UCSF Research Articles

Pain, anxiety and fear related to oral biopsies: a pilot study

The objective of this prospective study was to measure the level of pain and anxiety before, during, and after an oral biopsy, and fear memory 7 days following the procedure. This was a single-center, prospective, survey-based observational pilot study of patients seen from April 2022 to June 2023 at the Sol Silverman Oral Medicine Clinic, at the University of California San Francisco (UCSF). We assessed the level of pain and anxiety before, during, and after oral biopsies and a fear memory interview on the 7th day post oral biopsy. Sixty patients participated in the study (median age: 56.5 years (range: 20-95 years); 65% females). Most patients had a punch oral biopsy (84%). The median score for pain was 2 (range 0-9) on day 1 post biopsy and 0 (range 0-4) on day 7 post biopsy (p < .0001); the median score for anxiety was 0 (range 0-3) on day 1 post biopsy and 0 (range 0-2) on day 7 post biopsy. During the phone interview on day 7, patients reported a median score of 1 for pain (range: 0-8), unpleasantness (range 0-9) and anxiety/fear (range 0-10). Oral biopsy is a well-tolerated procedure with minimal pain and anxiety/fear.

Abstract 4827: Financial toxicity among cancer survivors during the COVID-19 pandemic

Abstract Background: Financial toxicity (FT), the financial impact of cancer and its treatments on patients’ employment, income, and health insurance, can have significant short- and long-term consequences for cancer survivors. With significant increases in cancer survivorship and the changing demographics of the United States, a need exists to identify those most susceptible to FT. This study evaluated FT prevalence during the COVID-19 pandemic and identified factors associated with greater FT risk. Methods: Data were collected from 1,147 cancer survivors recruited from previous National Cancer Institute-funded studies, from electronic health record searches for patients with cancer diagnoses at University of California, San Francisco (UCSF) and Mount Sinai Medical Center and Columbia University Medical Center in New York City, and the Dr. Susan Love Foundation for Breast Cancer Research. Adults, diagnosed with cancer and proficient in English, completed an online survey via the Research Electronic Data Capture (REDCap) system between May 27, 2020 and February 21, 2021. FT was assessed for the past 14 days using the validated 11-item COmprehensive Score for financial Toxicity (COST) measure. Patients were categorized by score: no FT (COST scores &amp;gt;25), mild FT (14-25), and moderate/severe FT (0-13). Using Pearson’s chi-square test of independence, and univariate ordinal logistic regression, the study evaluated sociodemographic and clinical characteristics associated with FT, including age, race and ethnicity, gender, household income, education, marital status, health insurance status, and cancer site. Results: The COST measure had excellent reliability for the sample (Cronbach’s alpha = 0.911). Overall, 9% of respondents reported moderate/severe FT (MSFT), 16% mild. Race/ethnicity, education level, annual household income, cancer site, and years from diagnosis (p-values ≤ 0.035) were associated with FT. Current health insurance coverage was not associated with FT (p=0.456). 18% Black, 13% Asian American, 17% mixed, and 20% other races/ethnicities reported MSFT, while 8% non-Hispanic White and 5% Hispanic respondents reported the same. 31% of survivors with annual household income &amp;lt;$40,000 reported MSFT vs. 7% with ≥$40,000 income. 14% of survivors with less than a college degree reported MSFT vs. 8% amongst those with a college degree or higher. For men, the odds of having FT (mild or MSFT) were 0.60 (95% CI 0.40, 0.90) times that of women. Survivors &amp;lt;50 years old at diagnosis had 7.53 (95% CI 4.09, 13.83) times the odds of FT (mild or MSFT) vs. those aged ≥75 years. Conclusions: These preliminary analyses from this cross-sectional study characterizes the prevalence and determinants of FT experienced by cancer survivors during the COVID-19 pandemic. The next steps will include multivariable analysis and comparison with pre-pandemic data, to identify those at greatest risk and inform interventions. Citation Format: Tanvi Srivastava, Salma Shariff-Marco, Samuel L. Washington, Christine Miaskowski, June M. Chan. Financial toxicity among cancer survivors during the COVID-19 pandemic [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4827.

