Public comfort with the use of ChatGPT and expectations for healthcare.

OBJECTIVES: To examine whether comfort with the use of ChatGPT in society differs from comfort with other uses of AI in society and to identify whether this comfort and other patient characteristics such as trust, privacy concerns, respect, and tech-savviness are associated with expected benefit of the use of ChatGPT for improving health. MATERIALS AND METHODS: We analyzed an original survey of U.S. adults using the NORC AmeriSpeak Panel (n = 1787). We conducted paired t-tests to assess differences in comfort with AI applications. We conducted weighted univariable regression and 2 weighted logistic regression models to identify predictors of expected benefit with and without accounting for trust in the health system. RESULTS: Comfort with the use of ChatGPT in society is relatively low and different from other, common uses of AI. Comfort was highly associated with expecting benefit. Other statistically significant factors in multivariable analysis (not including system trust) included feeling respected and low privacy concerns. Females, younger adults, and those with higher levels of education were less likely to expect benefits in models with and without system trust, which was positively associated with expecting benefits (P = 1.6 × 10-11). Tech-savviness was not associated with the outcome. DISCUSSION: Understanding the impact of large language models (LLMs) from the patient perspective is critical to ensuring that expectations align with performance as a form of calibrated trust that acknowledges the dynamic nature of trust. CONCLUSION: Including measures of system trust in evaluating LLMs could capture a range of issues critical for ensuring patient acceptance of this technological innovation.

Equity and AI governance at academic medical centers.

OBJECTIVES: To understand whether and how equity is considered in artificial intelligence/machine learning governance processes at academic medical centers. STUDY DESIGN: Qualitative analysis of interview data. METHODS: We created a database of academic medical centers from the full list of Association of American Medical Colleges hospital and health system members in 2022. Stratifying by census region and restricting to nonfederal and nonspecialty centers, we recruited chief medical informatics officers and similarly positioned individuals from academic medical centers across the country. We created and piloted a semistructured interview guide focused on (1) how academic medical centers govern artificial intelligence and prediction and (2) to what extent equity is considered in these processes. A total of 17 individuals representing 13 institutions across 4 census regions of the US were interviewed. RESULTS: A minority of participants reported considering inequity, racism, or bias in governance. Most participants conceptualized these issues as characteristics of a tool, using frameworks such as algorithmic bias or fairness. Fewer participants conceptualized equity beyond the technology itself and asked broader questions about its implications for patients. Disparities in health information technology resources across health systems were repeatedly identified as a threat to health equity. CONCLUSIONS: We found a lack of consistent equity consideration among academic medical centers as they develop their governance processes for predictive technologies despite considerable national attention to the ways these technologies can cause or reproduce inequities. Health systems and policy makers will need to specifically prioritize equity literacy among health system leadership, design oversight policies, and promote critical engagement with these tools and their implications to prevent the further entrenchment of inequities in digital health care.

Advancing maturity modeling for precision oncology.

Introduction: This study aimed to map the maturity of precision oncology as an example of a Learning Health System by understanding the current state of practice, tools and informatics, and barriers and facilitators of maturity. Methods: We conducted semi-structured interviews with 34 professionals (e.g., clinicians, pathologists, and program managers) involved in Molecular Tumor Boards (MTBs). Interviewees were recruited through outreach at 3 large academic medical centers (AMCs) (n = 16) and a Next Generation Sequencing (NGS) company (n = 18). Interviewees were asked about their roles and relationships with MTBs, processes and tools used, and institutional practices. The interviews were then coded and analyzed to understand the variation in maturity across the evolving field of precision oncology. Results: The findings provide insight into the present level of maturity in the precision oncology field, including the state of tooling and informatics within the same domain, the effects of the critical environment on overall maturity, and prospective approaches to enhance maturity of the field. We found that maturity is relatively low, but continuing to evolve, across these dimensions due to the resource-intensive and complex sociotechnical infrastructure required to advance maturity of the field and to fully close learning loops. Conclusion: Our findings advance the field by defining and contextualizing the current state of maturity and potential future strategies for advancing precision oncology, providing a framework to examine how learning health systems mature, and furthering the development of maturity models with new evidence.

