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ABSTRACT Background Post‐transplant malignancy is a major determinant of long‐term outcomes after solid organ transplantation. Whether simultaneous pancreas–kidney (SPK) transplantation confers a differential post‐transplant cancer risk compared With kidney transplantation alone (KA) remains uncertain. Methods We conducted a retrospective propensity score–matched cohort study of adult transplant recipients at three Mayo Clinic sites between 2001 and 2017. SPK recipients ( n = 484) were matched 1:1 with KA recipients using propensity scores. The primary outcome was post‐transplant cancer incidence analyzed using Fine–Gray competing risks regression with death as a competing event. Standardized incidence ratios (SIRs) were calculated relative to the US general population. Cox proportional hazards models with cancer modeled as a time‐varying covariate evaluated associations with mortality and death‐censored graft failure. Results Over a median follow‐up of 10 years, overall cancer incidence was similar between SPK and KA recipients (subdistribution hazard ratio [sHR] 0.80, 95% CI 0.63–1.02; p = 0.07). The observed trend toward lower cancer incidence in SPK recipients was driven by a lower incidence of non‐melanoma skin cancer (NMSC) (sHR 0.72, 95% CI 0.53–0.97; p = 0.03), which was attenuated after age adjustment (sHR 0.76, p = 0.07). Incidence of other malignancies did not differ between groups. Compared with the US general population, cancer risk excluding NMSC was approximately twofold higher in both cohorts (SIR 2.18 for SPK vs. 2.23 for KA). Incident malignancy was strongly associated with increased mortality (HR 3.40 in KA and 2.07 in SPK) but not with a statistically significant increase in graft failure. Conclusions In this propensity score–matched cohort study, overall post‐transplant malignancy incidence was comparable between SPK and KA recipients. Both groups experienced substantially elevated cancer risk relative to the general population, and incident malignancy was strongly associated with mortality. These findings suggest that malignancy risk is driven primarily by shared immunologic and demographic factors rather than transplant type.

Hypothyroidism, also called&nbsp;underactive thyroid&nbsp;or&nbsp;low thyroid, is a&nbsp;disorder of the endocrine system&nbsp;in which the&nbsp;thyroid gland&nbsp;does not produce enough&nbsp;thyroid hormone.&nbsp;It can cause a number of symptoms, such as&nbsp;poor ability to tolerate cold, a&nbsp;feeling of tiredness,&nbsp;constipation,&nbsp;depression, and&nbsp;weight gain.&nbsp;Occasionally there may be swelling of the front part of the neck due to&nbsp;goiter.&nbsp;Untreated cases of hypothyroidism during&nbsp;pregnancy&nbsp;can lead to delays in&nbsp;growth and intellectual development&nbsp;in the baby or&nbsp;congenital iodine deficiency syndrome.<br /> Worldwide,&nbsp;too little iodine&nbsp;in the diet is the most common cause of hypothyroidism.&nbsp;Hashimoto's thyroiditis&nbsp;is the most common cause of hypothyroidism in countries with sufficient dietary iodine.&nbsp;Less common causes include previous treatment with&nbsp;radioactive iodine, injury to the&nbsp;hypothalamus&nbsp;or the&nbsp;anterior pituitary&nbsp;gland, certain medications,&nbsp;a lack of a functioning thyroid at birth, or previous&nbsp;thyroid surgery.&nbsp;The diagnosis of hypothyroidism, when suspected, can be confirmed with&nbsp;blood tests&nbsp;measuring&nbsp;thyroid-stimulating hormone&nbsp;(TSH) and&nbsp;thyroxine&nbsp;levels.

