Transitional dynamics in oncology clinical trials: evaluating the impact of Clinical Trials Act on cooperative groups.

OBJECTIVE: large-scale multicentre clinical trials conducted by cooperative groups have generated a lot of evidence to establish better standard treatments. The Clinical Trials Act was enforced on 1 April 2018, in Japan, and it has remarkably increased the operational burden on investigators, but its long-term impact on cancer cooperative groups is unknown. METHODS: a survey was conducted across the nine major cooperative groups that constitute the Japan Cancer Trials Network to assess the impact of Clinical Trials Act on the number of newly initiated trials from fiscal year (from 1 April to 31 March) 2017 to 2022 and that of ongoing trials on 1 April in each year from 2018 to 2023. RESULTS: the number of newly initiated trials dropped from 38 trials in fiscal year 2017 to 26 trials in fiscal year 2018, surged to 50 trials in fiscal year 2019, but then gradually decreased to 25 trials by fiscal year 2022. Specified clinical trials decreased from 32 trials in fiscal year 2019 to 12 trials in fiscal year 2022. The number of ongoing trials was 220 trials in 2018, peaked at 245 trials in 2020, but then gradually decreased to 219 trials by 2023. The number of specified clinical trials has been in consistent decline. By April 2023, of the 20 ongoing non-specified clinical trials, nine adhered to Clinical Trials Act and 11 followed the Ethical Guidelines for Medical and Health Research Involving Human Subjects. CONCLUSION: the number of multicentre clinical trials in oncology gradually decreased after the Clinical Trials Act's enforcement, which underscores the need for comprehensive amendment of the Clinical Trials Act to streamline the operational process.

Navigating the Regulatory Landscape to Develop Pediatric Oncology Drugs: Expert Opinion Recommendations.

Regulatory changes have been enacted in the United States (US) and European Union (EU) to encourage the development of new treatments for pediatric cancer. Here, we review some of the factors that have hampered the development of pediatric cancer treatments and provide a comparison of the US and EU regulations implemented to address this clinical need. We then provide some recommendations for each stage of the oncology drug development pathway to help researchers maximize their chance of successful drug development while complying with regulations. A key recommendation is the engagement of key stakeholders such as regulatory authorities, pediatric oncologists, academic researchers, patient advocacy groups, and a Pediatric Expert Group early in the drug development process. During drug target selection, sponsors are encouraged to consult the Food and Drug Administration (FDA), European Medicines Agency (EMA), and the FDA target list, in addition to relevant US and European consortia that have been established to characterize and prioritize oncology drug targets. Sponsors also need to carefully consider the resourcing requirements for preclinical testing, which include ensuring appropriate access to the most relevant databases, clinical samples, and preclinical models (cell lines and animal models). During clinical development, sponsors can account for the pharmacodynamic (PD)/pharmacokinetic (PK) considerations specific to a pediatric population by developing pediatric formulations, selecting suitable PD endpoints, and employing sparse PK sampling or modeling/simulation of drug exposures where appropriate. Additional clinical considerations include the specific design of the clinical trial, the potential inclusion of children in adult trials, and the value of cooperative group trials.

In the last few decades, great progress has been made in developing new treatments for adult cancers. However, development of new treatments for childhood cancers has been much slower. To encourage drug companies (sponsors) to develop effective treatments for childhood cancer, authorities in the United States (US) and Europe have made new rules for drug development. Under these new rules, sponsors developing drugs for specific cancers in adults have to consider whether the target of that drug also causes cancers in children. If this is the case, sponsors have to carry out clinical studies of their drug in children who have cancer that is caused by the same drug target. In this article, we describe some reasons for why drug development for childhood cancers has been slow and the rules created to address this problem in the US and Europe. We share some recommendations to help sponsors maximize their chances of developing an effective drug in children while satisfying the new rules. Specifically, sponsors need to be aware of the differences between studying drugs in adults versus children and how these influence the way the drug is tested. We make several recommendations for each stage of the development process, beginning with what is needed even before human studies begin. Finally, we highlight some issues that sponsors need to think about during drug development, from the preclinical stage (testing drugs in cells and animals) through to clinical testing in adults and pediatric patients with cancer.

