseen by technology users, we performed a systematic review of the literature. In this paper, we focus on recent publications related to the use of WES in the pediatric context and analyze the most prominent challenges raised by technology users. This is particularly relevant considering that a) most patients currently undergoing testing using WES to identify the genetic basis for rare diseases are children and b) their lack of capacity to consent for themselves makes them a vulnerable population and generates the need for specific ethical, legal and regulatory procedures. We identified key challenges that related to four main categories: (1) intake; (2) sequence production and analysis; (3) reporting of results and counseling considerations and (4) collaborative data interpretation and data sharing. We then contextualize these challenges in light of the recent recommendations and guidelines, published by professional societies that have significant potential to impact the field.