Category: Statistics

Diabetologia. 2025 Jun 27. doi: 10.1007/s00125-025-06473-9. Online ahead of print.

ABSTRACT

AIMS/HYPOTHESIS: Excess type 2 diabetes mellitus in minority ethnic groups remains unexplained, although greater fat mass makes a strong contribution. We hypothesised that height and weight through infancy in South Asian and Black African/Caribbean subgroups is more adverse than in White populations. These, allied to poor socioeconomic position, determine greater fat mass at age 7 years.

METHODS: We report a secondary analysis from the UK Millennium Cohort Study, including 12,280 births of White ethnicity, and 358 of Indian, 650 of Pakistani, 268 of Bangladeshi, 163 of Black Caribbean and 277 of Black African ethnicity between 2000 and 2002. Birthweight was reported, and heights and weights were measured at ages 3, 5, 7, 11, 14 and 17 years. Bioimpedance captured fat mass, indexed to height, at ages 7, 11, 14 and 17 years. Standardised differences in anthropometry, using the White group as the comparator, were calculated. We explored the effect of early growth on ethnic differences in fat-mass index at age 7 years. Confounders included maternal anthropometry, smoking, infant breastfeeding, education, parental income and area-level socioeconomic deprivation.

RESULTS: All minority ethnic subgroups had lower birthweight and accelerated infant height and weight growth compared with White children. By age 3 years, mean height was greater in all minority ethnic groups than in White children. This height advantage was progressively lost, first in Bangladeshi children. By age 17 years in boys/girls, Indians were 1.77/2.48 cm, Pakistanis 2.24/3.44 cm, Bangladeshis 4.83/5.95 cm and Black Caribbeans 1.64/0.49 cm shorter than White children. Heights were equivalent in Black African children. By age 17 years, all South Asian children were lighter, and Black African/Caribbean children heavier, than White children. The anthropometric gradient by ethnicity in children mirrored that in mothers. Girls from minority ethnic groups were more likely to be menstruating by age 11 years than White girls (range 12-27% vs 9%). At age 7 years, standardised fat-mass index (kg/m²) in boys/girls was 0.17/0.01 SDs greater in Indian, 0.21/0.04 in Pakistani, 0.18/0.16 in Bangladeshi, 0.48/0.35 in Black Caribbean and 0.37/0.75 in Black African children than in White children. These differences persisted to age 17 years. Weight gain to age 3 years, and in Black Africans/Caribbeans, adverse individual and neighbourhood socioeconomic position, contributed to ethnic differences in fat mass.

CONCLUSIONS/INTERPRETATION: Minority ethnic groups in the UK have poorer childhood growth than White children, achieving shorter height, greater fat mass and earlier female puberty. Mirroring of maternal and offspring ethnic subgroup gradients in height and weight indicates intergenerational transmission. Persistent adverse socioeconomic circumstances perpetuate ethnic adversity in early life accrual of body fat.

DATA AVAILABILITY: All MCS data used in this analysis are available from UK Data Service with an end user licence ( https://ukdataservice.ac.uk/find-data/ ).

PMID:40579638 | DOI:10.1007/s00125-025-06473-9

J Racial Ethn Health Disparities. 2025 Jun 27. doi: 10.1007/s40615-025-02523-5. Online ahead of print.

ABSTRACT

OBJECTIVE: To assess providers’ substance use screening/testing practices in patient care and identify disparities in their application. We hypothesized that patient race and social vulnerability (SV) are independently and jointly associated with increased rates of provider self-reported substance use screening/testing.

METHODS: A 2 × 2 factorial vignette design was used to survey OB/GYN, Midwifery, and Family Medicine providers. The patients’ age and medical characteristics were identical in each vignette, but two elements varied dichotomously: (1) the patient’s race (Black vs. White) and (2) the patient’s level of SV. Descriptive statistics were computed to assess respondent characteristics. Chi-square or Fisher’s exact tests were performed to assess disparities in substance use screening/testing practices.

