Implementing Precision Medicine Programs and Clinical Trials in the Community-Based Oncology Practice: Barriers and Best Practices

An Interdisciplinary Perspective on Improving Cancer Care in the State of Mississippi as an Example of Cancer Care Improvements in the Global South

Cancer disparities, a critical public health issue, particularly in states such as Mississippi, where socioeconomic factors significantly influence health outcomes, require our collective attention. This paper delves into the multifaceted nature of cancer disparities through a macro-level analysis of cancer data, specifically focusing on Mississippi as a microcosm of broader national and global trends. Two key indices, the Socio-Demographic Index (SDI) and the Social Deprivation Index (SDeI), provide valuable insights. The former offers a macro-level understanding of the socioeconomic factors that shape health and cancer outcomes. The latter quantifies disadvantages in small areas, identifying regions that need scientific, policy, and administrative support. The poor health care and cancer care (CC) outcomes in Mississippi are well documented and detailed here. However, SDI and SDeI data are not yet available in Mississippi. With biological, technological, and clinical research design advancements and other new innovative strategies emerging in the past decade in CC, a 'leapfrogging' of CC outcomes in Mississippi is within our reach. To achieve this goal, an interdisciplinary approach (IDA) addressing and solving the challenges faced in Mississippi is required. The IDA team must include disciplines that can determine SDI and SDeI for Mississippi and tie those findings to successfully apply new technological advances and innovations efficiently and cost-effectively by building infrastructure and developing implementation strategies. This can serve as a pilot demonstration project that will also help other similar regions within the United States, as well as the Global South.

Precision oncology implementation in a regional-based health care system: A professional consensus to define the pathway

OBJECTIVE

Precision Oncology requires deep changes in organizational settings but little evidence has been identified about the best strategy to guarantee the delivery of this innovation to patients. In the Italian health care system, high heterogeneity could jeopardize equal access opportunity for patients. Following a consensus method, we aim to define shared solutions to address these issues in clinical practice.

METHOD

A Delphi RAND method was chosen to record the consensus among involved health care professionals in the Italian region of Friuli Venezia Giulia. The item generation phase was conducted following a bottom-up approach.

RESULTS

Ten statements were defined on the main topics that emerged from the direct observation of the current practice, focusing on Molecular Tumor Board organization, massive parallel sequencing technology application, laboratory report content and informed consensus submission. All the statements reached a strong consensus and have been shared with the health care government authorities of our region.

CONCLUSIONS

The direct observation of the current practice in different health care authorities allowed to define ten statements as solution proposals to solve the identified complexities. This methodological approach could be applied in different organizational models but aiming to achieve a homogeneous clinical outcome for patients.

Examining external control arms in oncology: A scoping review of applications to date

OBJECTIVES

Randomized controlled trials (RCTs) are the gold standard for evaluating the comparative efficacy and safety of new cancer therapies. However, enrolling patients in control arms of clinical trials can be challenging for rare cancers, particularly in the context of precision oncology and targeted therapies. External Control Arms (ECAs) are a potential solution to address these challenges in clinical research design. We conducted a scoping review to explore the use of ECAs in oncology.

METHODS

We systematically searched four databases, namely MEDLINE, EMBASE, Web of Science, and Scopus. We screened titles, abstracts, and full texts for eligible articles focusing on patients undergoing therapy for cancer, employing ECAs, and reporting clinical outcomes.

RESULTS

Of the 629 articles screened, 23 were included in this review. The earliest included studies were published in 1996, while most studies were published in the past 5 years. 44% (10/23) of ECAs were employed in blood-related cancer studies. Geographically, 30% (7/23) of studies were conducted in the United States, 22% (5/23) in Japan, and 9% (2/23) in South Korea. The primary data sources used to construct the ECAs involved pooled data from previous trials (35%, 8/23), administrative health databases (17%, 4/23) and electronic medical records (17%, 4/23). While 52% (12/23) of the studies employed methods to align treatment and ECAs characteristics, 48% (11/23) lacked explicit strategies.

CONCLUSION

ECAs offer a valuable approach in oncology research, particularly when alternative designs are not feasible. However, careful methodological planning and detailed reporting are essential for meaningful and reliable results.

Performance of a novel spectroscopy-based tool for adjuvant therapy decision-making in hormone receptor-positive breast cancer: a validation study

PURPOSE

Digistain Index (DI), measured using an inexpensive mid-infrared spectrometer, reflects the level of aneuploidy in unstained tissue sections and correlates with tumor grade. We investigated whether incorporating DI with other clinicopathological variables could predict outcomes in patients with early breast cancer.

METHODS

DI was calculated in 801 patients with hormone receptor-positive, HER2-negative primary breast cancer and ≤ 3 positive lymph nodes. All patients were treated with systemic endocrine therapy and no chemotherapy. Multivariable proportional hazards modeling was used to incorporate DI with clinicopathological variables to generate the Digistain Prognostic Score (DPS). DPS was assessed for prediction of 5- and 10-year outcomes (recurrence, recurrence-free survival [RFS] and overall survival [OS]) using receiver operating characteristics and Cox proportional hazards regression models. Kaplan-Meier analysis evaluated the ability of DPS to stratify risk.

RESULTS

DPS was consistently highly accurate and had negative predictive values for all three outcomes, ranging from 0.96 to 0.99 at 5 years and 0.84 to 0.95 at 10 years. DPS demonstrated statistically significant prognostic ability with significant hazard ratios (95% CI) for low- versus high-risk classification for RFS, recurrence and OS (1.80 [CI 1.31-2.48], 1.83 [1.32-2.52] and 1.77 [1.28-2.43], respectively; all P < 0.001).