Use of the socio-ecological model to explore trusted sources of COVID-19 information in Black and Latinx communities in Michigan.

BACKGROUND: Identifying trusted sources of health information and exploring what makes these sources trustworthy is an important aspect of public health. This exploration requires embracing the cultural differences in minoritized communities, which are often treated as homogeneous. This qualitative study identifies and analyze the sources of trusted COVID-19 information among Black and Latinx communities in Michigan and assesses the rationale underlying this trust. METHODS: Interviews were conducted with 24 Black and 16 Latinx participants (n = 40) in four Michigan counties significantly impacted by COVID-19. The socio-ecological model was applied as an analytical framework for understanding the entities considered trusted sources of information. Within each level of the model, the dimensions of trustworthiness most salient for participants were identified. RESULTS: We found that sources of information came from all levels of the model, including interpersonal (COVID-19 survivors, church representatives, friends, relatives), organizational (employers, healthcare providers, traditional news reports), social media (hybrid source), community (members and groups), and public policy (county health department, federal and state government). Furthermore, participants determined whether they could trust information about COVID-19 by cross-referencing multiple resources. We identified competence, confidence, communication, and system trust as the dimensions of trustworthiness most often reported by participants. CONCLUSIONS: Our research suggests public health communications should engage in cross-referencing practices, providing information from sources at all levels of interaction, cultural competency, and awareness of historical/structural inequities. These efforts would be further strengthened by attending to needs for both factual information as well as care and personal connection.

Characterization of outcomes in patients with advanced genitourinary malignancies treated with immune checkpoint inhibitors.

PURPOSE: Several immune checkpoint inhibitors (ICIs) are FDA approved for treatment of genitourinary (GU) malignancies. We aim to determine demographic and clinicopathologic characteristics that significantly affect clinical outcomes in patients with advanced stage GU malignancies treated with ICIs. MATERIALS AND METHODS: We performed a single-center, consecutive, retrospective cohort analysis on patients with metastatic or unresectable GU malignancies who were treated with ICIs at the University of Michigan. Immune-related adverse events (irAEs), putative immune-mediated allergies, and overall response rates (ORR) were assessed. Comorbidity index scores were calculated. Survival analysis was performed to evaluate progression-free survival (PFS) and overall survival (OS), stratifying and controlling for a variety of clinicopathologic baseline factors including site of metastases. RESULTS: A total of 160 patients were identified with advanced renal cell carcinoma (RCC) or urothelial carcinoma. Median PFS and OS were 5.0 and 23.6 months for RCC, and 2.8 and 9.6 months for urothelial carcinoma, respectively. Patients who experienced increased frequency and higher grade irAEs had better ICI treatment response (P < 0.0001). Presence of liver metastases was associated with poor response to ICI therapy (P = 0.001). Multivariable modeling demonstrates that patients with urothelial carcinoma and liver metastases had statistically worse PFS and OS compared to patients with RCC or other sites of metastases, respectively. CONCLUSION: Greater frequency and higher grades of irAEs are associated with better treatment response in patients with RCC and urothelial malignancy receiving ICI therapy. The presence of liver metastases denotes a negative predictive marker for immunotherapy efficacy. SUMMARY: Immune checkpoint inhibitors (ICI) are increasingly used to treat genitourinary (GU) malignancies. However, clinical data regarding patients with advanced-stage GU malignancies treated with ICI is lacking. Thus, we performed a single-center, retrospective cohort study on patients with metastatic and unresectable renal cell carcinoma (RCC) and urothelial carcinoma who were treated with ICIs at the University of Michigan to provide demographic and clinicopathologic data regarding this population. We specifically focused on immune-related adverse events (irAEs), immune-mediated allergies, and the associated overall response rates (ORR). To better assess performance status, we calculated comorbidity scores for all patients. Finally, survival analyses for progression-free survival (PFS) and overall survival (OS) were performed using Kaplan-Meier analysis and Cox proportional hazards modeling, stratifying and controlling for clinicopathologic baseline factors, including sites of metastases, in our multivariable analysis. A total of 160 patients were identified with advanced RCC or urothelial carcinoma. We found decreased PFS (2.8 vs. 5.0 months) and decreased OS (9.8 vs. 23.6 months) for urothelial carcinoma compared to RCC patients. We noted that patients who experienced increased frequency and higher grades of irAEs had better treatment ORR with ICI therapy (P ≤ 0.0001). The presence of liver metastases was associated with worse ORR (P = 0.001), PFS (P = 0.0014), and OS (P = 0.0028) compared to other sites of metastases including lymph node, lung, and CNS/bone. The poor PFS and OS associated with urothelial carcinoma and liver metastases were preserved in our multivariable modeling after controlling for pertinent clinical factors. We conclude that greater frequency and higher grades of irAEs are associated with better treatment response in GU malignancy patients receiving ICI, a finding that is consistent with published studies in other cancers. The presence of liver metastases represents a significantly poor predictive marker in GU malignancy treated with ICI. Our findings contribute to the growing body of literature that seeks to understand the clinicopathologic variables and outcomes associated with ICI therapy.

