Cost-effectiveness of precision medicine: a scoping review

Overview of Venous Thromboembolism and Emerging Therapeutic Technologies Based on Nanocarriers-Mediated Drug Delivery Systems

Venous thromboembolism (VTE) is a serious health condition and represents an important cause of morbidity and, in some cases, mortality due to the lack of effective treatment options. According to the Centers for Disease Control and Prevention, 3 out of 10 people with VTE will have recurrence of a clotting event within ten years, presenting a significant unmet medical need. For some VTE patients, symptoms can last longer and have a higher than average risk of serious complications; in contrast, others may experience complications arising from insufficient therapies. People with VTE are initially treated with anticoagulants to prevent conditions such as stroke and to reduce the recurrence of VTE. However, thrombolytic therapy is used for people with pulmonary embolism (PE) experiencing low blood pressure or in severe cases of DVT. New drugs are under development, with the aim to ensure they are safe and effective, and may provide an additional option for the treatment of VTE. In this review, we summarize all ongoing trials evaluating anticoagulant interventions in VTE listed in clinicaltrials.gov, clarifying their underlying mechanisms and evaluating whether they prevent the progression of DVT to PE and recurrence of thrombosis. Moreover, this review summarizes the available evidence that supports the use of antiplatelet therapy for VTE. Since thrombolytic agents would cause off-target effects, targeted drug delivery platforms are used to develop various therapeutics for thrombotic diseases. We discuss the recent advances achieved with thrombus-targeting nanocarriers as well as the major challenges associated with the use of nanoparticle-based therapeutics.

Personalized medicine: Clinical oncology on molecular view of treatment

Cancer, the second leading global cause of death, impacts both physically and emotionally. Conventional treatments such as surgeries, chemotherapy, and radiotherapy have adverse effects, driving the need for more precise approaches. Precision medicine enables more targeted treatments. Genetic mapping, alongside other molecular biology approaches, identifies specific genes, contributing to accurate prognoses. The review addresses, in clinical use, a molecular perspective on treatment. Biomarkers like alpha-fetoprotein, beta-human chorionic gonadotropin, 5-hydroxyindoleacetic acid, programmed death-1, and cytotoxic T lymphocyte-associated protein 4 are explored, providing valuable information. Bioinformatics, with an emphasis on artificial intelligence, revolutionizes the analysis of biological data, offering more accurate diagnoses. Techniques like liquid biopsy are emphasized for early detection. Precision medicine guides therapeutic strategies based on the molecular characteristics of the tumor, as evidenced in the molecular subtypes of breast cancer. Classifications allow personalized treatments, highlighting the role of trastuzumab and endocrine therapies. Despite the benefits, challenges persist, including high costs, tumor heterogeneity, and ethical issues. Overcoming obstacles requires collaboration, ensuring that advances in molecular biology translate into accessible benefits for all.

Bridging the Divide: A Review on the Implementation of Personalized Cancer Medicine

The shift towards personalized cancer medicine (PCM) represents a significant transformation in cancer care, emphasizing tailored treatments based on the genetic understanding of cancer at the cellular level. This review draws on recent literature to explore key factors influencing PCM implementation, highlighting the role of innovative leadership, interdisciplinary collaboration, and coordinated funding and regulatory strategies. Success in PCM relies on overcoming challenges such as integrating diverse medical disciplines, securing sustainable investment for shared infrastructures, and navigating complex regulatory landscapes. Effective leadership is crucial for fostering a culture of innovation and teamwork, essential for translating complex biological insights into personalized treatment strategies. The transition to PCM necessitates not only organizational adaptation but also the development of new professional roles and training programs, underscoring the need for a multidisciplinary approach and the importance of team science in overcoming the limitations of traditional medical paradigms. The conclusion underscores that PCM's success hinges on creating collaborative environments that support innovation, adaptability, and shared vision among all stakeholders involved in cancer care.

Patient-centered precision care in anaesthesia - the PC-square (PC) 2 approach

PURPOSE OF REVIEW

This review navigates the landscape of precision anaesthesia, emphasising tailored and individualized approaches to anaesthetic administration. The aim is to elucidate precision medicine principles, applications, and potential advancements in anaesthesia. The review focuses on the current state, challenges, and transformative opportunities in precision anaesthesia.

RECENT FINDINGS

The review explores evidence supporting precision anaesthesia, drawing insights from neuroscientific fields. It probes the correlation between high-dose intraoperative opioids and increased postoperative consumption, highlighting how precision anaesthesia, especially through initiatives like Safe Brain Initiative (SBI), could address these issues. The SBI represents multidisciplinary collaboration in perioperative care. SBI fosters effective communication among surgical teams, anaesthesiologists, and other medical professionals.

SUMMARY

Precision anaesthesia tailors care to individual patients, incorporating genomic insights, personalised drug regimens, and advanced monitoring techniques. From EEG to cerebral/somatic oximetry, these methods enhance precision. Standardised reporting, patient-reported outcomes, and continuous quality improvement, alongside initiatives like SBI, contribute to improved patient outcomes. Precision anaesthesia, underpinned by collaborative programs, emerges as a promising avenue for enhancing perioperative care.

Nuclear Cardiology in the Era of Precision Medicine: Tailoring Treatment to the Individual Patient

Nuclear cardiology, employing advanced imaging technologies like positron emission tomography (PET) and single photon emission computed tomography (SPECT), is instrumental in diagnosing, risk stratifying, and managing heart diseases. Concurrently, precision medicine advocates for treatments tailored to each patient's genetic, environmental, and lifestyle specificities, promising a revolution in personalized cardiovascular care. This review explores the synergy between nuclear cardiology and precision medicine, highlighting advancements, potential enhancements in patient outcomes, and the challenges and opportunities of this integration. We examined the evolution of nuclear cardiology technologies, including PET and SPECT, and their role in cardiovascular diagnostics. We also delved into the principles of precision medicine, focusing on genetic and molecular profiling, data analytics, and individualized treatment strategies. The integration of these domains aims to optimize diagnostic accuracy, therapeutic interventions, and prognostic evaluations in cardiovascular care. Advancements in molecular imaging and the application of artificial intelligence in nuclear cardiology have significantly improved the precision of diagnostics and treatment plans. The adoption of precision medicine principles in nuclear cardiology enables the customization of patient care, leveraging genetic information and biomarkers for enhanced therapeutic outcomes. However, challenges such as data integration, accessibility, cost, and the need for specialized expertise persist. The confluence of nuclear cardiology and precision medicine offers a promising pathway toward revolutionizing cardiovascular healthcare, providing more accurate, effective, and personalized patient care. Addressing existing challenges and fostering interdisciplinary collaboration is crucial for realizing the full potential of this integration in improving patient outcomes.

A QALY is [still] a QALY is [still] a QALY? : Evaluating proportional shortfall as the answer to the problem of equity in healthcare allocations

Despite clinical evidence of drug superiority, therapeutic modalities, like combination immunotherapy, are mostly considered cost-ineffective due to their high costs per life year(s) gained. This paper, taking an ethical stand, reevaluates the standard cost-effectiveness analysis with that of the more recent justice-enhanced methods and concludes by pointing out the shortcomings of the current methodologies.