CONCLUSION

DPS showed high accuracy and predictive performance, was able to stratify patients into low or high-risk, and considering its cost and rapidity, has the potential to offer clinical utility.

Qualitative assessment of knowledge, attitude and practice of oncologists about precision medicine in cancer patients- study from Lahore, Pakistan

BACKGROUND

Precision medicine (PM) is in great progressive stages in the West and allows healthcare practitioners (HCPs) to give treatment according to the patient's genetic findings, physiological and environmental characteristics. PM is a relatively new treatment approach in Pakistan Therefore, it is important to investigate the level of awareness, attitude, and challenges faced by oncology physicians while practicing PM for various therapies, especially cancer treatment.

OBJECTIVES

The present study aims to explore the level of awareness, attitude, and practice of PM in Pakistan along with the challenges faced by the oncologists for the treatment of cancer using the PM approach.

METHODS

Phenomenology-based qualitative approach was used. Face-to-face in-depth interviews were conducted using the purposive sampling approach among oncologists in Lahore, Pakistan. The data were analyzed using thematic content analysis to identify themes and sub-themes.

RESULTS

Out of 14 physicians interviewed 11 were aware of PM. They were keen on training to hone their skills and agreed on providing PM. Oncologists believed PM was expensive and given to affluent patients only. Other impeding factors include cost, lack of knowledge, and drug unavailability.

CONCLUSIONS

Despite basic knowledge and will to practice, resource and cost constraints were marked as significant barriers. Additional training programs and inclusion into the curriculum may help to pave the way to PM implementation in the future. In addition, health authorities and policymakers need to ensure a cheaper PM treatment can be made available for all cancer patients.

Evaluation of the effectiveness of a nationwide precision medicine program for patients with advanced non-small cell lung cancer in Germany: a historical cohort analysis

Background

The national Network Genomic Medicine (nNGM) Lung Cancer provides comprehensive and high-quality multiplex molecular diagnostics and standardized personalized treatment recommendation for patients with advanced non-small cell lung cancer (aNSCLC) in Germany. The primary aim of this study was to investigate the effectiveness of the nNGM precision medicine program in terms of overall survival (OS) using real-world data (RWD).

Methods

A historical nationwide cohort analysis of patients with aNSCLC and initial diagnosis between 04/2019 and 06/2020 was conducted to compare treatment and OS of patients with and without nNGM-participation. Patients participating within the nNGM (nNGM group) were selected based on a prospective nNGM database. The electronic health records (EHR) of the prospective nNGM database were case-specifically linked to claims data (AOK, German health insurance). The control group was selected from claims data of patients receiving usual care without nNGM-participation (non-nNGM group). The minimum follow-up period was six months.

Findings

Overall, n = 509 patients in the nNGM group and n = 7213 patients in the non-nNGM group met the inclusion criteria. Patients participating in the nNGM had a significantly improved OS compared to the non-nNGM group (median OS: 10.5 months vs. 8.7 months, p = 0.008, HR = 0.84, 95% CI: 0.74-0.95). The 1-year survival rates were 46.8% (nNGM) and 41.3% (non-nNGM). The use of approved tyrosine kinase inhibitors (TKI) in the first-line setting was significantly higher in the nNGM group than in the non-nNGM group (nNGM: 8.4% (43/509) vs. non-nNGM: 5.1% (366/7213), p = 0.001). Overall, patients receiving first-line TKI treatment had significantly higher 1-year OS rates than patients treated with PD-1/PD-L1 inhibitors and/or chemotherapy (67.2% vs. 40.2%, p < 0.001).

Interpretation

This is the first study to demonstrate a significant survival benefit and higher utilization of targeted therapies for aNSCLC patients participating within nNGM. Our data indicate that precision medicine programs can enhance collaborative personalized lung cancer care and promote the implementation of treatment innovations and the latest scientific knowledge into clinical routine care.

Funding

The study was funded by the AOK Federal Association Germany.

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.

Efficient automated error detection in medical data using deep-learning and label-clustering

Medical datasets inherently contain errors from subjective or inaccurate test results, or from confounding biological complexities. It is difficult for medical experts to detect these elusive errors manually, due to lack of contextual information, limiting data privacy regulations, and the sheer scale of data to be reviewed. Current methods for training robust artificial intelligence (AI) models on data containing mislabeled examples generally fall into one of several categories-attempting to improve the robustness of the model architecture, the regularization techniques used, the loss function used during training, or selecting a subset of data that contains cleaner labels. This last category requires the ability to efficiently detect errors either prior to or during training, either relabeling them or removing them completely. More recent progress in error detection has focused on using multi-network learning to minimize deleterious effects of errors on training, however, using many neural networks to reach a consensus on which data should be removed can be computationally intensive and inefficient. In this work, a deep-learning based algorithm was used in conjunction with a label-clustering approach to automate error detection. For dataset with synthetic label flips added, these errors were identified with an accuracy of up to 85%, while requiring up to 93% less computing resources to complete compared to a previous model consensus approach developed previously. The resulting trained AI models exhibited greater training stability and up to a 45% improvement in accuracy, from 69 to over 99% compared to the consensus approach, at least 10% improvement on using noise-robust loss functions in a binary classification problem, and a 51% improvement for multi-class classification. These results indicate that practical, automated a priori detection of errors in medical data is possible, without human oversight.

