Impact of Cancer Therapy on Clonal Hematopoiesis Mutations and Subsequent Clinical Outcomes.

Exposure to cancer therapies is associated with an increased risk of clonal hematopoiesis (CH). The objective of our study was to investigate the genesis and evolution of CH following cancer therapy. In this prospective study, we undertook error-corrected duplex DNA sequencing in blood samples collected prior to and at two timepoints following chemoradiation in patients with esophageal or lung cancer recruited from 2013-2018. We applied a customized workflow to identify the earliest changes in CH mutation count and clone size and determine their association with clinical outcomes. Our study included 29 patients (87 samples). Their median age was 67 years, 76% (n = 22) were male; the median follow-up period was 3.9 years. The most mutated genes were DNMT3A, TET2, TP53, and ASXL1. We observed a two-fold increase in the number of mutations from before to after treatment in TP53, which differed from all other genes examined (P < .001). Among mutations detected before and after treatment, we observed an increased clone size in 38% and a decreased clone size in 5% of TP53 mutations (odds ratio = 3.7; 95% CI = 1.75-7.84; P < .001). Changes in mutation count and clone size were not observed in other genes. Individuals with an increase in the number of TP53 mutations following chemoradiation experienced shorter overall survival (hazard ratio = 7.07; 95% CI = 1.50-33.46; P = .014). In summary, we found an increase in the number and size of TP53 CH clones following chemoradiation that were associated with clinical outcomes.

On the acceptance, commissioning, and quality assurance of electron FLASH units.

Background & Purpose: FLASH or ultra-high dose rate (UHDR) radiation therapy (RT) has gained attention in recent years for its ability to spare normal tissues relative to conventional dose rate (CDR) RT in various preclinical trials. However, clinical implementation of this promising treatment option has been limited because of the lack of availability of accelerators capable of delivering UHDR RT. Commercial options are finally reaching the market that produce electron beams with average dose rates of up to 1000 Gy/s. We established a framework for the acceptance, commissioning, and periodic quality assurance (QA) of electron FLASH units and present an example of commissioning. Methods: A protocol for acceptance, commissioning, and QA of UHDR linear accelerators was established by combining and adapting standards and professional recommendations for standard linear accelerators based on the experience with UHDR at four clinical centers that use different UHDR devices. Non-standard dosimetric beam parameters considered included pulse width, pulse repetition frequency, dose per pulse, and instantaneous dose rate, together with recommendations on how to acquire these measurements. Results: The 6- and 9-MeV beams of an UHDR electron device were commissioned by using this developed protocol. Measurements were acquired with a combination of ion chambers, beam current transformers (BCTs), and dose-rate-independent passive dosimeters. The unit was calibrated according to the concept of redundant dosimetry using a reference setup. Conclusions: This study provides detailed recommendations for the acceptance testing, commissioning, and routine QA of low-energy electron UHDR linear accelerators. The proposed framework is not limited to any specific unit, making it applicable to all existing eFLASH units in the market. Through practical insights and theoretical discourse, this document establishes a benchmark for the commissioning of UHDR devices for clinical use.

Plasmonic nano-aperture label-free imaging of single small extracellular vesicles for cancer detection.

BACKGROUND: Small extracellular vesicle (sEV) analysis can potentially improve cancer detection and diagnostics. However, this potential has been constrained by insufficient sensitivity, dynamic range, and the need for complex labeling. METHODS: In this study, we demonstrate the combination of PANORAMA and fluorescence imaging for single sEV analysis. The co-acquisition of PANORAMA and fluorescence images enables label-free visualization, enumeration, size determination, and enables detection of cargo microRNAs (miRs). RESULTS: An increased sEV count is observed in human plasma samples from patients with cancer, regardless of cancer type. The cargo miR-21 provides molecular specificity within the same sEV population at the single unit level, which pinpoints the sEVs subset of cancer origin. Using cancer cells-implanted animals, cancer-specific sEVs from 20 µl of plasma can be detected before tumors were palpable. The level plateaus between 5-15 absolute sEV count (ASC) per µl with tumors ≥8 mm3. In healthy human individuals (N = 106), the levels are on average 1.5 ASC/µl (+/- 0.95) without miR-21 expression. However, for stage I-III cancer patients (N = 205), nearly all (204 out of 205) have levels exceeding 3.5 ASC/µl with an average of 12.2 ASC/µl (±9.6), and a variable proportion of miR-21 labeling among different tumor types with 100% cancer specificity. Using a threshold of 3.5 ASC/µl to test a separate sample set in a blinded fashion yields accurate classification of healthy individuals from cancer patients. CONCLUSIONS: Our techniques and findings can impact the understanding of cancer biology and the development of new cancer detection and diagnostic technologies.

