Citations

7518 Background: Monoclonal gammopathy of undetermined significance (MGUS) is common, yet only a minority progress to malignant plasma-cell disorders. Mayo risk stratification uses baseline factors and is commonly implemented/validated in a Cox proportional hazards (CoxPH) framework, which may miss prognostic longitudinal patterns. Methods: We assembled 15,158 MGUS patients with longitudinal laboratory data and progression outcomes (smoldering multiple myeloma, multiple myeloma, AL amyloidosis, or Waldenström macroglobulinemia). We compared a Mayo-factor Cox proportional hazards (CoxPH) baseline versus STRaTS, a transformer-based survival model, to predict progression risk at 3-, 5-, and 10-year horizons. STRaTS leveraged longitudinal trajectories of routine labs including hemoglobin, platelets, differential counts (neutrophils/lymphocytes/monocytes), immunoglobulins (IgG/IgA/IgM), free light chains (kappa/lambda), M-spike, and creatinine. To minimize bias, we used laboratory results collected from 1–3 years after diagnosis and started follow-up at year 3; patients progressing before year 3 or lacking follow-up beyond year 3 were excluded. A total of 7,305 patients met eligibility and were split into train/validation/test cohorts of 4,383/1,461/1,461. Discrimination was assessed by concordance index (C-index). Clinical operating performance was evaluated on a held-out test cohort by comparing sensitivity and specificity at the same proportion of patients selected for intensified surveillance (same workload). Results: Among MGUS patients with complete baseline Mayo factors(N=3,388), Kaplan–Meier–estimated 3-/5-/10-year cumulative progression risk was 0.1/0.4/3.4% (Low), 3.0/4.3/7.9% (Low-Intermediate), 4.4/6.4/14.1% (High-Intermediate), and 8.9/12.5/16.9% (High). On a held-out test cohort, STRaTS demonstrated superior discrimination versus the Mayo-factor CoxPH (C-index 0.75 vs 0.538; p<0.0001). Both models were trained and evaluated on identical train/test splits. At the same surveillance workload, STRaTS achieved higher sensitivity with comparable specificity; when 40.3% of patients were selected for closer surveillance, 3-year sensitivity was 81.0% for STRaTS versus 47.6% for CoxPH (Table). Conclusions: Among MGUS patients who remain progression-free at 3 years, transformer-based survival modeling of longitudinal laboratory trajectories provides more accurate individualized conditional progression risk estimates and improved workload-matched identification of progressors compared with the conventional Mayo/Cox approach. Sensitivity/specificity (%). Operating Point Flagged % STRaTS Sens / Spec (%) CoxPH Sens / Spec (%) Int+High, 3y 40.3 81.0 / 58.5 47.6 / 58.9 Int+High, 5y 40.3 81.2 / 60.4 46.9 / 58.8 Int+High, 10y 40.3 25.0 / 56.3 23.8 / 58.7 Two-Group High (≥2 factors), 5y 5.6 37.4 / 93.4 35.4 / 93.1