OncoCTMiner: streamlining precision oncology trial matching via molecular profile analysis

By establishing omics sequencing of patient tumors as a crucial element in cancer treatment, the extensive implementation of precision oncology necessitates effective and prompt execution of clinical studies for approving molecular-targeted therapies. However, the substantial volume of patient sequencing data, combined with strict clinical trial criteria, increasingly complicates the process of matching patients to precision oncology studies. To streamline enrollment in these studies, we developed OncoCTMiner, an automated pre-screening platform for molecular cancer clinical trials. Through manual tagging of eligibility criteria for 2227 oncology trials, we identified key bio-concepts such as cancer types, genes, alterations, drugs, biomarkers and therapies. Utilizing this manually annotated corpus along with open-source biomedical natural language processing tools, we trained multiple named entity recognition models specifically designed for precision oncology trials. These models analyzed 460 952 clinical trials, revealing 8.15 million precision medicine concepts, 9.32 million entity-criteria-trial triplets and a comprehensive precision oncology eligibility criteria database. Most significantly, we developed a patient-trial matching system based on cancer patients' clinical and genetic profiles, which can seamlessly integrate with the omics data analysis platform. This system expedites the pre-screening process for potentially suitable precision oncology trials, offering patients swifter access to promising treatment options. Database URL  https://oncoctminer.chosenmedinfo.com.

Representativeness of Patients Enrolled in the Lung Cancer Master Protocol (Lung-MAP)

PURPOSE

Lung Cancer Master Protocol (Lung-MAP), a public-private partnership, established infrastructure for conducting a biomarker-driven master protocol in molecularly targeted therapies. We compared characteristics of patients enrolled in Lung-MAP with those of patients in advanced non-small-cell lung cancer (NSCLC) trials to examine if master protocols improve trial access.

METHODS

We examined patients enrolled in Lung-MAP (2014-2020) according to sociodemographic characteristics. Proportions for characteristics were compared with those for a set of advanced NSCLC trials (2001-2020) and the US advanced NSCLC population using SEER registry data (2014-2018). Characteristics of patients enrolled in Lung-MAP treatment substudies were examined in subgroup analysis. Two-sided tests of proportions at an alpha of .01 were used for all comparisons.

RESULTS

A total of 3,556 patients enrolled in Lung-MAP were compared with 2,215 patients enrolled in other NSCLC studies. Patients enrolled in Lung-MAP were more likely to be 65 years and older (57.2% v 46.3%; P < .0001), from rural areas (17.3% v 14.4%; P = .004), and from socioeconomically deprived neighborhoods (42.2% v 36.7%, P < .0001), but less likely to be female (38.6% v 47.2%; P < .0001), Asian (2.8% v 5.1%; P < .0001), or Hispanic (2.4% v 3.8%; P = .003). Among patients younger than 65 years, Lung-MAP enrolled more patients using Medicaid/no insurance (27.6% v 17.8%; P < .0001). Compared with the US advanced NSCLC population, Lung-MAP under represented patients 65 years and older (57.2% v 69.8%; P < .0001), females (38.6% v 46.0%; P < .0001), and racial or ethnic minorities (14.8% v 21.5%; P < .0001).

CONCLUSION

Master protocols may improve access to trials using novel therapeutics for older patients and socioeconomically vulnerable patients compared with conventional trials, but specific patient exclusion criteria influenced demographic composition. Further research examining participation barriers for under represented racial or ethnic minorities in precision medicine clinical trials is warranted.

Toward a More Just System of Care in Molecular Pathology

Policy Points American health care policy must be critically assessed to establish the role it plays in sustaining and alleviating the health disparities that currently exist in molecular genetic testing. It is critical to understand the economic and sociocultural influences that drive patients to undergo or forgo molecular testing, especially in marginalized patient populations. A multipronged solution with actions necessary from multiple stakeholders is required to reduce the cost of health care, rebalance regional disparities, encourage physician engagement, reduce data bias, and earn patients' trust.

CONTEXT

The health status of a population is greatly influenced by both biological processes and external factors. For years, minority and low socioeconomic patient populations have faced worse outcomes and poorer health in the United States. Experts have worked extensively to understand the issues and find solutions to alleviate this disproportionate burden of disease. As a result, there have been some improvements and successes, but wide gaps still exist. Diagnostic molecular genetic testing and so-called personalized medicine are just now being integrated into the current American health care system. The way in which these tests are integrated can either exacerbate or reduce health disparities.

METHODS

We provide case scenarios-loosely based on real-life patients-so that nonexperts can see the impacts of complex policy decisions and unintentional biases in technology without needing to understand all the intricacies. We use data to explain these findings from an extensive literature search examining both peer-reviewed and gray literature.

FINDINGS

Access to diagnostic molecular genetic testing is not equitable or sufficient, owing to at least five major factors: (1) cost to the patient, (2) location, (3) lack of provider buy-in, (4) data-set bias, and (5) lack of public trust.

CONCLUSIONS

Molecular genetic pathology can be made more equitable with the concerted efforts of multiple stakeholders. Confronting the five major factors identified here may help us usher in a new era of precision medicine without its discriminatory counterpart.

MatchMiner: an open-source platform for cancer precision medicine

Widespread, comprehensive sequencing of patient tumors has facilitated the usage of precision medicine (PM) drugs to target specific genomic alterations. Therapeutic clinical trials are necessary to test new PM drugs to advance precision medicine, however, the abundance of patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to PM trials. To facilitate enrollment onto PM trials, we developed MatchMiner, an open-source platform to computationally match genomically profiled cancer patients to PM trials. Here, we describe MatchMiner’s capabilities, outline its deployment at Dana-Farber Cancer Institute (DFCI), and characterize its impact on PM trial enrollment. MatchMiner’s primary goals are to facilitate PM trial options for all patients and accelerate trial enrollment onto PM trials. MatchMiner can help clinicians find trial options for an individual patient or provide trial teams with candidate patients matching their trial’s eligibility criteria. From March 2016 through March 2021, we curated 354 PM trials containing a broad range of genomic and clinical eligibility criteria and MatchMiner facilitated 166 trial consents (MatchMiner consents, MMC) for 159 patients. To quantify MatchMiner’s impact on trial consent, we measured time from genomic sequencing report date to trial consent date for the 166 MMC compared to trial consents not facilitated by MatchMiner (non-MMC). We found MMC consented to trials 55 days (22%) earlier than non-MMC. MatchMiner has enabled our clinicians to match patients to PM trials and accelerated the trial enrollment process.