Small extracellular vesicles (sEVs) are tiny particles derived from cells that can be detected in bodily fluids such as blood. Detecting sEVs and analyzing their contents may potentially help us to diagnose disease, for example by observing differences in sEV numbers or contents in the blood of patients with cancer versus healthy people. Here, we combine two imaging methods ­ our previously developed method PANORAMA and imaging of fluorescence emitted by sEVs­to visualize and count sEVs, determine their size, and analyze their cargo. We observe differences in sEV numbers and cargo in samples taken from healthy people versus people with cancer and are able to differentiate these two populations based on our analysis of sEVs. With further testing, our approach may be a useful tool for cancer diagnosis and provide insights into the biology of cancer and sEVs.

Personalized Composite Dosimetric Score-Based Machine Learning Model of Severe Radiation-Induced Lymphopenia Among Patients With Esophageal Cancer.

PURPOSE: Radiation-induced lymphopenia (RIL) is common among patients undergoing radiation therapy (RT)' Severe RIL has been linked to adverse outcomes. The severity and risk of RIL can be predicted from baseline clinical characteristics and dosimetric parameters. However, dosimetric parameters, e.g. dose-volume (DV) indices, are highly correlated with one another and are only weakly associated with RIL. Here we introduce the novel concept of "composite dosimetric score" (CDS) as the index that condenses the dose distribution in immune tissues of interest to study the dosimetric dependence of RIL. We derived an improved multivariate classification scheme for risk of grade 4 RIL (G4RIL), based on this novel RT dosimetric feature, for patients receiving chemo RT for esophageal cancer. METHODS AND MATERIALS: DV indices were extracted for 734 patients who received chemo RT for biopsy-proven esophageal cancer. Nonnegative matrix factorization was used to project the DV indices of lung, heart, and spleen into a single CDS; XGBoost was employed to explore significant interactions among predictors; and logistic regression was applied to combine the resultant CDS with baseline clinical factors and interaction terms to facilitate individualized prediction of immunotoxicity. Five-fold cross-validation was applied to evaluate the model performance. RESULTS: The CDS for selected immune organs at risk (ie, heart, lung, and spleen) (OR 1.791; 95 CI [1.350, 2.377]) was a statistically significant risk determinant for G4RIL. Pearson correlation coefficients for CDS versus G4RIL risk for individual immune organs at risk were greater than any single DV indicx. Personalized prediction of G4RIL based on CDS and 4 clinical risk factors yielded an area under the curve value of 0.78. Interaction between age and CDS revealed that G4RIL risk increased more sharply with increasing CDS for patients aged ≥65 years. CONCLUSIONS: Risk of immunotoxicity for patients undergoing chemo RT for esophageal cancer can be predicted by CDS. The CDS concept can be extended to immunotoxicity in other cancer types and in dose-response models currently based on DV indices. Personalized treatment planning should leverage composite dosimetric scoring methods rather than using individual or subsets of DV indices.

Redefining FLASH RT: the impact of mean dose rate and dose per pulse in the gastrointestinal tract.

