Bill Byrom

Clinician assessment of adverse events in oncology systematically underestimates the severity and frequency of symptoms that patients actually experience, creating risks in both drug development and routine care. Electronic patient-reported outcome (ePRO) systems help to address this gap by enabling frequent remote symptom monitoring, bringing the patient voice into the care pathway between clinic visits. Published studies confirm that automated data-driven alerting in response to ePRO data entries can drive better patient outcomes including reduced emergency department visits, delayed physical function deterioration, and improved symptom control, with early intervention the likely mechanism. Translating this evidence into practice demands deliberate attention to how data are visualized, communicated, and acted upon. This perspectives article examines, primarily in the context of oncology clinical trials, the tools and design principles that translate ePRO data into timely clinical action, including heatmap visualizations that reveal symptom trajectories at a glance, predefined alert thresholds that trigger proactive responses, and patient-facing self-management support delivered at the moment of reporting. The regulatory, ethical and methodological case for embedding active monitoring within oncology trial design is also considered.

Patient-reported outcomes assessing treatment toxicity and its impact, and aspects of quality of life, have become increasingly important components of oncology drug development including early phase dose optimization studies. Despite insights from these data, there are limitations on drawing inferences about whether a treatment is tolerable or intolerable, which requires understanding individual risk-benefit assessments that vary between patients, cancer types, and stages of disease. This commentary examines unresolved methodological issues requiring more research rigor and attention: the development of tolerability thresholds based upon toxicity severity data; the direct measurement of tolerability through specific patient self-report measures; and overcoming the challenge of baseline value assessment in important measures such as single item side-effect bother assessments. We call for further research to resolve these challenges and drive more robust inference-making from patient-reported outcomes data collected in cancer clinical trials.

While patient-reported outcome measures are regularly incorporated into phase 3 clinical trials, they have been infrequently used in early phase trials. However, the patient’s perspective is vital to fully understanding dose toxicity and selecting an optimal dose. This viewpoint paper reviews the rationale for and practical approach to collecting patient-reported outcome data in early phase oncology drug development and the rationale for electronic collection.

The increased use of sensor‐based digital health technologies (DHTs) in clinical trials brought to light concerns about implementation practices that might introduce burden on trial participants, resulting in suboptimal compliance and become an additional complicating factor in clinical trial conduct. These concerns may contribute to the lower‐than‐anticipated uptake of DHT deployment and data use for regulatory decision‐making, despite well‐articulated benefits. The Electronic Clinical Outcome Assessment (eCOA) Consortium gathered collective experience on deploying sensor‐based DHTs and supplemented this with relevant literature focusing on mechanisms that may enhance participant compliance. The process for DHT implementation starts with identifying a clinical concept of interest followed by a digital measure selection, defining active or passive data capture and their sources, the number of sensors with respective body location, plus the duration and frequency of use in the context of perceived participant burden. Roundtable discussions among patient groups, physicians, and technology providers prior to protocol development can be very impactful for optimizing trial design. While diversity and inclusion are essential for any clinical trial, patient populations should be considered carefully in the context of trial‐specific aims, requirements, and anticipated patient burden. Minimizing site burden includes assessment of training, research engagement, and logistical burden which needs to be triaged differently for early and late‐stage clinical trials. Additional considerations include sharing trial results with study participants and leveraging publicly available data for compliance modeling. To the best of our knowledge, this report provides holistic considerations for sensor‐based DHT implementation that may optimize participant compliance.

UNSTRUCTURED While patient-reported outcome measures (PROMs) are regularly incorporated into phase III clinical trials, there has been little use of PROMs in early phase trials [1]. However, the patient perspective is a vital element of fully understanding dose-toxicity and selecting an optimal dose. This viewpoint paper reviews the rationale for, and practical approach to, collection of patient-reported outcomes (PRO) data in early-phase oncology drug development, and the rationale for electronic collection.

Background: Providing informed consent means agreeing to participate in a clinical trial and having understood what is involved. Flawed informed consent processes, including missing dates and signatures, are common regulatory audit findings. Electronic consent (eConsent) uses digital technologies to enable the consenting process. It aims to improve participant comprehension and engagement with study information and to address data quality concerns. Objective: This systematic literature review aimed to assess the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, and study enrollment and retention rates, as well as the effects of eConsent on the time patients took to perform the consenting process (“cycle time”) and on-site workload in comparison with traditional paper-based consenting. Methods: The systematic review was conducted and reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Ovid Embase and Ovid MEDLINE were systematically searched for publications reporting original, comparative data on the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, enrollment and retention rates, cycle time, and site workload. The methodological validity of the studies that compared outcomes for comprehension, acceptability, and usability across paper consent and eConsent was assessed. Study methodologies were categorized as having “high” validity if comprehensive assessments were performed using established instruments. Results: Overall, 37 publications describing 35 studies (13,281 participants) were included. All studies comparing eConsenting and paper-based consenting for comprehension (20/35, 57% of the studies; 10 with “high” validity), acceptability (8/35, 23% of the studies; 1 with “high” validity), and usability (5/35, 14% of the studies; 1 with “high” validity) reported significantly better results with eConsent, better results but without significance testing, or no significant differences in overall results. None of the studies reported better results with paper than with eConsent. Among the “high” validity studies, 6 studies on comprehension reported significantly better understanding of at least some concepts, the study on acceptability reported statistically significant higher satisfaction scores, and the study on usability reported statistically significant higher usability scores with eConsent than with paper (P<.05 for all). Cycle times were increased with eConsent, potentially reflecting greater patient engagement with the content. Data on enrollment and retention were limited. Comparative data from site staff and other study researchers indicated the potential for reduced workload and lower administrative burden with eConsent. Conclusions: This systematic review showed that compared with patients using paper-based consenting, patients using eConsent had a better understanding of the clinical trial information, showed greater engagement with content, and rated the consenting process as more acceptable and usable. eConsent solutions thus have the potential to enhance understanding, acceptability, and usability of the consenting process while inherently being able to address data quality concerns, including those related to flawed consenting processes.