Liver transplantation for hepatocellular carcinoma in India: Are we ready for 2040?

Liver transplantation (LT) for hepatocellular carcinoma (HCC) has been widely researched and is well established worldwide. The cornerstone of this treatment lies in the various criteria formulated by expert consensus and experience. The variations among the criteria are staggering, and the short- and long-term out comes are controversial. To study the differences in the current practices of LT for HCC at different centers in India and discuss their clinical implications in the future. We conducted a survey of major centers in India that performed LT in December 2022. A total of 23 responses were received. The centers were classified as high- and low-volume, and the current trend of care for patients und ergoing LT for HCC was noted. Of the 23 centers, 35% were high volume center (> 500 Liver transplants) while 52% were high-volume centers that performed more than 50 transplants/year. Approximately 39% of centers had performed > 50 LT for HCC while the percent distribution for HCC in LT patients was 5%-15% in approximately 73% of the patients. Barring a few, most centers were divided equally between University of California, San Francisco (UCSF) and center-specific criteria when choosing patients with HCC for LT, and most (65%) did not have separate transplant criteria for deceased donor LT and living donor LT (LDLT). Most centers (56%) preferred surgical resection over LT for a Child A cirrhosis patient with a resectable 4 cm HCC lesion. Positron-emission tomography-computed tomography (CT) was the modality of choice for metastatic workup in the majority of centers (74%). Downstaging was the preferred option for over 90% of the centers and included transarterial chemoembolization, transarterial radioembolization, stereotactic body radiotherapy and atezolizumab/bevacizumab with varied indications. The alpha-fetoprotein (AFP) cut-off was used by 74% of centers to decide on transplantation as well as to downstage tumors, even if they met the criteria. The criteria for successful downstaging varied, but most centers conformed to the UCSF or their center-specific criteria for LT, along with the AFP cutoff values. The wait time for LT from down staging was at least 4-6 wk in all centers. Contrast-enhanced CT was the preferred imaging modality for post-LT surveillance in 52% of the centers. Approximately 65% of the centers preferred to start everolimus between 1 and 3 months post-LT. The current predicted 5-year survival rate of HCC patients in India is less than 15%. The aim of transplantation is to achieve at least a 60% 5-year disease free survival rate, which will provide relief to the prediction of an HCC surge over the next 20 years. The current worldwide criteria (Milan/UCSF) may have a higher 5-year survival (> 70%); however, the majority of patients still do not fit these criteria and are dependent on other suboptimal modes of treatment, with much lower survival rates. To make predictions for 2040, we must prepare to arm ourselves with less stringent selection criteria to widen the pool of patients who may undergo transplantation and have a chance of a better outcome. With more advanced technology and better donor outcomes, LDLT will provide a cutting edge in the fight against liver cancer over the next two decades.

The people behind the papers - Emily Bulgar and Benoit Bruneau.

The transcription factor brachyury (TBXT in humans) promotes epithelial-mesenchymal transition (EMT) both during gastrulation and in cancer contexts and is widely used as a marker of nascent mesoderm. In their study, Benoit Bruneau and colleagues reveal the role of TBXT dosage in early human gastrulation. To know more about their work, we spoke to the first author, Emily Bulgar, and the corresponding author, Benoit Bruneau, Professor at the Department of Pediatrics, University of California San Francisco (UCSF) and Director of the Gladstone Institute of Cardiovascular Disease.

Algorithmic Identification of Treatment-Emergent Adverse Events From Clinical Notes Using Large Language Models: A Pilot Study in Inflammatory Bowel Disease.

Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmacovigilance due to methodological limitations in text mining. Large language models (LLMs) like Bidirectional Encoder Representations from Transformers (BERT) have shown progress in a range of natural language processing tasks but have not yet been evaluated on adverse event (AE) detection. We adapted a new clinical LLM, University of California - San Francisco (UCSF)-BERT, to identify serious AEs (SAEs) occurring after treatment with a non-steroid immunosuppressant for inflammatory bowel disease (IBD). We compared this model to other language models that have previously been applied to AE detection. We annotated 928 outpatient IBD notes corresponding to 928 individual patients with IBD for all SAE-associated hospitalizations occurring after treatment with a non-steroid immunosuppressant. These notes contained 703 SAEs in total, the most common of which was failure of intended efficacy. Out of eight candidate models, UCSF-BERT achieved the highest numerical performance on identifying drug-SAE pairs from this corpus (accuracy 88-92%, macro F1 61-68%), with 5-10% greater accuracy than previously published models. UCSF-BERT was significantly superior at identifying hospitalization events emergent to medication use (P < 0.01). LLMs like UCSF-BERT achieve numerically superior accuracy on the challenging task of SAE detection from clinical notes compared with prior methods. Future work is needed to adapt this methodology to improve model performance and evaluation using multicenter data and newer architectures like Generative pre-trained transformer (GPT). Our findings support the potential value of using large language models to enhance pharmacovigilance.

Using human-centered design to develop and implement a pediatric mental health care access program.

In 2019, the University of California at San Francisco (UCSF) launched the Child and Adolescent Psychiatry Portal (CAPP), a pediatric mental health care access (PMHCA) program providing remote mental health consultation services to pediatric primary care providers (PCPs) throughout Northern and Central California. The development and implementation of CAPP was guided by Human-Centered Design (HCD), an iterative, rapid-paced innovation process focusing on stakeholders' needs and experiences, which shaped the development of CAPP's programs. The resulting key programmatic elements are designed for pediatric workforce development: (1) PCP consultation with a child and adolescent psychiatrist via a telephone warmline; and (2) training and education for providers. CAPP has grown rapidly since its launch, having enrolled 1,714 providers from 257 practices spread across 36 counties and provided 3,288 consults on 2,703 unique lives as of August 2023. Preliminary evaluation findings indicate high PCP satisfaction with CAPP's services, despite continued challenges of integrating behavioral health into primary care. Throughout the HCD and implementation process, multidisciplinary partnerships have proven critical in providing end-user input to inform and improve program design. This growing network of partnerships, developed through the cultivation of personal relationships and trust over time, has also proven essential for CAPP's rapid growth and sustainability. Overall, this Community Case Study highlights the critical role of partnerships and the importance of taking a people-centered approach, as captured in CAPP's motto, "Connecting for Care."

Measuring Implicit Bias in ICU Notes Using Word-Embedding Neural Network Models

Language in nonmedical data sets is known to transmit human-like biases when used in natural language processing (NLP) algorithms that can reinforce disparities. It is unclear if NLP algorithms of medical notes could lead to similar transmissions of biases. Can we identify implicit bias in clinical notes, and are biases stable across time and geography? To determine whether different racial and ethnic descriptors are similar contextually to stigmatizing language in ICU notes and whether these relationships are stable across time and geography, we identified notes on critically ill adults admitted to the University of California, San Francisco (UCSF), from 2012 through 2022 and to Beth Israel Deaconess Hospital (BIDMC) from 2001 through 2012. Because word meaning is derived largely from context, we trained unsupervised word-embedding algorithms to measure the similarity (cosine similarity) quantitatively of the context between a racial or ethnic descriptor (eg, African-American) and a stigmatizing target word (eg, nonco-operative) or group of words (violence, passivity, noncompliance, nonadherence). In UCSF notes, Black descriptors were less likely to be similar contextually to violent words compared with White descriptors. Contrastingly, in BIDMC notes, Black descriptors were more likely to be similar contextually to violent words compared with White descriptors. The UCSF data setalso showed that Black descriptors were more similar contextually to passivity and noncompliance words compared with Latinx descriptors. Implicit bias is identifiable in ICU notes. Racial and ethnic group descriptors carry different contextual relationships to stigmatizing words, depending on when and where notes were written. Because NLP models seem able to transmit implicit bias from training data, use of NLP algorithms in clinical prediction could reinforce disparities. Active debiasing strategies may be necessary to achieve algorithmic fairness when using language models in clinical research.

Advancing noninvasive glioma classification with diffusion radiomics: Exploring the impact of signal intensity normalization.