Comparing Survival Outcomes for Advanced Cancer Patients Who Received Complex Genomic Profiling Using a Synthetic Control Arm

BACKGROUND

Complex genomic profiling (CGP) has transformed cancer treatment decision making, yet there is a lack of robust and quantifiable evidence for how utilisation of CGP improves patient outcomes.

OBJECTIVE

This study evaluated cohort level clinical effectiveness of CGP to improve overall survival (OS) in real-world advanced cancer patients using a registry-based matched control population.

PATIENTS AND METHODS

Two cohorts of advanced and refractory cancer patients were seen in consecutive series for early phase trial enrolment consideration. The first cohort (CGP group) accessed tumour profiling via a research study; while the second cohort that followed was not profiled. Overall survival between cohorts was compared using Kaplan-Meier curves and Cox proportional hazard models. Potential confounding was analysed and adjusted for using stabilised weights based on propensity scores.

RESULTS

Within the CGP group, 25 (17.6%) patients received treatment informed by CGP results and this subgroup had significantly improved survival compared with CGP patients in whom results did not impact their treatment (unadjusted HR = 0.44, (0.22-0.88), p = 0.02). However, when comparing the entire CGP cohort with the No CGP cohort, no significant survival benefit was evident with adjusted median OS for CGP of 13.5 months (9.2-17.0) compared with 11.0 (9.2-17.4) for No CGP (adjusted HR = 0.92, (0.65-1.30), p = 0.63).

CONCLUSIONS

This study utilised real-world data to simulate a control arm and quantify the clinical effectiveness of genomic testing. The magnitude of survival benefit for patients who had CGP result-led treatments was insufficient to drive an overall survival gain for the entire tested population. Translation of CGP into clinics requires strategies to ensure higher rates of tested patients obtain clinical benefit to deliver on the value proposition of CGP in an advanced cancer population.

Surveying the Genomic Landscape Supporting the Development of Precision Military Aerospace Medicine

INTRODUCTION: Precision medicine is an approach to healthcare that is modifying clinical management by leveraging technological advances in genomics that assess a patient's genetic information to identify unique predispositions. While the civilian sector is integrating genomics widely to personalize diagnosis and treatment, the military medical environment has reacted more slowly. The operational requirements of military service encourage a tailored approach for focusing military precision medicine on occupation-specific conditions. Here, we present a survey of the genomic landscape related to military aerospace medicine.METHODS: We collated observations from genome-wide association studies (GWAS) relating genetic markers to conditions that may negatively influence flight operations and for which the U.S. Air Force School of Aerospace Medicine's Aeromedical Consult Service (ACS) provides aeromedical waiver guidance. Our sources for identifying relevant literature were the GWAS Catalog, the Atlas of GWAS Summary Statistics, and PubMed/Google Scholar searches.RESULTS: Using the ACS guidance as a starting point, we found 1572 papers describing 84 clinical conditions with genetic associations. The earliest aeromedical GWAS publication was in 2006, increasing to 225 publications in 2019. We identified 42,020 polymorphisms from more than 84 million participants across the studies.CONCLUSION: Our study revealed areas where deeper investigations into how genetic markers manifest in clinical diagnosis, prevention, or risk management could lead to increased medical readiness. Additionally, our results show those clinical areas for which guidance could include genetic risk considerations.Chapleau RR, Regn DD, de Castro MJ. Surveying the genomic landscape supporting the development of precision military aerospace medicine. Aerosp Med Hum Perform. 2022; 93(2):89-93.

Optimizing the Diagnosis and Biomarker Testing for Patients with Intrahepatic Cholangiocarcinoma: A Multidisciplinary Approach

Cholangiocarcinoma (CCA) is a heterogenous group of malignancies originating in the biliary tree, and associated with poor prognosis. Until recently, treatment options have been limited to surgical resection, liver-directed therapies, and chemotherapy. Identification of actionable genomic alterations with biomarker testing has revolutionized the treatment paradigm for these patients. However, several challenges exist to the seamless adoption of precision medicine in patients with CCA, relating to a lack of awareness of the importance of biomarker testing, hurdles in tissue acquisition, and ineffective collaboration among the multidisciplinary team (MDT). To identify gaps in standard practices and define best practices, multidisciplinary hepatobiliary teams from the University of California (UC) Davis and UC Irvine were convened; discussions of the meeting, including optimal approaches to tissue acquisition for diagnosis and biomarker testing, communication among academic and community healthcare teams, and physician education regarding biomarker testing, are summarized in this review.

Understanding Factors Associated With Anaplastic Lymphoma Kinase Testing Delays in Patients With Non-Small Cell Lung Cancer in a Large Real-World Oncology Database

CONTEXT.—

With multiple therapeutic options available for patients with advanced non-small cell lung cancer, the timely ordering and return of results to determine therapy are of critical importance.

OBJECTIVE.—

To assess factors impacting anaplastic lymphoma kinase (ALK) test ordering and time to result delivery.

