BMC Medicine最新文献

Background: Radioactive iodine-refractory differentiated thyroid cancer (RAIR-DTC) remains a therapeutic challenge, especially after progression on prior systemic therapies. While immune checkpoint inhibitors combined with antiangiogenic agents have shown synergy in other tumors, data in RAIR-DTC are limited. This study evaluated camrelizumab plus apatinib in first-line and salvage settings.

Methods: This open-label, single-arm, phase II trial (NCT04560127) enrolled patients with locally advanced or metastatic RAIR-DTC. Patients received intravenous camrelizumab (200 mg every 2 weeks) and oral apatinib (250 mg daily) in 4-week cycle until progression or intolerable toxicity. The primary endpoint was progression-free survival (PFS). Secondary endpoints included objective response rate (ORR), overall survival (OS), disease control rate (DCR), and safety.

Results: Between September 2020 and August 2021, 20 patients were enrolled and treated. As of the data cutoff, the median follow-up was 28.4 months (IQR, 22.3-31.2). Median PFS was 11.0 months (95% CI, 6.0-14.2), with 11.6 months (95% CI, 4.8-NE) in treatment-naïve patients and 11.0 months (95% CI, 3.7-19.4) in pretreated patients. Median OS was not reached. The confirmed ORR was 30.0% (95% CI, 11.9-54.3), with 6 patients achieving partial response, and DCR was 95.0% (95% CI, 75.1-99.9). The most common grade ≥ 3 treatment-related adverse events were increased gamma-glutamyltransferase (40.0%) and increased alanine aminotransferase (30.0%).

Conclusions: Camrelizumab plus apatinib demonstrated promising efficacy and manageable toxicity in RAIR-DTC across both first-line and salvage settings, supporting further evaluation as a potential second-line option in the absence of established standard therapies in this setting.

Trial registration: The study was registered at clinicaltrials.gov with the identifier NCT04560127.

Background: The Mediterranean diet (MedDiet) is strongly associated with lower cardiovascular disease (CVD) risk and is particularly rich in polyphenols, bioactive compounds with potential cardioprotective effects. However, the specific phenolic compounds underlying these benefits remain unclear. The objective of this study was to develop a urinary multi-metabolite signature of phenolic compounds reflecting MedDiet adherence and to evaluate its prospective association with CVD risk.

Methods: In a case-cohort nested study within the PREDIMED trial, we measured 62 phenolic metabolites in spot urine by liquid chromatography-high-resolution mass spectrometry at baseline and after 1 year in 1180 individuals: 653 incident CVD cases (stroke, myocardial infarction, CVD death, or heart failure) and a random subcohort of 603 participants (76 overlapping cases). We applied elastic net regression to derive a urinary multi-metabolite signature prospectively associated with MedDiet adherence, measured by the validated 14-item Mediterranean Diet Adherence Screener (MEDAS). Multivariable Cox models were used to estimate hazard ratios (HRs) of CVD by levels of the multi-metabolite signature.

Results: The urinary multi-metabolite signature, comprising eight phenolic compounds selected by elastic net regression, was inversely associated with CVD risk in a dose-response pattern (HR per SD = 0.80 (0.68-0.94); HR Q4 vs Q1 = 0.48 (0.30-0.78); p-trend = 0.002). The metabolites included in the signature were derived from foods typical of the MedDiet, particularly virgin olive oil, wine, nuts, fruits, and vegetables. After 1 year, MedDiet interventions significantly increased urolithin A metabolites (derived from walnuts) compared to the control group.

Conclusions: We identified a urinary multi-metabolite signature of MedDiet adherence that is prospectively associated with lower CVD incidence. These findings support that polyphenols derived from the MedDiet showed inverse associations with cardiovascular outcomes.

Trial registration: The study was registered with the International Standard Randomized Controlled Trial Number (ISRCTN) 35739639.

Background: Percutaneous coronary intervention (PCI) is a cornerstone in the management of coronary artery disease; however, postoperative gastrointestinal bleeding (GIB) represents a significant complication that adversely impacts patient prognosis. Numerous factors influence GIB, yet no comprehensive meta-analysis has synthesized these to date. Current predictive tools, such as the CRUSADE and PRECISE-DAPT scores, exhibit limited efficacy in forecasting GIB following PCI, underscoring the urgent need for a more precise model to enhance risk management.

Methods: This study employed a meta-analysis to identify risk factors for GIB post-PCI and subsequently developed predictive models based on these findings. The meta-analysis incorporated 77 studies encompassing a total of 7,211,114 patients with PCI. Ten predictive models were constructed from the analysis and validated in an external cohort of 3425 patients with PCI from two tertiary hospitals.