This study investigates the influence of diffusion-weighted Magnetic Resonance Imaging (DWI-MRI) on radiomic-based prediction of glioma types according to molecular status and assesses the impact of DWI intensity normalization on model generalizability. Radiomic features, compliant with image biomarker standardization initiative standards, were extracted from preoperative MRI of 549 patients with diffuse glioma, known IDH, and 1p19q-status. Anatomical sequences (T1, T1c, T2, FLAIR) underwent N4-Bias Field Correction (N4) and WhiteStripe normalization (N4/WS). Apparent diffusion coefficient (ADC) maps were normalized using N4 or N4/z-score. Nine machine-learning algorithms were trained for multiclass prediction of glioma types (IDH-mutant 1p/19q codeleted, IDH-mutant 1p/19q non-codeleted, IDH-wild type). Four approaches were compared: Anatomical, anatomical + ADC naive, anatomical + ADC N4, and anatomical + ADC N4/z-score. The University of California San Francisco (UCSF)-glioma dataset (n = 409) was used for external validation. Naïve-Bayes algorithms yielded overall the best performance on the internal test set. Adding ADC radiomics significantly improved AUC from 0.79 to 0.86 (P = .011) for the IDH-wild-type subgroup, but not for the other 2 glioma subgroups (P > .05). In the external UCSF dataset, the addition of ADC radiomics yielded a significantly higher AUC for the IDH-wild-type subgroup (P ≤ .001): 0.80 (N4/WS anatomical alone), 0.81 (anatomical + ADC naive), 0.81 (anatomical + ADC N4), and 0.88 (anatomical + ADC N4/z-score) as well as for the IDH-mutant 1p/19q non-codeleted subgroup (P < .012 each). ADC radiomics can enhance the performance of conventional MRI-based radiomic models, particularly for IDH-wild-type glioma. The benefit of intensity normalization of ADC maps depends on the type and context of the used data.

Safety of high-dose-rate brachytherapy in patients with prostate cancer and inflammatory bowel disease: A case series.

Inflammatory bowel disease (IBD) is a relative contraindication to external beam radiation therapy (EBRT) for prostate cancer patients due to fear of increased risk of gastrointestinal (GI) toxicity. High-dose-rate (HDR) brachytherapy, capable of minimizing radiation dose to surrounding tissues, is a feasible alternative. Given limited data, this study examined the safety profile of HDR brachytherapy in this setting. We conducted a retrospective review of patients with localized prostate cancer and IBD treated with HDR brachytherapy at the University of California San Francisco (UCSF), between 2010 and 2022. Eligibility criteria included biopsy-proven prostate cancer, no distant metastases, absence of prior pelvic radiotherapy, IBD diagnosis, and at least one follow-up visit post-treatment. Eleven patients were included, with a median follow-up of 28.7 months. The median dose administered was 2700 cGy (range, 1500-3150 cGy) over 2 fractions (range, 1-3 fractions). Two patients also received EBRT. Rectal spacers (SpaceOAR) were applied in seven patients. All patients experienced acute genitourinary (GU) toxicity, ten of which were grade 1 and one was grade 2. Eight patients experienced late grade 1 GU toxicity, and three patients had late grade 2 GU toxicity. GI toxicities were similarly low-grade, with six grade 1 acute toxicity, no grade 2 or higher acute toxicity, six grade 1 late toxicity, and one late grade 2 GI toxicity. No grade 3 or higher acute or late GI or GU toxicities were reported. HDR brachytherapy appears to be a safe and tolerable treatment modality for patients with prostate cancer and IBD, with minimal acute and late GI and GU toxicity. These findings warrant multi-institutional validation due to small sample size.

Researching COVID to enhance recovery (RECOVER) pregnancy study: Rationale, objectives and design.

