ChatBot Support for Cancer

Overseen By Michell Kim

Age: 18+

Sex: Any

Trial Phase: Phase 2

Sponsor: Abramson Cancer Center at Penn Medicine

Disqualifiers: Bed bound, Wheelchair reliant

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Prior Safety Data This treatment has passed at least one previous human trial

Compensation: Varies

Number of Visits: Unknown

Duration: 13 weeks

70 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests a new method to help cancer patients manage symptoms during treatment using a chatbot (a digital communication tool) and activity tracking with a FitBit. The goal is to determine if these tools can reduce unnecessary emergency room visits and prevent treatment delays. Participants will use either the activity tracker alone or both the tracker and the chatbot. The trial seeks adults with head and neck, lung, or gastrointestinal cancer who are receiving chemotherapy and radiation and have a mobile device for activity tracking. As a Phase 2 trial, the research focuses on measuring the treatment's effectiveness in an initial, smaller group of people.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

Is there any evidence suggesting that this trial's treatments are likely to be safe?

Research shows that chatbots are being explored for their potential use in cancer care. Previous studies have tested chatbots to assess their ability to gather information from patients. Reports suggest these tools can help answer common patient questions and provide support during treatment. Although chatbots appear promising, they remain new in cancer care, resulting in limited direct evidence about their safety. However, because chatbots only involve communication and do not alter medical treatment directly, they are likely safe. This study is in an early phase, focusing mainly on understanding safety and practicality. While chatbots seem promising, their effectiveness and safety are still under careful study. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about using a ChatBot for cancer support because it offers a unique way to help patients manage their treatment journey. Unlike standard care, which usually involves chemotherapy and radiation therapies, the ChatBot provides real-time, personalized interaction and guidance, potentially improving patient engagement and emotional support. This innovative approach could enhance patients' quality of life by making it easier to track their symptoms, manage side effects, and feel less isolated during treatment. By integrating technology with traditional cancer care, there's hope for a more holistic treatment experience.

What evidence suggests that this trial's treatments could be effective for managing cancer symptoms?

Research shows that chatbots can greatly assist cancer patients by providing medical information and support. In this trial, some participants will use a ChatBot alongside activity monitoring. Studies have found that these chatbots help patients better understand their condition and feel more confident in managing it. They also assist in handling symptoms and offer mental and social support. Early findings suggest that using chatbots in cancer care could reduce unnecessary hospital visits by helping patients address symptoms early. This approach might make cancer treatment less disruptive to daily life by keeping patients well-informed and connected to their care team. ^{1 3 6 7 8}

Who Is on the Research Team?

Arun Goel, MD

Principal Investigator

University of Pennsylvania

Kristine Kim, MD

Principal Investigator

University of Pennsylvania

Nishant Shah, MD

Principal Investigator

University of Pennsylvania

Are You a Good Fit for This Trial?

Adults over 18 with head and neck, lung, or gastrointestinal cancer undergoing chemo and radiation can join. They must own a mobile device for texts and FitBit data, read/respond in English, and consent to the study. Bed-bound patients or those needing wheelchairs for walking cannot participate.

Inclusion Criteria

Possession of a mobile device that can receive SMS texts and deliver FitBit data wirelessly

Ability to read and respond in English

I am an adult with cancer in my head, neck, lung, or gastrointestinal system and am receiving both chemotherapy and radiation.

Exclusion Criteria

I am bedridden and cannot care for myself.

I use a wheelchair to get around.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive standard of care chemotherapy and radiation therapy regimens, with activity monitoring and optional ChatBot use

13 weeks

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• ChatBot

Trial Overview

The trial is testing if using a chatbot along with activity monitoring via FitBit can help manage symptoms early on during cancer treatment. It aims to see if this reduces unnecessary clinic visits, emergency room trips, hospital stays, and treatment interruptions.

How Is the Trial Designed?

Group I: Activity Monitoring and ChatBot Experimental Treatment 1 Intervention

Patients will receive standard of care chemotherapy and radiation therapy regimens, activity monitoring and utilize a ChatBot

Group II: Activity Monitoring without ChatBot Active Control 1 Intervention

Patients will receive standard of care chemotherapy and radiation therapy regimens, activity monitoring alone

Who Is Running the Clinical Trial?

Abramson Cancer Center at Penn Medicine

Lead Sponsor

Trials

425

Recruited

464,000+

Abramson Cancer Center of the University of Pennsylvania

Lead Sponsor

Trials

360

Recruited

108,000+

Published Research Related to This Trial

Chatbots are AI-driven tools that can enhance communication between healthcare providers and patients, facilitating follow-up, screening, and treatment adherence.

Their potential applications in oncology are particularly promising, as they can improve patient engagement and data collection, which may lead to better health outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Healthcare ex Machina: Are conversational agents ready for prime time in oncology? Bibault, JE., Chaix, B., Nectoux, P., et al.[2020]

In a study involving 142 women with breast cancer, the artificial conversational agent (chatbot) Vik provided answers that were as satisfying as those given by a group of physicians, with a success rate of 69% compared to 64% for physicians, demonstrating noninferiority.

This research suggests that chatbots like Vik can effectively inform patients about their treatment, potentially reducing the need for in-person consultations for minor health concerns, allowing doctors to focus on patients who require more direct care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Chatbot Versus Physicians to Provide Information for Patients With Breast Cancer: Blind, Randomized Controlled Noninferiority Trial. Bibault, JE., Chaix, B., Guillemassé, A., et al.[2020]

The CancerHelp-Talking Touchscreen (CancerHelp-TT) program significantly improved cancer knowledge among patients with Stage I-III breast or colorectal cancer, with an effect size of 0.48, indicating its effectiveness in enhancing patient understanding during treatment.

