Cancer Care Ontario

Variations in the implementation of emerging data nomenclature standards and usage of artificial intelligence (AI) tools in Canadian radiation therapy (RT) centres have not yet been fully characterized. To address this, a current state analysis was conducted to serve as a baseline assessment and to identify gaps and opportunities for harmonized pan-Canadian data practices and the adoption of AI in clinical settings within radiation oncology. A survey was distributed to all Canadian RT centres with the aim to describe the perceived status and characteristics of implementation of standardized nomenclature, usage of AI tools, and relevant gaps and opportunities in this field. Thirty three of 51 (64.7%) Canadian RT centres responded. Responses characterized variation in standardized nomenclature implementation and usage of AI tools across centres, with some trends between regions. Approximately two-thirds of RT centres were using TG-263 guidance of the American Association of Physicists in Medicine (70.0%, n=23). whereas only a third of centres reported awareness of next steps for O3. The most commonly-reported barriers to data standardization included a lack of resources and forcing functions. Automation and quality improvement were recognized as facilitators, with (81.8%, n=27) are using automation tools to support standardization. This current state analysis informs and directs future initiatives to improve standardized nomenclature implementation and support informed AI adoption within RT, with the goal of ultimately improving RT quality and safety. Canada is well-positioned to lead data standardization efforts and serve as a case study to potentially provide guidance at an international level to equal partners.

559 Background: Despite advances with immune checkpoint inhibitors (ICI) and vascular endothelial growth factor (VEGF)–targeted tyrosine kinase inhibitors, outcomes in metastatic renal cell carcinoma (mRCC) remain variable, with primary resistance and treatment-limiting toxicities The gut microbiome influences both ICI response and immune-related toxicity. The PERFORM trial (NCT04163289) is a single-arm, phase I study evaluating the safety of healthy-donor fecal microbiota transplantation (FMT) given before and during first-line ICI-based therapy in patients with mRCC. Methods: In this trial, 20 untreated mRCC patients received encapsulated healthy-donor FMT (LND101) prior to standard ICI-based regimens (ipilimumab–nivolumab, pembrolizumab–axitinib, or pembrolizumab–lenvatinib). The primary endpoint was safety. Secondary clinical endpoints included objective response (ORR), clinical benefit (complete or partial response or stable disease lasting six months or longer), progression-free survival (PFS), overall survival (OS), and quality of life (QoL). Results: FMT was well-tolerated with no FMT-related serious toxicity. Median follow-up was 21.9 months (range, 5.6–53.3). One patient (5%) experienced grade 1 gastrointestinal event attributed to FMT. Any-grade irAEs occurred in 95%; grade ≥3 in 50%, consistent with historical ICI rates. No grade 4–5 toxicities related to FMT or systemic therapy were observed. Among 18 evaluable patients, the ORR was 44% (n = 8) including two complete responses (11%). Primary progressive disease occurred in five patients (28 %). Clinical benefit was achieved in 72% (n = 13). Only 1 of 8 responders (12.5%) developed grade ≥3 irAEs vs 8 of 10 non-responders (80%) (p = 0.018). Median PFS and OS were 11.15 and 36 months, respectively. QoL remained stable over the first four treatment cycles without evidence of decline attributable to FMT. Conclusions: Encapsulated healthy-donor FMT administered before ICI-based therapy was safe and feasible in patients with previously untreated mRCC. Clinical activity was consistent with contemporary regimens, and severe immune-related toxicity was uncommon among responders. These data support further evaluation of FMT with ICI therapy in larger, multi-center trials to validate safety and clinical benefit. Clinical trial information: NCT04163289 .