Pregnancy induces unique physiologic changes to the immune response and hormonal changes leading to plausible differences in the risk of developing post-acute sequelae of SARS-CoV-2 (PASC), or Long COVID. Exposure to SARS-CoV-2 during pregnancy may also have long-term ramifications for exposed offspring, and it is critical to evaluate the health outcomes of exposed children. The National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC aims to evaluate the long-term sequelae of SARS-CoV-2 infection in various populations. RECOVER-Pregnancy was designed specifically to address long-term outcomes in maternal-child dyads. RECOVER-Pregnancy cohort is a combined prospective and retrospective cohort that proposes to enroll 2,300 individuals with a pregnancy during the COVID-19 pandemic and their offspring exposed and unexposed in utero, including single and multiple gestations. Enrollment will occur both in person at 27 sites through the Eunice Kennedy Shriver National Institutes of Health Maternal-Fetal Medicine Units Network and remotely through national recruitment by the study team at the University of California San Francisco (UCSF). Adults with and without SARS-CoV-2 infection during pregnancy are eligible for enrollment in the pregnancy cohort and will follow the protocol for RECOVER-Adult including validated screening tools, laboratory analyses and symptom questionnaires followed by more in-depth phenotyping of PASC on a subset of the overall cohort. Offspring exposed and unexposed in utero to SARS-CoV-2 maternal infection will undergo screening tests for neurodevelopment and other health outcomes at 12, 18, 24, 36 and 48 months of age. Blood specimens will be collected at 24 months of age for SARS-CoV-2 antibody testing, storage and anticipated later analyses proposed by RECOVER and other investigators. RECOVER-Pregnancy will address whether having SARS-CoV-2 during pregnancy modifies the risk factors, prevalence, and phenotype of PASC. The pregnancy cohort will also establish whether there are increased risks of adverse long-term outcomes among children exposed in utero. Clinical Trial Registration: http://www.clinicaltrials.gov. Unique identifier: NCT05172011.

The Social, Mental, and Physical Health Impacts of the COVID-19 Pandemic on People With HIV: Protocol of an Observational International Multisite Study.

As the COVID-19 pandemic spread across the world, immunocompromised individuals such as people with HIV (PWH) may have faced a disproportionate impact on their health and HIV outcomes, both from COVID-19 and from the strategies enacted to contain it. Based on the SPIRIT guidelines, we describe the protocol for an international multisite observational study being conducted by The International Nursing Network for HIV Research, with the Coordinating Center based at the University of California, San Francisco (UCSF) School of Nursing. Site Principal Investigators implement a standardized protocol to recruit PWH to complete the study online or in-person. Questions address demographics; HIV continuum of care indicators; mental and social health; COVID-19 and vaccination knowledge, attitudes, behaviors, and fears; and overall outcomes. Results of this study will contribute to knowledge that can inform responses to future public health crises to minimize their impacts on vulnerable populations such as PWH.

The Asian Cohort for Alzheimer’s Disease pilot study at University of California San Francisco: A focus on recruitment of Chinese American older adults

AbstractBackgroundAsian American and Canadian (ASAC) populations have long been under‐represented in Alzheimer’s disease (AD) research. The Asian Cohort for Alzheimer’s Disease (ACAD) is the first large US and Canada cohort to study genetic and non‐genetic AD risk factors specifically for older ASAC persons. The University of California San Francisco (UCSF) is one of ACAD’s largest recruitment sites for Chinese American participants.MethodThe UCSF ACAD team has adopted a collaborative multifaceted approach to outreach, recruitment, and data collection including a) recruitment from community partners, social media platforms, clinic referrals, CARE (a research recruitment registry for Asian Americans, Native Hawaiians, and Pacific Islanders), and other ongoing studies (e.g., UCSF’s Alzheimer’s Disease Research Center); b) coordination of multilingual and culturally appropriate outreach events with multiple San Francisco Bay Area community organizations that serve the Chinese American community; c) pilot of ACAD’s data collection packet and procedures in two testing modes (in‐person, on‐line) and three spoken languages (Cantonese, English, Mandarin).ResultAs of January 2023, UCSF has enrolled 121 participants, 116 (95.87%) of whom have completed their visits since we began enrollment in July 2021. Out of the 116 participants, 80 (68.97%) were co‐enrolled with other ongoing studies, 21 (18.10%) were recruited from outreach events in the community, and 15 (12.93%) participated in ACAD through CARE registry, clinic referrals, or social media platforms. The age of our cohort ranges from 60‐90 years (m = 70.45 years). Most of the participants were females (72.4%) and had a college or graduate level education (68.97%). Approximately 50% of the participants completed the study in Mandarin, 32.76% in English, and 17.24% in Cantonese. Nearly two‐thirds of the participants completed their visits virtually. Consensus diagnoses were fully reviewed on 106 participants, including 61 cognitively normal controls, 16 with subjective cognitive complaints, 23 with mild cognitive impairments, and 6 with AD diagnosis.ConclusionACAD aims to enhance the representation of ASAC communities in AD research. The use of culturally and linguistically tailored approaches has and will continue to assist us in outreach, recruitment, and data collection efforts as we aim to expand our sample size and collect longitudinal data.