Results: A total of 129 influencing factors were included, with a meta-analysis conducted on 71, identifying 60 factors significantly associated with GIB. Model I, the most clinically applicable model comprising nine risk factors (female sex, advanced age, smoking, prior gastrointestinal ulcer, renal insufficiency, non-use of proton pump inhibitors, anticoagulant use, anemia, and glycoprotein IIb/IIIa receptor antagonist administration), demonstrated superior performance in external validation with an AUC of 0.842. This outperformed the CRUSADE score (AUC = 0.770) and PRECISE-DAPT score (AUC = 0.772), with DeLong's test, significant positive Net Reclassification Improvement Index, and Integrated Discrimination Improvement further confirming its enhanced clinical utility.

Conclusions: GIB following PCI is influenced by a multitude of factors. Model I excels in predicting this complication, surpassing existing scoring systems, and offers substantial clinical value by enabling personalized risk management to improve patient outcomes. All nine predictors are routinely available at the bedside or in the electronic health record, facilitating immediate clinical implementation without additional testing.

Background: Ageing involves heterogeneous brain grey matter (GM) patterns that may overlap with dementia-related changes. We evaluated cognitively unimpaired older adults to identify specific GM patterns, their clinical and cognitive profiles, and longitudinal trajectories.

Methods: We analysed 746 participants from the Gothenburg H70 study using random forest cross-sectional clustering based on MRI measures of cortical thickness and subcortical volume across 41 regions. Using regression-based models, we examined associations with clinical, MRI variables, biochemical, and CSF Alzheimer biomarkers (n = 286) and assessed 5-year longitudinal cognitive and brain trajectories.

Results: Five clusters emerged, mainly differing in frontoparietal regions. Compared to Cluster 1 (reference), Cluster 2 showed diffuse GM loss, higher odds of diabetes (OR = 2.54, 95% CI [1.27-5.06]) and at-risk alcohol consumption (OR = 1.83, 95% CI [1.13-2.97]), poorer episodic memory (β =  - 0.19, p = 0.014) and visuospatial abilities (β =  - 0.21, p = 0.044), and greater longitudinal decline in MMSE (β_slope =  - 0.45, p = 0.035) and increase in white matter hyperintensity volume (β_slope = 1.84, p = 0.004). Cluster 3 showed thicker GM and lower BMI (OR = 0.57, 95% CI [0.35-0.94]). Cluster 4 had preserved GM, lower smoking habits (OR = 0.62, 95% CI [0.40-0.95]), triglyceride levels (OR = 0.55, 95% CI [0.32-0.95]) and depression (OR = 0.17, 95% CI [0.05-0.56]), higher education (OR = 2.52, 95% CI [1.08-5.87]), and better cognition in multiple domains. Cluster 5 had a mixed GM pattern and higher odds of heart disease (OR = 3.44, 95% CI [1.48-8.01]).

Conclusions: Cardiovascular and psychosocial factors influence GM integrity, which in turn relates to cognition. Targeting these risk factors may preserve brain health in late life.

Background: Retail food environments in the UK use intense marketing strategies to promote the purchase and consumption of less-healthy foods that are associated with ill-health. To help address this issue, the Food (Promotion and Placement) regulations were introduced in England from October 2022, banning the placement of foods high in fat, salt, or sugar (HFSS) at checkouts, aisle-ends, and entrances in qualifying retail settings. Ahead of their introduction, this study examined health experts' (i) perspectives on the likely effectiveness of these regulations and (ii) recommendations to enhance their impact.

Methods: This cross-sectional qualitative study aimed to recruit health experts to partake in focus groups/semi-structured interviews via MS Teams. Data were collected, coded, and analysed by three researchers with input from senior colleagues, using Braun and Clarke's reflexive thematic analysis method.

Results: Data were collected between October 2021 and March 2022 from 28 health experts, including public health and food policy academics (n = 9) and experts from civil society organisations (n = 19). Health experts perceived regulations as a major policy innovation which recognised businesses' role in driving poor dietary choices that contribute to obesity. They also raised concerns about the outdated nutrient profiling model, limited regulatory scope, and weak enforcement. They were apprehensive about the potential for disproportionate impacts on smaller businesses and certain consumer groups. To enhance the impact of the regulations, they recommended funding independent and diverse evaluations, mandating the reporting of business sales data, and strengthening enforcement efforts. To improve the regulations' effectiveness, they also suggested establishing mechanisms to refine regulatory guidance and introducing complementary policies within the food system.