Background: The understanding of how varying radiation beam parameter settings affect the induction and magnitude of the FLASH effect remains limited. Purpose: We sought to evaluate how the magnitude of radiation-induced gastrointestinal (GI) toxicity (RIGIT) depends on the interplay between mean dose rate (MDR) and dose per pulse (DPP). Methods: C57BL/6J mice were subjected to total abdominal irradiation (11-14 Gy single fraction) under conventional irradiation (low DPP and low MDR, CONV) and various combinations of DPP and MDR up to ultra-high-dose-rate (UHDR) beam conditions. The effects of DPP were evaluated for DPPs of 1-6 Gy while the total dose and MDR were kept constant; the effects of MDR were evaluated for the range 0.3- 1440 Gy/s while the total dose and DPP were kept constant. RIGIT was quantified in non-tumor-bearing mice through the regenerating crypt assay and survival assessment. Tumor response was evaluated through tumor growth delay. Results: Within each tested total dose using a constant MDR (>100 Gy/s), increasing DPP led to better sparing of regenerating crypts, with a more prominent effect seen at 12 and 14 Gy TAI. However, at fixed DPPs >4 Gy, similar sparing of crypts was demonstrated irrespective of MDR (from 0.3 to 1440 Gy/s). At a fixed high DPP of 4.7 Gy, survival was equivalently improved relative to CONV for all MDRs from 0.3 Gy/s to 104 Gy/s, but at a lower DPP of 0.93 Gy, increasing MDR produced a greater survival effect. We also confirmed that high DPP, regardless of MDR, produced the same magnitude of tumor growth delay relative to CONV using a clinically relevant melanoma mouse model. Conclusions: This study demonstrates the strong influence that the beam parameter settings have on the magnitude of the FLASH effect. Both high DPP and UHDR appeared independently sufficient to produce FLASH sparing of GI toxicity, while isoeffective tumor response was maintained across all conditions.

Esophageal Cancer Outcomes After Definitive Chemotherapy With Intensity Modulated Proton Therapy.

Purpose: The effectiveness of intensity-modulated proton therapy (IMPT) for esophageal cancer treated with definitive concurrent chemoradiation therapy remains inadequately explored. We investigated long-term outcomes and toxicity experienced by patients who received IMPT as part of definitive esophageal cancer treatment. Patients and Methods: We retrospectively identified and analyzed 34 patients with locally advanced esophageal cancer who received IMPT with concurrent chemotherapy as a definitive treatment regimen at The University of Texas MD Anderson Cancer Center from 2011 to 2021. The median IMPT dose was 50.4 GyRBE in 28 fractions; concurrent chemotherapy consisted of fluorouracil and/or taxane and/or platinum. Survival outcomes were determined by the Kaplan-Meier method, and toxicity was scored according to the Common Terminology Criteria for Adverse Events version 4.0. Results: The median age of all patients was 71.5 years. Most patients had stage III (cT3 cM0) adenocarcinoma of the lower esophagus. At a median follow-up time of 39 months, the 5-year overall survival rate was 41.1%; progression-free survival, 34.6%; local regional recurrence-free survival, 78.1%; and distant metastasis-free survival, 65.0%. Common acute chemoradiation therapy-related toxicities included hematologic toxicity, esophagitis (and late-onset), fatigue, weight loss, and nausea (and late-onset); grade 3 toxicity rates were 26.0% for hematologic, 18.0% for esophagitis and 9.0% for nausea. No patient had grade ≥3 wt loss or radiation pneumonitis, and no patients had pulmonary fibrosis or esophageal fistula. No grade ≥4 events were observed except for hematologic toxicity (lymphopenia) in 2 patients. Conclusion: Long-term survival and toxicity were excellent after IMPT for locally advanced esophageal cancer treated definitively with concurrent chemoradiation therapy. When available, IMPT should be offered to such patients to minimize treatment-related cardiopulmonary toxicity without sacrificing outcomes.

Comparing 90-Day Postoperative Mortality After Neoadjuvant Proton-Based Versus Photon-Based Chemoradiotherapy for Esophageal Cancer.