Abstract A071: Results from cancer clinical trials health education in racial/ethnically diverse populations

Abstract Background: The University of California, San Francisco (UCSF), a National Cancer Institute (NCI) designated comprehensive cancer center implemented NCI’s Clinical Trials (CT) Education Initiative to promote awareness and conduct culturally tailored clinical trials engagement and education in racial/ethnically diverse populations. CT are studies that test ways to prevent, find and treat disease and ensure safety &amp; effectiveness. Racial/ethnic groups have both the highest death rate and shortest survival rate for most cancers. Minority population CT participation is low and more diverse enrollment is needed for progress toward health equity. Methods: UCSF Community Health Educators engaged community partners and conducted CT education. Topics included what are clinical trials, how they work and advance progress, the value of diversity &amp; inclusion, types and phases of CTs, informed consent, myths &amp; facts, mistrust, other concerns &amp; barriers, how to find &amp; enroll in CT &amp; sources for more information. Education sessions were evaluated using a 17-item pre-/post- survey to measure changes in CT knowledge and intention to participate. Changes in knowledge scores were assessed using the Wilcoxon Signed-rank sum test; changes in intent were assessed using the McNemar test. Results: There were 300 total participants (N=300 completed pre/post). Respondents: 76.5% female, 23.5% male; 53 average age; 70.9% African American, 1.4% American Indian, 8.4% Asian, 10.9% Latino, 1.7% Pacific Islander, 3.9% White &amp; 2.8% Multiracial. CT education significantly increased overall knowledge, the intention to seek out CT information and join CT. Clinical trials knowledge score ranged from 0 to 11 pre-education, 4 to 11 post, and improved by 0.50 points (4.6%). Post-education respondents strongly agreed or agreed: 74% to talk to a healthcare provider about CT; 77% importance of people of color CT participation; 48% intend to join a CT. Conclusion: CT education is a strategy to address cancer health disparities through community engaged partnerships &amp; education and demonstrated efficacy in increasing awareness &amp; knowledge of CT and advanced intent to enroll. Citation Format: Michelle Moseley, Eva Pardo, Ghila Andemeskel, Kim Rhoads. Results from cancer clinical trials health education in racial/ethnically diverse populations [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A071.

Stereotype Threat and Gender Bias in Internal Medicine Residency: It is Still Hard to be in Charge

BackgroundDespite similar numbers of women and men in internal medicine (IM) residency, women face unique challenges. Stereotype threat is hypothesized to contribute to underrepresentation of women in academic leadership, and exploring how it manifests in residency may provide insight into forces that perpetuate gender disparities.ObjectiveTo quantify the prevalence of stereotype threat in IM residency and explore experiences contributing to that stereotype threat.DesignWe used a mixed methods study design. First, we surveyed IM residents using the Stereotype Vulnerability Scale (SVS) to screen for stereotype threat. Second, we conducted focus groups with women who scored high on the SVS to understand experiences that led to stereotype threat.ParticipantsThe survey was sent to all IM residents at University of California, San Francisco (UCSF), in September–November 2019. Focus groups were conducted at UCSF in Spring 2020.ApproachThe survey included an adapted version of the SVS. For focus groups, we developed a focus group guide informed by literature on stereotype threat. We used a thematic approach to data analysis. The mixed methods design enabled us to draw metainferences by integrating the two data sources.Key ResultsSurvey response rate was 61% (110/181). Women were significantly more likely than men to have a score indicating stereotype threat vulnerability (77% vs 0%, p < 0.001). Four themes from focus groups characterized women’s experiences of gender bias and stereotype threat: gender norm tension, microaggressions and sexual harassment, authority questioned, and support and allyship.ConclusionsGender-based stereotype threat is highly prevalent among women IM residents. This phenomenon poses a threat to confidence and ability to execute patient care responsibilities, detracting from well-being and professional development. These findings indicate that, despite robust representation of women in IM training, further attention is needed to address gendered experiences and contributors to women’s vulnerability to stereotype threat.