BACKGROUND: Primary aldosteronism (PA) is a common and treatable cause of hypertension, yet data on the durability of medical treatment response beyond the first year are limited. Using the PA medical treatment outcomes framework, we evaluated long-term biochemical and clinical outcomes and factors associated with treatment response. METHODS: We conducted an international, multicenter, observational cohort study across 27 centers on 4 continents. Adults with PA treated with mineralocorticoid receptor antagonists and/or epithelial sodium channel blockers between 2016 and 2021 were included if follow-up data were available at ≥12 months. Biochemical and clinical responses were classified as complete, partial, or absent using PA medical treatment outcomes criteria. Ordinal logistic regression identified determinants of a favorable treatment response. RESULTS: The cohort included 1292 patients (47.5% women, mean age 52 years) with a median follow-up of 34 months (interquartile range, 21–51). At ≥12 months, 58.3% achieved a complete biochemical response, and 20.8% achieved a complete clinical response, with only 5% showing no response. Determinants of a favorable biochemical response included lower aldosterone and lateralization index, and higher renin and potassium levels at baseline. In those taking spironolactone, a higher daily dose was also associated with a favorable biochemical response. Determinants of a favorable clinical response included female sex, lower body mass index, shorter duration of hypertension, and absence of hypertension-mediated organ damage. CONCLUSIONS: Targeted medical therapy for PA can deliver sustained biochemical and clinical benefits. Early disease detection and adequate dose titration are highly actionable determinants of long-term treatment success.

The accurate diagnosis of disorders of gut-brain interaction (DGBI), such as functional dyspepsia and irritable bowel syndrome, is crucial for improving patient symptoms, outcomes and ultimately, quality of life. However, busy clinicians often face challenges in diagnosing and managing these conditions, particularly when patients present with non-specific gastrointestinal symptoms together with psychosocial distress and/or social issues. DGBI are among the most common reasons for gastroenterology referral, with a global prevalence of approximately 40% in adults based on large-scale epidemiologic studies. While diagnostic algorithms aid in positively identifying DGBI, they often overlook key factors influencing treatment decisions. The Rome V Multidimensional Clinical Profile (MDCP) offers a comprehensive, patient-centered framework that extends beyond diagnosis alone. It integrates five core domains: (1) the primary diagnosis, (2) clinical modifiers, (3) impact on daily activities and quality of life, (4) psychosocial modifiers, and (5) physiological features and biomarkers. By considering comorbidities, illness severity, psychosocial contributors, and potential biomarkers, the MDCP enables clinicians to develop a holistic understanding of the patient's condition. This multidimensional approach facilitates tailored, evidence-based treatment plans that address the biopsychosocial aspects of DGBI, ultimately enhancing symptom management and patient well-being. Furthermore, it highlights gaps in knowledge and stimulates targeted research into these highly prevalent disorders. This case-oriented educational review will evaluate three DGBIs – functional dyspepsia, irritable bowel syndrome, and chronic abdominal pain – using the MDCP approach.

ABSTRACT Background and Objectives Surgical management of ipsilateral breast tumor recurrence (IBTR) is often mastectomy. No guidelines specifically address contralateral prophylactic mastectomy (CPM) for this population. We assessed factors associated with CPM at the time of IBTR mastectomy. Methods Patients undergoing mastectomy for IBTR (10/2008‐5/2024) were identified. Demographics, tumor characteristics, and treatment details were assessed. Results Of the 381 eligible IBTR patients, 221 (58.0%) had a unilateral therapeutic mastectomy and 160 (42.0%) underwent mastectomy with CPM. CPM patients were younger ( p < 0.0001), with lower clinical T category tumors ( p < 0.001) and less HR + HER2‐ invasive disease ( p = 0.004). CPM patients were more likely to undergo germline genetic testing (63.1% vs 41.6%, p < 0.0001) and were twice as likely to have immediate breast reconstruction ( p < 0.0001). On multivariable analysis, younger age, HR‐HER2 + IBTR subtype, pathogenic variants known at the time of surgery (relative to negative testing and/or no genetic testing), immediate breast reconstruction, and prior radiation for index cancer were each associated with CPM (all p < 0.05). Conclusion In our series of 381 patients treated with mastectomy for IBTR, 42% also had a CPM. Multiple factors, including age, tumor stage and biology, immediate breast reconstruction, and genetic testing may impact CPM choice.