DESIGN.—

A retrospective study using a de-identified electronic health record database was performed. Postdiagnosis ALK tests (n = 14 657) were analyzed from 14 197 patients with advanced non-small cell lung cancer diagnosed between January 2015 and May 2019. Time from non-small cell lung cancer diagnosis to ALK sample receipt in the laboratory was a surrogate for test order time. Test ordering was considered delayed if order time was more than 20 days. Turnaround time from sample received to test result was calculated and considered delayed if more than 10 days. Multivariable logistic regression was used to assess factors associated with order time and turnaround time delays.

RESULTS.—

Median ALK test order time was 15 days, and 36.4% (5342) of all 14 657 orders were delayed. Factors associated with delays were non-fluorescent in situ hybridization testing, send-out laboratories, testing prior to 2018, nonadenocarcinoma histology, and smoking history. Median turnaround time was 9 days, and 40.3% (5906) of all 14 657 test results were delayed. Non-fluorescent in situ hybridization testing, tissue sample, and orders combining ALK with other biomarkers were associated with delayed ALK result reporting.

CONCLUSIONS.—

This study provides a snapshot of real-world ALK test ordering and reporting time in US community practices. Multiple factors impacted both test ordering time and return of results, revealing opportunities for improvement. It is imperative that patients eligible for targeted therapy be identified in a timely fashion.

Clinician perspectives on communication and implementation challenges in precision oncology

Aim: To describe patient communication challenges encountered by oncology clinicians, which represent a fundamental barrier to implementing precision oncology. Materials & methods: We conducted three focus groups including breast, melanoma and thoracic oncology clinicians regarding their precision oncology communication experiences. Transcripts were reviewed and coded using inductive thematic text analysis. Results: We identified four themes: varied definitions of precision oncology exist, clinicians and patients face unique challenges to precision oncology implementation, patient communication challenges engendered or heightened by precision oncology implementation and clinician communication solutions and training needs. Conclusion: This study elucidated clinicians' perspectives on implementing precision oncology and related communication challenges. Understanding these challenges and developing strategies to help clinicians navigate these discussions are critical for ensuring that patients reap the full benefits of precision oncology.

Evaluation of personalized cancer therapies based on comprehensive genomic profiling in a middle-sized oncologic center in Austria, the University Clinic Krems

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64 of 69 patients’ samples could be profiled. Median alterations: 4 (0 - 23), most frequently TP53, KRAS & CDKN2A/B.

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In 13 patients (20% of 64 successful profiles), personalized therapies could be initiated.

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Effectiveness was seen in 8/13 patients (61,5%) of the precision oncology cohort vs 3/22 (13,5%) treated with chemotherapy.

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Kaplan-Meier curves show significant PFS benefit for personalized treated patients (p = 0,0165; median 151 days vs 83 days).

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Personalized cancer therapy is effective and feasible also in the setting of a middle-sized oncologic center.

Background and Aim

To successfully apply personalized cancer therapies, thorough understanding of the patient's tumor is needed. In-depth, comprehensive genomic profiling systems allow gathering this knowledge by testing hundreds of cancer-related genes. Several large institutions have established precision oncology programs in recent years with promising results for patients. However, especially middle-sized oncologic institutions face challenges to implement such programs.

This study aims to retrospectively analyze the effects of comprehensive genomic tumor profiling with respect to feasibility and effectiveness in a middle-sized oncologic center in Austria.

Methods

From May 1st, 2016 to December 31st, 2019 patients at the University Clinic Krems, who suffered from CUP-syndromes plus patients, who were resistant to conventional therapy or have progressed after all available therapy lines, were offered to get their tumors analyzed by comprehensive genomic profiling in order to establish a customized therapy.

Results

Of 69 considered patients, 64 patients’ samples could be profiled. The median number of detected alterations was 4 (minimum 0; maximum 23). Most frequent alterations were reported for TP53, KRAS and CDKN2A/B.

In 13 patients (20% of 64 successful profiles), personalized therapies could be initiated. 22 patients were treated with another line of chemotherapy as no actionable alteration could be detected. Effectiveness, determined by a PFS of the newly initiated therapy longer than 130% of the last conventional therapy line, could be seen in 8 of 13 patients (61,5%) of the precision oncology cohort compared to only 3 of 22 patients (13,5%) in the chemotherapy group. Additionally, Kaplan-Meier curves of PFS demonstrate a significant benefit for personalized treated patients (p = 0,0165 with a median PFS of 151 days, compared to 83 days in the chemotherapy group).

Conclusion

In summary, personalized cancer therapy based on comprehensive genomic profiling is effective and feasible also in the setting of a middle-sized oncologic center.

Reshaping preoperative treatment of pancreatic cancer in the era of precision medicine

This review summarises the recent evidence on preoperative therapeutic strategies in pancreatic cancer and discusses the rationale for an imminent need for a personalised therapeutic approach in non-metastatic disease. The molecular diversity of pancreatic cancer and its influence on prognosis and treatment response, combined with the failure of 'all-comer' treatments to significantly impact on patient outcomes, requires a paradigm shift towards a genomic-driven approach. This is particularly important in the preoperative, potentially curable setting, where a personalised treatment allocation has the substantial potential to reduce pancreatic cancer mortality.

Integrating Academic and Community Cancer Care and Research through Multidisciplinary Oncology Pathways for Value-Based Care: A Review and the City of Hope Experience

As the US transitions from volume- to value-based cancer care, many cancer centers and community groups have joined to share resources to deliver measurable, high-quality cancer care and clinical research with the associated high patient satisfaction, provider satisfaction, and practice health at optimal costs that are the hallmarks of value-based care. Multidisciplinary oncology care pathways are essential components of value-based care and their payment metrics. Oncology pathways are evidence-based, standardized but personalizable care plans to guide cancer care. Pathways have been developed and studied for the major medical, surgical, radiation, and supportive oncology disciplines to support decision-making, streamline care, and optimize outcomes. Implementing multidisciplinary oncology pathways can facilitate comprehensive care plans for each cancer patient throughout their cancer journey and across large multisite delivery systems. Outcomes from the delivered pathway-based care can then be evaluated against individual and population benchmarks. The complexity of adoption, implementation, and assessment of multidisciplinary oncology pathways, however, presents many challenges. We review the development and components of value-based cancer care and detail City of Hope’s (COH) academic and community-team-based approaches for implementing multidisciplinary pathways. We also describe supportive components with available results towards enterprise-wide value-based care delivery.

