Citations

Importance Pyoderma gangrenosum (PG) is a rare neutrophilic dermatosis characterized by sterile ulcerative skin lesions. Multiple comorbidities and clinical features have been associated with PG, but no standardized guidelines exist for classifying PG phenotypes. Objective To develop an expert-established classification framework for PG phenotypes to inform treatment guidelines and future research endeavors. Evidence Review In this modified Delphi consensus study that included 23 board-certified dermatologists and Medical Dermatology Society members with expertise in PG, panelists completed 5 rounds of anonymous, iterative online surveys that were administered from December 2023 through July 2025. Before the beginning of the consensus exercise, a literature review was performed by nonvoting researchers to summarize existing data on PG clinical associations and comorbidities. A PubMed search from inception to September 2023 identified observational studies, narrative reviews, systematic reviews, and meta-analyses describing PG clinical associations and comorbidities that were published in English. Experts indicated their agreement with proposed PG phenotypes and disease modifiers with a consensus threshold of 70% or greater. Anonymous comments and aggregated results were presented in each subsequent round. In the final round, a framework of PG phenotypes and disease modifiers was proposed for agreement. Findings Twenty-three board-certified dermatologists and Medical Dermatology Society members with expertise in PG completed 5 rounds of iterative surveys. Consensus was reached on the final set of PG phenotypes and disease modifiers, with 83% of experts in agreement. PG phenotypes were overall classified into 2 major groups: PG with autoinflammatory syndromes and nonsyndromic PG. Nonsyndromic PG included 4 phenotypes: inflammatory bowel disease–associated PG, PG in association with hematologic cancers and blood dyscrasias, drug-induced PG, and other (including idiopathic) PG. Disease modifiers of PG phenotype presentations included involvement of special sites (head/neck, genitals, or peristomal skin) and extracutaneous manifestations. Conclusions and Relevance This expert-established, descriptive framework provides a standardized classification system for distinct PG phenotypes and its modifiers. This nomenclature may inform upcoming clinical guidelines and allow for consistency in reporting epidemiological research and outcomes among patients with PG.

Importance Although adding immune checkpoint inhibitors to neoadjuvant chemotherapy improves outcomes in high-risk early-stage breast cancer, opportunities remain to further enhance response. Dual checkpoint blockade offers a potential strategy to further enhance efficacy. Objective To evaluate the combination of anti−programmed cell death 1 protein (PD-1) cemiplimab and anti−lymphocyte activation gene 3 (LAG-3) added to neoadjuvant therapy in ERBB2 -negative early-stage, high-risk breast cancer. Design, Setting, and Participants The I-SPY2 (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis 2) is an ongoing randomized clinical platform trial being conducted at multiple US clinical sites including patients with early-stage (II or III) ERBB2 -negative, high-risk breast cancer. Participants, continuously enrolled since 2010, were adaptively randomized from February 2, 2020, to December 9, 2021, to one of several experimental neoadjuvant therapies or control groups based on receptor subtypes defined by hormone receptor (HR), ERBB2 status, and MammaPrint (Agendia Inc) molecular risk, categorized as high (MP1) or ultrahigh (MP2). Data were analyzed from January 1, 2022, to August 5, 2025. Interventions Both groups received weekly paclitaxel for 12 weeks, then doxorubicin and cyclophosphamide followed by surgery; concomitant with paclitaxel, the intervention group also received 4 doses of cemiplimab and fianlimab (PCF) every 3 weeks. Main Outcomes and Measures Pathologic complete response (pCR). Treatments graduated when they achieved 85% bayesian probability of success in a subtype-specific phase 3 trial. Pathway-specific biomarkers were assessed for response prediction. Results A total of 78 participants (mean [SD] age, 47 [39-54] years) were randomized to the intervention group, with 350 participants (mean [SD] age, 48 [39-57] years) randomized to the historical control population. PCF graduated in all clinical signatures, with pCR rates vs control of 44% (95% CI, 34%-53%) vs 21% (95% CI, 17%-25%) in all ERBB2 , 53% (95% CI, 39%-67%) vs 29% (95% CI, 22%-36%) in triple-negative, and 36% (95% CI, 23%-49%) vs 14% (95% CI, 9%-19%) in HR-positive and ERBB2 -negative disease. Among the total participants, 16 (21%) experienced adrenal insufficiency, including hypophysitis (11% grade 3 or 4), mostly occurring after immunotherapy completion. PCF was found to be highly effective in the subset of patients with immune signature positive status (ImPrint positive). Conclusions and Relevance In this randomized clinical trial, the combination of PD-1 and anti−LAG-3 inhibition with standard NAC was effective in early-stage ERBB2 -negative breast cancer, particularly in patients displaying a positive ImPrint immune signature. These results warrant further definitive trials. Trial Registration ClinicalTrials.gov Identifier: NCT01042379