Artificial intelligence in oncology: Path to implementation.

In recent years, the field of artificial intelligence (AI) in oncology has grown exponentially. AI solutions have been developed to tackle a variety of cancer-related challenges. Medical institutions, hospital systems, and technology companies are developing AI tools aimed at supporting clinical decision making, increasing access to cancer care, and improving clinical efficiency while delivering safe, high-value oncology care. AI in oncology has demonstrated accurate technical performance in image analysis, predictive analytics, and precision oncology delivery. Yet, adoption of AI tools is not widespread, and the impact of AI on patient outcomes remains uncertain. Major barriers for AI implementation in oncology include biased and heterogeneous data, data management and collection burdens, a lack of standardized research reporting, insufficient clinical validation, workflow and user-design challenges, outdated regulatory and legal frameworks, and dynamic knowledge and data. Concrete actions that major stakeholders can take to overcome barriers to AI implementation in oncology include training and educating the oncology workforce in AI; standardizing data, model validation methods, and legal and safety regulations; funding and conducting future research; and developing, studying, and deploying AI tools through multidisciplinary collaboration.

[Withholding or withdrawing life-sustaining treatments in acute oncology situations: History and regulatory aspects in France]. / La « Limitation et/ou arrêt des thérapeutiques ¼ (LAT) en oncologie face à une situation aigüe : historique et aspects réglementaires en France.

The management of oncology patients, especially hospitalized patients, can lead to almost daily discussions regarding therapeutic limitations. Here, we review the history and propose a summary of the texts framing the notion of "withholding and withdrawing life-sustaining treatment" in oncology practice in France. This decision is regulated by the Claeys-Léonetti Law of February 2, 2016 recommending a collegial discussion and its documentation in the medical record. The decision to withhold or withdraw life-sustaining treatments is the subject of discussion between the patient, his physicians and his family and may take place at any time during his management. The work of intensive-care physicians provides many useful recommendations for acute oncology situations, however articles specific for oncology practice are scarce; this is a topic that oncologists must take up.

Unraveling heterogeneity of the clinical pharmacogenomic guidelines in oncology practice among major regulatory bodies.

Pharmacogenomics (PGx) implementation in clinical practice is steadily increasing. PGx uses genetic information to personalize medication use, which increases medication efficacy and decreases side effects. The availability of clinical PGx guidelines is essential for its implementation in clinical settings. Currently, there are few organizations/associations responsible for releasing those guidelines, including the Clinical Pharmacogenetics Implementation Consortium, Dutch Pharmacogenetics Working Group, the Canadian Pharmacogenomics Network for Drug Safety and the French National Network of Pharmacogenetics. According to the US FDA, oncology medications are highly correlated to PGx biomarkers. Therefore, summarizing the PGx guidelines for oncology drugs will positively impact the clinical decisions for cancer patients. This review aims to scrutinize side-by-side available clinical PGx guidelines in oncology.

Cancer in Syrian refugees in Jordan and Lebanon between 2015 and 2017.

Protracted conflicts in the Middle East have led to successive waves of refugees crossing borders. Chronic, non-communicable diseases are now recognised as diseases that need to be addressed in such crises. Cancer, in particular, with its costly, multidisciplinary care, poses considerable financial and ethical challenges for policy makers. In 2014 and with funding from the United Nations High Commissioner for Refugees, we reported on cancer cases among Iraqi refugees in Jordan (2010-12) and Syria (2009-11). In this Policy Review, we provide data on 733 refugees referred to the United Nations High Commissioner for Refugees in Lebanon (2015-17) and Jordan (2016-17), analysed by cancer type, demographic risk factors, treatment coverage status, and cost. Results show the need for increased funding and evidence-based standard operating procedures across countries to ensure that patients have equitable access to care. We recommend a holistic response to humanitarian crises that includes education, screening, treatment, and palliative care for refugees and nationals and prioritises breast cancer and childhood cancers.

COVID-19 outbreak and cancer radiotherapy disruption in Italy: Survey endorsed by the Italian Association of Radiotherapy and Clinical Oncology (AIRO).

