The Lancet Diabetes & Endocrinology最新文献

{"title":"Getting smart about the food we eat | Julia Belluz, Kevin Hall, Food Intelligence, Headline Publishing Group (2025), p. 368, £22·00, ISBN: 9781472282194","authors":"Talha Burki","doi":"10.1016/s2213-8587(25)00358-4","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00358-4","url":null,"abstract":"","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"11 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Portion sizes and caloric inequity: a hidden driver of obesity disparities","authors":"Naveed Sattar, Zara S Sattar, Lindsey J Sattar, Jason M R Gill","doi":"10.1016/s2213-8587(25)00353-5","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00353-5","url":null,"abstract":"","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"37 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145559702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to Lancet Diabetes Endocrinol 2025; published online Nov 19. https://doi.org/10.1016/S2213-8587(25)00289-X","authors":"","doi":"10.1016/s2213-8587(25)00359-6","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00359-6","url":null,"abstract":"<em>Li M, Dal Maso L, Pizzato M, Rumgay H, Vaccarella S. Thyroid cancer in adolescents and young adults: a population-based study in 185 countries worldwide.</em> Lancet Diabetes Endocrinol <em>2025; published online Nov 19. https://doi.org/10.1016/S2213-8587(25)00289-X</em>—In Figure 6, two erroneous data points have been deleted from the scatter plot (one in part A and one in part B). This correction has been made as of November 21, 2025, and will be made to the printed version.","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"10 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heterogeneity in type 2 diabetes trajectories: informing public health approaches","authors":"Jonathan Pearson-Stuttard, Julia A Critchley","doi":"10.1016/s2213-8587(25)00332-8","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00332-8","url":null,"abstract":"No Abstract","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"1 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145553306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trajectories of type 2 diabetes and cancer in 330 000 individuals with prediabetes: 20-year observational study in England","authors":"Francesco Zaccardi, Suping Ling, Clare Gillies, Karen Brown, Melanie Jane Davies, Kamlesh Khunti","doi":"10.1016/s2213-8587(25)00285-2","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00285-2","url":null,"abstract":"&lt;h3&gt;Background&lt;/h3&gt;Higher than normal glucose concentrations have been linked to an increased risk of cancer. We aimed to describe the disease trajectories from prediabetes to cancer, accounting for the possible conversion to type 2 diabetes and risk of death.&lt;h3&gt;Methods&lt;/h3&gt;We used the Clinical Practice Research Datalink primary care records linked to hospital and mortality records to identify individuals aged 18–100 years with newly diagnosed prediabetes between Jan 1, 1998, and Nov 30, 2018, in England. Individuals were followed from the diagnosis of prediabetes until death or Nov 30, 2018, with two intermediate outcomes: type 2 diabetes and cancer. In a multistate model, we estimated state occupancy probabilities and lengths of stay (sojourn times) across eight states and seven transitions (eg, one transition from the prediabetes state to the cancer state; or three transitions from the prediabetes state to the type 2 diabetes, cancer, and death state).&lt;h3&gt;Findings&lt;/h3&gt;During a median follow-up of 7·7 years, 163 782 transitions occurred in 328 049 individuals. In both women and men, cancer incidence rates were greater in older individuals (aged ≥75 years at prediabetes diagnosis) and only marginally higher in those who developed type 2 diabetes versus those with prediabetes (over 10 years, the largest differences were 4·1 more cases per 1000 person-years in women and 4·8 more cases per 1000 person-years in men). 10 years after the diagnosis of prediabetes, the probability of remaining in the prediabetes state ranged from 23·2% (men aged ≥75 years at diagnosis) to 72·1% (men aged &lt;55 years), the probability of death following prediabetes ranged from 1·2% (women aged &lt;55 years) to 38·7% (women aged ≥75 years), the probability of developing type 2 diabetes and remaining in this state ranged from 7·9% (men aged ≥75 years) to 24·0% (women aged &lt;55 years), and the probability of developing cancer and remaining in this state ranged from 1·9% (men aged &lt;55 years) to 7·8% (men aged ≥65 to &lt;75 years) in men and women. During the 10 years following the diagnosis of prediabetes, individuals spent between 5·34 years (men aged ≥75 years at diagnosis) to 8·34 years (men aged &lt;55 years) in the prediabetes state. BMI, smoking, socioeconomic status, and ethnicity were associated with occupancy probabilities and sojourn times.