560 Background: Patients (pts) with early stage hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer (BC) remain at both short and long term risk of recurrence. While clinico-pathological and gene-based biomarkers provide insight into early and late recurrence risk, additional prognostic tools are needed. We previously developed (Saha et al. Clin Cancer Res , 2025) a new breast MRI image-based artificial intelligence prognostic tool (TumorSight Risk) composed of both radiographic and clinical information. Here we sought to validate this tool in an independent cohort. Methods: In this multi-center, blinded, prospective/retrospective validation study, we sought to validate the 5-year recurrence-free survival (RFS) according to pre-defined risk scores (0-100) and categories (“high” or “low”) via pre-specified cutoff (≥47) for pts with HR+/HER2- BC. Kaplan-Meier and Cox regression analyses were then used to assess the unadjusted and adjusted association between risk category/score and the 5-year RFS. Results: 2,129 pts with HR+/HER2- BC diagnosed between January 1, 2010, and December 31, 2024, who underwent breast MRI prior to surgery (no neoadjuvant therapy) were included from four institutions. Median age was 57 years, 16% were Black, 15% had grade 3 disease, 93% were clinical T1 or T2, and 85%/15% were clinical N0/N1. At a median follow up of 6.24 years, the unadjusted hazard ratio (HR) for RFS comparing low (n=1808) and high risk (n=321) pts was 2.71 (95% CI = 1.95 – 3.76, p = 3x10 -9 ). The estimated 5 year RFS rate according to risk score (low and high) was 95.5% (95% CI: 94.63 – 96.3%) and 89.6% (95% CI = 86.4 – 92.6%) while the 10 year RFS estimates were 88.9% (95% CI = 86.5 - 90.9%) and 69.6% (95% CI = 59.1 – 77.9%). Univariate subgroup analysis demonstrated that the risk score was prognostic by age (< 50 vs. ≥50 years), pathologic nodal status, grade, and surgery type, regardless of chemo-, endocrine, or radiation therapy administration. The observed continuous risk score was strongly associated with risk of recurrence, with a 22% increase in relative risk per 10-unit change in risk score (0-100), translating to a 2.4% (95% CI = 1.2 – 4.5%) and 25.5% (95% CI = 15.4 – 40.4%) risk of recurrence at 5-years for pts at the lowest (0-9) versus highest (90-100) risk score. The prognostic association between risk score and RFS remained after adjusting for pathologic T- and N-stage, grade, age, race, and treatment (p = 0.002). Conclusions: TumorSight Risk is a new image-based biomarker for HR+/HER2- BC that provides prognostic information independent of standard clinico-pathological parameters. Given the ready availability of breast MRI in most pts with BC, TumorSight Risk may be a convenient tool for estimating risk for recurrence.

Estimates of fibromyalgia prevalence vary widely worldwide due to differences in diagnostic criteria, study methodology, and population characteristics. Accurate estimates are essential to inform population-level surveillance, guide resource allocation, and highlight disparities in disease recognition and access to care. The objective of this systematic review and meta-analysis was to determine the global prevalence of fibromyalgia in the general population, and secondarily to identify factors moderating prevalence variation and to assess prevalence in defined at-risk subpopulations. Pooled prevalence estimates with 95% confidence intervals (CIs) were calculated using the inverse variance heterogeneity model with Freeman–Tukey transformation. Subgroup analyses were performed by sex, diagnostic criteria, country, and other study characteristics, and meta-regression assessed moderators including publication year and Human Development Index (HDI). Of 21,645 records identified, 1,728 underwent full-text review and 882 studies were included in the final analysis. Across 38 countries and 30,070,032 individuals (188 studies), the pooled fibromyalgia prevalence in the general population was 1.40% (95% CI, 0.49–2.47), with substantial heterogeneity (I 2 = 100%) and very low certainty of evidence. Among at-risk subpopulations (9,771,123 participants; 768 studies), prevalence was markedly higher in autoimmune and inflammatory conditions, such as chronic urticaria (37.1%), interstitial cystitis (30.8%), systemic sclerosis (20.6%), celiac disease (20.5%), and inflammatory bowel disease (19.9%), and elevated in chronic pain, rheumatologic, and post-infection cohorts. Meta-regression identified publication year (β = 0.008, P < .001) and HDI (β = 0.725, P = .002) as significant moderators of prevalence. In conclusion, fibromyalgia affects 1% to 2% of the global population, with substantially higher rates in at-risk subpopulations. Temporal and socioeconomic trends emphasize diagnostic inconsistency and global disparities in care.

Abstract Inflammatory bowel diseases (IBD), principally Crohn’s disease (CD) and ulcerative colitis (UC), are common chronic disorders involving inflammation and often progressive tissue damage. Genome-wide association studies have mapped many risk signals, but the causal variants, effector genes and relevant cellular contexts remain difficult to resolve, limiting mechanistic interpretation and therapeutic translation. Here we performed a multi-ancestry GWAS meta-analysis of 125,992 individuals with IBD and more than 1.2 million controls, identifying 619 independent association signals (374 novel) at 420 IBD regions that account for 77–80% of SNP-based heritability. Fine-mapping resolved 81 high-confidence variants, 41 not previously reported. Although most signals were shared between CD and UC, 39% showed IBD subtype specificity, with UC signals showing stronger enrichment in functional annotations from intestinal epithelial, secretory and enteroendocrine cells, and CD showing stronger genetic correlations with circulating inflammatory biomarkers, including C-reactive protein and glycoprotein acetylation. Latent causal modelling supported a causal effect of decreased high-density lipoprotein on CD risk. By integrating bulk and single-cell eQTL and pQTL resources using colocalisation and Mendelian randomisation, together with coding-variant evidence from exome sequencing, we prioritised 664 candidate effector genes across 341 signals, including 390 newly implicated IBD genes, revealing new biological mechanisms and candidate therapeutic targets supported by human genetics.