Abstract Background Molecular underpinnings and clinical characteristics of ERBB2/HER2-mutated colorectal cancers (CRCs) remain poorly understood. We aimed to comprehensively characterize the genomic landscape and clinical features of ERBB2/HER2-mutated CRC and to compare them with those of ERBB2/HER2-amplified CRC. Patients and methods We analyzed cBioPortal data from 4348 CRC patients with available ERBB2/HER2 profiling. Clinicodemographic features, microsatellite instability (MSI), tumor mutational burden, and alterations in 94 cancer-associated genes were evaluated using chi-square/Fisher’s exact test, Kruskal–Wallis test, and hierarchical clustering. Results ERBB2/HER2 putative driver mutations were identified in 95 patients (2.2%), amplifications in 87 (2.0%), and wild-type status in 4166 (95.8%). In the overall cohort, ERBB2/HER2-mutated tumors demonstrated significant KRAS enrichment (50.5%) compared to wild-type (37.7%; P = .014) and amplified tumors (18.4%; P < .001), alongside MSI enrichment (37.2% vs 1.6%; P < .001), elevated tumor mutational burden, and right-sided predominance. ERBB2/HER2-mutated tumors also showed broad driver co-alterations largely reflecting their MSI background. In contrast, ERBB2/HER2-amplified tumors exhibited left-sided predominance, with microsatellite stable (MSS)-restricted analyses revealing selective mutual exclusivity with KRAS (Log2 OR = −1.58; q = 0.019) and TP53 co-occurrence (Log2 OR = 2.04; q = 0.019). Hierarchical clustering confirmed that mutated and amplified tumors consistently occupy separate clusters across anatomical sites. Conclusion ERBB2/HER2 mutations and amplifications represent molecularly and clinically distinct subgroups. ERBB2/HER2-mutated tumors are characterized by an MSI-enriched, hypermutated background with frequent concurrent KRAS alterations, whereas amplified tumors exhibit selective KRAS mutual exclusivity and TP53 co-occurrence. These exploratory findings support alteration-specific therapeutic strategies in CRC.

Abstract Objectives Embedded pragmatic clinical trials (ePCTs) are conducted as part of routine clinical care and therefore use data collected from real-world data sources, such as electronic health record systems and administrative claims. A common approach for using these types of data across all phases of trial conduct is to create a computable phenotype (an explicitly defined data query data, including specified data types, data codes, and logical parameters) to capture patients with a clinical condition, exposure, symptom, characteristic, treatment, or outcome of interest. Materials and Methods The Electronic Health Record (EHR) Core Working Group of the NIH Pragmatic Trials Collaboratory captured the experiences of investigators in developing, adapting, and applying computable phenotype definitions in their studies. Results Four case studies describe different approaches to developing and using computable phenotypes in pragmatic trials. Discussion We recommend: (1) developing computable phenotypes as part of a team with multiple areas of expertise; (2) appropriate validation; (3) dissemination of salient details regarding phenotype creation; and (4) capturing and reporting any modifications made to phenotypes during the conduct of the trial. Conclusion A range of issues and decisions influence how computable phenotypes are developed and used in pragmatic clinical trials. Multidisciplinary teams that understand the context of the data, including the reason the data are collected and potential sources of bias, are best suited for the development and validation of phenotypes for ePCTs.