Purpose: Evidence suggests that proton-beam therapy (PBT) results in less toxicity and postoperative complications compared to photon-based radiotherapy in patients who receive chemoradiotherapy followed by esophagectomy for cancer. Ninety-day mortality (90DM) is an important measure of the postoperative (nononcologic) outcome as proxy of quality-of-care. We hypothesize that PBT could reduce 90DM compared to photon-based radiotherapy. Materials and Methods: From a single-center retrospective database patients treated with chemoradiotherapy before esophagectomy for cancer were selected (1998-2022). Univariable logistic regression was used to study the association of radiotherapy modality with 90DM. Three separate methods were applied to adjust for confounding bias, including multivariable logistic regression, propensity score matching, and inverse probability of treatment weighting. Stratified analysis for the age threshold that maximized the difference in 90DM (ie, ≥67 vs <67 years) was performed. Results: A total of 894 eligible patients were included and 90DM was 5/202 (2.5%) in the PBT versus 29/692 (4.2%) in the photon-based radiotherapy group (P = .262). After adjustment for age and tumor location, PBT versus photon-based radiotherapy was not significantly associated with 90DM (P = .491). The 90DM was not significantly different for PBT versus photon-based radiotherapy in the propensity score matching (P = .379) and inverse probability of treatment weighting cohort (P = .426). The stratified analysis revealed that in patients aged ≥67 years, PBT was associated with decreased 90DM (1.3% vs 8.8%; P = .026). Higher age significantly increased 90DM risk within the photon-based radiotherapy (8.8% vs 2.7%; P = .001), but not within the PBT group (1.3% vs 3.2%; P = .651). Conclusion: No statistically significant difference was observed in postoperative 90DM after esophagectomy for cancer between PBT and photon-based neoadjuvant chemoradiotherapy. However, among older patients a signal was observed that PBT may reduce 90DM risk.

Outcomes of Mechanical Thrombectomy for Patients With Stroke Presenting With Low Alberta Stroke Program Early Computed Tomography Score in Early and Late Time Windows.

BACKGROUND AND OBJECTIVES: This study aimed to compare outcomes of low Alberta Stroke Program Early Computed Tomography Score (ASPECTS) patients with stroke who underwent mechanical thrombectomy (MT) within 6 hours or 6 to 24 hours after stroke onset. METHODS: A retrospective cohort study was conducted using data from a large multicenter international registry from 2013 to 2023. Patients with low ASPECTS (2-5) who underwent MT for anterior circulation intracranial large vessel occlusion were included. A propensity matching analysis was conducted for patients presented in the early (<6 hours) vs late (6-24 hours) time window after symptom onset or last known normal. RESULTS: Among the 10 229 patients who underwent MT, 274 met the inclusion criteria. 122 (44.5%) patients were treated in the late window. Early window patients were older (median age, 74 years [IQR, 63-80] vs 66.5 years [IQR, 54-77]; P < .001), had lower proportion of female patients (40.1% vs 54.1%; P = .029), higher median admission National Institutes of Health Stroke Scale score (20 [IQR, 16-24] vs 19 [IQR, 14-22]; P = .004), and a higher prevalence of atrial fibrillation (46.1% vs 27.3; P = .002). Propensity matching yielded a well-matched cohort of 84 patients in each group. Comparing the matched cohorts showed there was no significant difference in acceptable outcomes at 90 days between the 2 groups (odds ratio = 0.90 [95% CI = 0.47-1.71]; P = .70). However, the rate of symptomatic ICH was significantly higher in the early window group compared with the late window group (odds ratio = 2.44 [95% CI = 1.06-6.02]; P = .04). CONCLUSION: Among patients with anterior circulation large vessel occlusion and low ASPECTS, MT seems to provide a similar benefit to functional outcome for patients presenting <6 hours or 6 to 24 hours after onset.

Unique sequelae of portal vein thrombosis in a pediatric patient with cystic echinococcosis: A case report.