Molecular Subtyping and Precision Medicine for Pancreatic Cancer

Substantial progress in recent years has dramatically increased our knowledge of the molecular basis of cancer, revealing new potential therapeutic targets and paving the way for effective personalised medicine for the treatment of many tumour types. However, pancreatic cancer has been lagging behind in this success and continues to be one of the most lethal solid malignancies. Its molecular heterogeneity and the unselected design of the majority of clinical trials to date can in part explain the reason for our failure to make a significant change in the survival outcomes for patients with pancreatic cancer. A changing paradigm in drug development is required to validate the new molecular taxonomy and to rapidly translate preclinical discovery into clinical trials. Here, we review the molecular subtyping of pancreatic cancer, the challenges in identifying effective treatment regimens according to defined low-prevalence molecular subgroups and we illustrate a new model of translational therapeutic development that was established in the U.K. (Precision-Panc) as a potentially effective solution to improve outcomes for patients with pancreatic cancer.

THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar

In 2016, the World Innovation Summit for Health (WISH) published its Forum Report on precision medicine "PRECISION MEDICINE - A GLOBAL ACTION PLAN FOR IMPACT". Healthcare is undergoing a transformation, and it is imperative to leverage new technologies to generate new data and support the advent of precision medicine (PM). Recent scientific breakthroughs and technological advancements have improved our disease knowledge and altered diagnosis and treatment approaches resulting in a more precise, predictive, preventative and personalized health care that is customized for the individual patient. Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. Additionally, personalized medicine promises to revolutionize healthcare, with its key goal of providing the right treatment to the right patient at the right time and dose, and thus the potential of improving quality of life and helping to bring down healthcare costs.This policy briefing will look in detail at the issues surrounding continued development, sustained investment, risk factors, testing and approval of innovations for better strategy and faster process. The paper will serve as a policy bridge that is required to enhance a conscious decision among the powers-that-be in Qatar in order to find a way to harmonize multiple strands of activity and responsibility in the health arena. The end goal will be for Qatar to enhance public awareness and engagement and to integrate effectively the incredible advances in research into healthcare systems, for the benefit of all patients.The PM policy briefing provides concrete recommendations on moving forward with PM initiatives in Qatar and internationally. Equally important, integration of PM within a primary care setting, building a coalition of community champions through awareness and advocacy, finally, communicating PM value, patient engagement/empowerment and education/continued professional development programs of the healthcare workforce.Key recommendations for implementation of precision medicine inside and outside Qatar: 1. Create Community Awareness and PM Education Programs 2. Engage and Empower Patients 3. Communicate PM Value 4. Develop appropriate Infrastructure and Information Management Systems 5. Integrate PM into standard Healthcare System and Ensure Access to Care PM is no longer futuristic. It is here. Implementing PM in routine clinical care does require some investment and infrastructure development. Invariably, cost and lack of expertise are cited as barriers to PM implementation. Equally consequential, are the curriculum and professional development of medical care experts.Policymakers need to lead and coordinate effort among stakeholders and consider cultural and faith perspectives to ensure success. It is essential that policymakers integrate PM approaches into national strategies to improve health and health care for all, and to drive towards the future of medicine precision health.

Value of Precision Medicine in Advanced Non-Small Cell Lung Cancer: Real-World Outcomes Associated with the Use of Companion Diagnostics

BACKGROUND

Companion diagnostic (CDx) testing for patients with advanced non-small cell lung cancer (aNSCLC) identifies patients more likely to benefit from biomarker-driven treatments.

METHODS

Patients with nonsquamous cell (non-Sq) aNSCLC from the Flatiron Health database (diagnosed January 1, 2011-May 31, 2018) who had CDx testing were compared with those who had no reported evidence of testing. The association between CDx testing and overall survival was evaluated by unadjusted and adjusted Cox proportional hazards regression models. Logistic regression analysis identified characteristics associated with CDx testing. The revised modified Lung Cancer Prognostic Index and other factors identified a priori were included in the adjusted models.

RESULTS

A total of 17,555 patients with non-Sq aNSCLC (CDx, n = 14,732; no CDx, n = 2,823) with mean ± SD age of 67.2 ± 10.0 years were included. Most were insured (91.7%) and white (67.1%). Asian patients and those who were never-smokers were more likely to undergo CDx testing. Those with CDx testing lived longer than those without (median [95% confidence interval (CI)] survival, 13.04 [12.62-13.40] vs. 6.01 [5.72-6.24] months) and had a decreased mortality risk (adjusted hazard ratio [95% CI], 0.72 [0.69-0.76]). A survival advantage was also seen for patients with CDx testing who received biomarker-driven first-line therapy.

CONCLUSION

Patients with non-Sq aNSCLC who had CDx testing had a greater survival benefit than those without, supporting broader use of CDx testing in routine clinical practice to identify patients more likely to benefit from precision medicine.