ABSTRACT Objectives The increasing volume of medical education research necessitates efficient, reliable, and scalable methods for conducting quality appraisals. The Medical Education Research Study Quality Instrument (MERSQI) is a widely used tool, although its manual scoring process remains resource‐intensive. This study evaluated how well large language models (LLMs) appraise medical education research using the MERSQI tool in comparison with human judges. Methods Three LLMs (GPT‐5, Claude Sonnet 4, and Gemini 2.5 Pro) assigned MERSQI domain scores to 1423 medical education research articles. The authors compared AI‐generated scores with human‐generated scores using intraclass correlation coefficients (ICCs) across the six MERSQI domains. They evaluated the agreement between AI‐ and human‐generated MERSQI composite scores using Bland–Altman plots. Results Domain‐level ICC values ranged from fair (0.24) to near perfect (0.81), with the lowest agreement observed in the ‘sampling,’ ‘validity evidence,’ and ‘data analysis’ domains. No single LLM consistently outperformed the others across all domains. Composite score agreement with human ratings was substantial and similar across LLMs (ICC range: 0.65–0.69). GPT‐5 produced slightly lower composite scores than humans, while Claude Sonnet 4 and Gemini 2.5 Pro produced higher scores, with Gemini showing the largest deviation. The Bland–Altman plots for Gemini 2.5 Pro suggested proportional bias, indicating its agreement with human scores varied across the range of study quality. Conclusions These LLMs demonstrated substantial agreement with human raters for MERSQI composite scores, but domain‐level agreement varied. Systematic differences in scoring patterns highlight the need for human oversight and additional calibrations before integrating LLMs into systematic review appraisal workflows.

ABSTRACT Multistate models offer a powerful framework for studying disease processes and can be used to formulate intensity‐based and more descriptive marginal regression models. They also represent a natural foundation for the construction of joint models for disease processes and dynamic marker processes, as well as joint models incorporating random censoring and intermittent observation times. This article reviews the ways multistate models can be formed and fitted to life history data. Recent work on pseudo‐values and the incorporation of random effects to model dependence on the process history and between‐process heterogeneity are also discussed. The software available to facilitate such analyses is listed.

Importance Chronic pain is a leading cause of disability, and many affected patients rely on long-term opioid therapy despite its unfavorable adverse effect profile. Spinal cord stimulation is an established therapy for chronic pain that may secondarily reduce opioid consumption by providing sustained analgesia. Objective To quantify changes in opioid use following spinal cord stimulation implantation for the treatment of chronic pain through a systematic review and meta-analysis. Data sources We conducted a comprehensive search of MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Scopus from each database’s inception to July 1, 2024. Study selection We included studies describing patients who underwent spinal cord stimulator implantation for the treatment of chronic pain. A total of 2,784 potential studies were identified and screened by multiple independent reviewers, yielding a final total of 43 studies included in the systematic review. Data extraction and synthesis Data extraction was completed by multiple independent reviewers following Preferred Reporting Items for Systematic Reviews and Meta-Analysis and Meta-analysis Of Observational Studies in Epidemiology guidelines. A random effects model with Hartung-Knapp-Sidik-Jonkman adjustment was used to estimate pooled estimates. Certainty assessment was performed following the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework. Main outcome(s) and measure(s) The primary outcomes were change in continuous opioid use (ie, morphine milligram equivalent (MME)) and categorical opioid use (yes/no) from preimplantation to 12 months following spinal cord stimulator implantation. Results Meta-analysis of 12 month continuous MME use comprising 22 study comparisons (1,666 individuals) revealed a weighted mean difference of −18.06 MME (95% CI −24.41 to −11.70; 95% prediction interval −38.29 to 2.17; p<0.001). Meta-analysis of categorical opioid use at 12 months comprising 24 study comparisons (1,527 individuals) revealed an OR of 0.47 (95% CI 0.30 to 0.75; 95% prediction interval 0.10 to 2.11; p=0.003), signifying lower odds of opioid continuation. Conclusions and relevance Spinal cord stimulation is associated with reduced opioid dose consumption and increased odds of opioid cessation at 12 months postimplantation compared with baseline in patients with chronic pain; however, both of these conclusions are supported by evidence of very low GRADE certainty. PROSPERO registration number CRD42024574921.