Moving toward precision medicine to predict drug sensitivity in patients with metastatic breast cancer

Tumor heterogeneity represents a major challenge in breast cancer, being associated with disease progression and treatment resistance. Precision medicine has been extensively applied to dissect tumor heterogeneity and, through a deeper molecular understanding of the disease, to personalize therapeutic strategies. In the last years, technological advances have widely improved the understanding of breast cancer biology and several trials have been developed to translate these new insights into clinical practice, with the ultimate aim of improving patients' outcomes. In the era of molecular oncology, genomics analyses and other methodologies are shaping a new treatment algorithm in breast cancer care. In this manuscript, we review the main steps of precision medicine to predict drug sensitivity in breast cancer from a translational point of view. Genomic developments and their clinical implications are discussed, along with technological advancements that could broaden precision medicine applications. Current achievements are put into perspective to provide an overview of the state-of-art of breast cancer precision oncology as well as to identify future research directions.

Neoadjuvant personalized cancer vaccines: the final frontier?

INTRODUCTION

Clinical trials of personalized cancer vaccines have shown that on-demand therapies that are manufactured for each patient, result in activated T cell responses against individual tumor neoantigens. However, their use has been traditionally restricted to adjuvant settings and late-stage cancer therapy. There is growing support for the implementation of PCV earlier in the cancer therapy timeline, for reasons that will be discussed in this review.

AREAS COVERED

The efficacy of cancer vaccines may be to some extent dependent on treatment(s) given prior to vaccine administration. Tumors can undergo radical immunoediting following treatment with immunotherapies, such as checkpoint inhibitors, which may affect the presence of the very mutations targeted by cancer vaccines. This review will cover the topics of neoantigen cancer vaccines, tumor immunoediting, and therapy timing.

EXPERT OPINION

Therapy timing remains a critical topic to address in optimizing the efficacy of personalized cancer vaccines. Most personalized cancer vaccines are being evaluated in late-stage cancer patients and after treatment with checkpoint inhibitors, but they may offer a greater benefit to the patient if administered in earlier clinical settings, such as the neoadjuvant setting, where patients are not facing T cell exhaustion and/or a further compromised immune system.

OSATS scoring confirms ICG enhancement of performance in laparoscopic radical gastrectomy: a post-hoc analysis of a randomized controlled trial

BACKGROUND

Indocyanine green (ICG) fluorescence imaging is effective in increasing the number of lymph node dissections during laparoscopic radical gastrectomy; however, no studies have attempted to explain this phenomenon.

METHODS

This study utilized the data from a previous randomized controlled trial (FUGES-012 study) investigating ICG-guided laparoscopic radical gastrectomy performed between November 2018 and July 2019. The Objective Structured Assessments of Technical Skills (OSATS) scoring system was used to grade videos from the ICG and non-ICG groups. Patients with an OSATS score greater than 29 were classified as the high-OSATS population, while those with an OSATS score less than or equal to 29 were classified as the low-OSATS population.

RESULTS

A total of 258 patients were included in the modified intention-to-treat analysis: 129 in the ICG group and 129 in the non-ICG group. The OSATS score of the ICG group was higher than that of the non-ICG group (29.6±2.6 vs. 26.6±3.6; P <0.001). The ICG group underwent a significantly higher mean total number of lymph node dissections than the non-ICG group (50.5±15.9 vs. 42.0±10.3; adjusted P <0.001). The group assigned to ICG use, better OSATS (high-OSATS) scores were observed, which correlated with greater D2 lymph node retrieval (54.1±15.0 vs. 47.2±8.7; adjusted P =0.039). Finally, the ICG group had a lower rate of lymph node noncompliance than that of the non-ICG group (31.8 vs. 57.4%; P <0.001).

CONCLUSIONS

By applying the ICG fluorescence navigation technique, better OSATS scores were observed, which correlated with greater lymph node retrieval and a lower lymph node noncompliance rate, as recommended for individualized laparoscopic radical gastrectomy.

The Buzz Surrounding Precision Medicine: The Imperative of Incorporating It into Evidence-Based Medical Practice

Precision medicine (PM), through the integration of omics and environmental data, aims to provide a more precise prevention, diagnosis, and treatment of disease. Currently, PM is one of the emerging approaches in modern healthcare and public health, with wide implications for health care delivery, public health policy making formulation, and entrepreneurial endeavors. In spite of its growing popularity and the buzz surrounding it, PM is still in its nascent phase, facing considerable challenges that need to be addressed and resolved for it to attain the acclaim for which it strives. In this article, we discuss some of the current methodological pitfalls of PM, including the use of big data, and provide a perspective on how these challenges can be overcome by bringing PM closer to evidence-based medicine (EBM). Furthermore, to maximize the potential of PM, we present real-world illustrations of how EBM principles can be integrated into a PM approach.

An Assessment of the Knowledge and Perceptions of Precision Medicine (PM) in the Rwandan Healthcare Setting

INTRODUCTION

Precision medicine (PM) or personalized medicine is an innovative approach that aims to tailor disease prevention and treatment to consider the differences in people's genes, environments, and lifestyles. Although many efforts have been made to accelerate the universal adoption of PM, several challenges need to be addressed in order to advance PM in Africa. Therefore, our study aimed to establish baseline data on the knowledge and perceptions of the implementation of PM in the Rwandan healthcare setting.

METHOD

A descriptive qualitative study was conducted in five hospitals offering diagnostics and oncology services to cancer patients in Rwanda. To understand the existing policies regarding PM implementation in the country, two additional institutions were surveyed: the Ministry of Health (MOH), which creates and sets policies for the overall vision of the health sector, and the Rwanda Biomedical Center (RBC), which coordinates the implementation of health sector policies in the country. The researchers conducted 32 key informant interviews and assessed the functionality of available PM equipment in the 5 selected health facilities. The data were thematically categorized and analyzed.

RESULTS

The study revealed that PM is perceived as a complex and expensive program by most health managers and health providers. The most cited challenges to implementing PM included the following: the lack of policies and guidelines; the lack of supportive infrastructures and limited suppliers of required equipment and laboratory consumables; financial constraints; cultural, behavioral, and religious beliefs; and limited trained, motivated, and specialized healthcare providers. Regarding access to health services for cancer treatment, patients with health insurance pay 10% of their medical costs, which is still too expensive for Rwandans.

CONCLUSION

The study participants highlighted the importance of PM to enhance healthcare delivery if the identified barriers are addressed. For instance, Rwandan health sector leadership might consider the creation of specialized oncology centers in all or some referral hospitals with all the necessary genomic equipment and trained staff to serve the needs of the country and implement a PM program.

Mapping the value for money of precision medicine: a systematic literature review and meta-analysis

Objective

This study aimed to quantify heterogeneity in the value for money of precision medicine (PM) by application types across contexts and conditions and to quantify sources of heterogeneity to areas of particular promises or concerns as the field of PM moves forward.

Methods

A systemic search was performed in Embase, Medline, EconLit, and CRD databases for studies published between 2011 and 2021 on cost-effectiveness analysis (CEA) of PM interventions. Based on a willingness-to-pay threshold of one-time GDP per capita of each study country, the net monetary benefit (NMB) of PM was pooled using random-effects meta-analyses. Sources of heterogeneity and study biases were examined using random-effects meta-regressions, jackknife sensitivity analysis, and the biases in economic studies checklist.

Results

Among the 275 unique CEAs of PM, publicly sponsored studies found neither genetic testing nor gene therapy cost-effective in general, which was contradictory to studies funded by commercial entities and early stage evaluations. Evidence of PM being cost-effective was concentrated in a genetic test for screening, diagnosis, or as companion diagnostics (pooled NMBs, $48,152, $8,869, $5,693, p < 0.001), in the form of multigene panel testing (pooled NMBs = $31,026, p < 0.001), which only applied to a few disease areas such as cancer and high-income countries. Incremental effectiveness was an essential value driver for varied genetic tests but not gene therapy.

