Cannabis use for symptom management among patients with cancer has increased significantly in recent years, with many reporting benefits for pain, anxiety, sleep, nausea, appetite as well as other symptoms. However, rigorous prospective data on the potential benefits and harms of cannabis use in this population are lacking. This Commentary describes a United States National Cancer Institute (NCI)-led initiative addressing this research gap by supporting five prospective observational studies evaluating the benefits and harms of cannabis use among a large, heterogeneous samples of patients with cancer undergoing active systemic treatment. We provide an overview of each study, including cancer type, treatment modalities, inclusion/exclusion criteria, data collection methods, and both patient-reported and cancer-related outcomes.

Background. The goal of this manuscript was to provide an overview of the current National Cancer Institute (NCI)-funded large cancer epidemiology survivor cohorts (CESCs). Methods. Large CESCs were defined as observational cohort studies following at least 1,000 cancer survivors over time and collecting data on survivorship outcomes. CESCs with NCI grant funding on June 1, 2024, were identified in two ways: 1) by identifying grants funded under cancer epidemiology cohort-relevant Notice of Funding Opportunities; and 2) by applying the Research, Condition, and Disease Categorization indexed concepts related to cohorts to the entire NCI grant portfolio in NIH’s proprietary Query, View, Report system and reviewing grants identified via this search for inclusion. Results. Thirty active grants supporting large CESCs were identified. Of the 30 CESCs, 36.7% are comprised of survivors of mixed cancer types; the remaining 63.3% are following survivors diagnosed with cancer of a single anatomical type or grouping (e.g. blood cancers). Special populations of focus include adult survivors of pediatric cancers, adolescent and young adult cancer survivors, pediatric cancer survivors, and stem cell transplant survivors. Notable gaps include cohorts following long-term cancer survivors, survivors of less common cancer types, and survivors from understudied populations. Conclusions. CESCs highlighted in this manuscript represent a substantial investment in exploring the multifaceted factors that influence cancer outcomes. These cohorts encompass an increasing diversity of cancer types, treatments, and populations. Impact: CESCs provide valuable insights into clinical and molecular risk factors associated with cancer survivorship outcomes that inform guidelines and interventions.

The US Food and Drug Administration (FDA) and National Institutes of Health (NIH) share a mutual interest in facilitating efficient, well-designed clinical studies of drugs, devices, and biological products. Recent advances in science and technology, as well as innovative approaches to research design and methodology, provide opportunities to enhance efficiency in medical product development and improve participant engagement in clinical trials. Recent initiatives across the FDA and NIH focus on evidence modernization approaches. Fostering appropriate use of novel designs and sources of evidence, such as real-world data (RWD) to support marketing authorizations and satisfy postapproval study requirements, may be enhanced by using consensus terminology for innovative study designs. To facilitate effective communication within the scientific community, FDA and NIH formed an interagency collaborative initiative to define clinical research terms related to innovative study designs, with a focus on studies using RWD, for FDA-regulated medical products or broader research and foster a shared understanding of terms across the clinical research ecosystem. The FDA-NIH Modernizing Research and Evidence (MoRE) Glossary Working Group (MGWG) was initiated in April 2023 to evaluate terms inadequately defined within the clinical research community that would benefit from development of a consensus definition. The MGWG conducted a landscape evaluation of common innovative design terminology that may lack clarity or concordance. Subsequently, the MGWG reviewed whether and how existing regulations, guidance, and policies use or define such terms. Following the landscape evaluation, the MGWG engaged in rigorous review to seek consensus definitions. In addition, federal agencies sought public input via a request for information before publishing the included terms and definitions. The MGWG developed the MoRE Consensus Definitions, comprising 40 clinical research terms and definitions related to innovative clinical study designs that support scientific, patient, clinical, and regulatory decision-making. The MoRE Consensus Definitions are intended to facilitate effective communication about clinical research and enable transparency around innovative clinical study designs. This publication makes available the glossary developed through this collaboration and serves as an accessible resource for the clinical research enterprise. Furthermore, as clinical research is continuously evolving, additional efforts may focus on emerging new vocabulary and evolving use of current terms to benefit medical product development.