IMPLICATIONS FOR PRACTICE

Companion diagnostic (CDx) testing coupled with biomarker-driven treatment offers a greater survival benefit for patients with advanced non-small cell lung cancer (aNSCLC). In this study, patients with nonsquamous aNSCLC from Flatiron Health, a large, real-world oncology database, with CDx testing had a reduced mortality risk and lived longer than patients without reported evidence of CDx testing; those who received biomarker-driven therapy as their first line of treatment were likely to survive three times longer than those who did not. These results demonstrate the clinical utility of CDx testing as the first step in treating nonsquamous aNSCLC in real-world clinical practice.

A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Purpose:

Pancreatic ductal adenocarcinoma (PDAC) arising in patients with a germline BRCA1 or BRCA2 (gBRCA) mutation may be sensitive to platinum and PARP inhibitors (PARPi). However, treatment stratification based on gBRCA mutational status alone is associated with heterogeneous responses.

Experimental Design:

We performed a seven-arm preclinical trial consisting of 471 mice, representing 12 unique PDAC patient-derived xenografts, of which nine were gBRCA mutated. From 179 patients whose PDAC was whole-genome and transcriptome sequenced, we identified 21 cases with homologous recombination deficiency (HRD), and investigated prognostic biomarkers.

Results:

We found that biallelic inactivation of BRCA1/BRCA2 is associated with genomic hallmarks of HRD and required for cisplatin and talazoparib (PARPi) sensitivity. However, HRD genomic hallmarks persisted in xenografts despite the emergence of therapy resistance, indicating the presence of a genomic scar. We identified tumor polyploidy and a low Ki67 index as predictors of poor cisplatin and talazoparib response. In patients with HRD PDAC, tumor polyploidy and a basal-like transcriptomic subtype were independent predictors of shorter survival. To facilitate clinical assignment of transcriptomic subtype, we developed a novel pragmatic two-marker assay (GATA6:KRT17).

Conclusions:

In summary, we propose a predictive and prognostic model of gBRCA-mutated PDAC on the basis of HRD genomic hallmarks, Ki67 index, tumor ploidy, and transcriptomic subtype.

The Community Oncology and Academic Medical Center Alliance in the Age of Precision Medicine: Cancer Genetics and Genomics Considerations

Recent public policy, governmental regulatory and economic trends have motivated the establishment and deepening of community health and academic medical center alliances. Accordingly, community oncology practices now deliver a significant portion of their oncology care in association with academic cancer centers. In the age of precision medicine, this alliance has acquired critical importance; novel advances in nucleic acid sequencing, the generation and analysis of immense data sets, the changing clinical landscape of hereditary cancer predisposition and ongoing discovery of novel, targeted therapies challenge community-based oncologists to deliver molecularly-informed health care. The active engagement of community oncology practices with academic partners helps with meeting these challenges; community/academic alliances result in improved cancer patient care and provider efficacy. Here, we review the community oncology and academic medical center alliance. We examine how practitioners may leverage academic center precision medicine-based cancer genetics and genomics programs to advance their patients' needs. We highlight a number of project initiatives at the City of Hope Comprehensive Cancer Center that seek to optimize community oncology and academic cancer center precision medicine interactions.

The application of stratified medicine to dementia care

Stratified medicine has been successfully used in many areas of medicine, perhaps most notably oncology. There is now both a growing evidence base and mounting enthusiasm, supported at a governmental level and across industry, academia and clinical medicine, to apply this approach to neurodegenerative illnesses, including dementia, as these provide the greatest clinical and social challenge of our times. In this article we consider definitions of stratified medicine, look at its application in other medical specialties, review the national context in the UK and consider the current state, future potential and specific considerations of applying stratified medicine to dementia.

Molecular profiling for precision cancer therapies

The number of druggable tumor-specific molecular aberrations has grown substantially in the past decade, with a significant survival benefit obtained from biomarker matching therapies in several cancer types. Molecular pathology has therefore become fundamental not only to inform on tumor diagnosis and prognosis but also to drive therapeutic decisions in daily practice. The introduction of next-generation sequencing technologies and the rising number of large-scale tumor molecular profiling programs across institutions worldwide have revolutionized the field of precision oncology. As comprehensive genomic analyses become increasingly available in both clinical and research settings, healthcare professionals are faced with the complex tasks of result interpretation and translation. This review summarizes the current and upcoming approaches to implement precision cancer medicine, highlighting the challenges and potential solutions to facilitate the interpretation and to maximize the clinical utility of molecular profiling results. We describe novel molecular characterization strategies beyond tumor DNA sequencing, such as transcriptomics, immunophenotyping, epigenetic profiling, and single-cell analyses. We also review current and potential applications of liquid biopsies to evaluate blood-based biomarkers, such as circulating tumor cells and circulating nucleic acids. Last, lessons learned from the existing limitations of genotype-derived therapies provide insights into ways to expand precision medicine beyond genomics.

Multidisciplinary therapy strategy of precision medicine in clinical practice

The application of precision medicine concept in clinical work needs a period of practice and experience accumulation. The present article introduced an example of functioning approach named "multidisciplinary therapy strategy of precision medicine" (MDTS-PM), clinical practice and process, decision-making, and therapies. The MDTS-PM integrates multidisciplinary experts and develops real-time therapeutic strategy based on clinical phenomes and gene sequencing of tissue DNA and circulating DNA. The strength of MDTS-PM is the combination of dynamical clinical phenomes, genetic information, diagnosis, and treatment to make the therapy more targeted and specific. MDTS-PM provides comprehensive, whole-process, and personalized diagnosis and treatment services for patients with complex cancer or complex drug resistance progression; provides guidance for further adjustment of drug use; and establishes a multidisciplinary cooperative team, improves the quality of clinical diagnosis and treatment, and optimizes the process of medical services.