Conclusion

Precision medicine's value for money across application types and contexts was difficult to conclude from published studies, which might be subject to systematic bias. The conducting and reporting of CEA of PM should be locally based and standardized for meaningful comparisons.

Can knowledgeable experts assess costs and outcomes as if they were ignorant? An experiment within precision medicine evaluation

OBJECTIVES

The purpose of this study is to evaluate the validity of the standard approach in expert judgment for evaluating precision medicines, in which experts are required to estimate outcomes as if they did not have access to diagnostic information, whereas in fact, they do.

METHODS

Fourteen clinicians participated in an expert judgment task to estimate the cost and medical outcomes of the use of exome sequencing in pediatric patients with intractable epilepsy in Thailand. Experts were randomly assigned to either an "unblind" or "blind" group; the former was provided with the exome sequencing results for each patient case prior to the judgment task, whereas the latter was not provided with the exome sequencing results. Both groups were asked to estimate the outcomes for the counterfactual scenario, in which patients had not been tested by exome sequencing.

RESULTS

Our study did not show significant results, possibly due to the small sample size of both participants and case studies.

CONCLUSIONS

A comparison of the unblind and blind approach did not show conclusive evidence that there is a difference in outcomes. However, until further evidence suggests otherwise, we recommend the blind approach as preferable when using expert judgment to evaluate precision medicines because this approach is more representative of the counterfactual scenario than the unblind approach.

Therapeutic Phage Monitoring: A Review

With the global rise in antimicrobial resistance, there has been a renewed interest in the application of therapeutic phages to treat bacterial infections. Therapeutic phage monitoring (TPM) is proposed as an essential element of phage therapy (PT) protocols to generate data and fill knowledge gaps regarding the in vivo efficacy of therapeutic phages, patients' immune responses to PT, and the wider ecological effects of PT. By monitoring phage concentrations in blood and tissues, together with immune responses and possible ecological changes during PT, TPM may enable the optimization of dosing and the implementation of precision medicine approaches. Furthermore, TPM can validate diagnostic surrogates of efficacy, direct research efforts, and establish quality assurance indicators for therapeutic phage products. Thus, TPM holds great potential for enhancing our understanding of the multidirectional phage-bacteria-host interactions and advancing "best practice" PT, ultimately improving patient care.

Economic evaluations of predictive genetic testing: A scoping review

Predictive genetic testing can provide information about whether or not someone will develop or is likely to develop a specific condition at a later stage in life. Economic evaluation can assess the value of money for such testing. Studies on the economic evaluation of predictive genetic testing have been carried out in a variety of settings, and this research aims to conduct a scoping review of findings from these studies. We searched the PubMed, Web of Science, Embase, and Cochrane databases with combined search terms, from 2019 to 2022. Relevant studies from 2013 to 2019 in a previous systematic review were also included. The study followed the recommended stages for undertaking a scoping review. A total of 53 studies were included, including 33 studies from the previous review and 20 studies from the search of databases. A significant number of studies focused on the US, UK, and Australia (34%, 23%, and 11%). The most frequently included health conditions were cancer and cardiovascular diseases (68% and 19%). Over half of the studies compared predictive genetic testing with no genetic testing, and the majority of them concluded that at least some type of genetic testing was cost-effective compared to no testing (94%). Some studies stated that predictive genetic testing is becoming more cost-effective with the trend of lowering genetic testing costs. Studies on predictive genetic testing covered various health conditions, particularly cancer and cardiovascular diseases. Most studies indicated that predictive genetic testing is cost-effective compared to no testing.

Oncogenic Proteomics Approaches for Translational Research and HIV-Associated Malignancy Mechanisms

Recent advances in the field of proteomics have allowed extensive insights into the molecular regulations of the cell proteome. Specifically, this allows researchers to dissect a multitude of signaling arrays while targeting for the discovery of novel protein signatures. These approaches based on data mining are becoming increasingly powerful for identifying both potential disease mechanisms as well as indicators for disease progression and overall survival predictive and prognostic molecular markers for cancer. Furthermore, mass spectrometry (MS) integrations satisfy the ongoing demand for in-depth biomarker validation. For the purpose of this review, we will highlight the current developments based on MS sensitivity, to place quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data for future applications in cancer precision medicine. We will also discuss malignancies associated with oncogenic viruses such as Acquire Immunodeficiency Syndrome (AIDS) and suggest novel mechanisms behind this phenomenon. Human Immunodeficiency Virus type-1 (HIV-1) proteins are known to be oncogenic per se, to induce oxidative and endoplasmic reticulum stresses, and to be released from the infected or expressing cells. HIV-1 proteins can act alone or in collaboration with other known oncoproteins, which cause the bulk of malignancies in people living with HIV-1 on ART.

Predicting and Mitigating Freshmen Student Attrition: A Local-Explainable Machine Learning Framework

With the emergence of novel methods for improving machine learning (ML) transparency, traditional decision-support-focused information systems seem to need an upgrade in their approach toward providing more actionable insights for practitioners. Particularly, given the complex decision-making process of humans, using insights obtained from group-level interpretation of ML models for designing individual interventions may lead to mixed results. The present study proposes a hybrid ML framework by integrating established predictive and explainable ML approaches for decision support systems involving the prediction of human decisions and designing individualized interventions accordingly. The proposed framework is aimed at providing actionable insights for designing individualized interventions. It was showcased in the context of college students' attrition problem using a large and feature-rich integrated data set of freshman college students containing information about their demographics, educational, financial, and socioeconomic factors. A comparison of feature importance scores at the group- vs. individual-level revealed that while group-level insights might be useful for adjusting long-term strategies, using them as a one-size-fits-all strategy to design and implement individual interventions is subject to suboptimal outcomes.

Precision Medicine in Type 1 Diabetes

Type 1 diabetes is a complex, chronic disease in which the insulin-producing beta cells in the pancreas are sufficiently altered or impaired to result in requirement of exogenous insulin for survival. The development of type 1 diabetes is thought to be an autoimmune process, in which an environmental (unknown) trigger initiates a T cell-mediated immune response in genetically susceptible individuals. The presence of islet autoantibodies in the blood are signs of type 1 diabetes development, and risk of progressing to clinical type 1 diabetes is correlated with the presence of multiple islet autoantibodies. Currently, a "staging" model of type 1 diabetes proposes discrete components consisting of normal blood glucose but at least two islet autoantibodies (Stage 1), abnormal blood glucose with at least two islet autoantibodies (Stage 2), and clinical diagnosis (Stage 3). While these stages may, in fact, not be discrete and vary by individual, the format suggests important applications of precision medicine to diagnosis, prevention, prognosis, treatment and monitoring. In this paper, applications of precision medicine in type 1 diabetes are discussed, with both opportunities and barriers to global implementation highlighted. Several groups have implemented components of precision medicine, yet the integration of the necessary steps to achieve both short- and long-term solutions will need to involve researchers, patients, families, and healthcare providers to fully impact and reduce the burden of type 1 diabetes.

A global analysis of the value of precision medicine in oncology - The case of non-small cell lung cancer

Objectives

Biomarker testing is indispensable for the implementation of precision medicine (PM) in oncology. The aim of this study was to assess the value of biomarker testing from a holistic perspective based on the example of advanced non-small cell lung cancer (aNSCLC).