BACKGROUND:The goal of this article was to provide an overview of the current NCI-funded large cancer epidemiology survivor cohorts (CESC). METHODS:Large CESCs were defined as observational cohort studies following at least 1,000 cancer survivors over time and collecting data on survivorship outcomes. CESCs with NCI grant funding on June 1, 2024 were identified in two ways: (i) by identifying grants funded under cancer epidemiology cohort-relevant Notice of Funding Opportunities and (ii) by applying the Research, Condition, and Disease Categorization-indexed concepts related to cohorts to the entire NCI grant portfolio in the NIH's proprietary Query, View, Reporting System and reviewing grants identified via this search for inclusion. RESULTS:Thirty active grants supporting large CESCs were identified. Of the 30 CESCs, 36.7% are comprised of survivors of mixed cancer types; the remaining 63.3% are following survivors diagnosed with cancer of a single anatomic type or grouping (e.g., blood cancers). Special populations of focus include adult survivors of pediatric cancers, adolescent and young adult cancer survivors, pediatric cancer survivors, and stem cell transplant survivors. Notable gaps include cohorts following long-term cancer survivors, survivors of less common cancer types, and survivors from understudied populations. CONCLUSIONS:CESCs highlighted in this article represent a substantial investment in exploring the multifaceted factors that influence cancer outcomes. These cohorts encompass an increasing diversity of cancer types, treatments, and populations. IMPACT:CESCs provide valuable insights into clinical and molecular risk factors associated with cancer survivorship outcomes that inform guidelines and interventions.

12081 Background: Prior small retrospective studies suggest that cannabis might compromise the efficacy of ICIs for cancer therapy due to its immunosuppressive properties. Evidence from large prospective studies is lacking. Methods: We addressed this research gap in the DiRECT Cohort (URCC21038, NCT05364086), an ongoing, observational trial enrolling self-identified Black and White cancer patients (melanoma excluded) who are about to start ICI-containing therapy through the URCC NCORP Research Base nationwide clinical trial network. Longitudinal data on cannabis use are collected through self-administered surveys at baseline (A1), 6 months (A3), and annually (A4+), along with clinical data and patient-reported outcomes on physical and psychological symptoms. This interim analysis on cannabis use includes 1,666 patients enrolled between 04/01/2022 and 08/31/2024, with outcome data updated to 11/30/2024. Results: The mean age was 63.7 (±12.4) years; 408 (24.5%) patients were Black; 905 (54.3%) were women; the most common diagnosis was lung cancer (621 or 37.3%); and a majority had stage IV disease (906 or 54.4%). At A1, 284 (17.1%) patients reported cannabis use in any form, mostly orally (58.1%) or via inhalation (32.3%). Use rates remained stable at A3 (15.6%) and A4 (15.4%) (P = 0.47); yet patients reported fewer days of use in a month (P < 0.0001) but more times in a day (P = 0.07) than at A1. Cannabis users were younger and more likely to be Black, from states with permissive cannabis laws, and current or former cigarette smokers (P’s < 0.05), with no differences observed by gender, cancer type, or stage. After a median follow-up of 10.4 months (range: 0.03-31.0), 381 patients died, and 174 patients had progressed disease or entered hospice care. Median overall survival (OS) and event-free survival (EFS) were slightly higher in cannabis users than non-users at A1 (6.1 vs. 5.3 months, P = 0.07 and 6.0 vs. 5.4 months, P = 0.15, respectively). Cox hazards models adjusted for age, gender, cancer type, and stage revealed no significant association between cannabis use and OS (adjusted hazards ratio [aHR] = 0.82, 95% CI 0.61-1.10) or EFS (aHR = 0.92, 95% CI 0.72-1.17). Subgroup univariate analysis showed cannabis use was associated with longer OS and EFS within men (n = 743) and former smokers (n = 765) (P’s < 0.05), which became non-significant after adjusting for covariates in Cox models, except for OS within former smokers (aHR = 0.52, 95% CI 0.33-0.83). A significant interaction was noted between cannabis use and smoking status (P = 0.02). Conclusions: In this nationwide, diverse community-based oncology cohort, 17% of patients reported cannabis use concurrent with ICI therapy. Unlike previous retrospective studies, our prospective analysis finds no detrimental effect of cannabis on OS or EFS. Further analyses are ongoing to elucidate its impact on symptom management. Clinical trial information: NCT05364086 .

