Gupta, Arjun

230 Background: The burden of symptoms and financial toxicity are well-documented adverse effects of cancer treatments. Recently, logistic toxicity has emerged, referring to the detrimental impact of logistical demands associated with cancer treatment on patient well-being. For non- English speaking patients, language barriers can affect their treatment experience, increasing logistic burdens. Methods: Between September 2024 and May 2025, semi-structured qualitative interviews were conducted with 21 low English proficiency (LEP)/non-English speaking adults with cancer. The interviews explored logistic challenges faced due to LEP and its impact on patients' cancer care experience. Transcripts were analyzed using an inductive thematic analysis approach. Results: Of the 39 identified eligible individuals, 26 provided consent, and 21 (81%) completed the interview. The most common primary language of the participants was Spanish (9, 43%), followed by Somali (3, 14%), Arabic and Korean (2, 9%), and Amharic, Mandarin, Hmong, Russian, and Vietnamese (1, 5%). Seven major themes emerged regarding the logistic burdens of cancer care: (1) communication challenges, (2) navigating healthcare systems, (3) emotional distress from diagnosis and communication barriers, (4) financial toxicity, (5) transportation challenges, (6) adverse treatment effects, and (7) concerns about the political climate and its impact on resources. Conclusions: The increase in non-English languages in the U.S. highlights the need to understand the unique challenges faced by these patients. This study identified logistic toxicity themes consistent with previous research, while also revealing unique challenges. Further research is necessary to explore strategies to mitigate logistic burdens among those with LEP. Theme Illustrative Quotes Communication challenges “Communication with the psychologist was challenging … I couldn’t express myself effectively and it left me unsatisfied with the interaction.” Navigating healthcare systems “dealing with the insurance, it has been difficult … I have to depend on another person to help me” Emotional distress from diagnosis and communication barriers “In addition to my sickness, the lack of communication and understanding… makes me very sad.” Financial toxicity “...there's no income. There is nothing to feed our children.” Transportation challenges “I have to leave home 2 or 3 hours in advance because people will help me, not within my time, but within their own time.” Adverse treatment effects “I noticed weird feelings in my limbs. I'm not able to write down or hold anything. It makes everything difficult.” Concerns about current political climate and its impact on existing resources “… that they don't want Spanish spoken in the United States. They're not going to provide help for people like me at the hospitals…”

Abstract Rationale: Effective communication is crucial in healthcare, especially in acute care settings, so that patients/family members can understand treatment options, and share preferences and goals of care. For those with a non-English language preference (NELP), or who have difficulty communicating in English, professional interpreters are recognized as the gold standard in supporting bidirectional communication. However, interpreters are not always readily available for all languages or clinical settings prompting the exploration of other options for translation and interpretation. The recent developments in artificial intelligence (AI), specifically machine translation have enabled more accurate and emotional machine interpretation and translation. Methods: We conducted a systematic review to explore the usability and usefulness of AI-assisted interpretation and translation tools for improving communication between patients and clinicians including verbal and written communication. A comprehensive search of several databases including Ovid MEDLINE(R), Ovid Embase, APA PsycInfo, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, and Scopus via Elsevier was performed, resulting in 2629 studies. We included studies evaluating tools for direct patient-clinician communication. For verbal communication, we included articles assessing speech interpretation, and for written communication, we focused on discharge instruction translation. Results: A total of 18 studies were included in the final analysis. Among these, 5 assessed the use of speech interpretation and 13 examined text translation of discharge materials. 14 (78%) studies found these novel AI tools beneficial for patient care, whereas 11 (62%) studies highlighted the risks, indicating that these tools can lead to serious mistakes with potential clinical harm. 5 (28%) studies reported participant satisfaction with the use of these tools in their care. Translation and interpretation accuracy varied notably across languages, with lower accuracy scores observed in languages with limited digital resources, such as Haitian Creole and Vietnamese. Conclusion: AI-assisted interpretation and translation in healthcare has several advantages including broader language accessibility than usual resources and potential cost savings for institutions and demonstrates evidence of patient satisfaction. However, these novel tools operate using multiple phases and each stage is prone to errors which may negatively impact patient care and outcomes.. AI-based interpretation and translation show promising potential, however, it is not yet ready for widespread clinical use, so professional language interpreters should be used whenever possible. Future studies should focus on evaluating accuracy as well as how best to integrate these technologies in real-time clinical settings without compromising patient safety and quality of care.