Materials and methods

A partitioned survival model was populated with data from pivotal clinical trials of first-line treatments in aNSCLC. Three testing scenarios were considered; "no biomarker testing" encompassing chemotherapy treatment, "sequential testing" for EGFR and ALK encompassing treatment with targeted- or chemotherapy, and "multigene testing" covering EGFR, ALK, ROS1, BRAF, NTRK, MET, RET and encompassing treatment with targeted- or immuno(chemo)therapy. Analyses of health outcomes and costs were run for nine countries (Australia, Brazil, China, Germany, Japan, Poland, South Africa, Turkey, United States). A 1-year and 5-year time horizon was applied. Information on test accuracy was combined with country-specific information on epidemiology and unit costs.

Results

Compared to the no-testing scenario, survival improved and treatment-related adverse events decreased with increased testing. Five-year survival increased from 2% to 5-7% and to 13-19% with sequential testing and multigene testing, respectively. The highest survival gains were observed in East Asia due to a higher local prevalence of targetable mutations. Overall costs increased with increased testing in all countries. Although costs for testing and medicines increased, costs for treatment of adverse events and end-of-life care decreased throughout all years. Non-health care costs (sick leave and disability pension payments) decreased during the first year but increased over a 5-year horizon.

Conclusion

The broad use of biomarker testing and PM in aNSCLC leads to more efficient treatment assignment and improves health outcomes for patients globally, in particular prolonged progression-free disease phase and overall survival. These health gains require investment in biomarker testing and medicines. While costs for testing and medicines would initially increase, cost decreases for other medical services and non-health care costs may partly offset the cost increases.

Genome tumor profiling in endometrial cancer and clinical relevance in endometrial cancer management: a retrospective single-center experience

OBJECTIVE

Next-generation sequencing (NGS) analysis has become an essential tool for endometrial carcinoma management. Moreover, molecular-driven therapies play an increasingly remarkable role in the era of precision oncology. This study aims to determine the clinical relevance of NGS testing in endometrial carcinoma management by analyzing the clinical benefit of NGS-driven targeted therapies.

METHODS

A single-center retrospective study was conducted on 25 endometrial carcinoma patients who underwent Foundation Medicine CDx assay at Fondazione Policlinico Universitario Agostino Gemelli, IRCCS (Rome, Italy). Tumor samples were analyzed by Foundation One CDx. A descriptive analysis of tumor genome profiles was performed. Assessment of clinical benefit according to RECIST 1.1 criteria was analyzed for patients who received a tailored treatment according to actionable targets identified by NGS testing.

RESULTS

Out of 25 endometrial carcinoma patients, 11 received targeted therapy. One patient was excluded from the clinical benefit assessment because of COVID-19-related death 1 month after starting the treatment. Eight of the remaining 10 patients benefited from targeted therapies, with an overall clinical benefit rate of 80%. A targeted agent belonging to the PI3K pathway was given to seven patients, with evidence of three partial responses (42.9%), three stable diseases (42.9%), and one progressive disease (14.2%) according to RECIST 1.1 criteria. One complete response (33.3%), one stable disease (33.3%), and one progressive disease (33.3%) were observed in the three patients treated with poly(ADP-ribose) polymerase (PARP) inhibitors according to their homologous recombination deficiency (HRD) status.

CONCLUSION

This study highlights the importance of characterizing the mutation profile of patient tumors through NGS. Our findings suggest a clinical benefit of using NGS-driven targeted therapies in endometrial carcinoma patients. However, this personalized approach could benefit the health system in terms of cost-effectiveness by reducing the costs of inappropriate, ineffective, and often expensive treatments.

The Singapore National Precision Medicine Strategy

Precision medicine promises to transform healthcare for groups and individuals through early disease detection, refining diagnoses and tailoring treatments. Analysis of large-scale genomic-phenotypic databases is a critical enabler of precision medicine. Although Asia is home to 60% of the world's population, many Asian ancestries are under-represented in existing databases, leading to missed opportunities for new discoveries, particularly for diseases most relevant for these populations. The Singapore National Precision Medicine initiative is a whole-of-government 10-year initiative aiming to generate precision medicine data of up to one million individuals, integrating genomic, lifestyle, health, social and environmental data. Beyond technologies, routine adoption of precision medicine in clinical practice requires social, ethical, legal and regulatory barriers to be addressed. Identifying driver use cases in which precision medicine results in standardized changes to clinical workflows or improvements in population health, coupled with health economic analysis to demonstrate value-based healthcare, is a vital prerequisite for responsible health system adoption.

Starring Role of Biomarkers and Anticancer Agents as a Major Driver in Precision Medicine of Cancer Therapy

Precision medicine is the most modern contemporary medicine approach today, based on great amount of data on people's health, individual characteristics, and life circumstances, and employs the most effective ways to prevent and cure diseases. Precision medicine in cancer is the most precise and viable treatment for every cancer patient based on the disease's genetic profile. Precision medicine changes the standard one size fits all medication model, which focuses on average responses to care. Consolidating modern methodologies for streamlining and checking anticancer drugs can have long-term effects on understanding the results. Precision medicine can help explicit anticancer treatments using various drugs and even in discovery, thus becoming the paradigm of future cancer medicine. Cancer biomarkers are significant in precision medicine, and findings of different biomarkers make this field more promising and challenging. Naturally, genetic instability and the collection of extra changes in malignant growth cells are ways cancer cells adapt and survive in a hostile environment, for example, one made by these treatment modalities. Precision medicine centers on recognizing the best treatment for individual patients, dependent on their malignant growth and genetic characterization. This new era of genomics progressively referred to as precision medicine, has ignited a new episode in the relationship between genomics and anticancer drug development.

Evaluation of an inflammation-based score for identification of appropriate patients for comprehensive genomic profiling

Performance status (PS) is widely used as an assessment of general condition in patients before performing comprehensive genomic profiling (CGP). However, PS scoring is dependent on each physician, and there is no objective and universal indicator to identify appropriate patients for CGP. Overall, 263 patients were scored using the modified Glasgow prognostic score (mGPS) from 0 to 2 based on the combination of serum albumin and c-reactive protein (CRP): 0, albumin ≥ 3.5 g/dl and CRP ≤ 0.5 mg/dl; 1, albumin < 3.5 g/dl or CRP > 0.5 mg/dl; and 2, albumin < 3.5 g/dl and CRP > 0.5 mg/dl. Overall survival was compared between mGPS 0-1 and mGPS 2 groups. The prognosis of patients with PS 0-1 and mGPS 2 was also evaluated. Thirty-nine patients (14.8%) were mGPS 2. Patients with mGPS 2 had significant shorter survival (14.7 months vs 4.6 months, p < 0.01). Twenty-eight patients were PS 0-1 and mGPS 2, and their survival was also short (5.6 months). Evaluation of mGPS is a simple and useful method for identifying patients with adequate prognosis using CGP.

The Additional Economic Burden of Frailty in Adult Cervical Deformity Patients Undergoing Surgical Intervention

SUMMARY OF BACKGROUND DATA

The influence of frailty on economic burden following corrective surgery for the adult cervical deformity (CD) is understudied and may provide valuable insights for preoperative planning.

OBJECTIVE

To assess the influence of baseline frailty status on the economic burden of CD surgery.

STUDY DESIGN

Retrospective cohort.