&lt;h3&gt;Interpretation&lt;/h3&gt;The trajectories of type 2 diabetes and cancer following a diagnosis of prediabetes varied substantially by age at prediabetes diagnosis and, to a lesser extent, other sociodemographic and lifestyle factors, with most younger individuals (aged &lt;55 years) remaining in the prediabetes state. Strategies to improve the prevention and early identification of type 2 diabetes and cancer in individuals with prediabetes should be tailored to the age at which prediabetes is diagnosed.&lt;h3&gt;Funding&lt;/h3&gt;National Institute for Health and Care Research (NIHR) Applied Research Collaboration, East Midlands, NIHR Le","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"133 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145553307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The rise of thyroid cancer incidence in adolescents and young adults","authors":"Tommaso Porcelli, Martin Schlumberger","doi":"10.1016/s2213-8587(25)00321-3","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00321-3","url":null,"abstract":"No Abstract","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"26 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145553305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thyroid cancer in adolescents and young adults: a population-based study in 185 countries worldwide","authors":"Mengmeng Li, Luigino Dal Maso, Margherita Pizzato, Harriet Rumgay, Salvatore Vaccarella","doi":"10.1016/s2213-8587(25)00289-x","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00289-x","url":null,"abstract":"<h3>Background</h3>Cancer burden among adolescents and young adults (AYAs) aged 15–39 years has increased during the past two decades, with thyroid cancer being a major contributor. We aimed to comprehensively evaluate trends and the current burden of thyroid cancer among AYAs globally.<h3>Methods</h3>We obtained annual incidence and mortality data of thyroid cancer from the Cancer Incidence in Five Continents Plus and the WHO Mortality databases. Temporal trends were displayed using the average annual percent changes of age-standardised incidence rates estimated during 2003–2017. The national estimates of incidence and mortality of thyroid cancer and other cancer types for 185 countries in 2022 were obtained from the GLOBOCAN platform. Incidence-to-mortality ratios were compared by cancer type. We estimated the correlation of human development index (HDI) with thyroid cancer incidence and mortality.<h3>Findings</h3>Thyroid cancer incidence rates among AYAs have increased rapidly since the 2000s in most countries, whereas mortality rates remained stably low. Notable increases in incidence were found in South Korea, Cyprus, Ecuador, and Türkiye, with particularly pronounced rises in China. During 2003–2017, the average annual percent changes of thyroid cancer incidence were greater than 10% in six countries and greater than 5% in 19 countries. In 2022, there were approximately 237 000 new cases and around 2100 deaths from thyroid cancer, ranking among the top three most diagnosed cancers in 100 countries for females and in 26 countries for males. By 2022, thyroid cancer accounted for 20·3% of all new cancer cases in female AYAs and 13·6% in male AYAs, ranking as the second most diagnosed cancer among female AYAs, after breast cancer, and the most common cancer among male AYAs. Thyroid cancer incidence rates varied greatly by country, continent, and HDI, while mortality rates were less variable. The incidence-to-mortality ratios for thyroid cancer among AYAs exceeded 3300 for females and 600 for males (&lt;100 for other cancer types) in some countries. HDI was strongly and positively correlated with thyroid cancer incidence, whereas its association with mortality was negative but weak.<h3>Interpretation</h3>The epidemiological profile of thyroid cancer among AYAs indicates a large expansion of overdiagnosis to younger populations. Increased efforts are required to prevent unnecessary diagnosis and treatment due to overuse of diagnostic procedures.<h3>Funding</h3>Guangzhou Science and Technology Project, Guangdong Basic and Applied Basic Research Foundation, Italian Association for Cancer Research, Italian Ministry of Health, and Young Talents Program of Sun Yat-sen University Cancer Center.","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"29 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145553304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adrenal tumour imaging: clinical, molecular, and radiomics perspectives","authors":"Karel Pacak, Michael A Blake, Ann T Sweeney, Abhishek Jha, Alessio Imperiale, Habib Zaidi, Marco Raffaelli, Zbyněk Tüdös, Henri Timmers, Ashley Grossman, Svenja Nölting, David Taïeb","doi":"10.1016/s2213-8587(25)00300-6","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00300-6","url":null,"abstract":"Adrenal tumours have become a common incidental finding in the radiological evaluation of patients. Estimates suggest that 1–10% of the general population currently harbours an adrenal tumour, peaking in prevalence in the seventh and eighth decades of life. Advances in CT and MR have contributed to