The field of precision oncology has witnessed several advances that stimulated the development of new clinical trial designs and the emergence of real-world data (RWD) as an important resource for evidence generation in healthcare decision-making. Here, we highlight our experience with an innovative approach to a set of Adaptive, Universal Principles for Real-world Observational Studies (AUPROS). To demonstrate the utility of these principles, we used a mixed-methods approach to assess three studies that follow AUPROS at Princess Margaret Cancer Centre: (1) Molecular Epidemiology of ThorAcic Lesions (METAL), (2) Translational Head And NecK Study (THANKS), and (3) CAnadian CAncers With Rare Molecular Alterations (CARMA; NCT04151342). We performed resource assessments, stakeholder-directed surveys and discussions, analysis of funding, research output, collaborations, and a Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis. Based on these analyses, AUPROS is an approach that is applicable to a wide range of observational study designs. The universality of AUPROS allows for multi-purpose analyses of various RWD, and the adaptive nature creates opportunities for multi-source funding and collaborations. Following AUPROS can offer cost and logistical benefits and may lead to increased research productivity. Several challenges were identified pertinent to ethics approvals, sustainability, complex coordination, and data quality that require local adaptation of these principles.

Expanding legal access to medical cannabis across the United States increases availability and use of cannabis products to manage cancer-related symptoms and treatment side effects despite the lack of research-based evidence on its potential benefits and harms. To address knowledge gaps in how cancer patients access and use cannabis, their perceived risks and benefits with its use, and whether cancer patients discuss cannabis use with their healthcare providers during treatment, the National Cancer Institute (NCI) supported 12 NCI-designated comprehensive cancer centers to conduct surveys, which included NCI standardized core questions on cannabis use during treatment, among their cancer patient populations. This overview highlights key results from the articles contained in the monograph, which includes a summary of the results of core questions across all centers and reports from individual or groups of cancer centers on survey results related to the sourcing of cannabis, associated cost, behavioral factors associated with cannabis use (such as smoking, drinking, or using other substances), patient-provider communication on cannabis use during treatment, ethnic variations in patterns, sources, and reasons for cannabis use as well as methodologic concerns related to survey data analysis. The results of these surveys of cannabis use after the diagnosis of cancer lay the groundwork for much-needed research to answer the questions of benefits and harms, including potential interactions with cancer treatments for cancer patients.

PURPOSE Use of genomic testing, especially multimarker panels, is increasing in the United States. Not all tests and related treatments are covered by health insurance, which can result in substantial patient out-of-pocket (OOP) costs. Little is known about oncologists' treatment decisions with respect to patient insurance coverage and OOP costs for genomic testing. METHODS We identified 1,049 oncologists who used multimarker tumor panels from the 2017 National Survey of Precision Medicine in Cancer Treatment. Separate multivariable ordinal logistic regressions examined associations of oncologist-, practice-, and area-level characteristics and oncologists' ratings of importance (very, somewhat, or a little/not important) of insurance coverage and OOP costs for genomic testing in treatment decisions, adjusting for oncologist years of experience, sex, race and ethnicity, specialty, use of next-generation sequencing (NGS) tests, region, tumor boards, patient insurance mix, and area-level socioeconomic characteristics. RESULTS Among oncologists, 47.3%, 32.7%, and 20.0% reported that patient insurance coverage for genomic testing was very, somewhat, or a little/not important, respectively, in treatment decisions. In addition, 56.9%, 28.0%, and 15.2% reported that OOP costs for testing were very, somewhat, or a little/not important, respectively. In adjusted analyses, oncologists who used NGS tests were more likely to report patient insurance and OOP costs as important (odds ratio [OR], 2.00 [95% CI, 1.16 to 3.45] and OR, 2.12 [95% CI, 1.22 to 3.68], respectively) in treatment decisions compared with oncologists who did not use these tests, as were oncologists who treated solid tumors, rather than only hematological cancers. More years of experience and higher percentages of Medicaid or self-paid/uninsured patients in the practice were associated with reporting insurance coverage (OR, 1.43 [95% CI, 1.09 to 1.89]) and OOP costs (OR, 1.51 [95% CI, 1.13 to 2.01]) as important. Oncologists in practices with molecular tumor boards for genomic tests were less likely to report coverage (OR, 0.63 [95% CI, 0.47 to 0.85]) and OOP costs (OR, 0.72 [95% CI, 0.53 to 0.97]) as important than their counterparts in practices without these tumor boards. CONCLUSION Most oncologists rate patient health insurance and OOP costs for genomic tests as important considerations in subsequent treatment recommendations. Modifiable factors associated with these ratings can inform interventions to support patient-physician decision making about care.