Abstract Background Breast cancer is etiologically heterogeneous, but which risk factors differ in their associations across tumor subtypes remains unclear. We conducted a large, pooled analysis to evaluate independent, dose-response associations between breast cancer risk factors and quantitative tumor features. Methods Analyses of 15,731 invasive breast cancers from 24 studies evaluated associations (p-trend) between reproductive and hormonal factors, body mass index (BMI), alcohol, smoking, and family history in relation to quantitative immunohistochemistry measures on tissue microarrays (ER, PR, HER2, KI67, TP53) and tumor grade. Analyses in a subset of 10 population-based studies estimated subtype-specific odds ratios (ORs) comparing cases to controls. A Bayesian False Discovery Probability (BFDP) &lt;0.2 was used to identify associations with strong statistical evidence. Results Nulliparity and later age at menopause were associated with higher ER-positivity (p-trend=0.021 and 0.001, respectively), with corresponding OR[ER+] (95% CI) = 1.49 (1.16-1.90) for nulliparous vs. parous and 1.07 (1.03-1.11) per 5 years. Current combined menopausal hormone therapy (MHT) use was associated with lower grade (p-trend&lt;0.001), with OR [grade1] = 3.37 (2.69-4.21) for current vs. never users. Higher BMI was associated with lower ER-positivity and higher grade in premenopausal women (p-trend&lt;0.001 and &lt;0.001), with OR[ER+] = 0.80 (0.74-0.87) and OR[grade1] = 0.75 (0.63-0.88) per 5 units, and with higher PR-positivity and higher grade in postmenopausal women (p-trend&lt;0.001 and &lt;0.001), with OR[PR+] = 1.08 (1.03-1.14) and OR[grade 3] = 1.10 (1.04-1.17) per 5 units. Conclusion This pooled analysis of 15,731 cases showed that nulliparity, age at menopause, MHT, and BMI have independent, dose-response associations with ER, PR, and grade, clarifying patterns of etiologic heterogeneity. Associations with HER2, KI67 and TP53, or other risk factors did not meet our threshold for strong evidence.

Objective We aimed to use machine learning (ML) models to investigate the impact of clinical, social and behavioural factors on 1-year progression from pre-diabetes to type 2 diabetes mellitus (DM). Design A retrospective cohort study. Setting A large health system including eight sites in southeast Michigan. Participants Adults with haemoglobin A1c (HbA1c) between 5.7% and 6.4% for two consecutive years between 1 January 2008 and 31 December 2023, and no prior history of type 2 DM or metformin use. Primary outcome measure New-onset type 2 DM (HbA1c ≥6.5%) in 1 year. Results Among 11 809 individuals, 815 (6.9%) progressed to type 2 DM within 1 year. CatBoost demonstrated the best performance (average area under the curve 0.78). Prior-year HbA1c was the most influential covariate (SHapley Additive exPlanations 1.02). Traditional metabolic factors (high-density lipoprotein, body mass index (BMI), white blood cell, age, gender, triglycerides) also contributed. Lastly, while inclusion of social and behavioural determinants of health (SBDH) did not significantly improve the overall model performance, depression emerged as the prominent SBDH covariate. Depression was a stronger predictor of diabetes progression in individuals with higher baseline BMI and lower baseline HbA1c. Conclusions Inclusion of social and behavioural covariates provided no incremental value for prediction of diabetes progression from pre-diabetes. However, machine learning revealed that depression may play a role in progression to type 2 DM.