SummaryPatient navigation comprises person-centred activities focused on addressing barriers and facilitating timely access to health care. Despite demonstrated effectiveness, the scope of patient navigation remains unclear. To clarify the scope of patient navigation and support global implementation, the Global Initiative to Advance Cancer Navigation for Better Outcomes (GINO) aimed to develop a practice framework for patient navigation in cancer care. Phase 1 involved reviewing patient navigation literature and identifying key areas of practice. Phase 2 involved a modified Delphi process with international experts in navigation (July to December 2024) to establish consensus on practices to include in the framework. Patient navigation experts across regions and disciplines were invited. Two rounds of online surveys were conducted where participants rated the importance of each practice on a scale from 1 (“Not important”) to 5 (“Critically important”). Practices rated ≥4 by ≥ 75% of participants in Round 2 met consensus criteria. The remaining items were discussed in a consensus meeting. Eighty-one experts from 29 countries (n = 45, 56% high-income, n = 36, 44% low-middle-income) participated in Round 1. Of these, 60 also participated in Round 2, including healthcare practitioners (n = 30, 50%), navigators (n = 16, 27%), researchers (n = 24, 40%), and advocates (n = 10, 17%). After Round 2, 27/35 (77%) practices reached consensus for inclusion. After the consensus meeting, two items were reworded, and 32 items were included in the final framework. We reached consensus among international experts on the contents of the GINO practice framework for patient navigation in cancer care. By describing the scope of patient navigation, the framework can support the development and implementation of patient navigation programs globally.

Meta-analyses assessing test accuracy typically require extracting true positive (TP), false negative (FN), false positive (FP), and true negative (TN) counts from each study, commonly organized in a 2 × 2 table. However, many published test accuracy studies do not report all of these counts, which can limit the ability of a meta-analysis to fully capture the available evidence on the screening or diagnostic accuracy of a given test. Fortunately, test accuracy studies often report sufficient parameters, such as sensitivity and specificity, that enable the estimation of unreported counts. The relationships between these commonly reported parameters and the unreported cell counts may be expressed mathematically and organized into a system of four linear equations. The basic principles of solving such systems using matrix methods are introduced, accompanied by examples illustrating the development and solution of linear systems with unknown TP, FN, TN, and TN counts. Approaches for handling rounding errors of reported test accuracy parameters in publications are also demonstrated. Additionally, methods for obtaining a bound solution are explored in scenarios where the solution for missing test accuracy counts results in a system with three linear equations and four unknowns, leading to non-unique solutions. Simulation studies are conducted to assess the performance of these methods, and practical guidance for their implementation is provided. The Microsoft Excel spreadsheets and SAS and R code for the examples presented in this article are available in the Supporting Information.

“No way am I doing that treatment.” My husband, Michael, uttered those words through gritted teeth as he stumbled to our car after being fitted for his radiation mask. In over 20 years of marriage, I had never seen him in such a terrifying and terrified state. We had been told repeatedly that

Using a standardized data template, this study retrospectively collected data about colorectal cancer (CRC) screening activity in 2020 and 2021 to estimate the impact of the COVID-19 pandemic compared to the pre-pandemic period (2018 or 2019). Data were collected from 17 programs in 14 countries of which 15 were population-based programs. Invitation coverage was decreased by up to 53.7% in 2020. Participation among those invited was similar in both periods for all programs. The maximum backlog in invitations was less than 7.4 months in 2020 and 3.3 months for 2021. Nine out of 15 programs observed a decrease in the number of detected CRCs in 2020. Four programs showed a positive percentage change in CRCs detected in 2021 relative to the pre-pandemic period. Half of the countries observed a worse stage-distribution in 2020/2021. Overall, organized CRC screening programs operated at lower screening activity, but screening outcomes were similar compared to the pre-pandemic period.

Sexual dysfunction is a prevalent and often under-addressed concern among prostate cancer survivors, significantly affecting quality of life for patients and their partners. The True North Sexual Health and Rehabilitation eClinic (SHAReClinic) is a virtual, biopsychosocial intervention developed to improve access to sexual health support for prostate cancer survivors and their partners. This study used a qualitative descriptive design to examine barriers and facilitators influencing the integration of SHAReClinic into oncology care across nine Canadian health care centres. Semi-structured interviews were conducted with 17 knowledge users, including health care providers and institutional leaders. Data were analyzed using a hybrid deductive-inductive thematic approach guided by the Consolidated Framework for Implementation Research (CFIR) 2.0. Participants described SHAReClinic as a much-needed resource, particularly in the absence of standardized sexual health pathways in oncology care. The virtual format was seen as accessible and well suited to addressing sensitive topics. However, limited funding, lack of institutional support, and workflow integration challenges emerged as primary barriers to implementation. Findings offer practical, theory-informed guidance for integrating SHAReClinic into oncology care and highlight key considerations for developing sustainable and scalable survivorship care models.