Abstract Introduction Distinct temperature patterns have long been recognized to correlate with fevers of differing etiologies. While the use of wearable sensors for high-frequency temperature monitoring (HFTM) on a near minute-by-minute basis has been shown to detect fevers earlier than standard-of-care nursing vital sign assessments in hospitalized patients, leveraging these high-resolution datasets to computationally identify unique digital signatures for real-time diagnosis of underlying fever etiology has not been widely explored. Diagnostic uncertainty is common in patients undergoing hematopoietic stem cell transplantation (HCT), with only 20–30% of febrile neutropenic episodes being microbiologically documented. We hypothesized that unique temperature patterns extracted from HFTM data collected during episodes of febrile neutropenia could be used to develop a supervised machine learning classifier capable of accurately predicting underlying fever etiology in HCT patients. Methods We analyzed 68 clinically independent fever episodes recorded in HCT patients (n=90) outfitted with an FDA-cleared wireless temperature sensor (TempTraq®, BlueSpark Technologies) that measured axillary temperature every 2 minutes throughout hospitalization. Time-series features were extracted from temperature traces spanning 1 hour before to 3 hours after fever onset and used to train a suite of machine-learning models to distinguish engraftment fevers from other fever etiologies. Model training and evaluation were performed using repeated stratified 5-fold patient-level cross-validation, yielding 100 train-test evaluations. Results Among all classification models, the logistic regression classifier provided the best overall performance and interpretability, achieving 94% specificity (95% CI, 0.84–1.0) for identifying engraftment fevers with a mean AUROC of 0.88 ± 0.10. Feature importance analysis demonstrated that both clinical variables and HFTM-derived temperature dynamics contributed to model performance, with a strong reliance on time-series features captured within the first 4 hours of fever onset. Conclusion Our study provides a demonstration that continuous temperature data collected from patients outfitted with wearable sensors can be leveraged not only for early fever detection but also for machine learning–based diagnosis of fever etiology. These findings suggest that dynamic temperature patterns contain clinically meaningful physiologic information that with further studies could support real-time diagnostic decision-making and guide safe de-escalation of empiric antibiotics during febrile neutropenia in patients undergoing intensive cancer therapy.

PURPOSE Bone metastases (BM) occur in approximately 30% of patients with metastatic renal cell carcinoma (mRCC) and are associated with poor survival and symptomatic skeletal events (SSEs). Radium-223, an alpha-emitting bone-seeking radioisotope, and cabozantinib, a tyrosine kinase inhibitor, have demonstrated activity in BM. RADICAL (Alliance A031801; ClinicalTrials.gov identifier: NCT04071223 ) evaluated cabozantinib ± radium-223 in mRCC with BM. METHODS This phase II trial enrolled patients with mRCC of any histology with ≥1 BM. Patients were randomly assigned 1:1 to cabozantinib ± radium-223, stratified by osteoclast-targeted therapy (OTT), prior therapy, opioid use, and International mRCC Database Consortium (IMDC) risk. The primary end point was SSE-free survival (SSE-FS). Secondary end points included safety, objective response rate (ORR), progression-free survival, and overall survival (OS). A target of 124 evaluable patients was planned, with a prespecified interim futility analysis at 50% of expected SSE-FS events; the trial would stop if the stratified hazard ratio (sHR) > 1.0. RESULTS The prespecified interim futility analysis was conducted after 90 patients were enrolled and crossed the futility boundary, leading to closure at 98 patients. The final analysis included all 98 patients. Median age was 63 years, 82.7% had clear cell histology, and 79.6% were using an OTT. IMDC risk was favorable (18.4%), intermediate (67.3%), and poor (14.3%). Median follow-up was 13.1 months. Median SSE-FS for cabozantinib with radium-223 versus cabozantinib was 16.7 versus 17.6 months (sHR, 1.46 [90% CI, 0.86 to 2.51]). Median OS was 28.3 versus 19.7 months (sHR, 1.40 [95% CI, 0.70 to 2.79]). ORR was 19.4% versus 25.0% ( P = .78). Grade ≥3 adverse events were similar across arms (69.6% v 75.5%). CONCLUSION Radium-223 did not improve SSE-FS when added to cabozantinib. The combination demonstrated a manageable safety profile.