MATERIALS AND METHODS

CD patients with frailty scores and baseline and two-year Neck Disability Index data were included. Frailty score was categorized patients by modified CD frailty index into not frail (NF) and frail (F). Analysis of covariance was used to estimate marginal means adjusting for age, sex, surgical approach, and baseline sacral slope, T1 slope minus cervical lordosis, C2-C7 angle, C2-C7 sagittal vertical axis. Costs were derived from PearlDiver registry data. Reimbursement consisted of a standardized estimate using regression analysis of Medicare payscales for services within a 30-day window including length of stay and death. This data is representative of the national average Medicare cost differentiated by complication/comorbidity outcome, surgical approach, and revision status. Cost per quality-adjusted life-year (QALY) at two years was calculated for NF and F patients.

RESULTS

There were 126 patients included. There were 68 NF patients and 58 classified as F. Frailty groups did not differ by overall complications, instance of distal junctional kyphosis, or reoperations (all P >0.05). These groups had similar rates of radiographic and clinical improvement by two years. NF and F had similar overall cost ($36,731.03 vs. $37,356.75, P =0.793), resulting in equivocal costs per QALYs for both patients at two years ($90,113.79 vs. $80,866.66, P =0.097).

CONCLUSION

F and NF patients experienced similar complication rates and upfront costs, with equivocal utility gained, leading to comparative cost-effectiveness with NF patients based on cost per QALYs at two years. Surgical correction for CD is an economical healthcare investment for F patients when accounting for anticipated utility gained and cost-effectiveness following the procedure.

LEVEL OF EVIDENCE

III.

From hormone replacement therapy to regenerative scaffolds: A review of current and novel primary hypothyroidism therapeutics

Primary hypothyroidism severely impacts the quality of life of patients through a decrease in the production of the thyroid hormones T3 and T4, leading to symptoms affecting cardiovascular, neurological, cognitive, and metabolic function. The incidence rate of primary hypothyroidism is expected to increase in the near future, partially due to increasing survival of patients that have undergone radiotherapy for head and neck cancer, which induces this disease in over half of those treated. The current standard of care encompasses thyroid hormone replacement therapy, traditionally in the form of synthetic T4. However, there is mounting evidence that this is unable to restore thyroid hormone signaling in all tissues due to often persistent symptoms. Additional complications are also present in the form of dosage difficulties, extensive drug interactions and poor patience compliance. The alternative therapeutic approach employed in the past is combination therapy, which consists of administration of both T3 and T4, either synthetic or in the form of desiccated thyroid extract. Here, issues are present regarding the lack of regulation concerning formulation and lack of data regarding safety and efficacy of these treatment methods. Tissue engineering and regenerative medicine have been applied in conjunction with each other to restore function of various tissues. Recently, these techniques have been adapted for thyroid tissue, primarily through the fabrication of regenerative scaffolds. Those currently under investigation are composed of either biopolymers or native decellularized extracellular matrix (dECM) in conjunction with either primary thyrocytes or stem cells which have undergone directed thyroid differentiation. Multiple of these scaffolds have successfully restored an athyroid phenotype in vivo. However, further work is needed until clinical translation can be achieved. This is proposed in the form of exploration and combination of materials used to fabricate these scaffolds, the addition of peptides which can aid restoration of tissue homeostasis and additional in vivo experimentation providing data on safety and efficacy of these implants.

Tools for the Economic Evaluation of Precision Medicine: A Scoping Review of Frameworks for Valuing Heterogeneity-Informed Decisions

BACKGROUND AND OBJECTIVE

Precision medicine highlights the importance of exploring heterogeneity in the effectiveness and costs of interventions. Our objective was to identify and compare frameworks for valuing heterogeneity-informed decisions, and consider their strengths and weaknesses for application to precision medicine.

METHODS

We conducted a scoping review to identify papers that proposed an analytical framework to place a value, in terms of costs and health benefits, on using heterogeneity to inform treatment selection. The search included English-language papers indexed in MEDLINE, Embase or EconLit, and a manual review of references and citations. We compared the frameworks qualitatively considering: the purpose and setting of the analysis; the types of precision medicine interventions where the framework could be applied; and the framework's ability to address the methodological challenges of evaluating precision medicine.

RESULTS

Four analytical frameworks were identified: value of stratification, value of heterogeneity, expected value of individualised care and loss with respect to efficient diffusion. Each framework is suited to slightly different settings and research questions. All focus on maximising net benefit, and quantify the opportunity cost of ignoring heterogeneity by comparing individualised or stratified decisions to a means-based population-wide decision. Where the frameworks differ is in their approaches to uncertainty, and in the additional metrics they consider.

CONCLUSIONS

Identifying and utilising heterogeneity is at the core of precision medicine, and the ability to quantify the value of heterogeneity-informed decisions is critical. Using an analytical framework to value heterogeneity will help provide evidence to inform investment in precision medicine interventions, appropriately capturing the value of targeted health interventions.

Cost-effectiveness of molecularly matched off-label therapies for end-stage cancer - the MetAction precision medicine study

BACKGROUND

Precision cancer medicine (PCM), frequently used for the expensive and often modestly efficacious off-label treatment with medications matched to the tumour genome of end-stage cancer, challenges healthcare resources. We compared the health effects, costs and cost-effectiveness of our MetAction PCM study with corresponding data from comparator populations given best supportive care (BSC) in two external randomised controlled trials.

METHODS

We designed three partitioned survival models to evaluate the healthcare costs and quality-adjusted life years (QALYs) as the main outcomes. Cost-effectiveness was calculated as the incremental cost-effectiveness ratio (ICER) of PCM relative to BSC with an annual willingness-to-pay (WTP) threshold of EUR 56,384 (NOK 605,000). One-way and probabilistic sensitivity analyses addressed uncertainty.

RESULTS

We estimated total healthcare costs (relating to next-generation sequencing (NGS) equipment and personnel wages, molecularly matched medications to the patients with an actionable tumour target and follow-up of the responding patients) and the health outcomes for the MetAction patients versus costs (relating to estimated hospital admission) and outcomes for the BSC cases. The ICERs for incremental QALYs were twice or more as high as the WTP threshold and relatively insensitive to cost decrease of the NGS procedures, while reduction of medication prices would contribute significantly towards a cost-effective PCM strategy.

CONCLUSIONS

The models suggested that the high ICERs of PCM were driven by costs of the NGS diagnostics and molecularly matched medications, with a likelihood for the strategy to be cost-effective defying WTP constraints. Reducing drug expenses to half the list price would likely result in an ICER at the WTP threshold. This can be an incentive for a public-private partnership for sharing drug costs in PCM, exemplified by ongoing European initiatives.

CLINICALTRIALS.GOV, IDENTIFIER

NCT02142036.

Application of precision medicine in clinical routine in haematology-Challenges and opportunities

Precision medicine is revolutionising patient care in cancer. As more knowledge is gained about the impact of specific genetic lesions on diagnosis, prognosis and treatment response, diagnostic precision and the possibility for optimal individual treatment choice have improved. Identification of hallmark genetic aberrations such as the BCR::ABL1 gene fusion in chronic myeloid leukaemia (CML) led to the rapid development of efficient targeted therapy and molecular follow-up, vastly improving survival for patients with CML during recent decades. The assessment of translocations, copy number changes and point mutations are crucial for the diagnosis and risk stratification of acute myeloid leukaemia and myelodysplastic syndromes. Still, the often heterogeneous and complex genetic landscape of haematological malignancies presents several challenges for the implementation of precision medicine to guide diagnosis, prognosis and treatment choice. This review provides an introduction and overview of the important molecular characteristics and methods currently applied in clinical practice to guide clinical decision making in haematological malignancies of myeloid and lymphoid origin. Further, experimental ways to guide the choice of targeted therapy for refractory patients are reviewed, such as functional precision medicine using drug profiling. An example of the use of pipeline studies where the treatment is chosen according to the molecular characteristics in rare solid malignancies is also provided. Finally, the future opportunities and remaining challenges of precision medicine in the real world are discussed.