Conclusions: Health experts believed that the regulations represent a significant step to curb the promotion of unhealthy foods in retail environments but will be insufficient on their own to improve population diet. To maximise their impact, a systems approach is essential, addressing shortcomings of the regulations, supporting smaller retailers in adopting health initiatives, and implementing thorough monitoring and evaluation. The regulations must form part of a comprehensive set of policies across various sectors, including manufacturing and retail, to accelerate food system transformation and address the dietary drivers of ill-health.

Background: Biological age, estimated by DNA methylation-based (DNAm) clocks, has been reported to be associated with lung cancer risk. However, the extent to which tobacco smoking behaviours can explain this association and the extent to which DNAm clocks and their components can inform risk assessment for lung cancer remains to be elucidated. This study aimed to evaluate the relationship between DNAm clocks, smoking, and lung cancer risk.

Methods: We analyzed four prospective cohorts (MCCS, Australia, 324 cases/324 controls; NSHDS, Sweden, 190 cases/190 controls; EPIC, Italy, 160 cases/107 controls; and NOWAC, Norway, 115 case/70 controls) with blood samples collected before lung cancer diagnosis. Study participants were restricted to those with a history of smoking. Incidence sampling was used to match one control to each of the lung cancer cases by cohort, sex, date of blood collection, age, and smoking status in MCCS and NSHDS. The risk discriminative performance of age-adjusted DNAm clocks and their components was compared with that of the Prostate, Lung, Colorectal, and Ovarian model 2012 (PLCO_m2012) lung cancer risk model.

Results: We found several DNAm clocks positively associated with lung cancer risk (Hannum: OR = 1.13, 95% CI = 1.02-1.26; PhenoAge: OR = 1.25, 95% CI = 1.12-1.40; DunedinPACE: OR = 1.44, 95% CI = 1.29-1.62; PCGrimAge (a principal component-denoised GrimAge): OR = 1.79, 95% CI = 1.56-2.06), after adjustment for age and tobacco smoking. Tobacco smoking explained a modest proportion of variance in most age-adjusted DNAm clocks (R² < 11%), except for PCGrimAge, where it accounted for ~ 30% of variance in both lung cancer cases and controls. Detailed smoking adjustments attenuated the PCGrimAge association with lung cancer risk by 13%. In a secondary analysis adjusting for PCGrimAge components and the PLCO_m2012 score, DNA methylation-predicted packyears emerged as an independent predictor of lung cancer risk (OR = 2.23, 95% CI = 1.58-3.14). The area under the receiver operating characteristic curve (AUC) for the PLCO_m2012 model was 0.66 (95% CI = 0.61-0.71) compared with 0.72 (95% CI = 0.67-0.77) for the PCGrimAge model (P_difference = 0.03). Combining PCGrimAge with PLCO_m2012 provided similar risk discrimination as PCGrimAge alone (AUC = 0.72, 95% CI = 0.67-0.77).

Conclusions: Methylation-based biological clocks capture epigenetic marks left by exposure to tobacco smoke, and some clocks may inform lung cancer risk assessment by complementing or replacing traditional prediction models.

Background: The city built environment plays a crucial role in influencing population vulnerability to temperature extremes, yet population-based evidence has been limited.

Methods: We included 21,494 urban residents from a nationally representative cohort study. Temperature extremes were defined using residential address-specific thresholds lasting for ≥ 3 days. Street view images within participants' residences (500-m radius) were evaluated using semantic segmentation by DeepLabV3 Plus-ResNet101 pretrained by the Cityscapes dataset. Cox proportional hazard models and interaction models were applied to explore the moderating effects of street view-derived built environments on the effects of temperature extremes on mortality.

Results: Each additional day of heatwave (95th) and coldspell (5th) duration per year was associated with a 6% (HR = 1.06, 1.03-1.08) and 4% (HR = 1.04, 1.01-1.08) increase in all-cause mortality risk, respectively. Lower sky view factor (SVF) and openness, and higher grayness, building coverage, and interface enclosure (IE) were associated with increased risks of mortality. Street view-derived built environment factors could modify the associations between temperature extremes and mortality. Specifically, high levels of IE, along with low levels of SVF and openness, across different road levels intensified the effects of heatwaves. Conversely, low levels of IE, along with high levels of SVF and openness, in residential roads amplified the effects of coldspells.

Conclusions: Our findings provide insights for evidence-based urban planning and public health strategies, emphasizing the need for adaptive, context-specific urban design that balances the potentially competing demands of population heat resilience and cold adaptation.