Development, acceptability, appropriateness and appeal of a cancer clinical trials implementation intervention for rural- and minority-serving urology practices

Background

Few community urologists offer cancer patients the opportunity to participate in cancer clinical trials, despite national guidelines that recommend it, depriving an estimated 260,000 urological cancer patients of guideline-concordant care each year. Existing strategies to increase urologists’ offer of clinical trials are designed for resource-rich environments and are not feasible for many community urologists. We sought to design an implementation intervention for dissemination in under-resourced community urology practices and to compare its acceptability, appropriateness and adoption appeal among trial-naïve and trial-experienced urologists.

Methods

We used a design-for-dissemination approach, informed by the Theoretical Domains Framework and Behavior Change Wheel, to match determinants of the clinical trial offer to theoretically informed implementation strategies. We described the implementation intervention in evaluation workshops offered at urology professional society meetings. We surveyed participants to assess the implementation intervention’s acceptability and appropriateness using validated instruments. We also measured adoption appeal, intention to adopt and previous trial offer.

Results

Our design process resulted in a multi-modal implementation intervention, comprised of multiple implementation strategies designed to address six domains from the Theoretical Domains Framework. Evaluation workshops delivered at four meetings, convened five separate professional societies. Sixty-one percent of those offered an opportunity to participate in the implementation intervention indicated intention to adopt. Average implementation intervention acceptability and appropriateness ratings were 4.4 and 4.4 (out of 5), respectively. Acceptability scores were statistically significantly higher among those offering trials compared to those not (p = 0.03). Appropriateness scores did not differ between those offering trials and those not (p = 0.24). After urologists ranked their top three innovation attributes, 43% of urologists included practice reputation in their top three reasons for offering clinical trials; 30% listed practice differentiation among their top three reasons. No statistically significant differences were found between those who offered trials and those who did not among any of the innovation attributes.

Conclusions

LEARN|INFORM|RECRUIT is a promising implementation intervention to address low accrual to clinical trials, poised for implementation and effectiveness testing. The implementation intervention is appealing to its target audience and may have equal uptake among trial-naïve and trial-experienced practices.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3658-z) contains supplementary material, which is available to authorized users.

Determining If a Somatic Tumor Mutation Is Targetable and Options for Accessing Targeted Therapies

Targeted cancer therapies are drugs and biologics designed to affect cancer cell growth by blocking or interfering with specific molecular pathways in the cancer cell. Use of targeted agents usually requires verification through molecular testing that the patient's tumor harbors the molecular biomarker that is the target of the drug or is predictive of treatment benefit. Genomic mutations may be clinically actionable if they are associated with response or resistance to a potential therapy. If a genomic test reveals an actionable alteration, there are several options for accessing the targeted therapy. This article is intended to help clinicians determine if a tumor mutation is potentially treatable with a marketed or investigational drug or biologic product and to offer guidance on how to access the product of interest.

Critical Aspects of a Sustainable Clinical Research Program in the Community-Based Oncology Practice

Increasing enrollment into clinical trials is a top priority across the field of oncology. Because the vast majority of those afflicted with cancer receive their care in the community, creating strong clinical research programs in the community-based setting is important. This article comprehensively outlines the most important elements of creating and sustaining a successful community-based research program. Establishing a clear mission and defining the scope of the research program in collaboration with key physicians and administrative leadership are critical to success. Standard operating procedures should detail operational processes. Ensuring sound financial planning and protected physician time are crucial for a healthy program. Providing mentorship opportunities to investigators and other team members will provide necessary guidance for junior investigators and long-term program stability. Prioritizing provider and patient volunteer engagement through education and awareness will potentially improve enrollment and research ownership. Incorporating administrative and clinical research staff and health care providers, including physicians, advanced practice providers, and pharmacists, will result in a multidisciplinary and unified approach and may also promote research as a routine part of patient care. Regular safety and scientific meetings will reduce regulatory complications and, most importantly, improve patient care. Other keys to a successful program include establishing a diverse trial portfolio, collaboration between different institutions, and ensuring appropriate technological infrastructure. Serial programmatic review provides opportunities to refine suboptimal practices and recognize successful strategies. Community-based research programs are critical to improve access to optimal cancer care. Implementation of successful programs is possible with a collaborative and multidisciplinary approach.

US Cancer Centers of Excellence Strategies for Increased Inclusion of Racial and Ethnic Minorities in Clinical Trials

PURPOSE:

Participation of racial and ethnic minority groups (REMGs) in cancer trials is disproportionately low despite a high prevalence of certain cancers in REMG populations. We aimed to identify notable practices used by leading US cancer centers that facilitate REMG participation in cancer trials.

METHODS:

The National Minority Quality Forum and Sustainable Healthy Communities Diverse Cancer Communities Working Group developed criteria by which to identify eligible US cancer centers—REMGs comprise 10% or more of the catchment area; a 10% to 50% yearly accrual rate of REMGs in cancer trials; and the presence of formal community outreach and diversity enrollment programs. Cancer center leaders were interviewed to ascertain notable practices that facilitate REMG accrual in clinical trials.

RESULTS:

Eight cancer centers that met the Communities Working Group criteria were invited to participate in in-depth interviews. Notable strategies for increased REMG accrual to cancer trials were reported across five broad themes: commitment and center leadership, investigator training and mentoring, community engagement, patient engagement, and operational practices. Specific notable practices included increased engagement of health care professionals, the presence of formal processes for obtaining REMG patient/caregiver input on research projects, and engagement of community groups to drive REMG participation. Centers also reported an increase in the allocation of resources to improving health disparities and increased dedication of research staff to REMG engagement.

CONCLUSION:

We have identified notable practices that facilitate increased participation of REMGs in cancer trials. Wide implementation of such strategies across cancer centers is essential to ensure that all populations benefit from advances in an era of increasingly personalized treatment of cancer.