PURPOSE: Advances in genomic techniques have led to increased use of next-generation sequencing (NGS). We evaluated the extent to which these tests guide treatment decisions. METHODS: We developed and distributed a survey assessing NGS use and outcomes to a survey pool of ASCO members. Comparisons between groups were performed with Wilcoxon two-sample, chi-square, and Fisher's exact tests. RESULTS: Among 178 respondents, 62% were male, 54% White, and 67% affiliated with academic centers. More than half (56%) indicated that NGS provided actionable information to a moderate or great extent. Use was highest (median ≥ 70% of cases) for lung and gastric cancer, and lowest (median < 25% of cases) in head and neck and genitourinary cancers. Approximately one third of respondents reported that, despite identification of an actionable molecular variant, patients were sometimes or often unable to access the relevant US Food and Drug Administration–approved therapy. When NGS did not provide actionable results, individuals reporting great or moderate guidance overall from NGS in treatment recommendations were more likely to request the compassionate use of an unapproved drug (P < .001), enroll on a clinical trial (P < .01), or treat off-label with a drug approved for another indication (P = .02). CONCLUSION: When NGS identifies an actionable result, a substantial proportion of clinicians reported encountering challenges obtaining approved therapies on the basis of these results. Perceived overall impact of NGS appears associated with clinical behavior unrelated to actionable NGS test results, including pursuing off-label or compassionate use of unapproved therapies or referring to a clinical trial.

The advent of the genomic age has created a rapid increase in complexity for the development and selection of drug treatments. A key component of precision medicine is the use of genetic information to improve therapeutic effectiveness of drugs and prevent potential adverse drug reactions. Pharmacoepidemiology, as a field, uses observational methods to evaluate the safety and effectiveness of drug treatments in populations. Pharmacoepidemiology by virtue of its focus, tradition, and research orientation can provide appropriate study designs and analysis methods for precision medicine. The objective of this manuscript is to demonstrate how pharmacoepidemiology can impact and shape precision medicine and serve as a reference for pharmacoepidemiologists interested in contributing to the science of precision medicine. This paper depicts the state of the science with respect to the need for pharmacoepidemiology and pharmacoepidemiological methods, tools and approaches for precision medicine; the need for and how pharmacoepidemiologists use their skills to engage with the precision medicine community; and recommendations for moving the science of precision medicine pharmacoepidemiology forward. We propose a new integrated multidisciplinary approach dedicated to the emerging science of precision medicine pharmacoepidemiology.

The landscape of both recreational and medicinal cannabis use has changed dramatically over the past decade; however, research examining the risks and benefits of cannabis and cannabinoid use has lagged significantly behind the increased media promotion and their use by the general public and cancer patients. The National Cancer Institute (NCI) has supported cannabis-related research projects and funding opportunity announcements. In addition, NCI organized a virtual symposium on December 15-18, 2020, to discuss recent research findings on the use of cannabis and cannabinoids in relationship to cancer risk, prevention, and care. Specifically, the symposium sought to highlight the state of the science regarding cannabis, including the chemical constituents of cannabis (eg, cannabinoids), and cancer research involving cannabis, including cancer epidemiology, use in cancer patients, cancer biology and prevention, and preclinical and clinical cancer symptom and treatment side effect management with cannabis and cannabinoids as therapeutics. The symposium identified promising areas of future study, current barriers to conducting the research, and strategies to overcome those barriers. The series of papers in this special edition provide a summary of the symposium sessions as well as a synopsis of opportunities and challenges related to conducting research in this area.