RESULTS: Providers shown the SV patient vignette, compared to providers shown the vignette for a non-SV patient, reported that the patient’s housing (41% vs. 10%, p < 0.01), substance use history (97% vs. 67%, p < 0.01), and the number of prenatal care visits (59% vs. 27%, p = 0.02) influenced their decision to screen/test the patient for substance use. Providers shown the vignette for the SV Black patient were more likely to report the patient’s housing (47% vs. 6%, p = 0.04), substance use history (93% vs. 56%, p = 0.01), and gestational age (20% vs. 0%, p = 0.03) influenced their screening/testing recommendations.

CONCLUSION: Providers reported that the patient’s level of SV influenced their decision to recommend screening/testing. The combination of race and SV had the largest impact on reported decisions regarding screening/testing practices. The results of this study highlight the need for standardized institutional substance use detection protocols to reduce provider bias and discrimination in substance use screening/testing based on individual patient demographics.

PMID:40579635 | DOI:10.1007/s40615-025-02523-5

J Racial Ethn Health Disparities. 2025 Jun 27. doi: 10.1007/s40615-025-02490-x. Online ahead of print.

ABSTRACT

BACKGROUND: Racial disparities in surgical outcomes are well documented across various procedures, including oncological and reconstructive breast surgery. However, it remains unclear whether these inequalities extend to reduction mammoplasty.

METHODS: We queried the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database between 2011 and 2022 to identify adult female patients who underwent breast reduction and reported their racial identity. 30-day postoperative outcomes were compared across four racial groups-Asian, Black/African American, American Indian/Alaskan Native, and Native Hawaiian/Pacific Islander-against White patients using univariate and confounder-adjusted multivariate analyses.

RESULTS: The study cohort included 26,329 female patients, with 64% (n = 16,930) identified as White, 34% (n = 8,873) as Black/African American, 1.2% (n = 326) as Asian, 0.41% (n = 109) as American Indian/Alaska Native, and 0.35% (n = 91) as Native Hawaiian/Pacific Islander. A total of 1,660 adverse events (6.3%) occurred, with complication rates ranging from 4.0% (n = 13) in Asian patients to 6.5% (n = 1,108) in White patients. While breast reduction surgery was generally safe across all racial groups, multivariable analysis identified subtle yet statistically significant disparities: Black/African American patients had a significantly lower likelihood of overall (OR = 0.81) and surgical complications (OR = 0.65), including superficial incisional infections (OR = 0.50; all p < 0.001), but a higher risk of deep incisional infections (OR = 1.4; p = 0.013) and unplanned readmissions (OR = 1.3; p < 0.001). Asian patients demonstrated a significantly lower risk of surgical complications (OR = 0.23; p = 0.041).

CONCLUSION: Breast reduction surgery is generally safe across all racial groups; however, our findings also unveiled subtle racial disparities in its postoperative outcomes. Black/African American patients were found to have a lower risk of overall and surgical complications but were more susceptible to deep incisional infections and unplanned readmissions. Asians were significantly less likely to experience surgical complications. These results reinforce the strong safety profile of reduction mammoplasty while underscoring the need for further research into the underlying factors contributing to differential outcomes.

PMID:40579632 | DOI:10.1007/s40615-025-02490-x

Theor Appl Genet. 2025 Jun 27;138(7):163. doi: 10.1007/s00122-025-04948-2.