Cost-Effectiveness Analysis of Standardized Clinical Nutrition Diagnosis and Treatment Pathway in Patients with Pulmonary Infection

Objective

From the perspective of economics, this study discusses the value of establishing a standardized clinical nutrition diagnosis and treatment pathway in the diagnosis and treatment of pulmonary infection and provides a reference for optimizing the diagnosis and treatment pathway of pulmonary infection.

Methods

The patients who received the nutrition diagnosis and treatment pathway intervention in 2017 were counted as the routine group and were subdivided into the conventional intervention group (C1) and conventional control group (C2) according to whether the standardized nutrition therapy was applied or not. The patients who received the nutrition diagnosis and treatment pathway intervention in 2020 were counted as the experimental group and were subdivided into the experimental intervention group (T1) and the experimental control group (T2) according to whether standardized intervention was applied or not. The total hospitalization expenses, average daily hospitalization cost, nutrition support expenses, plasma albumin before and after nutrition support, readmission, and other indicators of all patients were recorded and compared. The cost-effectiveness ratio (CER), incremental cost-effectiveness ratio (ICER), and cost-effectiveness threshold for cost-effectiveness analysis were adopted.

Results

Compared with the C2 group, the C1 group had higher total hospitalization expenses, average daily hospitalization expenses, nutritional support expenses, and plasma albumin improvement rate and lower readmission rate (P < 0.001). Compared with the T2 group, the T1 group had higher total hospitalization cost, average daily hospitalization expenses, nutritional support expenses, and plasma albumin improvement rate and lower readmission rate (P < 0.001). Taking the improvement rate of plasma albumin as the effect index, compared with the C1 group, the T1 group has less investment cost and better effect, and the ICER is negative (below the cost-effect threshold). And taking the readmission rate as the effective index, compared with the C1 group, the T1 group invested less cost and had a better effect, and the ICER was negative (below the cost-effect threshold).

Conclusion

For the patients with pulmonary infection, whether the improvement rate of plasma albumin or the readmission rate is used as the impact index, the standardized nutrition diagnosis and treatment pathway in 2020 is more economical than the nonstandardized nutrition diagnosis and treatment pathway.

Cost-Effectiveness of PD-L1 Testing in Non-Small Cell Lung Cancer (NSCLC) Using In Vitro Diagnostic (IVD) Versus Laboratory-Developed Test (LDT)

INTRODUCTION

Accurate PD-L1 testing for non-small cell lung cancer (NSCLC) maximizes the benefits of immune checkpoint inhibitor (ICI) drugs like pembrolizumab. False negative test results deny ICI treatments to eligible patients, worsening clinical and economic outcomes, while false positives increase costs by using ICI treatments without their benefits. This study evaluates the cost-effectiveness of PD-L1 testing with an in vitro diagnostic (IVD) compared to a laboratory-developed test (LDT) for allocating patients with NSCLC to treatment with either pembrolizumab or chemotherapy using the German healthcare system as a model.

METHODS

We developed a decision analytical model to evaluate the cost-effectiveness of PD-L1 testing with a regulatory body approved IVD compared to an LDT from the national German healthcare payer (statutory health insurance system) perspective. Accuracy of PD-L1 testing was based on data from two independent proficiency testing programs. The 1-year model was based on outcomes data from the KEYNOTE-024 clinical trial and treatment patterns reflecting current German practices.

RESULTS

IVDs produced accurate PD-L1 testing results in 93% (752/811) of tested cases compared to 73% (492/672) with LDTs. Most misclassifications concerned false negatives, occurring in 21% of LDTs vs 7% of IVDs. Total costs of the IVD group (48,878 €) were 196 € higher than the LDT group (48,682 €). These costs incorporate testing, first- and second-line therapy, managing treatment-related grade 3+ adverse events (AEs), and end-of-life costs for those who died within the year. Total effectiveness (percentage of patients successfully diagnosed and prescribed the correct therapy per German treatment guidelines) was 19 percentage points higher for the IVD group (88%) compared to the LDT group (69%). These differences in costs and effects lead to an incremental cost-effectiveness ratio (ICER) of 1057 €.

CONCLUSION

Compared to LDT technology, on-label IVD use for PD-L1 testing is only slightly more costly and substantially more effective for aligning patients with PD-L1-positive NSCLC with ICI therapy according to German practice guidelines. Given these findings, changes to testing and reimbursement policies may be considered to maximize patient outcomes in NSCLC.

A State-of-the-Art Roadmap for Biomarker-Driven Drug Development in the Era of Personalized Therapies

Advances in biotechnology have enabled us to assay human tissue and cells to a depth and resolution that was never possible before, redefining what we know as the “biomarker”, and how we define a “disease”. This comes along with the shift of focus from a “one-drug-fits-all” to a “personalized approach”, placing the drug development industry in a highly dynamic landscape, having to navigate such disruptive trends. In response to this, innovative clinical trial designs have been key in realizing biomarker-driven drug development. Regulatory approvals of cancer genome sequencing panels and associated targeted therapies has brought personalized medicines to the clinic. Increasing availability of sophisticated biotechnologies such as next-generation sequencing (NGS) has also led to a massive outflux of real-world genomic data. This review summarizes the current state of biomarker-driven drug development and highlights examples showing the utility and importance of the application of real-world data in the process. We also propose that all stakeholders in drug development should (1) be conscious of and efficiently utilize real-world evidence and (2) re-vamp the way the industry approaches drug development in this era of personalized medicines.

A Precision Medicine Agenda in Traumatic Brain Injury

Traumatic brain injury remains a leading cause of death and disability across the globe. Substantial uncertainty in outcome prediction continues to be the rule notwithstanding the existing prediction models. Additionally, despite very promising preclinical data, randomized clinical trials (RCTs) of neuroprotective strategies in moderate and severe TBI have failed to demonstrate significant treatment effects. Better predictive models are needed, as the existing validated ones are more useful in prognosticating poor outcome and do not include biomarkers, genomics, proteonomics, metabolomics, etc. Invasive neuromonitoring long believed to be a "game changer" in the care of TBI patients have shown mixed results, and the level of evidence to support its widespread use remains insufficient. This is due in part to the extremely heterogenous nature of the disease regarding its etiology, pathology and severity. Currently, the diagnosis of traumatic brain injury (TBI) in the acute setting is centered on neurological examination and neuroimaging tools such as CT scanning and MRI, and its treatment has been largely confronted using a "one-size-fits-all" approach, that has left us with many unanswered questions. Precision medicine is an innovative approach for TBI treatment that considers individual variability in genes, environment, and lifestyle and has expanded across the medical fields. In this article, we briefly explore the field of precision medicine in TBI including biomarkers for therapeutic decision-making, multimodal neuromonitoring, and genomics.

