JMIR Cancer

Bispecific antibodies are novel immunotherapies approved for the treatment of patients with relapsed or refractory multiple myeloma (MM). While these therapies induce deep and durable responses, they are associated with adverse events, such as cytokine release syndrome and immune effector cell–associated neurotoxicity syndrome, that require specific protocols for monitoring, prevention, and treatment. Due to the potential risk of cytokine release syndrome and immune effector cell–associated neurotoxicity syndrome, current US labeling recommends inpatient administration during step-up dosing of bispecific antibodies, which typically occurs in academic centers and can often restrict the number of patients that can be treated. The administration of bispecific antibodies in the outpatient and community setting can enhance the patient experience and reduce resource use, which is a barrier to the widespread uptake of these treatments. With bispecific antibodies being evaluated in earlier lines of therapy for MM, the broader use of these agents will underscore the need for more accessible and less resource-intensive options that ensure safe outpatient administration. In this Viewpoint, we aim to provide practical recommendations built from our own real-world perspectives and case examples for institutions seeking to implement remote patient monitoring (RPM) strategies to support the outpatient dosing of bispecific antibodies in patients with MM. We discuss how the use of RPM has the potential to improve adverse event detection and management, improve patient outcomes, and decrease resource use and costs. While specific approaches will vary based on the needs of each treatment center, our experiences suggest that RPM implementation can be safe and feasible for both academic and community practices.

Digital health platforms have become increasingly important sources of health information for cancer survivors. Cancer survivors frequently rely on digital resources to obtain information related to diagnosis, treatment, survivorship, and follow-up care. In this study, cancer information burden is defined as the perceived challenges associated with seeking, understanding, and evaluating cancer-related information, including the effort required to obtain information, frustration during information seeking, difficulty understanding information, and concern regarding information quality. As the online health information environment becomes increasingly complex, some survivors may experience difficulty locating, evaluating, and understanding cancer-related information. However, limited nationally representative research has examined how cancer information burden differs across demographic and socioeconomic groups.

Uninterrupted delivery of radiation therapy is critical to cancer treatment quality. Unplanned radiation treatment interruptions compromise tumor control and survival. Although previous studies have explored clinical and sociodemographic factors influencing treatment adherence, the role of psychosocial distress and related symptoms remains unclear.

Identification of metastasis status in non–small cell lung cancer (NSCLC) is a critical part of understanding disease prognosis, treatment courses, trial eligibility, and population-level cancer surveillance. However, metastasis status is inconsistently recorded in structured cancer registry fields, since manual abstraction of clinical notes is often an error-prone process. This challenge highlights an opportunity for leveraging large language models (LLMs) to conduct high-scale metastasis extraction from real-world clinical documentation.

Cervical nodal metastasis remains one of the strongest determinants of treatment planning and prognosis in oral squamous cell carcinoma. Histopathology remains the reference standard, but it does not provide immediate information at the point of surgical specimen assessment. Elastic scattering spectroscopy (ESS) offers rapid, label-free optical interrogation of tissue microstructure, and may support ex vivo nodal assessment.

Although effective, current chimeric antigen receptor T-cell (CAR-T) production methods—centralized, manual, and complex—are cost-intensive, time-consuming, and prone to variability. AIDPATH (AI-Powered Decentralized Production for Advanced Therapies in the Hospital) proposes a decentralized, automated alternative that integrates patient-specific data; optimizes resource use; and potentially improves cell viability, manufacturing efficiency, and patient outcomes.

Thyroid cancer is often labeled a “good cancer” due to high survival rates. However, many patients diagnosed with differentiated thyroid cancer (DTC) treated with radioactive iodine (RAI) experience short- and long-term symptoms as a result of treatment. These include salivary dysfunction, dry mouth, dry eyes, and nausea. Despite these challenges, patients report limited knowledge and unmet informational needs regarding RAI symptoms and symptom management. Evidence-based, patient-centered education to support symptom management during DTC survivorship is needed. Our team developed Radioactive Iodine Support (RAI Support), a prototype of a 4-week web-based intervention for RAI symptom management among survivors of DTC.

Preoperative nodal assessment in colorectal cancer (CRC) remains imperfect, and uncertainty regarding pathological lymph node metastasis (LNM) may persist despite conventional imaging. Machine learning using routinely available preoperative information may provide complementary patient-level risk estimates without requiring radiomic feature extraction or molecular testing.

Progression-free survival (PFS) is a critical end point in oncology, yet real-world applications of individualized, explainable machine learning (ML) predictions remain limited.

Promotional activities, such as social marketing approaches, are important for raising cancer awareness and increasing breast cancer screening participation. Such interventions are designed to facilitate change and maintain positive health behaviors at both the community and society level. With the growing use of these promotional activities in public health, it is pertinent to map available studies to inform future evaluations and the development of effective interventions.

Informal caregivers play a fundamental role in the diagnosis, treatment, and care received by their family members. Caring for someone with dementia is particularly burdensome and can have negative effects on caregivers’ health. Despite caregivers being widely recognized as vulnerable, the psychosocial needs of caregivers who are managing cancer themselves remain unknown.

Patients with newly diagnosed gynecologic cancers often seek information online, but the quality of available resources may be inconsistent. Although GPT-4 may offer an alternative to traditional internet search engines, its performance remains largely under-studied in gynecologic oncology.