ABSTRACT

Multi-omics assisted prediction of disease resistance mechanisms using machine learning has the potential to accelerate the breeding of resistant legume varieties. Grain legumes, such as soybean (Glycine max (L.) Merr.), chickpea (Cicer arietinum L.), and lentil (Lens culinaris Medik.) play an important role in combating micronutrient malnutrition in the growing human population. However, plant diseases significantly reduce grain yield, causing 10-40% losses in major food crops. The genetic mechanisms associated with disease resistance in legumes have been widely studied using genomic approaches. Multi-omics data encompassing various biological layers such as the transcriptome, epigenome, proteome, and metabolome, in addition to the genome, enables researchers to gain a deeper understanding of these complementary layers and their roles in complex legume-pathogen interactions. Genomic prediction, used to select the best genotypes with desirable traits for breeding, has largely relied on genome-wide markers and statistical approaches to estimate the breeding values of individuals. Integrating multi-omics data into genomic prediction can be achieved using machine learning models, which can capture nonlinear relationships prevalent in high-dimensional data better than traditional statistical methods. This integration may enable more accurate predictions and identification of resistance mechanisms for breeding resistant legumes. Despite its potential, multi-omics integration for disease resistance prediction in legumes has been largely unexplored. In this review, we explore omics studies focusing on disease resistance in legumes and discuss how machine learning models can integrate multi-omics data for disease resistance prediction. Such multi-omics assisted prediction has the potential to reduce the breeding cycle for developing disease-resistant legume varieties.

PMID:40579624 | DOI:10.1007/s00122-025-04948-2

Eur J Orthop Surg Traumatol. 2025 Jun 27;35(1):284. doi: 10.1007/s00590-025-04392-4.

ABSTRACT

PURPOSE: To describe nonunion and fracture-related infection (FRI) rates and patient-reported outcomes following operative treatment for distal femur fractures in young patients.

METHODS: We retrospectively identified all patients (aged 18-50) who were operatively treated for a distal femur fracture between 2006 and 2023 with ≥ 3-month clinical follow-up at two Level 1 Trauma Centers. Outcomes included reoperation for nonunion and FRI; and PROMIS physical function (PF), depression, and anxiety (reference population mean: 50). Multiple linear regression was performed to identify factors associated with PROMIS-PF.

RESULTS: Eighty-six patients met inclusion criteria. The median age was 34 years, 71% were male, 42% had an open fracture, and for 38 patients PROMIS scores were collected at an average of 9.8 years after treatment. Eleven patients (13%) required reoperation for nonunion and 3 (3.5%) for FRI. Median PROMIS-PF was 47.0 (IQR: 41.2-52.4), depression 45.8 (IQR: 38.9-53.6), and anxiety 46.7 (IQR: 39.5-60.5). PROMIS-PF was lower than the reference population score (p < 0.05). Increased age (1-year; ß: – 0.39; 95%CI: – 0.62 to – 0.17; p < 0.001) and BMI (1-unit; ß: – 0.59; 95%CI: – 0.98 to – 0.20; p = 0.004) at time of injury were associated with worse PROMIS-PF scores and longer follow-up (1-year; ß: 0.79; 95% CI: 0.27 to 1.3; p = 0.004) with better scores.

CONCLUSION: One in 8 young patients with a distal femur fracture underwent reoperation for nonunion and one in 33 for FRI. Physical function scores were marginally lower than the reference population, whereas depression and anxiety scores were similar. The finding that physical function scores were more influenced by baseline patient factors than injury characteristics is important for prognostication and patient education. These results should be interpreted in the context of the small sample size, and future research with larger cohorts is needed to confirm these findings and better understand long-term functional outcomes in young patients following treatment of distal femur fractures.

PMID:40579623 | DOI:10.1007/s00590-025-04392-4

AAPS J. 2025 Jun 27;27(5):115. doi: 10.1208/s12248-025-01102-0.