This case report presents a rare complication of hepatic cystic echinococcosis in a 12-year-old Latino male, residing in a nonendemic region, who developed long-term sequelae of portal vein thrombosis accompanied by the emergence of a hyper-vascular sigmoid colon mass. Portal vein involvement in hepatic cystic echinococcosis is exceedingly uncommon, with limited documented cases. The presentation of the patient included intermittent hematochezia, abdominal pain, and fatigue. Imaging revealed liver cysts and chronic portal vein thrombosis with cavernous transformation, resulting in portal hypertension. Notably, the patient also exhibited mesenteric venous thrombosis, further complicating the clinical picture. The diagnosis was confirmed through echinococcus serology testing. Treatment involved a six month course of Albendazole, puncture-aspiration-injection-reaspiration procedure, splenectomy, and splenorenal shunt to alleviate portal hypertension. This case underscores the significance of considering portal hypertension secondary to hepatic cystic echinococcosis, even in nonendemic regions, particularly in pediatric patients with unique clinical presentations.

What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care.

Primary care physicians are likely both excited and apprehensive at the prospects for artificial intelligence (AI) and machine learning (ML). Complexity science may provide insight into which AI/ML applications will most likely affect primary care in the future. AI/ML has successfully diagnosed some diseases from digital images, helped with administrative tasks such as writing notes in the electronic record by converting voice to text, and organized information from multiple sources within a health care system. AI/ML has less successfully recommended treatments for patients with complicated single diseases such as cancer; or improved diagnosing, patient shared decision making, and treating patients with multiple comorbidities and social determinant challenges. AI/ML has magnified disparities in health equity, and almost nothing is known of the effect of AI/ML on primary care physician-patient relationships. An intervention in Victoria, Australia showed promise where an AI/ML tool was used only as an adjunct to complex medical decision making. Putting these findings in a complex adaptive system framework, AI/ML tools will likely work when its tasks are limited in scope, have clean data that are mostly linear and deterministic, and fit well into existing workflows. AI/ML has rarely improved comprehensive care, especially in primary care settings, where data have a significant number of errors and inconsistencies. Primary care should be intimately involved in AI/ML development, and its tools carefully tested before implementation; and unlike electronic health records, not just assumed that AI/ML tools will improve primary care work life, quality, safety, and person-centered clinical decision making.

Storylines of family medicine VIII: clinical approaches.

Storylines of Family Medicine is a 12-part series of thematically linked mini-essays with accompanying illustrations that explore the many dimensions of family medicine as interpreted by individual family physicians and medical educators in the USA and elsewhere around the world. In 'VIII: clinical approaches', authors address the following themes: 'Evaluation, diagnosis and management I-toward a working diagnosis', 'Evaluation, diagnosis and management II-process steps', 'Interweaving integrative medicine and family medicine', 'Halfway-the art of clinical judgment', 'Seamless integration in family medicine-team-based care', 'Technology-uncovering stories from noise' and 'Caring for patients with multiple long-term conditions'. May readers recognise in these essays the uniqueness of a family medicine approach to care.

Utility of intracranial pressure monitoring as a diagnostic tool in pediatric ventriculomegaly.

