Andrew S. Epstein

Palliative care, or care that aims to reduce suffering, manage symptoms, and improve quality‐of‐life for those living with serious illness, is recognized as essential to high‐quality cancer care. However, challenges to equitable and timely access and integration persist. Scientific and clinical practice advances in recent years have made considerable progress in leveraging technology and improving workflows for more efficient and scalable palliative care delivery, while also expanding palliative and supportive care services for patients across cancer types. In parallel, treatment advances have emerged to better address complex cancer–related symptoms alongside growing interest in technology to aid in symptom monitoring. These advances offer promising solutions for a future in which palliative and supportive care strategies are more readily accessible, and avoidable suffering for patients with cancer is prevented and/or relieved with evidence‐based and clinically useful approaches.

PURPOSE: Patient portals increase communication, but little is known about response rates or patient characteristics associated with patient responses to portal-enabled questionnaires about health-related values (HRVs). METHODS: We tested feasibility of sending seven HRV questions by portal to medical oncology patients, with responses automatically returned to clinicians. HRV questionnaires were sent 1 week in advance of scheduled follow-up visits. The primary feasibility measure was patient response rate. Secondarily, we assessed patient characteristics associated with responses, and oncology clinicians' impressions. RESULTS: One thousand five hundred fifty-six HRV questionnaires were sent by portal to as many individual patients of five total clinics between July 2023 and July 2024. Seven hundred thirty questionnaires were returned with at least one of the questions answered (47% response rate). Response rate increased significantly (45%-50%, P = .05) after April 2024 when the portal notification was updated with a personalized message from oncologists and two study clinics were added to the initial 3. Nonresponders either returned a blank questionnaire (133, 9%) or did not return anything (693, 45%). Response rates were significantly different by patient race ( P = .05): Asian (51%) and White (48%) versus Black (44%) and Hispanic (41%). Female patient responses were longer than males. Response time was associated with patients' oncology team and shorter after April 2024. Participating clinicians' impressions were consistently favorable. CONCLUSION: Automating a patient portal-driven process to broadly scale elicitation of medical oncology outpatients' HRVs and sending aggregated reports of HRVs to oncology teams are feasible and valued by clinicians. Patient characteristics appear to be associated with responses. Ongoing research will investigate technology-supported strategies to optimize response rates across diverse populations (including minoritized patients who may suffer digital health inequity), and measure effects on person-centered communication and care outcomes.

Background: Artificial intelligence (AI) is being rapidly integrated into oncologic care, yet little is known about how patients perceive these applications. Understanding patient perceptions is critical to ensuring AI applications align with their needs and preferences. Objective: This study aimed to evaluate oncology patients’ attitudes and beliefs on the use of AI across clinical touchpoints in cancer care. Methods: We conducted a cross-sectional survey study with adult oncology patients from September to December 2024. The survey assessed patients’ comfort with AI use across 8 clinical touchpoints of cancer care (eg, screening, diagnosis, treatment) on a 5-point Likert scale (1=very uncomfortable to 5=very comfortable). Patients also rated their concerns about AI, including potential harms related to its use (eg, medical errors, privacy breaches), on a 3-point Likert scale (1=not concerned to 3=very concerned). Results: Of 383 patients approached, 330 (86.2% response rate) participated; 184 (55.9%) were male, 162 (49.4%) were aged 65 years or older, 35 (10.8%) were Black, 40 (12.1%) were Hispanic or Latino, and 233 (72.6%) were actively receiving cancer treatment. Patients were most comfortable with AI use in cancer screening (80.2%) and supportive care applications, including exercise (78.2%), diet (74.8%), and herbs/supplements (72.4%). Patients were least comfortable with AI use to assist with diagnosis (70.4%), symptom management (67.5%), treatment planning (64.8%), and prognosis (61.5%). Nonetheless, about half (49.7%) were at least somewhat concerned with the use of AI in cancer care, most commonly about the loss of human interaction and medical errors. Conclusions: Although the majority of oncology patients had a favorable view of AI in cancer care, nearly half had concerns about potential harms. Incorporating patient perspectives into AI development is essential for patient-centered and high-quality cancer care.