ABSTRACT

In vitro dissolution testing is commonly performed to ensure that oral solid dosage medicines are of high quality and will achieve their targeted in vivo performance. However, this testing is time and material consuming. Therefore, pharmaceutical companies have been developing predictive dissolution models (PDMs) for drug product release based on fast at- and/or on-line measurements, including real-time release testing of dissolution (RTRT-D). Recently, PDMs have seen acceptance by major regulatory bodies as release tests for the dissolution critical quality attribute. In this paper, several methodologies are described to develop and validate a fit-for-purpose model, then to implement it as a surrogate release test for dissolution. These approaches are further exemplified by real-life case studies, which demonstrate that PDMs for release are not only viable but more sustainable than in vitro dissolution testing and can significantly accelerate drug product release. The rise of continuous manufacturing within the pharmaceutical industry further favors the implementation of real-time release testing. Therefore, a steep uptake of PDMs for release is expected once this methodology is globally accepted. To that end, it is advantageous for global regulators and pharmaceutical innovators to coalesce around a harmonized set of expectations for development, validation, implementation, and lifecycle of PDMs as part of drug product release testing.

PMID:40579614 | DOI:10.1208/s12248-025-01102-0

AAPS PharmSciTech. 2025 Jun 27;26(6):174. doi: 10.1208/s12249-025-03163-y.

ABSTRACT

Breast cancer (BC) is the most prevalent form of cancer among women worldwide, accounting for approximately 36% of cancer cases. Due to its inimitable pathological expression and restricted success of accessible therapeutic modalities, fanatical research in this area is essential. Our group has developed a nanovesicular lipid carrier system consisting of Exemestane (EXM) and Genistein (GNS), which have been successfully incorporated into both uncoated and chitosan-coated liposomes. This combination aims to enhance anticancer efficacy. EXM is known to cause bone loss, while GNS, a natural isoflavone, has been shown in research to possess bone-protective effects. Therefore, we combined these two compounds to mitigate the side effects of EXM. Our previous publication details the formulation development of uncoated EXM-GNS liposomes (EXM-GNS-LPS) and chitosan-coated EXM-GNS liposomes (CH-EXM-GNS-LPS), where we addressed the pharmacotechnical challenges of combining a synthetic drug with herbal drug. Both uncoated and coated liposomes were tested for their budding effects on bone loss induced by hormonal therapy. Pharmacokinetic and pharmacodynamic studies were conducted on rat models with breast cancer, treated with different formulations. Biochemical investigations revealed significant changes in biomarker levels, indicating effects on bone development and resorption. Improvements in bone health and anticancer efficacy were observed to be statistically significant (p < 0.05). Micro-CT analysis of bone samples showed that the chitosan-coated EXM-GNS liposome treatment group yielded the best results when evaluate against other treatment groups. Additionally, histological examination of the bone treated with CH-EXM-GNS-LPS demonstrated a marked restoration of trabecular bone architecture, characterized by a well-connected bone matrix and narrower inter-trabecular spaces compared to the toxic control group. The synergistic effect of EXM and GNS, encapsulated in liposomes, offers an innovative solution to the challenges of breast cancer treatment. The chitosan coating not only improved the stability and controlled release of the drugs but also provided additional benefits in terms of biocompatibility and targeting potential. Overall, the results of this study indicate that the CH-EXM-GNS-LPS formulation holds significant promise as a therapeutic and preventive strategy for bone loss associated with hormonal therapy in breast cancer patients. This work lays the foundation for future clinical applications, highlighting the potential for combining synthetic and natural compounds in advanced drug delivery systems to address complex, multifactorial health issues.

PMID:40579610 | DOI:10.1208/s12249-025-03163-y

Cancer Chemother Pharmacol. 2025 Jun 28;95(1):64. doi: 10.1007/s00280-025-04791-8.

ABSTRACT

PURPOSE: Insulin-like growth factor-1 (IGF-1) may play a role in breast cancer (BC) development. Metformin was found to exert anti-cancer function in several studies, partly by interference with the IGF-1 signaling pathway and reducing its blood levels. Therefore, our study aimed primarily to find out how metformin affected both IGF-1 levels and clinical outcomes in metastatic breast cancer patients (MBC) and secondarily to identify the correlation between post-treatment IGF-1 decline rates and BC prognosis and metastasis.