Developing and assessing the use of demonstration videos in the preclinical simulation laboratory.

This study aims to report the development of a preclinical simulation laboratory Demonstration Video Series (DVS) for the 2021-2022 academic year, measure its usage and usefulness, and compare these findings to the usage and usefulness of the existing didactic lecture videos. The DVS videos were intended to be viewed before each preclinical simulation laboratory session along with the pre-existing didactic lectures (DL) by University of California San Francisco (UCSF) learners. Usage measurements included the percentage of the class that viewed each video, the number of views that each video received, and the average duration of each video that was watched. Usefulness of the videos was measured by a survey that assessed learner perspective on knowledge and ability to apply that knowledge during the simulation lab exercises. Both usage and usefulness of the DVS were then compared to the usage and usefulness of the DL. Both descriptive statistics and independent sample hypothesis tests were performed to compare the differences in proportion between DVS and DL mediums. Statistically significant differences were found in terms of both usage and usefulness of the DVS compared to the DL, with DVS being utilized more overall. With an 81% response rate, survey analysis revealed statistically significant differences among the learners' perspectives on the usefulness of the DVS compared to the DL, with a clear preference for the DVS over the DL and an overwhelmingly positive perception of the DVS. The DVS was found to be a valuable addition to the preclinical laboratory sessions for first-year learners.

Transitions in development - an interview with Aydan Bulut-Karslioglu.

Aydan Bulut-Karslioglu is a Group Leader at the Max Planck Institute for Molecular Genetics, Germany, where her research focuses on the epigenetic and metabolic mechanisms regulating embryonic development. After completing her undergraduate degree in chemical engineering, Aydan shifted focus to molecular biology for her Master's degree and epigenetics during her PhD in Thomas Jenuwein's lab. After a stint in the USA for her postdoc at University of California, San Francisco (UCSF), Aydan was awarded the Sofja Kovalevskaja Award to move back to Europe in 2018 to start her own lab. Since then, Aydan has been awarded Development's Outstanding Paper Prize for 2022 and, most recently, a European Research Council Starting Grant Award for 2023. We caught up with Aydan over Zoom to hear more about her path from chemical engineering to molecular genetics, her research and what it means to be awarded these prizes.

Comparison of MRI-Based Staging and Pathologic Staging for Predicting Biochemical Recurrence of Prostate Cancer After Radical Prostatectomy.

BACKGROUND. Currently most clinical models for predicting biochemical recurrence (BCR) of prostate cancer (PCa) after radical prostatectomy (RP) incorporate staging information from RP specimens, creating a gap in preoperative risk assessment. OBJECTIVE. The purpose of our study was to compare the utility of presurgical staging information from MRI and postsurgical staging information from RP pathology in predicting BCR in patients with PCa. METHODS. This retrospective study included 604 patients (median age, 60 years) with PCa who underwent prostate MRI before RP from June 2007 to December 2018. A single genitourinary radiologist assessed MRI examinations for extraprostatic extension (EPE) and seminal vesicle invasion (SVI) during clinical interpretations. The utility of EPE and SVI on MRI and RP pathology for BCR prediction was assessed through Kaplan-Meier and Cox proportional hazards analyses. Established clinical BCR prediction models, including the University of California San Francisco Cancer of the Prostate Risk Assessment (UCSF-CAPRA) model and the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) model, were evaluated in a subset of 374 patients with available Gleason grade groups from biopsy and RP pathology; two CAPRA-MRI models (CAPRA-S model with modifications to replace RP pathologic staging features with MRI staging features) were also assessed. RESULTS. Univariable predictors of BCR included EPE on MRI (HR = 3.6), SVI on MRI (HR = 4.4), EPE on RP pathology (HR = 5.0), and SVI on RP pathology (HR = 4.6) (all p < .001). Three-year BCR-free survival (RFS) rates for patients without versus with EPE were 84% versus 59% for MRI and 89% versus 58% for RP pathology, and 3-year RFS rates for patients without versus with SVI were 82% versus 50% for MRI and 83% versus 54% for RP histology (all p < .001). For patients with T3 disease on RP pathology, 3-year RFS rates were 67% and 41% for patients without and with T3 disease on MRI. AUCs of CAPRA models, including CAPRA-MRI models, ranged from 0.743 to 0.778. AUCs were not significantly different between CAPRA-S and CAPRA-MRI models (p > .05). RFS rates were significantly different between low- and intermediate-risk groups for only CAPRA-MRI models (80% vs 51% and 74% vs 44%; both p < .001). CONCLUSION. Presurgical MRI-based staging features perform comparably to postsurgical pathologic staging features for predicting BCR. CLINICAL IMPACT. MRI staging can preoperatively identify patients at high BCR risk, helping to inform early clinical decision-making. TRIAL REGISTRATION. ClinicalTrials.gov NCT00026884 and NCT02594202.