While the intervention showed positive trends in self-efficacy, health beliefs, and satisfaction with communication, the overall effect sizes were small, suggesting that additional support may be necessary for vulnerable patients outside of cancer clinic settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Low Literacy, Multimedia Health Information Technology Intervention to Enhance Patient-Centered Cancer Care in Safety Net Settings Increased Cancer Knowledge in a Randomized Controlled Trial. Peipert, JD., Lad, T., Khosla, PG., et al.[2023]

A virtual interdisciplinary communication workshop was found to be feasible and acceptable for improving communication among oncology team members, based on feedback from 87 patients and 56 clinicians.

The workshop highlighted areas for improvement in communication practices, suggesting that targeted interventions can enhance patient care and safety in ambulatory oncology settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development and Evaluation of a Data-Driven, Interactive Workshop to Facilitate Communication and Teamwork in Ambulatory Medical Oncology Settings. Blok, AC., Costa, DK., Wright, NC., et al.[2023]

In a study involving 8 radiation oncologists, the AI chatbot ChatGPT was used to assist with various scientific tasks, achieving an average score of 50% for initial tasks and 56% for more complex analyses, indicating moderate efficacy in supporting research activities.

Less experienced researchers found ChatGPT more helpful for certain tasks but also scored lower overall, suggesting that while AI can assist, it may not adequately address the knowledge gaps of novice scientists, potentially leading to reliance on inaccurate AI-generated information.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Potential of ChatGPT in facilitating research in radiation oncology? Guckenberger, M., Andratschke, N., Ahmadsei, M., et al.[2023]

A study involving 14 clinicians revealed that motivations for reporting serious oncology-associated adverse drug reactions included scientific curiosity and public health concerns, but feedback from pharmaceutical manufacturers was predominantly negative.

The research highlights the need for improved pharmacovigilance mechanisms, such as big data and registries, to enhance the reporting and documentation of adverse drug events, addressing barriers like complacency and indifference among clinicians.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Caveat Medicus: Clinician experiences in publishing reports of serious oncology-associated adverse drug reactions. Bennett, CL., Schooley, B., Taylor, MA., et al.[2020]

A study involving 63 patients (20 using a chatbot and 43 receiving usual care) found that the chatbot significantly reduced emergency department visits and unscheduled hospitalizations for patients undergoing chemotherapy for gynecologic cancers.

Patients using the chatbot had an adjusted incidence rate ratio of 0.27 for ED visits and 0.31 for unscheduled hospitalizations, indicating a strong potential for chatbots to improve patient management and reduce healthcare burdens during cancer treatment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Using a chatbot to reduce emergency department visits and unscheduled hospitalizations among patients with gynecologic malignancies during chemotherapy: A retrospective cohort study. Huang, MY., Weng, CS., Kuo, HL., et al.[2023]

In a study assessing the quality of responses from AI chatbots ChatGPT and Bing regarding cancer-related questions, ChatGPT scored an average of 3.9 while Bing scored 3.2, indicating that ChatGPT provided higher quality information overall (P < 0.001).

Despite the potential of AI chatbots in healthcare, the study revealed that 3% of ChatGPT's responses and 15% of Bing's responses had serious shortcomings, highlighting the need for ongoing improvements to ensure accurate and supportive information for cancer patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Physician Assessment of ChatGPT and Bing Answers to American Cancer Society's Questions to Ask About Your Cancer. Janopaul-Naylor, JR., Koo, A., Qian, DC., et al.[2023]

Over 90% of cancer patients discussed potential adverse events with their physicians before starting chemotherapy, but about 75% still reported that their quality of life was negatively affected by these events, indicating a gap in understanding and coping mechanisms.

Common adverse events like tiredness, nausea, and low white blood cell counts were frequently discussed, yet many patients still experienced them, suggesting that better educational tools and resources are needed to help patients manage these side effects effectively.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Patients' Perceptions of Physician-Patient Discussions and Adverse Events with Cancer Therapy. Hershman, D., Calhoun, E., Zapert, K., et al.[2021]

A multidisciplinary expert group identified key signals that a new AI system should emit to enhance the management of adverse drug events (ADEs) in patients taking oral antineoplastic agents, including educational reminders for patients and alerts for necessary tests and examinations.

In a 6-month observational study at a university hospital, a total of 3,641 ADEs were reported, highlighting the importance of patient education and clinical monitoring in improving patient safety and quality of life.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Analysis of adverse drug events as a way to improve cancer patient care. Vicente-Oliveros, N., Gramage-Caro, T., Corral de la Fuente, E., et al.[2022]

The Chemotherapy Patient Monitor (CPM) significantly enhances communication between oncologists and patients, with 95% of patients reporting improved consultations and 83% of oncologists finding it useful during their visits.

In a study involving 26 patients with advanced colorectal cancer, the CPM did not lengthen consultation times in 82% of cases, indicating it can be effectively integrated into existing practices without increasing appointment durations.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluation of the chemotherapy patient monitor: an interactive tool for facilitating communication between patients and oncologists during the cancer consultation. Anderson, H., Espinosa, E., Lofts, F., et al.[2019]

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