METHODS: Fifty MBC female patients were randomly assigned to either the control group (who were administered conventional chemotherapy) and the intervention group (treated with metformin plus chemotherapy). An enzyme-linked immunosorbent assay (ELISA) was used to detect IGF-1 levels at baseline and three months post-treatment.

RESULTS: IGF-1 levels in the metformin group were significantly lower than in the control group (p = 0.011). Furthermore, the percentage of post-treatment drop in IGF-1 levels differed significantly between the control and metformin groups (p = 0.001). Patients whose IGF-1 levels increased after treatment had a statistically significant occurrence of progressive disease (disease progression) in the control group higher than in the metformin group (92.9% versus 87.5%).

CONCLUSION: The co-administration of metformin with chemotherapy significantly inhibited the IGF-1 signaling pathway, which reduced progressive diseases and reduced mortality in non-diabetic MBC patients. However, while metformin exerts a robust IGF-1 lowering effect, combination chemotherapy and low metastasis burden may further enhance this effect.

TRAIL REGISTRATION: Our trial was registered at clinicaltrials.gov (ID no. NCT04143282).

PMID:40579605 | DOI:10.1007/s00280-025-04791-8

Dig Dis Sci. 2025 Jun 27. doi: 10.1007/s10620-025-09127-3. Online ahead of print.

ABSTRACT

BACKGROUND: Visual or haptic assessments of the pylorus during endoscopy may result in the diagnosis of a pylorospasm. However, subjective assessments may be affected by inter-rater variability, the antro-duodenal motility phase and the distance to scope. We evaluated to what extent the visual impression, the endoscopic resistance to pyloric intubation and gastric contents correlate with objectively determined values using EndoFLIP measurements.

METHODS: Patients scheduled for FLIP panometry of the upper gastrointestinal tract due to esophageal or epigastric conditions from January 2021 until November 2022 were considered for the study. Inclusion criteria were an EndoFLIP measurement of the pylorus using a standardized protocol for distensibility assessment and documented subjective assessments during upper endoscopy. Statistical analyses including MANOVA and logistic regression were performed for group comparisons and to evaluate significance.

RESULTS: A total of 184 patients (56% female; mean age 49 ± 17.6 years) were included. The subjective assessment modalities of gastric and pyloric dimensions during endoscopy demonstrated high specificity (> 80%) but low sensitivity (< 50%) in detecting pylorospasm. Group comparisons and post hoc tests revealed no consistent significance between different subjective ratings. Logistic regression analysis showed that objectively determined measurements of pyloric dimensions using FLIP panometry were superior to subjective assessments in identifying pyloric dysfunction.

CONCLUSION: Subjective assessments of the pylorus during endoscopy are not reliable for diagnosing pyloric dysfunction, such as pylorospasm. This highlights the importance of measurements, not estimates, in the evaluation of pyloric function.

PMID:40579596 | DOI:10.1007/s10620-025-09127-3

Nat Cancer. 2025 Jun 27. doi: 10.1038/s43018-025-01001-5. Online ahead of print.

ABSTRACT

The capability to profile the landscape of antigen-binding affinities of a vast number of antibodies (B cell receptors, BCRs) will provide a powerful tool to reveal biological insights. However, experimental approaches for detecting antibody-antigen interactions are costly and time-consuming and can only achieve low-to-mid throughput. In this work, we developed Cmai (contrastive modeling for antigen-antibody interactions) to address the prediction of binding between antibodies and antigens that can be scaled to high-throughput sequencing data. We devised a biomarker based on the output from Cmai to map the antigen-binding affinities of BCR repertoires. We found that the abundance of tumor antigen-targeting antibodies is predictive of immune-checkpoint inhibitor (ICI) treatment response. We also found that, during immune-related adverse events (irAEs) caused by ICI, humoral immunity is preferentially responsive to intracellular antigens from the organs affected by the irAEs. We used Cmai to construct a BCR-based irAE risk score, which predicted the timing of the occurrence of irAEs.

PMID:40579590 | DOI:10.1038/s43018-025-01001-5