Abstract Inflammatory bowel disease (IBD) is a chronic immune-mediated disorder of the gastrointestinal tract whose genetic basis is only partly resolved because most risk variants identified by genome-wide association studies (GWAS) lie in non-coding regions, limiting direct gene assignment and biological interpretation 1,2 . Here we analysed whole-exome and whole-genome sequencing data from 86,213 IBD cases and 478,363 controls of European ancestry. We identified 68 IBD genes directly implicated by conditionally independent protein-coding associations across the allele frequency spectrum. Many newly implicated IBD genes are supported by orthogonal genomic or pleiotropic evidence, pointing to disease-related pathways and nominating targets with therapeutic relevance. We further identified allelic series and non-additive effects at key loci such as NOD2 and TYK2. These results show that large-scale sequencing can resolve disease genes and pathways that remain ambiguous from non-coding association alone, providing a more direct route from human genetics to biological insight and therapeutic hypotheses.

Summary Renal response (RenR) in light‐chain (AL) amyloidosis is associated with a lower risk of end‐stage kidney disease and improved survival. However, substantial variation exists in the time to and depth of RenR. We investigated variables associated with RenR in a retrospective study of newly diagnosed AL amyloidosis patients ( n = 350) assessable for RenR between 2010 and 2022. RenRs were recorded at 6, 12 and 24 months and best response. Deep RenR was defined as a ≥renal very good partial response (RenVGPR, >60% reduction in 24‐h proteinuria or ≤200 mg). Logistic regression and competing risk methods were used to examine variables associated with RenR. The median age was 64 years, and median follow‐up was 5.5 years. On multivariable logistic regression, obtaining ≥HemVGPR within 6 months, kappa isotype, high baseline difference between involved and uninvolved free light chains (dFLC ≥40 mg/dL), renal stage and autologous haematopoietic stem cell transplant (AHSCT) were significantly associated with deep RenR. Cumulative incidence rates for deep RenR, treating death or renal progression as a competing event, demonstrated that early HemR, first‐line AHSCT, lower renal stage and dFLC ≥40 mg/dL significantly increased the likelihood of deep RenR. Specific clonal plasma cell features, namely light‐chain isotype and baseline dFLC levels, independently influence the timing and depth of RenRs in AL amyloidosis following treatment, in addition to renal stage and HemR.

Abstract The genetic contributions of the X chromosome to Alzheimer’s disease (AD) remain poorly understood yet are expected to importantly shape sex differences in AD. We therefore performed large-scale X-chromosome-wide association studies (N=1,240,451), evaluating differential risk due to sex, APOE *4, and escape from X-chromosome inactivation, finding most X-linked loci appear relevant to female-biased AD etiology. In evaluating genetic pleiotropy with hormonal, lipid, and brain imaging traits, we discovered X-linked AD loci converged on white matter traits, particularly in the anterior corona radiata and splenium of the corpus callosum. Through brain-centric functional genomics analyses, we then nominated candidate causal genes, including 5 that appeared highly robust. Notably, we found the escape gene RBBP7 decreases AD risk in APOE *4 carriers likely through higher expression in excitatory neurons to counter tau-related neurodegeneration. Altogether, we provide an atlas of sex and APOE *4-informed candidate X-linked AD risk loci, genes, and mechanisms that will guide future studies.