Stanniocalcin 1 is a phagocytosis checkpoint driving tumor immune resistance.

Immunotherapy induces durable clinical responses in a fraction of patients with cancer. However, therapeutic resistance poses a major challenge to current immunotherapies. Here, we identify that expression of tumor stanniocalcin 1 (STC1) correlates with immunotherapy efficacy and is negatively associated with patient survival across diverse cancer types. Gain- and loss-of-function experiments demonstrate that tumor STC1 supports tumor progression and enables tumor resistance to checkpoint blockade in murine tumor models. Mechanistically, tumor STC1 interacts with calreticulin (CRT), an "eat-me" signal, and minimizes CRT membrane exposure, thereby abrogating membrane CRT-directed phagocytosis by antigen-presenting cells (APCs), including macrophages and dendritic cells. Consequently, this impairs APC capacity of antigen presentation and T cell activation. Thus, tumor STC1 inhibits APC phagocytosis and contributes to tumor immune evasion and immunotherapy resistance. We suggest that STC1 is a previously unappreciated phagocytosis checkpoint and targeting STC1 and its interaction with CRT may sensitize to cancer immunotherapy.

Immunotherapy in metastatic sarcomatoid renal cell carcinoma: A single institution experience.

INTRODUCTION: Immune checkpoint inhibitors (CPIs) were recently approved in advanced clear cell renal cell carcinoma (RCC) and could be a promising option for metastatic RCC with sarcomatoid differentiation (sRCC) which otherwise carry a poor prognosis. We sought to compare outcomes between patients who received immunotherapy (IO) including CPIs or high dose interleukin-2 (HD IL2) for metastatic sRCC versus those who did not. PATIENTS AND METHODS: We performed a single-center retrospective data analysis of 44 consecutive sRCC patients with any percentage of sarcomatoid differentiation from our institutional RCC database of whom 34 received IO and 10 patients did not. RESULTS: Baseline variables between the two groups were not significantly different except for a greater percentage of patients with ≥40% sarcomatoid differentiation in the non-IO cohort. At a median follow-up of 27.6 months, patients treated with IO had a median overall survival of 57.6 months compared to 6.6 months in patients not treated with IO (p = 0.0002). Overall response rates (ORR) between the IO and non-IO group were 35.3% and 0% respectively (p = 0.06). When IO was given in the 1st line setting, the ORR was 25.0%, as compared to 44.4% in the 2nd line setting and beyond though limitations of small sample sizes apply. Immune-related adverse events (IRAE) occurred in 38.2% of patients in the IO group, with grade 3 events (mostly gastrointestinal) in 20.6% with no grade 4 or 5 events. IRAEs led to interruption or discontinuation of immunotherapy in 26.5%. CONCLUSION: Our results support IO as an effective therapeutic option for patients with metastatic sarcomatoid RCC. Further study of various IO regimens, including those affecting the interleukin-2 signaling pathway, and their efficacy in neoadjuvant and adjuvant settings are warranted in sRCC.