Background: To identify the associations between thymic pathology and the prognosis of myasthenia gravis (MG) patients.

Methods: In this multicenter retrospective study, 1,254 myasthenia gravis (MG) patients who underwent thymectomy across four clinical centers were included. Participants were categorized by thymic pathology into thymomatous and non-thymomatous groups. Primary outcome was postoperative deterioration. Secondary outcomes comprised the proportion of patients achieving minimal manifestation status (MMS) within the first year after surgery and conversion from ocular MG (OMG) to generalized MG (GMG) within 2 years of symptom onset. Subgroup analyses assessed associations between world health organization (WHO) pathological type (both groups) or Masaoka stage (thymoma patients) and prognosis.

Results: Thymomas were associated with an increased risk of deterioration in both Cox regression (adjusted HR = 1.40 [1.18, 1.66], p < 0.001) and logistic regression analyses (1-year deterioration: adjusted OR = 1.59 [1.15, 2.20], p = 0.005; 3-year deterioration: adjusted OR = 1.40 [1.01, 1.94], p = 0.047). Additionally, thymomas were linked to a higher conversion rate (adjusted OR = 2.37 [1.15, 4.86], p = 0.019). However, thymoma showed no significant association with MMS (adjusted p = 0.682). In the thymoma subgroup, neither pathological type nor Masaoka stage was significantly associated with deterioration (pathological type: 1-year p = 0.069, 3-year p = 0.220; Masaoka stage: 1-year p = 0.944, 3-year p = 0.909), first-year MMS attainment (pathological type: p = 0.067; Masaoka stage: p = 0.579), or conversion rate (pathological type: p = 0.606; Masaoka stage: p = 0.163). Similarly, in the nonthymomatous group, WHO pathological type was not significantly correlated with deterioration (1-year p = 0.806, 3-year p = 0.654), MMS achieved (p = 0.940), or conversion (p = 0.755).

Conclusions: This study demonstrated an association between thymoma and higher risks of clinical deterioration, which was independent of WHO pathological type or Masaoka stage.

Background: Alcohol consumption has been linked to cancer risk. Evidence is strongest for seven cancer types: breast, colorectum, oesophagus, liver, mouth, pharynx, and larynx. However, evidence supporting a causal effect from Mendelian randomization is inconsistent.

Methods: We perform a comprehensive Mendelian randomization analysis to assess whether genetically-predicted alcohol consumption associates with risk of 20 cancers. Such associations would provide supportive evidence for a causal effect of alcohol consumption on cancer risk. We used 95 genetic variants associated with alcohol consumption at genome-wide significance. Primary analyses were conducted in European ancestry participants from UK Biobank (367,643 individuals), FinnGen (500,348 individuals), All of US (169,312 individuals), and Million Veteran Program (451,206 individuals). We also estimated associations in cancer-specific consortia.

Results: No association was observed between genetically-predicted alcohol consumption and overall cancer (odds ratio (OR) per 1 standard deviation increase in alcohol consumption 0.96, p = 0.45). Among the seven highlighted cancer types, we saw a multiply-corrected significant positive estimate for combined head/neck cancer (OR 1.51, p = 0.001), and nominally significant positive estimates for colorectal (OR 1.21, p = 0.035) and oesophageal (OR 1.42 p = 0.033) cancer. For liver cancer, there was a null estimate overall (OR 1.40, p = 0.10), but a nominally significant positive estimate in Million Veteran Program and when using the ADH1B-rs1229984 variant. For breast cancer, there was a null estimate in biobank data (OR 1.09, p = 0.25) and consortium data (OR 0.98, p = 0.84). Conversely, we observed multiply-corrected significant negative estimates for kidney cancer (OR 0.64, p = 0.0003) and endometrial cancer (OR 0.56, p = 0.0006), and nominally significant negative estimates for non-Hodgkin's lymphoma (OR 0.75, p = 0.010), myeloma (OR 0.61, p = 0.014), and some subtypes of ovarian cancer. There was a nominally significant positive association with cancer mortality (OR 1.44, p = 0.003), although this attenuated on adjustment for smoking heaviness. Limitations include potential invalidity of the genetic variants as instruments, limited power, multiple testing, variable cancer detection rates, and unrepresentativeness of the datasets.

Conclusions: We observed moderate-to-weak evidence supporting causal effects of alcohol consumption on risk of head/neck, oesophageal, and colorectal cancer, inconsistent evidence for liver cancer, and no evidence for breast cancer. Overall, human genetic data do not provide evidence that alcohol consumption is a cause of all cancers and suggest there may even be inverse associations with certain cancer types.