The British HIV Association recommends that new diagnoses be reviewed by an HIV specialist within two weeks. NHS England outcome measures include the proportion of new diagnoses commencing antiretroviral therapy (ART) within 91 days. We aimed to review the extent to which these recommendations were followed, to explore the topics discussed with new diagnoses, and to identify reasons behind delayed ART initiation. UK specialist HIV services were invited to retrospectively review the notes of their last 40 new diagnoses over a 15-month period. One-hundred and thirty-two services provided data for 2281 eligible individuals. Most new diagnoses were reviewed by a specialist within two weeks (67.7%) and were commenced on ART within 91 days (83%), however, there were some concerning delays in those tested at home and in general practice. Partner notification and treatment benefits were discussed with most individuals, unlike the availability of community support and U = U ("undetectable equals untransmittable"). Lengthy delays in ART initiation were mostly due to individuals initially declining ART or missing appointments. Our findings suggest a need for more streamlined pathways into HIV care, review of new diagnoses who have not commenced ART within 8 weeks, and protocol development to ensure discussion of relevant topics.

PURPOSE This study examines oncologist-reported reasons for not using multimarker tumor panel testing and the association between these reasons and oncologist-level, facility-level, and patient-mix characteristics. METHODS We used data collected from a nationally representative sample (N = 1,281) of medical oncologists participating in the National Cancer Institute's National Survey of Precision Medicine in Cancer Treatment. RESULTS In addition to testing not being seen as relevant (87%) and no evidence of test utility (77%), the most frequently reported reasons for not ordering a multimarker tumor panel test was difficulty in obtaining sufficient tissue (57%) and using individual gene tests (72%). These reasons were more likely to be reported by oncologists practicing in rural clinics and less likely to be reported by oncologists with an academic affiliation or with access to genetic services such as on-site genetic counselors and internal genetic testing policies. CONCLUSION Modifiable, organizational factors were associated with ordering multimarker tumor panels. Receipt of genomics training and organizational policies related to the use of genomics were associated with lower reporting of barriers to ordering multimarker tumor panels, pointing to potential targets for future studies aimed at increasing appropriate multimarker tumor panel testing in cancer treatment management.

PURPOSE Oncologists are increasingly using molecular profiling to inform personalized patient treatment decisions. Despite its promising utility, the integration of genomic testing into diverse clinical health care settings across geographic settings has been understudied. METHODS We used data from the National Survey of Precision Medicine in Cancer Treatment, a nationally representative sample of practicing US oncologists, to assess the availability of six genomic testing resources, including on-site pathology, contracts with outside laboratories, on-site genetic counselors, internal policies or protocols for using genomic and biomarker testing, electronic medical record alerts, and genomic or molecular tumor boards. We used multivariate logistic regression models to examine differences in the availability of each genomic testing resource by practice type and rurality while adjusting for payer mix and patient volume. RESULTS A larger proportion of multispecialty group and academic practices had genomic testing resources available compared with solo and nonacademic practices. Electronic medical record alerts were the least available resource, whereas contracts with outside laboratories were the most available resource. Compared with urban practices, there were significantly fewer practices located in rural areas that had on-site pathology, on-site genetic counselors, protocols for genomic tests, and molecular tumor boards. CONCLUSION Genomic testing resources varied by practice type and geography among a nationally representative sample of practicing oncologists. This variation has important implications for the development of interventions and policies to support the more equitable delivery of precision oncology to patients with cancer.

Background: The goals of this project were to assess the status of NCI's rare cancer–focused population science research managed by the Division of Cancer Control and Population Sciences (DCCPS), to develop a framework for evaluation of rare cancer research activities, and to review available resources to study rare cancers. Methods: Cancer types with an overall age-adjusted incidence rate of less than 20 cases per 100,000 individuals were identified using NCI Surveillance, Epidemiology and End Results (SEER) Program data. SEER data were utilized to develop a framework based on statistical commonalities. A portfolio analysis of DCCPS-supported active grants and a review of three genomic databases were conducted. Results: For the 45 rare cancer types included in the analysis, 123 active DCCPS-supported rare cancer-focused grants were identified, of which the highest percentage (18.7%) focused on ovarian cancer. The developed framework revealed five clusters of rare cancer types. The cluster with the highest number of grants (n = 43) and grants per cancer type (10.8) was the cluster that included cancer types of higher incidence, average to better survival, and high prevalence (in comparison with other rare cancers). Resource review revealed rare cancers are represented in available genomic resources, but to a lesser extent compared with more common cancers. Conclusions: This article provides an overview of the rare cancer–focused population sciences research landscape as well as information on gaps and opportunities. Impact: The findings of this article can be used to develop efficient and comprehensive strategies to accelerate rare cancer research. See related commentary by James V. Lacey Jr, p. 1300