Italy experienced one of the world's deadliest COVID-19 outbreaks and healthcare systems had to instantly reorganise activity. The Italian Radiation Oncology Departments adapted numerous solutions to minimize the disruptions. Information technologies, treatment prioritization and implementation of hypofractionation and protection procedures allowed balancing between cancer patient care and patient/healthcare workers safety.

The State of Cancer Care in America: Impact of State Policy on Access to High-Quality Cancer Care.

Health policy in America has shifted rapidly over the last decade, and states are increasingly exercising greater authority over health policy decision-making. This localization and regionalization of healthcare policy poses significant challenges for patients with cancer, providers, advocates, and policymakers. To identify the challenges and opportunities that lay ahead of stakeholders, NCCN hosted the 2019 Policy Summit: The State of Cancer Care in America on June 27, 2019, in Washington, DC. The summit featured multidisciplinary panel discussions to explore the implications for access to quality cancer care within a shifting health policy landscape from a patient, provider, and lawmaker perspective. This article encapsulates the discussion from this NCCN Policy Summit.

Publicly accessible evidence of health-related quality of life benefits associated with cancer drugs approved by the European Medicines Agency between 2009 and 2015.

OBJECTIVE: Health-related quality of life (HRQoL) is one of the most important patient-relevant study end-points for the direct measurement of the benefit of cancer drugs. Therefore, our aim is to detect cancer indications with no published information on HRQoL at the time of European Medicines Agency (EMA) approval and monitor any reported HRQoL evidence updates after at least three years of follow-up. METHODS: We included all cancer indications that were approved by the EMA between January 2009 and October 2015. Our main sources of information were the EMA website, clinicaltrials.gov and a systematic literature search in PubMed. Information on HRQoL outcomes was extracted alongside evidence on median overall survival. RESULTS: In total, we identified 110 indications, of which more than half (n = 58, 53%) were lacking available information on HRQoL assessments at the time of EMA approval. After a monitoring period of at least three years, 24 updates were identified, resulting in 34 (31%) therapies where information on HRQoL was still not available. For the 76 therapies with reported information on HRQoL, cancer-specific instruments were mostly used (n = 49/76). Regarding cumulative evidence on median overall survival and HRQoL, 33 (n = 33/110, 30%) as well as 15 (n = 15/110, 14%) cancer drugs were lacking information on both study end-points at the time of approval and after monitoring, respectively. CONCLUSION: Our results demonstrate that there is an urgent need of routine re-evaluation of reimbursed cancer drugs with initially missing information on major outcomes. Standardisation of the typology and quality of HRQoL assessments need to be improved to allow better comparability of results.

The Financial Effect of Medicare Coverage Design and Safety Net Options for Cancer Care.

BACKGROUND: National spending on specialty medications accounted for approximately $193 billion in 2016. The coverage design for Medicare Parts B and D has shifted medication costs to patients, which may prohibit patients from starting or maintaining therapy due to affordability. As a result, patients have enrolled in safety net financial options, such as patient assistance and foundation programs. Safety net options may provide savings not otherwise realized by Medicare; however, they may have a negative financial effect on health systems and pharmaceutical manufacturers. OBJECTIVES: To (a) quantify financial savings to Medicare as a result of patient enrollment in patient assistance programs and (b) quantify the financial effect of safety net options for patients, manufacturers, and the academic medical center that participated in this study. METHODS: A single-center, nonrandomized, retrospective pilot study of Medicare beneficiaries was conducted. Patients who were prescribed hematology/oncology specialty medications and enrolled in safety net options between July 2015 and June 2017 were included. Investigators collected data related to fill history, drug cost, and prescription coverage. The primary outcome was the overall cost savings to Medicare as a result of patient enrollment in patient assistance programs. Secondary outcomes included total patient out-of-pocket savings as a result of foundation copayment support, financial effect on manufacturers as a result of patient assistance programs, and health system revenue impact as a result of safety net options. Descriptive statistics were used. RESULTS: This study included 114 patients. Medicare saved $5,083,816.83 over 2 years as a result of patient assistance programs. Eight foundations provided $240,350.04 in patient insurance copayments. Nine manufacturers provided 2,243 free drug doses, valued at $3,379,032.34. The participating medical center missed the opportunity for $6,481,543.55 in revenue due to patient assistance programs. CONCLUSIONS: The participating medical center's efforts to improve access to oncology care took considerable time and resources. These activities, as well as unreimbursed infusion services, were costs to the medical center that may not be recognized by Medicare. Manufacturers also supported patient access through their sponsored patient assistance programs. The use of these services and safety net options resulted in cost savings to Medicare and their beneficiaries. DISCLOSURES: No outside funding supported this study. The authors have nothing to disclose. Findings from this study were part of a podium research presentation at the Great Lakes Pharmacy Residency Conference; April 25, 2018; West Lafayette, IN.