Aromatase inhibitor–induced musculoskeletal symptoms (AIMSS) were first recognized as a distinct entity in 2001, 5 years after the approval of the first aromatase inhibitor, anastrozole. Musculoskeletal symptoms can severely affect patients’ quality of life and also lead to premature discontinuation of aromatase inhibitor therapy. Several interventions for managing AIMSS have been investigated in the last decade, with some demonstrating promise. This article provides an evidence-based summary to guide practicing oncologists in regard to the epidemiology, prevention, and treatment of AIMSS.

PURPOSE: Routine use of extended-fraction (> 10 fractions) radiation therapy (RT) for palliation of bone metastases is recognized as a low-value intervention by the American Society for Radiation Oncology. We examined contemporary practice patterns of, and physician characteristics associated with extended-fraction RT use. MATERIALS AND METHODS: We conducted a retrospective cohort study using Medicare fee-for-service data. We included patients who underwent 2- or 3-dimensional external-beam RT for bone metastases between January 1, 2016, and December 31, 2018. Physicians treating > 10 patients over the study period were analyzed for their individual practice. Hierarchic logistic regression modeling was used to identify patient- and physician-level factors associated with extended-fraction RT use. RESULTS: A total of 12,221 patients (median age, 75.6 years; 40.9% women, 87.6% white) were included. The rate of extended-fraction RT was 23.4%. A total of 1,432 physicians treated any patient. Among the 382 physicians treating > 10 patients, 127 (33.2%) used extended-fraction RT > 30% (consensus threshold). Physician factors associated with decreased odds of extended-fraction RT were years since medical school graduation (≤ 10 years and 11-20 years v ≥ 31 years: adjusted odds ratio [aOR], 0.32 [95% CI, 0.20 to 0.51] and 0.64 [95% CI, 0.44 to 0.93]) and practicing in the Northeast or Midwest versus the South (aOR, 0.36 [95% CI, 0.22 to 0.58] and 0.48 [95% CI, 0.31 to 0.74]). Physicians treating > 20 patients ( v 11-14 patients) over the study period had increased odds of delivering extended-fraction RT (aOR, 1.53 [95% CI, 1.10 to 2.12]). CONCLUSION: In this study, almost one fourth of patients received extended-fraction RT, and one third of physicians had an extended-fraction RT use rate of > 30%. Personalized feedback of performance data, clinical pathways and peer review, and updated reimbursement models are potential mechanisms to address this low-value care.

Introduction: Neutropenic diets are commonly prescribed to cancer patients with neutropenia with the intention of reducing rates of infection. These diets are restrictive and are associated with lower patient satisfaction and possibly malnutrition. Further, it is unclear if these restrictive diets are effective in reducing infection. We performed a meta-analysis on the rates of infection reported in trials comparing the neutropenic diet to unrestricted diets in cancer patients with neutropenia. Methods and Materials: A comprehensive database search for all published randomized controlled trials comparing infection rates in cancer patients receiving a neutropenic diet versus an unrestricted diet was performed for all publications in English language from database’s inception until September 12, 2017. The search strategy, study selection, and subsequent analysis adhered to PRISMA guidelines. Random effects modeling was used to obtain pooled relative risks. The primary outcome measure was the rate of infection. Results: Five randomized controlled trials with a total of 388 patients were included in the final analysis. Patients mostly had acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), or sarcoma. Infection was noted in 53.7% patients in the neutropenic diet group, as compared with 50% in the unrestricted diet group. No significant difference in infection rate was observed between the neutropenic diet versus unrestricted diet groups, pooled risk ratio (RR) 1.13 (95% CI, 0.98-1.30; P=0.10). Conclusions: This meta-analysis of randomized controlled trials suggests that the use of neutropenic diet was not associated with decreased risk of infection in neutropenic cancer patients. The continued use of neutropenic diets should be questioned.