95 Background: Use of genomic testing to inform cancer treatment is an increasingly common practice in the US. Genomic testing and related treatment can be expensive and not all tests and treatments are covered by health insurance plans. Little is known about how often physicians discuss costs of genomic testing and related treatment with their patients, nor about the physician and/or practice factors associated with those discussions. Methods: We identified 1220 oncologists who participated in the National Survey of Precision Medicine in Cancer Treatment in 2017 and reported discussing genomic testing with their patients within 12 months. Weighted percentages were used to describe the frequency of cost discussions and multivariable polytomous logistic regression analyses were used to assess associations between physician and practice characteristics and the frequency of cost discussions. Results: Among oncologists who discussed genomic testing, 50.0% reported often discussing the likely costs of testing and related treatment; 26.3% reported sometimes discussing costs; and the remaining 23.7% reported never or rarely discussing costs. In adjusted analyses, oncologists who used next-generation sequencing gene panel tests were more likely to have cost discussions with their patients often (OR = 2.3; 95% CI: 1.6,3.2) or sometimes (OR = 1.8; 95% CI: 1.2, 2.7) compared to rarely or never. Other physician and practice factors associated with more frequent cost discussions were treating solid tumors only (rather than hematologic only or both hematologic and solid tumors), training in genomic testing, and working in practices with electronic medical record (EMR) alerts for genomic tests (all p < 0.05). Conclusions: Physician and practice factors are associated with discussions of the costs of genomic testing and related treatments. As professional organizations increasingly recommend discussions of costs with cancer patients, consideration of modifiable physician and practice factors, such as training in genomic testing and use of EMR alerts, may help achieve these aims.

Precision medicine using multi-marker tumor panel (MMTP) testing can help inform cancer treatment decisions. Oncologists’ knowledge of these tests and their ability to find up-to-date information about their application in clinical care is essential. This study aimed to (1) describe information sources used by oncologists to learn about new genomic tests and (2) examine characteristics associated with the use of each information source. The National Cancer Institute’s National Survey of Precision Medicine in Cancer Treatment surveyed a nationally representative sample of oncologists about MMTP testing. We examined the use of 11 information sources among oncologists that reported using MMTP tests (n = 1222). Bivariate analyses were used to examine whether information sources differed by oncologist- and practice-level characteristics and type of MMTP test. Most oncologists reported using peer-reviewed medical literature (88.8%), scientific conferences (87.9%), and medical professional societies (83.8%) to learn about MMTPs. In contrast, government websites, FDA inserts, and foundation resources were each used by < 36% of oncologists. The use of information sources differed by oncologist and practice characteristics. For example, a greater percentage of oncologists with an academic affiliation used peer-reviewed medical literature and scientific conferences, as compared to those without an academic affiliation (p = 0.006). As the number and type of MMTP tests increase, providing oncologists with current information about their appropriate application is essential. Further understanding of how oncologists use specific information sources may improve the dissemination and effective implementation of new MMTPs and help tailor educational interventions based on provider characteristics.