OBJECTIVE: Intracranial pressure (ICP) monitoring is commonly utilized for identifying pathologic ICP in cases of traumatic brain injury; however, its utility in hydrocephalic children has not been elucidated. Although patients with typical (pressure-active) hydrocephalus present with clear signs and/or symptoms and the need for cerebrospinal fluid (CSF) diversion is often clear, others may have arrested or pressure-compensated hydrocephalus with pathologic ICP elevation masked by ambiguous signs or are completely asymptomatic. Without treatment these pathologic ICP elevations may affect neurologic development or crescendo over time leading to neurological decline. The purpose of this study is to investigate the utility of ICP monitoring as a diagnostic tool in this relatively common patient population and identify ventriculomegaly patients with and without pathologic ICP, thus improving accuracy of identifying those with and without surgical needs. METHODS: 36 patients (≤ 17 years old) underwent 41 inpatient ICP recording sessions between 2016 and 2022 and were retrospectively reviewed. This included patients with a history of severe, nonprogressive ventriculomegaly and normal fundoscopic examinations lacking traditional signs and symptoms concerning for elevated ICP. Nighttime pathological plateau waves were defined as sustained elevations of ICP ≥ 2x baseline for a duration of ≥ 5 minutes. RESULTS: The mean age of patients was 5.5 years old (range 0-17 years old). 46.3% of patients had prior endoscopic third ventriculostomy (ETV), 14.6% had prior ventriculoperitoneal shunt (VPS), and 39% were without prior surgical intervention. Roughly half (51.2%) of patients had congenital ventriculomegaly while other patients had ventriculomegaly due to other pathologies such as germinal matrix hemorrhage/intraventricular hemorrhage (GMH/IVH) (29.3%), stroke (4.9%), cerebral infections/meningitis (2.4%), or unknown etiology (12.2%). The average procedure time was 19.1 ± 10.5 minutes, and mean length of stay was 2.8 ± 0.7 days. Pathologic ICP was demonstrated in 12 cases (29.3%), 4 (33.3%) of which were asymptomatic. Pathologic ICP was found in 7 of 19 (36.8%) in the prior ETV group, 1 of 6 (16.7%) in prior shunt group, and 4 of 16 (25%) in the non-surgical group (p = 0.649). Among those with pathologic ICP, 6 (50%) cases received an ETV, 5 (41.7%) cases underwent VPS placement, and 1 (8.3%) case underwent a VPS revision. There were no infectious complications or cases of hemorrhage. 4 patients required repositioning of the ICP monitor due to dislodgement. CONCLUSION: Inpatient ICP monitoring is a safe and effective diagnostic tool for evaluating the presence of pathologic ICP in severe, persistent non-progressive ventriculomegaly. The use of ICP monitoring may aid in identifying patients with pressure-compensated hydrocephalus who demonstrate pathologic ICP where surgical intervention may be warranted, while preventing unnecessary CSF diversion in those without pathology.

AI-guided histopathology predicts brain metastasis in lung cancer patients.

Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine H&E-stained primary tumor tissue sections from stage I-III NSCLC patients to predict the development of brain metastasis. Diagnostic slides from 158 patients with stage I-III NSCLC followed for at least 5 years for the development of brain metastases (Met+, 65 patients) versus no progression (Met-, 93 patients) were subjected to whole-slide imaging. Three separate iterations were performed by first selecting 118 cases (45 Met+, 73 Met-) to train and validate the DL algorithm, while 40 separate cases (20 Met+, 20 Met-) were used as the test set. The DL algorithm results were compared to a blinded review by four expert pathologists. The DL-based algorithm was able to distinguish the eventual development of brain metastases with an accuracy of 87% (p < 0.0001) compared with an average of 57.3% by the four pathologists and appears to be particularly useful in predicting brain metastases in stage I patients. The DL algorithm appears to focus on a complex set of histologic features. DL-based algorithms using routine H&E-stained slides may identify patients who are likely to develop brain metastases from those who will remain disease free over extended (>5 year) follow-up and may thus be spared systemic therapy. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

BTN1A1 is a novel immune checkpoint mutually exclusive to PD-L1.

BACKGROUND: While Programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) blockade is a potent antitumor treatment strategy, it is effective in only limited subsets of patients with cancer, emphasizing the need for the identification of additional immune checkpoints. Butyrophilin 1A1 (BTN1A1) has been reported to exhibit potential immunoregulatory activity, but its ability to function as an immune checkpoint remains to be systematically assessed, and the mechanisms underlying such activity have yet to be characterized. METHODS: BTN1A1 expression was evaluated in primary tumor tissue samples, and its ability to suppress T-cell activation and T cell-dependent tumor clearance was examined. The relationship between BTN1A1 and PD-L1 expression was further characterized, followed by the development of a BTN1A1-specific antibody that was administered to tumor-bearing mice to test the amenability of this target to immune checkpoint inhibition. RESULTS: BTN1A1 was confirmed to suppress T-cell activation in vitro and in vivo. Robust BTN1A1 expression was detected in a range of solid tumor tissue samples, and BTN1A1 expression was mutually exclusive with that of PD-L1 as a consequence of its inhibition of Janus-activated kinase/signal transducer and activator of transcription signaling-induced PD-L1 upregulation. Antibody-mediated BTN1A1 blockade suppressed tumor growth and enhanced immune cell infiltration in syngeneic tumor-bearing mice. CONCLUSION: Together, these results confirm that the potential of BTN1A1 is a bona fide immune checkpoint and a viable immunotherapeutic target for the treatment of individuals with anti-PD-1/PD-L1 refractory or resistant disease, opening new avenues to improving survival outcomes for patients with a range of cancers.