Pediatric Trials for Cancer Therapies With Targets Potentially Relevant to Pediatric Cancers.

The Research to Accelerate Cures and Equity (RACE) for Children Act was enacted in 2017 to authorize the US Food and Drug Administration (FDA) to require pediatric studies for new cancer drugs that have a molecular target relevant to the growth or progression of a pediatric cancer. To assess the possible scope of this new policy, we examined all 78 adult cancer drugs approved by the FDA from 2007 to 2017. Only 17 (21.8%) drugs received any pediatric labeling information. Based on the FDA's Pediatric Molecular Target List, we found that the RACE Act could have increased the proportion of cancer drugs potentially subject to pediatric study requirements from 0% to 78.2%. However, the actual effect of the legislation will depend on how often regulators require pediatric trials and on timely completion of such trials.

Contrasting evidence to reimbursement reality for off-label use (OLU) of drug treatments in cancer care: rationale and design of the CEIT-OLU project.

Background: Off-label use (OLU) of a drug reflects a perceived unmet medical need, which is common in oncology. Cancer drugs are often highly expensive and their reimbursement is a challenge for many healthcare systems. OLU is frequently regulated by reimbursement restrictions. For evidence-based healthcare, treatment ought to be reimbursed if there is sufficient clinical evidence for treatment benefit independently of patient factors not related to the treatment indication. However, little is known about the reality of OLU reimbursement and its association with the underlying clinical evidence. Here, we aim to investigate the relationship of reimbursement decisions with the underlying clinical evidence. Methods/ design: We will extract patient characteristics and details on treatment and reimbursement of cancer drugs from over 3000 patients treated in three Swiss hospitals. We will systematically search for clinical trial evidence on benefits associated with OLU in the most common indications. We will describe the prevalence of OLU in Switzerland and its reimbursement in cancer care, and use multivariable logistic regression techniques to investigate the association of approval/rejection of a reimbursement requests to the evidence on treatment effects and to further factors, including type of drug, molecular predictive markers and the health insurer. Discussion: Our study will provide a systematic overview and assessment of OLU and its reimbursement reality in Switzerland. We may provide a better understanding of the access to cancer care that is regulated by health insurers and we hope to identify factors that determine the level of evidence-based cancer care in a highly diverse western healthcare system.

Is Watson for Oncology per se Unreasonably Dangerous?: Making A Case for How to Prove Products Liability Based on a Flawed Artificial Intelligence Design.

Artificial intelligence (AI) machines hold the world's curiosity captive. Futuristic television shows like West World are set in desert lands against pink sunsets where sleek, autonomous AI fulfill every human need, desire, and kink. But I, Robot, a movie where robots turn against the humans they serve, reminds us that AI is precarious. Academicians who study how AI interacts with tort law, such as Jessica Allain, David Vladeck, and Sjur Dyrkoltbotn, claim that the current legal regime is incapable of addressing the liability issues AI present. Both Allain and Vladeck focus their research on whether tort law can accommodate claims against fully autonomous AI machines, while Dyrkoltbotn explores how AI can be leveraged to help plaintiffs identify the genesis of their injuries. The solution this article presents is not exclusively tailored to fully autonomous AI and does not identify how technology can be used in tort claims. It instead demonstrates that the current tort law regime can provide relief to plaintiffs who are injured by AI machines. In particular, this article argues that the manner in which Watson for Oncology is designed presents a new context in which courts should adopt a per se rule of liability that favors plaintiffs who bring damage claims against AI machines by expanding the definition of what it means for a device to be unreasonably dangerous.