BACKGROUND: Following approval of imatinib, a breakthrough tyrosine kinase inhibitor (TKI), survival significantly improved by more than 20% since 2001 among treated chronic myelogenous leukemia (CML) patients. Subsequently, more expensive second-generation TKIs with varying selectivity profiles have been approved. Population-based studies are needed to evaluate the real-world utilization of TKI therapies, particularly given their escalating costs and recommendations for maintenance therapy. OBJECTIVE: To assess the utilization patterns of first-line TKIs, overall and by specific agent, among elderly CML patients in the United States, and the cost implications. METHODS: CML patients aged 65 years and older at diagnosis between 2007 and 2015 were identified from population-based cancer registries in the linked Surveillance, Epidemiology, and End Results (SEER)-Medicare database. The percentage of CML patients receiving imatinib, dasatinib, or nilotinib within the first year of diagnosis was calculated along with time to first-line treatment initiation. Bivariate comparisons and Cox proportional hazards models were used to identify factors associated with TKI initiation. Average monthly patient responsibility, including patient out-of-pocket (OOP) costs, stratified by Part D low-income subsidy (LIS) status were also calculated. RESULTS: Among the 1,589 CML patients included, receipt of any TKI within 1 year of diagnosis increased from 66.2% to 78.9%. In 2015, the distribution of first-line TKI therapies was 41.3% imatinib, 28.3% dasatinib, and 9.3% nilotinib. Almost 60% of patients initiated TKI treatment within 3 months of diagnosis. Multivariable analysis indicated that TKI use in the first year was lower among the very elderly (aged > 75 years vs. 65-69 years: HR = 0.72; 95% CI = 0.63-0.83), patients with more comorbidities (Hierarchical Condition Category risk score >2 vs. HR = 0.74, 95% CI = 0.62-0.88), and patients ineligible for LIS (HR = 0.75; 95% CI = 0.65-0.87). Average monthly patient OOP cost was significantly lower for LIS-eligible versus LIS-ineligible patients: imatinib (2016: $12 vs. $487), dasatinib (2016: $34 vs. $557), and nilotinib (2016: $1 vs. $526). CONCLUSIONS: TKI use has increased significantly since 2007. While imatinib remained the most frequently prescribed first-line agent, by 2015 newer TKIs represented one third of the market share. Utilization patterns indicated persistent age, comorbidity, and financial barriers. TKI use is indicated for long-term therapy, and increased adoption of newer, more expensive agents raises concerns about the sustained affordability of CML treatment, particularly among unsubsidized patients.

Abstract Purpose: This study seeks to understand how the availability of genomic testing resources for cancer treatment vary by oncology practice setting and rurality. Background: Pervasive inequities in access to cancer care resources exist at the neighborhood and health system level. In particular, rurality and practice type have been linked to diminished access to care and poorer health outcomes. While these inequities persist, there have been many advancements in cancer care technology and oncologists are increasingly using genomic testing and next-generation sequencing technology to inform treatment decisions. Little is known about the availability of genomic testing resources in different oncology practice settings and at differing levels of rurality. Methods: This study used data from the National Survey of Precision Medicine in Cancer Treatment, the first nationally representative sample of oncologists (N=1,281) practicing in the United States. Oncologists were identified from the American Medical Association Masterfile for 2017 and were sampled by specialty, census region, metropolitan statistical area, sex, and age. The outcome, availability of genomic testing resources, was measured using one survey question asking oncologists if their primary practice has the following genomic testing resources: on-site pathology, contracts with outside labs, on-site genetic counselors, internal protocols for using genomic testing, electronic medical records (EMR) that alert providers when to order a genomic test, and molecular tumor boards. The predictor variables were rurality and practice type. Rurality was determined using Rural Urban Continuum Codes (RUCC) from 2013. Practice type was measured using the following six categories: solo practice academic, solo practice non-academic, single specialty group academic, single specialty group non-academic, multispecialty group academic, and multispecialty group non-academic. Descriptive statistics were presented, and chi-square tests were used to assess statistically significant difference. The weighted sampling design of the survey was accounted for using SAS statistical package version 9.4 (SAS, Cary NC). Results: Higher proportions of academic practices had genomic testing resources than non-academic practices. Higher proportions of multispecialty groups had genomic testing resources compared to single specialty group and solo practices. Compared to urban practices, lower proportions of rural practices had genomic testing resources for all except contracts with outside labs and EMR alerts. Conclusion: These data highlight the unequal distribution of genomic testing resources for cancer treatment by practice type and rurality. Future studies and interventions should strive to further assess factors affecting access to cancer care resources and explore health system level approaches to improve health equity. Citation Format: Brittany D. Gardner, Janeth Sanchez, Michelle Doose, Sallie J. Weaver, Shobha Srinivasan, Andrew Freedman, Janet S. de Moor. Distribution of genomic testing resources by oncology practice setting and rurality: A nationally representative analysis [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-210.