Peeking Into the Black Box of T Cell Receptor Signaling.

I have spent more than the last 40 years at the University of California, San Francisco (UCSF), studying T cell receptor (TCR) signaling. I was blessed with supportive mentors, an exceptionally talented group of trainees, and wonderful collaborators and colleagues during my journey who have enabled me to make significant contributions to our understanding of how the TCR initiates signaling. TCR signaling events contribute to T cell development as well as to mature T cell activation and differentiation.

AN OVERVIEW OF INTEGRATED MODULAR CURRICULUM FOR UNDERGRADUATE MEDICAL PROGRAMMES IN SOME IMPORTANT COUNTRIES

Several medical schools in the world including but not limited to the University of California, San Francisco (UCSF), the University of Michigan Medical School, the University of Liverpool, the University of Manchester, the University of Dundee, the University of Western Australia (UWA), and the University of Adelaide first adopted and then moved to a more integrated curriculum because of the concerns about the effectiveness of the integrated modular curriculum (IMC) and because IMC was not providing the necessary depth of knowledge. The All-India Institute of Medical Sciences (AIIMS), and the Christian Medical College (CMC) in Vellore, adopted but later reverted to the traditional curriculum. Other medical schools that have adopted and then left the IMC include the Armed Forces Medical College (AFMC) in Pune and the Maulana Azad Medical College (MAMC) in Delhi. History of IMC in medicine in some important countries is summarized here. Pak J Pysiol 2023;19(3):1–2

Negativity and Positivity in the ICU: Exploratory Development of Automated Sentiment Capture in the Electronic Health Record.

To develop proof-of-concept algorithms using alternative approaches to capture provider sentiment in ICU notes. Retrospective observational cohort study. The Multiparameter Intelligent Monitoring of Intensive Care III (MIMIC-III) and the University of California, San Francisco (UCSF) deidentified notes databases. Adult (≥18 yr old) patients admitted to the ICU. We developed two sentiment models: 1) a keywords-based approach using a consensus-based clinical sentiment lexicon comprised of 72 positive and 103 negative phrases, including negations and 2) a Decoding-enhanced Bidirectional Encoder Representations from Transformers with disentangled attention-v3-based deep learning model (keywords-independent) trained on clinical sentiment labels. We applied the models to 198,944 notes across 52,997 ICU admissions in the MIMIC-III database. Analyses were replicated on an external sample of patients admitted to a UCSF ICU from 2018 to 2019. We also labeled sentiment in 1,493 note fragments and compared the predictive accuracy of our tools to three popular sentiment classifiers. Clinical sentiment terms were found in 99% of patient visits across 88% of notes. Our two sentiment tools were substantially more predictive (Spearman correlations of 0.62-0.84, p values < 0.00001) of labeled sentiment compared with general language algorithms (0.28-0.46). Our exploratory healthcare-specific sentiment models can more accurately detect positivity and negativity in clinical notes compared with general sentiment tools not designed for clinical usage.