Citations

PURPOSE Limited treatment options exist for patients with locally advanced or metastatic biliary tract cancers (BTCs). Recently, several clinical trials provided preliminary evidence for human epidermal growth factor receptor 2 (HER2) as a new target for patients with HER2-expressing BTC. We conducted a systematic review and pooled analysis of the safety and efficacy of anti-HER2 agents in patients with advanced BTCs. METHODS A comprehensive search of PubMed/MEDLINE and EMBASE was performed to identify phase I, II, or III clinical trials published between January 2019 and March 2024 that evaluated anti-HER2 therapy in locally advanced or metastatic BTC. Participant data included in the analysis were from trials evaluating the efficacy and safety of various anti-HER2 agents. The primary end points included objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). The secondary end points included incidence of treatment-related adverse events (TRAEs), rate of treatment discontinuation, and death. RESULTS The analysis included 368 patients from eight publications diagnosed with advanced BTC. Patients were treated with several anti-HER2 agents including zanidatamab, pertuzumab plus trastuzumab, tucatinib plus trastuzumab, trastuzumab deruxtecan, trastuzumab plus chemotherapy, trastuzumab-pkrb plus chemotherapy, and neratinib. The pooled ORR and DCR were 34% (95% CI, 24 to 44) and 64% (95% CI, 51 to 77), respectively. The pooled weighted PFS and median overall survival were 4.8 and 9.4 months, respectively. The pooled duration of response for the reporting trials was 5.0 months. In the study cohort, 82.6% of patients experienced any adverse event and 32.1% experienced a grade 3-4 adverse event. Only 5.7% of the patients discontinued treatment secondary to TRAEs. CONCLUSION In patients with HER2-expressing BTCs, anti-HER2 therapies are viable options, particularly in the second-line setting.

Abstract Background The lupus anticoagulant (LAC) is an important laboratory criterion in the diagnosis of antiphospholipid antibody syndrome. LAC testing at the Mayo Clinic Special Coagulation Laboratory includes up to 13 tests, which are interpreted by trained physicians to identify the presence of LAC and rule out anticoagulant interferences. This feasibility study explored the use of two deep neural network (DNN) architectures for multilabel classification of LAC profiles as a first step toward automating interpretation. Methods Seven thousand two hundred and two retrospective cases were randomly split (64:16:20) for training, validation, and test, respectively. LAC positivity by dilute Russell's viper venom time (LAC-DRVVT) and activated partial thromboplastin time (LAC-APTT) and the presence of warfarin (WAR) and heparin (HEP) were adjudicated by one expert. DNN architectures included: single-output DNNs using domain-knowledge input feature selection and a single-column multioutput DNN using all 13 inputs. Results Domain-knowledge-naïve multioutput DNN achieved similar or improved performance for all 4 label prediction tasks compared with domain knowledge optimized DNNs: F1 scores of 0.977 vs 0.968 for LAC-DRVVT, 0.954 vs 0.945 for LAC-APTT, 0.961 vs 0.957 for HEP, and 0.995 vs 0.977 for WAR, respectively. Conclusions The comparable performance of the 4 domain knowledge optimized DNNs and the multioutput DNN using all 13 input features suggests that the DNN may learn feature importance or mapping to a task without explicit input selection. Given its relative simplicity and versatility, the multioutput DNN is the preferred choice for implementation in a clinical laboratory to standardize LAC diagnosis.

Abstract Richter transformation (RT) is defined as an aggressive lymphoma emerging in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL). Despite novel therapeutics developed in CLL, RT is associated with poor outcomes. In light of recent progress regarding the diagnostic procedures and therapeutic concepts of RT, an international group of experts, under the coordination of the European Research Initiative on CLL, has developed consensus recommendations for clinical procedures and future research on this disease. Patients with RT typically present with a rapid clinical decline, worsening B-symptoms, elevated lactate dehydrogenase, and/or rapidly enlarging lymphadenopathy. Workup should include a positron emission tomography–computed tomography scan for patients with suspected RT. An excisional biopsy should be taken from an accessible lesion, preferably with the highest fluorodeoxyglucose avidity, and analyzed for the presence of aggressive lymphoma. The molecular relationship to the original CLL clone(s) should be defined. Because no effective standard treatment for RT exists, patients should be treated in a clinical trial. Response of both RT and CLL should be assessed at an early time point, and survival end points should be prioritized in trial design. We hope that these recommendations can help to harmonize clinical and translational research and improve outcomes for patients with RT.