Artificial Intelligence-Generated Draft Replies to Patient Inbox Messages.

Importance: The emergence and promise of generative artificial intelligence (AI) represent a turning point for health care. Rigorous evaluation of generative AI deployment in clinical practice is needed to inform strategic decision-making. Objective: To evaluate the implementation of a large language model used to draft responses to patient messages in the electronic inbox. Design, Setting, and Participants: A 5-week, prospective, single-group quality improvement study was conducted from July 10 through August 13, 2023, at a single academic medical center (Stanford Health Care). All attending physicians, advanced practice practitioners, clinic nurses, and clinical pharmacists from the Divisions of Primary Care and Gastroenterology and Hepatology were enrolled in the pilot. Intervention: Draft replies to patient portal messages generated by a Health Insurance Portability and Accountability Act-compliant electronic health record-integrated large language model. Main Outcomes and Measures: The primary outcome was AI-generated draft reply utilization as a percentage of total patient message replies. Secondary outcomes included changes in time measures and clinician experience as assessed by survey. Results: A total of 197 clinicians were enrolled in the pilot; 35 clinicians who were prepilot beta users, out of office, or not tied to a specific ambulatory clinic were excluded, leaving 162 clinicians included in the analysis. The survey analysis cohort consisted of 73 participants (45.1%) who completed both the presurvey and postsurvey. In gastroenterology and hepatology, there were 58 physicians and APPs and 10 nurses. In primary care, there were 83 physicians and APPs, 4 nurses, and 8 clinical pharmacists. The mean AI-generated draft response utilization rate across clinicians was 20%. There was no change in reply action time, write time, or read time between the prepilot and pilot periods. There were statistically significant reductions in the 4-item physician task load score derivative (mean [SD], 61.31 [17.23] presurvey vs 47.26 [17.11] postsurvey; paired difference, -13.87; 95% CI, -17.38 to -9.50; P < .001) and work exhaustion scores (mean [SD], 1.95 [0.79] presurvey vs 1.62 [0.68] postsurvey; paired difference, -0.33; 95% CI, -0.50 to -0.17; P < .001). Conclusions and Relevance: In this quality improvement study of an early implementation of generative AI, there was notable adoption, usability, and improvement in assessments of burden and burnout. There was no improvement in time. Further code-to-bedside testing is needed to guide future development and organizational strategy.

Effectiveness of an Artificial Intelligence-Enabled Intervention for Detecting Clinical Deterioration.

Importance: Inpatient clinical deterioration is associated with substantial morbidity and mortality but may be easily missed by clinicians. Early warning scores have been developed to alert clinicians to patients at high risk of clinical deterioration, but there is limited evidence for their effectiveness. Objective: To evaluate the effectiveness of an artificial intelligence deterioration model-enabled intervention to reduce the risk of escalations in care among hospitalized patients using a study design that facilitates stronger causal inference. Design, Setting, and Participants: This cohort study used a regression discontinuity design that controlled for confounding and was based on Epic Deterioration Index (EDI; Epic Systems Corporation) prediction model scores. Compared with other observational research, the regression discontinuity design facilitates causal analysis. Hospitalized adults were included from 4 general internal medicine units in 1 academic hospital from January 17, 2021, through November 16, 2022. Exposure: An artificial intelligence deterioration model-enabled intervention, consisting of alerts based on an EDI score threshold with an associated collaborative workflow among nurses and physicians. Main Outcomes and Measures: The primary outcome was escalations in care, including rapid response team activation, transfer to the intensive care unit, or cardiopulmonary arrest during hospitalization. Results: During the study, 9938 patients were admitted to 1 of the 4 units, with 963 patients (median [IQR] age, 76.1 [64.2-86.2] years; 498 males [52.3%]) included within the primary regression discontinuity analysis. The median (IQR) Elixhauser Comorbidity Index score in the primary analysis cohort was 10 (0-24). The intervention was associated with a -10.4-percentage point (95% CI, -20.1 to -0.8 percentage points; P = .03) absolute risk reduction in the primary outcome for patients at the EDI score threshold. There was no evidence of a discontinuity in measured confounders at the EDI score threshold. Conclusions and Relevance: Using a regression discontinuity design, this cohort study found that the implementation of an artificial intelligence deterioration model-enabled intervention was associated with a significantly decreased risk of escalations in care among inpatients. These results provide evidence for the effectiveness of this intervention and support its further expansion and testing in other care settings.