Abstract Polygenic risk scores (PRSs), which quantify inherited susceptibility to complex traits and diseases, have emerged as valuable tools for risk stratification and precision medicine. Despite their promise, PRS developed on European cohorts often demonstrate substantially reduced predictive accuracy in non-European populations, due to differences in genetic architecture. The disproportionate representation of European ancestry cohorts in genome-wide association studies (GWAS) leads to inequitable deployment of PRS technologies across diverse populations. Here, we introduce PRANA (Polygenic Risk Adaptation via Neural-network Architecture), a deep learning framework that adapts an existing PRS developed on one population to other ancestries. Unlike methods that require large-scale GWAS in the target population, PRANA leverages pre-trained PRS models derived from European cohorts and adapts them using modestly sized cohorts from the target population. We evaluated PRANA on seven complex traits in South Asian, East Asian and Ashkenazi Jewish populations, as well as in selected smaller East Asian subpopulations where the scarcity of training data poses a particular challenge. PRANA mostly improved predictive performance of the baseline PRS models by 5%-20% in terms of effect size (β) and Nagelkerke’s R², and, in most cases, outperformed existing cross-ancestry multi-PRS approaches. These results highlight PRANA as a scalable and practical strategy to reduce disparities in genomic risk prediction and advance the equitable application of PRS in diverse populations.

Abstract Cardiovascular disease is the leading cause of morbidity and mortality globally, imposing a substantial patient burden. Digital biomarkers derived from digital health technologies enable quantifiable, near-continuous, real-world capture of pathophysiological signals and are increasingly used across cardiovascular medicine. Their growth is often supported by big data analytics, artificial intelligence and connected sensors within the Internet of Things. This scientific statement systematically reviews digital biomarkers, their clinical utility across the cardiovascular care continuum, and summarizes major methodological and implementation challenges. We searched PubMed/MEDLINE, Embase and Scopus for phase III–IV cardiovascular trials published between 1 January 2019 and 1 August 2024 that collected digital biomarkers. We identified 541 records and included 32 trials (40 reports) enrolling 32 246 participants (44.71% women; mean age 66.2 ± 11.0 years). Heart failure was the most frequent target condition (16 trials, 50%), followed by cardiac implantable electronic devices trials (12 trials, 38%). Digital biomarkers included cardiac rhythm and heart rate, blood pressure, body weight, impedance-based measures, haemodynamic pressures, and physical activity and sleep patterns captured using diverse sensor technologies. Methodological quality was good (modal quality score 5; range 3–7), although most trials were unblinded. Current studies suggest potential clinical utility in selected cardiovascular conditions. Implementation remains challenging because of measurement variability, privacy and regulatory requirements, affordability and reimbursement barriers and inequities in access. Robust validation and outcome- and cost-effectiveness evidence are still needed. Registration number: CRD42024573879.

Objective: Perimenopause is an under-recognized life stage that is often accompanied by complex and fluctuating symptoms. We aimed to quantify the prevalence of perimenopause uncertainty and explore the underlying drivers. Methods: We conducted a mixed-methods study using a cross-sectional survey of US women aged 35 years and above (N=7,640). We estimated the prevalence of perimenopause uncertainty and examined subgroup differences by age and symptom severity. Content analysis of free-text responses (n=409) identified key uncertainty drivers. Results: Overall, 34% (95% CI: 33%-35%) of participants reported being unsure of their reproductive stage. Uncertainty varied by age and symptom severity ( P < 0.001), peaking at 42% (95% CI: 41%-43%) among those aged 40-44 and 37% (95% CI: 36%-38%) among those with severe symptom burden. Content analysis revealed three main uncertainty drivers. Symptom confusion and attribution were the most common (56%), reflecting difficulties interpreting bodily changes and distinguishing perimenopause from other causes. Knowledge gaps and information seeking accounted for 28% of responses, highlighting limited health literacy, age-based assumptions, and active searches for evidence. Barriers to confirmation and care (16%) described dismissive health care encounters and reluctance to acknowledge perimenopause. Younger women (35-39 y) were more likely to cite knowledge gaps, while health care barriers peaked in the 40-44 age group ( P = 0.05). Conclusion: Perimenopause uncertainty is a prevalent and clinically meaningful phenomenon. Conceptually distinct from illness-focused uncertainty, this universal transition frequently involves ambiguity and limited validation. Clarifying symptom patterns, addressing knowledge gaps, and reducing barriers to confirmation may support women during perimenopause.