PURPOSE Long-term androgen deprivation therapy (ADT) improves survival in men with high-risk localized prostate cancer (PCa) receiving radiotherapy (RT). Predictive biomarkers are needed to guide ADT duration. METHODS A multimodal artificial intelligence (MMAI)–derived predictive biomarker was trained for long-term (LT) versus short-term (ST) ADT using pretreatment digital prostate biopsy images and clinical data (age, prostate-specific antigen, Gleason, and T stage) from six NRG Oncology phase III randomized radiotherapy trials. The novel MMAI-derived biomarker was developed to predict the differential benefit of LT-ADT on the primary end point, distant metastasis (DM). MMAI predictive utility was validated on a seventh randomized trial, RTOG 9202 (N = 1,192), which randomly assigned men to RT + ST-ADT (4 months) versus RT + LT-ADT (28 months). Fine-Gray and cumulative incidence analyses for DM, and secondarily, death with DM, were performed. Deaths without DM were treated as competing risks. RESULTS In the validation cohort (median follow-up, 17.2 years), LT-ADT significantly improved DM from 26% to 17% (subdistribution hazard ratio [sHR], 0.64 [95% CI, 0.50 to 0.82], P < .001). A significant biomarker-treatment predictive interaction was observed ( P = .04) for DM, whereby MMAI biomarker–positive men (n = 785, 66%) had reduced DM with LT-ADT versus ST-ADT (sHR, 0.55 [95% CI, 0.41 to 0.73], P < .001), whereas no treatment benefit was observed for MMAI biomarker–negative men (n = 407; sHR, 1.06 [95% CI, 0.61 to 1.84], P = .84). The estimated 15-year DM risk difference between RT + LT-ADT and RT + ST-ADT was 14% in MMAI biomarker–positive men and 0% in MMAI biomarker–negative men. The MMAI biomarker was also prognostic for DM, irrespective of treatment (sHR, 2.35 [95% CI, 1.72 to 3.19], P < .001). CONCLUSION To our knowledge, the MMAI model is the first validated predictive biomarker to guide ADT duration with RT in localized/locally advanced PCa. Approximately one third of men with high-risk PCa could safely be spared the additional 24 months of ADT and the associated morbidity.

Background Falls in people with multiple sclerosis (pwMS) lead to morbidity and expense. Objective Identify clinical metrics associated with falls. Methods Eighty-six pwMS completed fall surveys, timed 25-foot walk (T25FW), and motion analysis with Clario Opal devices. Logistic regression models were created. Results Median age was 54.5 years (range 21–73), 62% (53) were female. The cohort included 58% with relapsing (50) and 42% with progressive MS (36). Those who reported falling in the last year were older (median age 58 vs 52.5, p = .03) and had a higher Patient Determined Disease Step (PDDS) score (median 3 vs 1, p < .0001). Falls were associated with worse balance metrics including sway area (median 2.3 degrees 2 vs 1.2, p = .01), jerk (median 3.3 m 2 /s 5 vs 1.6, p = .005), and slower T25FW (median 11.5 s vs 8; p < .0001). A multivariable regression model based on gait aid use and T25FW time >10.8 s (c = 0.80) was derived. Having both features portended a probability of falling of 0.97, while having neither, a probability of 0.26. Conclusions Falls in pwMS are more frequent in patients who are older, have higher PDDS, slower walking, and worse balance. Gait aid use and T25FW >10.8 s were strongly associated with falls in the past year.

Abstract Pulmonary hypertension is a complex and irreversible pulmonary vascular disease with a significant impact on patients’ lives. Pulmonary hypertension is categorized into five groups according to its etiology. Frailty is a multifaceted disorder that leads to physical, social, cognitive, and psychological decline. Several studies have linked a high occurrence of frailty to heart failure and chronic lung diseases, but the prevalence and impact of frailty in pulmonary arterial hypertension (PAH) remain largely unexplored. At the molecular level, inflammation, oxidative stress, cellular senescence, and mitochondrial dysfunction play pivotal roles in the pathophysiology of frailty in pulmonary hypertension. Dysfunction of cardiac, respiratory, and skeletal muscles results in exercise intolerance, which promotes deconditioning and frailty. Exercise training in PAH, heart failure, and chronic lung disease has shown promise in improving quality of life, exertion tolerance, and frailty scores. Properly designed studies are needed to elucidate the predictive value of frailty and to identify assessment and treatment tools in pulmonary hypertension, particularly PAH, to aid clinicians in individualizing care plans and improving patient outcomes. In this narrative review, we describe the pathobiology of frailty in pulmonary hypertension, assessment tools, the impact of frailty on different pulmonary hypertension groups, and suggestions for potential interventions.