Survival outcomes and toxicity of adjuvant immunotherapy after definitive concurrent chemotherapy with proton beam radiation therapy for patients with inoperable locally advanced non-small cell lung carcinoma.

INTRODUCTION: Adjuvant immunotherapy (IO) following concurrent chemotherapy and photon radiation therapy confers an overall survival (OS) benefit for patients with inoperable locally advanced non-small cell lung carcinoma (LA-NSCLC); however, outcomes of adjuvant IO after concurrent chemotherapy with proton beam therapy (CPBT) are unknown. We investigated OS and toxicity after CPBT with adjuvant IO versus CPBT alone for inoperable LA-NSCLC. MATERIALS AND METHODS: We analyzed 354 patients with LA-NSCLC who were prospectively treated with CPBT with or without adjuvant IO from 2009 to 2021. Optimal variable ratio propensity score matching (PSM) matched CPBT with CPBT + IO patients. Survival was estimated with the Kaplan-Meier method and compared with log-rank tests. Multivariable Cox proportional hazards regression evaluated the effect of IO on disease outcomes. RESULTS: Median age was 70 years; 71 (20%) received CPBT + IO and 283 (80%) received CPBT only. After PSM, 71 CPBT patients were matched with 71 CPBT + IO patients. Three-year survival rates for CPBT + IO vs CPBT were: OS 67% vs 30% (P < 0.001) and PFS 59% vs 35% (P = 0.017). Three-year LRFS (P = 0.137) and DMFS (P = 0.086) did not differ. Receipt of adjuvant IO was a strong predictor of OS (HR 0.40, P = 0.001) and PFS (HR 0.56, P = 0.030), but not LRFS (HR 0.61, P = 0.121) or DMFS (HR 0.61, P = 0.136). There was an increased incidence of grade ≥3 esophagitis in the CPBT-only group (6% CPBT + IO vs 17% CPBT, P = 0.037). CONCLUSION: This study, one of the first to investigate CPBT followed by IO for inoperable LA-NSCLC, showed that IO conferred survival benefits with no increased rates of toxicity.

The LRRK2 kinase substrates RAB8a and RAB10 contribute complementary but distinct disease-relevant phenotypes in human neurons.

Mutations in the LRRK2 gene cause familial Parkinson's disease presenting with pleomorphic neuropathology that can involve α-synuclein or tau accumulation. LRRK2 mutations are thought to converge upon a pathogenic increase in LRRK2 kinase activity. A subset of small RAB GTPases has been identified as LRRK2 substrates, with LRRK2-dependent phosphorylation resulting in RAB inactivation. We used CRISPR-Cas9 genome editing to generate a novel series of isogenic iPSC lines deficient in the two most well-validated LRRK2 substrates, RAB8a and RAB10, from deeply phenotyped healthy control lines. Thorough characterization of NGN2-induced neurons revealed opposing effects of RAB8a and RAB10 deficiency on lysosomal pH and Golgi organization, with isolated effects of RAB8a and RAB10 ablation on α-synuclein and tau, respectively. Our data demonstrate largely antagonistic effects of genetic RAB8a or RAB10 inactivation, which provide discrete insight into the pathologic features of their biochemical inactivation by pathogenic LRRK2 mutation in human disease.