Abstract Background There is limited data on immune checkpoint inhibitor (ICI) use in patients with non-small cell lung cancer (NSCLC) and known pericardial effusions. Methods This international multi-center observational retrospective study included patients with advanced NSCLC with or without pericardial effusions receiving ICIs. Immune-related adverse events (irAEs) were graded per CTCAE v5.0. Overall survival (OS) and progression-free survival (PFS) were estimated by the Kaplan-Meier method. Cox proportional hazards multivariable models assessed the association between survival outcomes and clinicopathologic variables, and an inverse probability of treatment weighting (IPTW) model compared outcomes between the two groups. Results A total of 1248 patients with advanced NSCLC treated with ICIs across 13 institutions were included. Of these, 85 patients (6.8%) had pre-existing pericardial effusions. Compared to controls, patients with pericardial effusions were younger (median age 63 vs 67 years, P = .007), diagnosed more frequently with PD-L1 positive tumors (96% vs 76%, P < .001), and had a higher median number of baseline metastatic sites (3 vs 1, P < .001). IrAEs were similar between both groups (42% vs 38%), and no cardiac irAEs occurred in patients with pericardial effusions. PFS (median 5.6 vs 4.6 months, P = .3) and OS (median 10.2 vs 14.7 months, P = .50) were not statistically different between patients with pericardial effusions and the controls, respectively. In both multivariable and IPTW models, pericardial effusions were not associated with PFS or OS. Conclusions Among patients with NSCLC and pre-existing pericardial effusions, ICIs demonstrate meaningful clinical benefit similar to those without effusions, with no new cardiac or severe toxicities.

ABSTRACT Introduction Multiple myeloma is a malignant plasma cell disorder predominantly affecting older adults and poses a significant health burden due to its incurable nature, high relapse rate, and associated immune dysfunction. Daratumumab, when added to standard therapy, has shown promising results in large trials. This meta‐analysis compared clinical trials of daratumumab‐containing regimens with standard therapies in the treatment of multiple myeloma. The primary outcomes analyzed were overall response rate (ORR) and progression‐free survival (PFS). Methods A systematic search of PubMed, Scopus, Cochrane CENTRAL, and Google Scholar was performed from January 2015 through December 2024. After screening via Rayyan, data were extracted on an Excel spreadsheet. Quality was assessed using the Cochrane RoB 2.0 tool. Eligible randomized controlled trials (RCTs) were included and analyzed using RevMan 5.4. Outcomes assessed were ORR and PFS. Adverse effects were compared among therapies. Results Nine Phase III RCTs ( n = 4556) were included, with a mean follow‐up of 44.3 months. Daratumumab‐based regimens significantly improved PFS (HR 0.55, 95% CI 0.46–0.66) but did not confer a statistically significant overall survival advantage (RR 0.90, p = 0.25). ORR was inconsistent, with five trials favoring daratumumab and one favoring control. Safety analyses showed higher risks of pneumonia (RR 1.74, p < 0.0001), secondary malignancies (RR 1.46, p = 0.003), neutropenia (RR 1.25, p = 0.006), and thrombocytopenia (RR 1.17, p = 0.01). Lymphopenia showed a numerical increase but was not statistically significant. Conclusion Daratumumab plus standard therapy regimens significantly improve PFS in multiple myeloma, though the overall survival benefit remains unproven. While efficacy is notable, treatment is associated with increased risks of infections, hematological toxicities, and secondary malignancies, highlighting the need for careful patient selection and vigilant monitoring. Trial Registration The authors have confirmed clinical trial registration is not needed for this submission.