Abstract Rationale Increased risk of coronavirus disease (COVID-19) hospitalization and death has been reported among patients with clinical lung disease. Objectives To test the association of objective measures of prepandemic lung function and structure with COVID-19 outcomes in U.S. adults. Methods Prepandemic obstruction (FEV1/FVC &lt; 0.70) and restriction (FEV1/FVC ⩾ 0.7, FVC &lt; 80%) were defined based on the most recent spirometry exam conducted in 11 prospective U.S. general population–based cohorts. Severe obstruction was classified by FEV1 &lt; 50%. Percentage emphysema, percentage high-attenuation areas, and interstitial lung abnormalities were defined on computed tomography in a subset. Incident COVID-19 was ascertained via questionnaires, serosurvey, and medical records from 2020 to 2023 and classified as severe (hospitalized or fatal) or nonsevere. Cause-specific hazard models were adjusted for sociodemographics, anthropometry, smoking, comorbidities, and COVID-19 vaccination status. Measurements and Main Results Among 29,323 participants (mean age, 67 yr), there were 748 severe incident COVID-19 cases over median follow-up of 17.3 months from March 1, 2020. Greater hazards of severe COVID-19 were associated with severe obstruction (vs. normal; adjusted hazard ratio [aHR], 2.11; 95% confidence interval [CI], 1.02–1.27), restriction (vs. normal; aHR, 1.40; 95% CI, 1.12–1.76), and percentage emphysema (highest vs. lowest quartile; aHR, 1.64; 95% CI, 1.03–2.61), but not greater high-attenuation areas or interstitial lung abnormalities. COVID-19 vaccination provided greater absolute risk reduction in these groups. Results were similar in participants without smoking, obesity, or clinical cardiopulmonary disease. Conclusions Prepandemic severe spirometric obstruction, spirometric restriction, and greater percentage emphysema lung on computed tomography were associated with risk of severe COVID-19. These findings support enhanced COVID-19 risk mitigation for individuals with impaired lung health and warrant further mechanistic studies on interactions of lung function, structure, and vulnerability to acute respiratory illnesses.

Background: Artificial intelligence (AI) platforms can potentially enhance clinical decision-making (CDM) in primary care settings. OpenEvidence (OE), an AI tool, draws from trusted sources to generate evidence-based medicine (EBM) recommendations to address clinical questions. However, its effectiveness in real-world primary care cases remains unknown. Objective: To evaluate the performance of OE in providing EBM recommendations for five common chronic conditions in primary care: hypertension, hyperlipidemia, diabetes mellitus type 2, depression, and obesity. Methods: Five patient cases were retrospectively analyzed. Physicians posed specific clinical questions, and OE responses were evaluated on clarity, relevance, evidence support, impact on CDM, and overall satisfaction. Four independent physicians provided ratings using a 0 to 4 scale. Results: OE provided accurate, evidence-based recommendations in all cases, aligning with physician plans. OE was scored on a scale of zero to four, where zero was very unclear, and four was very clear. Mean scores across cases were clarity (3.55 ± 0.60), relevance (3.75 ± 0.44), support (3.35 ± 0.49), and satisfaction (3.60 ± 0.60). However, the impact on CDM was limited (1.95 ± 1.05), as OE primarily reinforced rather than modified plans. Conclusion: OE was rated high in clarity, relevance, and evidence-based support, reinforcing physician decisions in common chronic conditions. While the impact on CDM was minimal due to the study’s retrospective nature, OE shows promise in augmenting the primary care physician. Prospective trials are needed to evaluate its utility in complex cases and multidisciplinary settings.

» Femoroacetabular impingement (FAI) is the premature contact of the femoral head-neck junction with the superior acetabular rim during hip range of motion, which may further damage intra-articular soft tissue structures and lead to the accelerated development of osteoarthritis. » FAI syndrome is diagnosed by a triad of symptoms, clinical signs, and imaging findings, and is a common cause of hip pain in young patients that have a significant impact on patient hip-related function and quality of life. » The treatment of FAI syndrome begins with noninvasive nonoperative modalities such as patient education and supervised exercise-based physical therapy. For recalcitrant symptoms, various injections have been explored for both diagnostic and therapeutic purposes; however, the efficacy of these interventions have generally not been demonstrated outside of the short term » In this article, we examine the available literature regarding the nonoperative treatment of FAI and provide insight into the effectiveness of current treatment modalities.