improved characterisation of adrenal masses, and novel radiopharmaceuticals are being developed for molecular characterisation and disease subtyping. As a result, the imaging and management of adrenal tumours have been important subjects of many guidelines and consensus statements. New radiomics approaches, together with machine learning, are now being introduced and are quickly shaping the way that imaging data are analysed and interpreted. Furthermore, the development of theranostics links the molecular biology of functioning tumours to targeted treatment options. In this Review, we summarise up-to-date imaging and follow-up approaches for adrenal tumours to provide patients with the most accurate diagnosis, thereby avoiding unnecessary additional tests or surgery.","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"73 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145536715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comorbidities and mortality in subgroups of adults with diabetes with up to 14 years follow-up: a prospective cohort study in Sweden","authors":"Olof Asplund, Manonanthini Thangam, Rashmi B Prasad, Carl Lejonberg, Ola Ekström, Liisa Hakaste, J Gustav Smith, Anders H Rosengren, Jan Oscarsson, Björn Carlsson, Tiinamaija Tuomi, Ola Hansson, Emma Ahlqvist","doi":"10.1016/s2213-8587(25)00283-9","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00283-9","url":null,"abstract":"&lt;h3&gt;Background&lt;/h3&gt;Subgroups of adult-onset diabetes, namely severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), and mild obesity-related diabetes (MOD) or mild age-related (MARD) diabetes, have been defined with clinical variables and a machine-learning approach. Our aim was to describe their long-term outcomes and mortality.&lt;h3&gt;Methods&lt;/h3&gt;In this prospective cohort study in Sweden, we used data from two subsets of the All New Diabetics in Scania (ANDIS) project cohort of individuals diagnosed with diabetes at regional care centres and enrolled within 1 year of diagnosis. Included participants were 18 years or older, did not have pancreatitis, and had complete data for cluster variables. We used GAD antibodies, Homeostasis Model Assessment 2 β cell and insulin resistance indices, BMI, HbA&lt;sub&gt;1c&lt;/sub&gt;, and age at the diagnosis of diabetes to group individuals, and logistic and Fine–Gray proportional hazards regression to study prevalent and incident comorbidities, using the MARD group as comparator.&lt;h3&gt;Findings&lt;/h3&gt;Between Jan 1, 2008, and Nov 3, 2016, for ANDIS1 and Nov 4, 2016, and April 6, 2022, for ANDIS2, a total of 25 590 were screened for eligibility, resulting in 19 076 participants being included in the analysis (9057 from ANDIS1 and 10 019 from ANDIS2; 11 171 men and 7905 women). The median follow-up time was 9·63 years (IQR 4·05) in ANDIS1 and 2·83 years (2·76) in ANDIS2. The SAID and SIDD subgroups had the highest HbA&lt;sub&gt;1c&lt;/sub&gt; values at diagnosis and over time, and the highest age-adjusted and sex-adjusted risk of retinopathy (SAID adjusted hazard ratio [HR] 1·35 [95% CI 1·08–1·70]; SIDD 2·11 [1·82–2·44]) and neuropathy (2·58 [1·87–3·56]; 2·13 [1·69–2·70]). At the diagnosis of diabetes, SIRD had the highest prevalence of hypertension (2336 [69·8%] of 3348) and dyslipidaemia (1484 [44·4%]), and kidney (366 [10·9%]), cardiovascular (1026 [30·6%]), and steatotic liver disease (38 [1·1%]). Despite large differences in HbA&lt;sub&gt;1c&lt;/sub&gt;, both SIDD and SIRD had an increased risk of incident kidney disease, including kidney failure (SIDD adjusted HR 2·94 [1·69–5·09]; SIRD 3·41 [2·06–5·64]), and myocardial infarction (1·44 [1·13–1·82]; 1·51 [1·22–1·87]). SIRD and MOD had the highest risk of atrial fibrillation (adjusted HR 1·32 [1·13–1·54]; 1·58 [1·26–1·98]). The risk of stroke was only increased in SIDD (adjusted HR 1·32 [1·07–1·62]), and steatotic liver disease (3·29 [2·32–4·66]) and heart failure (1·55 [1·34–1·79]) in SIRD. SIDD, SIRD, and MOD had the highest risk of total mortality (adjusted HRs 1·44–1·52) even after adjustment for established risk factors (age, sex, BMI, hypertension, LDL, and smoking), largely driven by cardiovascular mortality.&lt;h3&gt;Interpretation&lt;/h3&gt;Diabetes subgroups could inform on outcomes, as well as guide treatment and follow-up needed for newly diagnosed individuals with diabetes. SIRD stands out as a high-risk subgroup that is not identified","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"317 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145515562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The long and winding road to precision diabetology","authors":"Michael Roden","doi":"10.1016/s2213-8587(25)00303-1","DOIUrl":"https://doi.org/10.1016/s2213-8587(25)00303-1","url":null,"abstract":"No Abstract","PeriodicalId":48790,"journal":{"name":"The Lancet Diabetes & Endocrinology","volume":"27 1","pages":""},"PeriodicalIF":44.5,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145515563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}