Objective To estimate the association between the billing (profit) margin and clinical benefit of cancer treatments and use by oncologists. Design Retrospective population based cohort study Setting Population based sample using fee-for-service Medicare claims data. Participants Medicare beneficiaries with an incident cancer diagnosis from 2015 to 2020; included all patients with cancer treatment indications for which the available treatment options varied in clinical benefit and billing margin. Main outcomes and measures The primary outcome was the cancer treatment each patient received among treatment options recommended by the National Comprehensive Cancer Network (NCCN). The characteristics of interest were provider billing margin (defined at the patient treatment level, using Medicare reimbursement rates corresponding to the patient’s diagnosis date) and a proxy measure of clinical benefit (rank order of treatments based on Evidence Blocks scores developed by the NCCN, corresponding to the patient’s diagnosis date). The association between treatment received, billing margin, and clinical benefit was modeled using a conditional logit model with inverse probability-of-treatment weights applied at the patient treatment level to control for patient and provider characteristics. Results Twelve cancer indications were examined comprising 19 397 individual patients. Provider billing margin ranged from $0 to $12 692 (£9440; €10 800) for each course of treatment. No association was found between a $100 increase in provider billing margin and the likelihood of treatment use (odds ratio 0.97, 95% confidence interval 0.91 to 1.03). Higher clinical benefit was associated with greater treatment use (1.62, 1.15 to 2.29). Conclusions In this observational study of Medicare beneficiaries, selection of cancer treatments was associated with the treatment’s clinical benefit but not billing margin. Therefore, it is unlikely that policy and price changes that affect the billing margin of cancer treatments would shift patterns of use.

Introduction: Electronic patient portals are increasingly used to improve care and patient–clinician communication. Portal‐elicited health‐related values (HRVs) were evaluated as to whether they contain themes similar to those arising from nurse‐led in‐person discussions. Methods: HRV questionnaires, consisting of seven questions, were sent by portal to patients of five solid tumor clinics from July 2023 to August 2024. Applying a theoretical framework generated from prior analysis of in‐person nurse‐led discussions with patients about their HRVs, questionnaires were coded via thematic content analysis. Results: A total of 1556 HRV questionnaires were sent to individual patients. Of 852 unique patients who returned questionnaires with response to at least one question, a random subset of 200 patients’ responses (167 gastrointestinal cancers, 33 genitourinary cancers) were analyzed by an interdisciplinary team. Analysis identified five themes consistent with those previously identified from in‐person discussions: cancer as threat/disruption; expression of personhood and desire to retain a sense of self; communication with loved ones and the medical team as a tool for maintaining individual agency; connection to others as core to social identity and a source of individual strength; and sources of meaning and fulfillment. Uniquely identified by our analysis of portal responses were elements of financial toxicity and spiritual and existential well‐being. Conclusion: Elicitation of patient values through the electronic portal provides valuable insights into the HRV of patients with solid tumors. The electronic portal captures values comparable to those elicited in in‐person discussions, supporting efforts to scale such initiatives while preserving the content of patients’ reports as a basis for discussion of their HRVs with clinicians.