Out of Date or Best Before? A Commentary on the Relevance of Economic Evaluations Over Time

The impact of time on the applicability and relevance of historical economic evaluations can be considerable. Ignoring this may lead to the use of weak or invalid evidence to inform important research questions or resource allocation decisions, as historical economic evaluations may have reached different conclusions compared to if a similar study had been conducted more recently. There are multiple factors that contribute towards evidence becoming outdated including changes to the relevant decision problem (e.g. comparators), changes to parameters (such as costs, utilities and resource use) and methodological updates (e.g. recommendations on uncertainty analysis). Researchers reviewing economic evaluations need to consider whether changes over time would influence the study design and results if the evaluation were repeated, to the extent that it is no longer helpful or informative. In this paper, we summarise these key issues and make recommendations about how and whether researchers can future proof their economic evaluations.

Four Aspects Affecting Health Economic Decision Models and Their Validation

Health care decision makers in many jurisdictions use cost-effectiveness analysis based on health economic decision models for policy decisions regarding coverage and price negotiation for medicines and medical devices. While validation of health economic decision models has always been considered important, many reviews of model-based cost-effectiveness studies report limitations regarding their validation. The current opinion paper discusses four aspects of current health economic decision modeling with relevance for future directions in model validation: increased use of complex models, international cooperation, open-source modeling, and stakeholder involvement. First, new, more complex clinical study designs and treatment strategies may require relatively complex model structures and/or input data analyses. Simultaneously, more widespread technical knowledge along with wider data availability have led to a broader range of model types. This puts extra requirements on model validation and transparency. Second, increased international cooperation of policy makers and, in particular, health technology assessment (HTA) authorities in performing model assessments is discussed in relation to the repeated use of health economic models (multi-use disease models). We argue such coordinated efforts may benefit model validity. Third, open-source modeling is discussed as one possible answer to increased transparency requirements. Finally, involvement of all relevant stakeholders throughout the whole decision process is an ongoing development that necessarily also includes health economic modeling. We argue this implies that model validity should be considered in a broader perspective, with more focus on conceptual modeling, model transparency, accuracy requirements, and choice of relevant model outcomes than previously.

Implementation of personalised medicine policies in mental healthcare: results from a stated preference study in the UK

BACKGROUND

Public support for the implementation of personalised medicine policies (PMPs) within routine care is important owing to the high financial costs involved and the potential for redirection of resources from other services.

AIMS

We aimed to determine the attributes of a PMP most likely to elicit public support for implementation. We also aimed to determine whether such support differed between a depression PMP and one for cystic fibrosis.

METHOD

In a discrete-choice experiment, paired vignettes illustrating both the current model of care (CMoC) and a hypothetical PMP for either depression or cystic fibrosis were presented to a representative sample of the UK public (n = 2804). Each vignette integrated varying attributes, including anticipated therapeutic benefit over CMoC, and the annual cost to the taxpayer. Respondents were invited to express their preference for either the PMP or CMoC within each pair.

RESULTS

The financial cost was the most important attribute influencing public support for PMPs. Respondents favoured PMP implementation where it benefited a higher proportion of patients or was anticipated to be more effective than CMoC. A reduction in services for non-eligible patients reduced the likelihood of support for PMPs. Respondents were more willing to fund PMPs for cystic fibrosis than for depression.

CONCLUSIONS

Cost is a significant factor in the public's support for PMPs, but essential caveats, such as protection for services available to PMP-ineligible patients, may also apply. Further research should explore the factors contributing to condition-specific nuances in public support for PMPs.

How Genetics Can Improve Clinical Practice in Chronic Kidney Disease: From Bench to Bedside

Chronic kidney disease (CKD) is considered a major global health problem with high socio-economic costs: the risk of CKD in individuals with an affected first degree relative has been found to be three times higher than in the general population. Genetic factors are known to be involved in CKD pathogenesis, both due to the possible presence of monogenic pathologies as causes of CKD, and to the role of numerous gene variants in determining susceptibility to the development of CKD. The genetic study of CKD patients can represent a useful tool in the hands of the clinician; not only in the diagnostic and prognostic field, but potentially also in guiding therapeutic choices and in designing clinical trials. In this review we discuss the various aspects of the role of genetic analysis on clinical management of patients with CKD with a focus on clinical applications. Several topics are discussed in an effort to provide useful information for daily clinical practice: definition of susceptibility to the development of CKD, identification of unrecognized monogenic diseases, reclassification of the etiological diagnosis, role of pharmacogenetics.

The patients view on genetics and functional imaging for precision medicine: a willingness-to-pay analysis

Purpose: Willingness-to-pay (WTP) analyses can support allocation processes considering the patients preferences in personalized medicine. However, genetic testing especially might imply ethical concerns that have to be considered. Methods: A WTP questionnaire was designed to compare preferences for imaging and genetic testing in cancer patients and to evaluate potential ethical concerns. Results: Comparing the options of imaging and genetics showed comparable WTP values. Ethical concerns about genetic testing seemed to be minor. Treatment success was the top priority irrespective of the diagnostic modality. In general, the majority of patients considered personalized medicine to be beneficial. Conclusion: Most patients valued personalized approaches and rated the benefits of precision medicine of overriding importance irrespective of modality or ethical concerns.

Precision medicine in public health in India: Nascent but poised in the right direction

Precision medicine (PM) in public health offers a new paradigm. Over a past few decades, there has been very rapid development in science and technology, especially in medical-clinical research to enhance the likelihood of preventive treatment which is personalized to an individual. This combined with digital health and accessibility of environmental and behavioral data offers a unique opportunity for specific prevention advice to individuals and thus to population at large. Indian with its 1.3 billion population and its ethnic diversity with high burden of disease offers a unique opportunity for the role of PM in public health. The article further explores the status and way forward for PM in India.

Comparison of submucosal and subserosal approaches toward optimized indocyanine green tracer-guided laparoscopic lymphadenectomy for patients with gastric cancer (FUGES-019): a randomized controlled trial

BACKGROUND

Application of indocyanine green (ICG) fluorescence imaging is effective in guiding laparoscopic radical lymphadenectomy for gastric cancer. However, the optimal approach for indocyanine green injection is controversial. Therefore, the objective of this study was aimed to compare the efficacy and ICG injection between the preoperative submucosal and intraoperative subserosal approaches for lymph node (LN) tracing during laparoscopic gastrectomy.

METHOD

This randomized controlled trial (ClinicalTrials.gov, NCT04219332) included 266 patients with potentially resectable gastric cancer (cT1-T4a, N0/+, M0) enrolled from a tertiary teaching center between December 2019 and October 2020. The primary endpoint was total number of retrieved LNs.

RESULTS

In total, 259 patients (n = 130 and n = 129 in the submucosal and subserosal groups, respectively) were included in the per-protocol analysis. There are no significant differences in total number of retrieved LNs between the two groups (49.8 vs. 49.2, P = 0.713). The rate of LN noncompliance in the submucosal group was comparable to that in the subserosal group (32.3% vs. 33.3%, P = 0.860). No significant difference was found between the submucosal and subserosal groups in terms of the incidence (17.7% vs. 16.3%; P = 0.762) or severity of postoperative complications. The mean fluorescence cost in the submucosal group was higher than that in the subserosal group ($335.3 vs. $182.4; P < 0.001). The overall treatment satisfaction score was lower in the submucosal group than in the subserosal group (70.5 vs. 76.1%, P = 0.048).

CONCLUSION

ICG administered by subserosal injection was comparable to that administered by submucosal injection for lymph node tracing in gastric cancer. However, the former approach imposed a lower economic and mental burden on patients undergoing laparoscopic D2 lymphadenectomy.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04219332 .