BACKGROUND Providing informed consent means agreeing to participate in a clinical trial and having understood what is involved. Flawed informed consent processes, including missing dates and signatures, are common regulatory audit findings. Electronic consent (eConsent) uses digital technologies to enable the consenting process. It aims to improve participant comprehension and engagement with study information and to address data quality concerns. OBJECTIVE This systematic literature review aimed to assess the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, and study enrollment and retention rates, as well as the effects of eConsent on the time patients took to perform the consenting process (“cycle time”) and on-site workload in comparison with traditional paper-based consenting. METHODS The systematic review was conducted and reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Ovid Embase and Ovid MEDLINE were systematically searched for publications reporting original, comparative data on the effectiveness of eConsent in terms of patient comprehension, acceptability, usability, enrollment and retention rates, cycle time, and site workload. The methodological validity of the studies that compared outcomes for comprehension, acceptability, and usability across paper consent and eConsent was assessed. Study methodologies were categorized as having “high” validity if comprehensive assessments were performed using established instruments. RESULTS Overall, 37 publications describing 35 studies (13,281 participants) were included. All studies comparing eConsenting and paper-based consenting for comprehension (20/35, 57% of the studies; 10 with “high” validity), acceptability (8/35, 23% of the studies; 1 with “high” validity), and usability (5/35, 14% of the studies; 1 with “high” validity) reported significantly better results with eConsent, better results but without significance testing, or no significant differences in overall results. None of the studies reported better results with paper than with eConsent. Among the “high” validity studies, 6 studies on comprehension reported significantly better understanding of at least some concepts, the study on acceptability reported statistically significant higher satisfaction scores, and the study on usability reported statistically significant higher usability scores with eConsent than with paper (P<.05 for all). Cycle times were increased with eConsent, potentially reflecting greater patient engagement with the content. Data on enrollment and retention were limited. Comparative data from site staff and other study researchers indicated the potential for reduced workload and lower administrative burden with eConsent. CONCLUSIONS This systematic review showed that compared with patients using paper-based consenting, patients using eConsent had a better understanding of the clinical trial information, showed greater engagement with content, and rated the consenting process as more acceptable and usable. eConsent solutions thus have the potential to enhance understanding, acceptability, and usability of the consenting process while inherently being able to address data quality concerns, including those related to flawed consenting processes.

Background: Visual analogue scales (VASs) are used in a variety of patient-, observer- and clinician-reported outcome measures. While typically included in measures originally developed for pen-and-paper completion, a greater number of clinical trials currently use electronic approaches to their collection. This leads researchers to question whether the measurement properties of the scale have been conserved during the migration to an electronic format, particularly because electronic formats often use a different scale length than the 100 mm paper standard. Methods: We performed a review of published studies investigating the measurement comparability of paper and electronic formats of the VAS. Results: Our literature search yielded 26 studies published between 1997 and 2018 that reported comparison of paper and electronic formats using the VAS. After excluding 2 publications, 23 of the remaining 24 studies included in this review reported electronic formats of the VAS (eVAS) and paper formats (pVAS) to be equivalent. A further study concluded that eVAS and pVAS were both acceptable but should not be interchanged. eVAS length varied from 21 to 200 mm, indicating that 100 mm length is not a requirement. Conclusions: The literature supports the hypothesis that eVAS and pVAS provide comparable results regardless of the VAS length. When implementing a VAS on a screen-based electronic mode, we recommend following industry best practices for faithful migration to minimise the likelihood of non-comparability with pVAS.

Aim: To understand the impact of anticancer treatment on oncology patients’ ability to use electronic solutions for completing patient-reported outcomes (ePRO). Materials & methods: Semi-structured interviews were conducted with seven individuals who had experienced a cancer diagnosis and treatment. Results: Participants reported that the following would impact the ability to interact with an ePRO solution: peripheral neuropathy of the hands (4/7), fatigue and/or concentration and memory issues (6/7), where they are in a treatment cycle (5/7). Approaches to improve usability included: larger, well-spaced buttons to deal with finger numbness, the ability to pause a survey and complete at a later point and presenting the recall period with every question to reduce reliance on memory. Conclusion: Symptoms associated with cancers and anticancer treatments can impact the use of technologies. The recommendations for optimizing the electronic implementation of patient-reported outcome instruments in this population provides the potential to improve data quality in oncology trials and places patient needs at the forefront to ensure ‘fit-for-purpose’ solutions.