PURPOSE: The Medicare part D Low-Income Subsidy (LIS) improves access to oral cancer drugs, but provides no assistance for clinician-administered/part B drugs. This analysis assessed the association between LIS participation and receipt of optimal cancer treatment. METHODS: We investigated initial systemic therapy using SEER-Medicare data (2015-2017) and National Comprehensive Cancer Network (NCCN) Evidence Blocks (EB) as the standard for treatment recommendations. We included cancer clinical scenarios wherein (1) ≥one treatment was optimal (higher efficacy and safety scores) versus other treatments; (2) identifiable in SEER-Medicare (eg, not defined by clinical data unavailable in registry data or claims); and (3) both EB and ASCO Value Framework agreed regarding optimal treatment. We fit logistic regression models to assess the association between receipt of systemic therapy ( v no therapy) and patient and provider characteristics. Contingent on receipt of treatment, we modeled the likelihood of receiving a treatment ranked (by EB scores) within the highest or lowest quartile for that cancer type. RESULTS: Nine thousand two hundred and ninety patients were included across 11 clinical scenarios. Fifty-seven percent (5,336) of patients received any systemic therapy and 43% (3,954) received no systemic therapy. Compared with non-LIS participants, LIS participants were less likely to receive any systemic therapy versus no systemic therapy (odds ratio, 0.64 [95% CI, 0.57 to 0.72]). Contingent on receiving systemic therapy, LIS participants received treatment ranked within the worst quartile 24.8% of the time, compared with 21.9% of non-LIS patients (adjusted prevalence difference, 4.3% [95% CI, 0.5 to 8.2]). CONCLUSION: LIS participants were less likely to receive systemic therapy at all and were more likely to receive treatments that receive low NCCN EB scores.

Through careful word choice and never‐ending presence, oncology teams can provide ongoing, and even amplified support and care for hospice‐eligible patients and caregivers. Voicing nonabandonment, eliciting patient priorities and concerns, and making clear the myriad benefits of hospice care resources can all help oncology clinicians deliver high quality end‐of‐life cancer care.

ASCO Guidelines provide recommendations with comprehensive review and analyses of the relevant literature for each recommendation, following the guideline development process as outlined in the ASCO Guidelines Methodology Manual . ASCO Guidelines follow the ASCO Conflict of Interest Policy for Clinical Practice Guidelines . Clinical Practice Guidelines and other guidance (“Guidance”) provided by ASCO is not a comprehensive or definitive guide to treatment options. It is intended for voluntary use by providers and should be used in conjunction with independent professional judgment. Guidance may not be applicable to all patients, interventions, diseases, or stages of diseases. Guidance is based on review and analysis of relevant literature, and is not intended as a statement of the standard of care. ASCO does not endorse third-party drugs, devices, services, or therapies and assumes no responsibility for any harm arising from or related to the use of this information. See complete disclaimer in Appendix 1 and 2 (online only) for more. PURPOSE: To provide evidence-based guidance to oncology clinicians, patients, nonprofessional caregivers, and palliative care clinicians to update the 2016 ASCO guideline on the integration of palliative care into standard oncology for all patients diagnosed with cancer. METHODS: ASCO convened an Expert Panel of medical, radiation, hematology-oncology, oncology nursing, palliative care, social work, ethics, advocacy, and psycho-oncology experts. The Panel conducted a literature search, including systematic reviews, meta-analyses, and randomized controlled trials published from 2015-2023. Outcomes of interest included quality of life (QOL), patient satisfaction, physical and psychological symptoms, survival, and caregiver burden. Expert Panel members used available evidence and informal consensus to develop evidence-based guideline recommendations. RESULTS: The literature search identified 52 relevant studies to inform the evidence base for this guideline. RECOMMENDATIONS: Evidence-based recommendations address the integration of palliative care in oncology. Oncology clinicians should refer patients with advanced solid tumors and hematologic malignancies to specialized interdisciplinary palliative care teams that provide outpatient and inpatient care beginning early in the course of the disease, alongside active treatment of their cancer. For patients with cancer with unaddressed physical, psychosocial, or spiritual distress, cancer care programs should provide dedicated specialist palliative care services complementing existing or emerging supportive care interventions. Oncology clinicians from across the interdisciplinary cancer care team may refer the caregivers (eg, family, chosen family, and friends) of patients with cancer to palliative care teams for additional support. The Expert Panel suggests early palliative care involvement, especially for patients with uncontrolled symptoms and QOL concerns. Clinicians caring for patients with solid tumors on phase I cancer trials may also refer them to specialist palliative care. Additional information is available at www.asco.org/supportive-care-guidelines .