Patients' and professionals' views related to ethical issues in precision medicine: a mixed research synthesis

BACKGROUND

Precision medicine development is driven by the possibilities of next generation sequencing, information technology and artificial intelligence and thus, raises a number of ethical questions. Empirical studies have investigated such issues from the perspectives of health care professionals, researchers and patients. We synthesize the results from these studies in this review.

METHODS

We used a systematic strategy to search, screen and assess the literature for eligibility related to our research question. The initial search for empirical studies in five data bases provided 665 different records and we selected 92 of these publications for inclusion in this review. Data were extracted in a spreadsheet and categorized into different topics representing the views on ethical issues in precision medicine.

RESULTS

Many patients and professionals expect high benefits from precision medicine and have a positive attitude towards it. However, patients and professionals also perceive some risks. Commonly perceived risks include: lack of evidence for accuracy of tests and efficacy of treatments; limited knowledge of patients, which makes informed consent more difficult; possible unavailability of access to precision medicine for underprivileged people and ethnic minorities; misuse of data by insurance companies and employers, potential of racial stigmatization due to genetic information; unwanted communication of incidental findings; changes in doctor-patient-relationship through focusing on data; and the problem that patients could feel under pressure to optimize their health.

CONCLUSIONS

National legislation and guidelines already minimize many risks associated with precision medicine. However, from our perspective some problems require more attention. Should hopes for precision medicine's benefits be fulfilled, then the ethical principle of justice would require an unlimited access to precision medicine for all people. The potential for autonomous patients' decisions must be greatly enhanced by improvements in patient education. Harm from test results must be avoided in any case by the highest possible data security level and communication guidelines. Changes in the doctor-patient relationship and the impact of precision medicine on the quality of life should be further investigated. Additionally, the cost-effectiveness of precision medicine should be further examined, in order to avoid malinvestment.

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.

Polymeric Nanoparticle Delivery of Combination Therapy with Synergistic Effects in Ovarian Cancer

Treatment of ovarian cancer is challenging due to late stage diagnosis, acquired drug resistance mechanisms, and systemic toxicity of chemotherapeutic agents. Combination chemotherapy has the potential to enhance treatment efficacy by activation of multiple downstream pathways to overcome drug resistance and reducing required dosages. Sequence of delivery and the dosing schedule can further enhance treatment efficacy. Formulation of drug combinations into nanoparticles can further enhance treatment efficacy. Due to their versatility, polymer-based nanoparticles are an especially promising tool for clinical translation of combination therapies with tunable dosing schedules. We review polymer nanoparticle (e.g., micelles, dendrimers, and lipid nanoparticles) carriers of drug combinations formulated to treat ovarian cancer. In particular, the focus on this review is combinations of platinum and taxane agents (commonly used first line treatments for ovarian cancer) combined with other small molecule therapeutic agents. In vitro and in vivo drug potency are discussed with a focus on quantifiable synergistic effects. The effect of drug sequence and dosing schedule is examined. Computational approaches as a tool to predict synergistic drug combinations and dosing schedules as a tool for future nanoparticle design are also briefly discussed.

Pharmacogenomics Implementation and Hurdles to Overcome; In the Context of a Developing Country

Having multiple dimensions, uncertainties and several stakeholders, the costly pharmacogenomics (PGx) is associated with dynamic implementation complexities. Identification of these challenges is critical to harness its full potential, especially in developing countries with fragile healthcare systems and scarce resources. This is the first study aimed to identify most salient challenges related to PGx implementation, with respect to the experiences of early-adopters and local experts' prospects, in the context of a developing country in the Middle East. To perform a comprehensive reconnaissance on PGx adoption challenges a scoping literature review was conducted based on national drug policy components: efficacy/safety, access, affordability and rational use of medicine (RUM). Strategic option development and analysis workshop method with cognitive mapping as the technique was used to evaluate challenges in the context of Iran. The cognitive maps were face-validated and analyzed via Decision Explorer XML. The findings indicated a complex network of issues relative to PGx adoption, categorized in national drug policy indicators. In the rational use of medicine category, ethics, education, bench -to- bedside strategies, guidelines, compliance, and health system issues were found. Clinical trial issues, test's utility, and biomarker validation were identified in the efficacy group. Affordability included pricing, reimbursement, and value assessment issues. Finally, access category included regulation, availability, and stakeholder management challenges. The current study identified the most significant challenges ahead of clinical implementation of PGx in a developing country. This could be the basis of a policy-note development in future work, which may consolidate vital communication among stakeholders and accelerate the efficient implementation in developing new-comer countries.

Genetic predisposition in type 2 diabetes: A promising approach toward a personalized management of diabetes

Diabetes mellitus, also known simply as diabetes, has been described as a chronic and complex endocrine metabolic disorder that is a leading cause of death across the globe. It is considered a key public health problem worldwide and one of four important non-communicable diseases prioritized for intervention through world health campaigns by various international foundations. Among its four categories, Type 2 diabetes (T2D) is the commonest form of diabetes accounting for over 90% of worldwide cases. Unlike monogenic inherited disorders that are passed on in a simple pattern, T2D is a multifactorial disease with a complex etiology, where a mixture of genetic and environmental factors are strong candidates for the development of the clinical condition and pathology. The genetic factors are believed to be key predisposing determinants in individual susceptibility to T2D. Therefore, identifying the predisposing genetic variants could be a crucial step in T2D management as it may ameliorate the clinical condition and preclude complications. Through an understanding the unique genetic and environmental factors that influence the development of this chronic disease individuals can benefit from personalized approaches to treatment. We searched the literature published in three electronic databases: PubMed, Scopus and ISI Web of Science for the current status of T2D and its associated genetic risk variants and discus promising approaches toward a personalized management of this chronic, non-communicable disorder.

Deep Digital Phenotyping and Digital Twins for Precision Health: Time to Dig Deeper

This viewpoint describes the urgent need for more large-scale, deep digital phenotyping to advance toward precision health. It describes why and how to combine real-world digital data with clinical data and omics features to identify someone’s digital twin, and how to finally enter the era of patient-centered care and modify the way we view disease management and prevention.

Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine

To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core discipline of precision medicine, and currently, the clinical application of cutting-edge genomic medicine aimed at improving the prevention, diagnosis and treatment of a wide range of diseases is promoted. However, although the Human Genome Project was completed in 2003 and large-scale genetic analyses have since been accomplished worldwide with the development of next-generation sequencing (NGS), explaining the mechanism of disease onset only using genetic variation has been recognized as difficult. Meanwhile, the importance of epigenetics, which describes inheritance by mechanisms other than the genomic DNA sequence, has recently attracted attention, and, in particular, many studies have reported the involvement of epigenetic deregulation in human cancer. So far, given that genetic and epigenetic studies tend to be accomplished independently, physiological relationships between genetics and epigenetics in diseases remain almost unknown. Since this situation may be a disadvantage to developing precision medicine, the integrated understanding of genetic variation and epigenetic deregulation appears to be now critical. Importantly, the current progress of artificial intelligence (AI) technologies, such as machine learning and deep learning, is remarkable and enables multimodal analyses of big omics data. In this regard, it is important to develop a platform that can conduct multimodal analysis of medical big data using AI as this may accelerate the realization of precision medicine. In this review, we discuss the importance of genome-wide epigenetic and multiomics analyses using AI in the era of precision medicine.