Tag: statistics

Adv Sci (Weinh). 2026 Feb 11:e21531. doi: 10.1002/advs.202521531. Online ahead of print.

ABSTRACT

Long-read sequencing promises to unravel the complexity of polymorphic immune genes including HLA, KIR, IG, and TCR, yet existing tools fall short in accuracy and scope. Here, we present SpecImmune, the first unified computational framework to simultaneously genotype these genes alongside the intricate CYP family from long-read data. Employing an iterative graph-based haplotype reconstruction algorithm, SpecImmune delivers precise diploid assemblies for each locus from diverse data types. Validated on 1019 samples from the 1kGP ONT cohort, 42 PacBio CLR and 9 PacBio HiFi samples from HGSVC, and 47 PacBio HiFi plus 37 ONT samples from HPRC, SpecImmune achieved 98% four-field HLA typing accuracy, surpassing HLA*LA by 11% and SpecHLA by 12%. It also delivers robust KIR and germline IG/TCR genotyping and supports multi-locus CYP allele detection, positioning it among the first integrated long-read solutions across immune gene families. Beyond superior performance, SpecImmune uncovers elevated germline IG/TCR heterozygosity in African populations ( $p=9.45\times {10}^{–86}$ ) and, through 1kGP analysis, suggests widespread cross-family co-evolution, clustering immune genes into two functionally distinct communities: the Integrated Immune-Metabolic Community and the Adaptive Presentation Community. Additionally, it enables allele-specific drug dosing recommendations and offers flexible customization for new loci, advancing immunology, precision medicine, and evolutionary genomics.

PMID:41669879 | DOI:10.1002/advs.202521531

Biometrics. 2026 Jan 6;82(1):ujag014. doi: 10.1093/biomtc/ujag014.

ABSTRACT

Estimating the causal effect of a treatment or health policy with observational data can be challenging due to an imbalance of and a lack of overlap between treated and control covariate distributions. In the presence of limited overlap, researchers choose between (1) methods (e.g., inverse probability weighting) that imply traditional estimands but whose estimators are at risk of considerable bias and variance; and (2) methods (e.g., overlap weighting) which imply a different estimand by modifying the target population to reduce variance. We propose a framework for navigating the tradeoffs between variance and bias due to imbalance and a lack of overlap and the targeting of the estimand of scientific interest. We introduce a bias decomposition that encapsulates bias due to (1) the statistical bias of the estimator; and (2) estimand mismatch, i.e., deviation from the population of interest. We propose two design-based metrics and an estimand selection procedure that help illustrate the tradeoffs between these sources of bias and variance of the resulting estimators. Our procedure allows analysts to incorporate their domain-specific preference for preservation of the original research population versus reduction of statistical bias. We demonstrate how to select an estimand based on these preferences with an application to right heart catheterization data.

PMID:41669864 | DOI:10.1093/biomtc/ujag014

Biometrics. 2026 Jan 6;82(1):ujag011. doi: 10.1093/biomtc/ujag011.

ABSTRACT

A spatial sampling design determines where sample locations are placed in a study area to achieve precise estimates of population parameters. Many environmental variables have positive spatial associations, and spatially balanced designs perform well. The recently published dynamic assignment sampling (DAS) design draws spatially balanced master or over-samples in auxiliary spaces. This article proposes a new objective function for DAS to draw doubly balanced master or over-samples, where two balancing properties are satisfied: approximately balanced on auxiliary variables and spatially balanced. All we require is a measure of the distance between population units. Numerical results show that the method generates spatially balanced, balanced, or doubly balanced master or over-samples and compares favorably with established fixed sample size designs. We provide an example application using total aboveground biomass over a large study area in Eastern Amazonia, Brazil, and design-based variance estimators.

PMID:41669863 | DOI:10.1093/biomtc/ujag011

Biometrics. 2026 Jan 6;82(1):ujag009. doi: 10.1093/biomtc/ujag009.

ABSTRACT

Individually randomized trials allow participants to be included in a trial multiple times, with independent randomization at each inclusion. Often referred to as re-randomization designs, these trials have been shown to increase trial recruitment rates. Treatment effect estimators remain unbiased but are more precise than for designs with more participants but no repeat inclusions, but do rely on additional assumptions. Here, we introduce a new class of cluster randomized trial designs: repeated inclusion cluster randomized trials, where some clusters are randomized serially in the same trial. The trial in which clusters are initially included may have a standard cluster randomized design or a longitudinal variant, such as a cluster randomized crossover design. Allowing clusters to participate multiple times in the same trial could reduce the need to recruit new clusters; useful when cluster recruitment is difficult. Assuming a constant treatment effect across repeated inclusions, we show that when equal numbers of clusters and participants are included in each treatment group in each study period, power will be the same or higher as for a similar trial where clusters are not re-randomized but which has the same total number of measurements. Whether power is maintained or increased depends on the study design and the within-cluster correlation structure; increasing the number of within-cluster comparisons increases study power.

PMID:41669862 | DOI:10.1093/biomtc/ujag009

Circ Cardiovasc Interv. 2026 Feb 11:e015932. doi: 10.1161/CIRCINTERVENTIONS.125.015932. Online ahead of print.

ABSTRACT

BACKGROUND: Calcified nodules (CNs) represent a high-risk coronary lesion phenotype associated with target lesion revascularization (TLR). Although rotational atherectomy (RA) is an established treatment for calcified lesions, its benefit for CNs remains unclear. This study aimed to evaluate the impact of RA on TLR and to identify specific morphological features on intravascular ultrasound that may influence its therapeutic effect for CNs.

METHODS: In a substudy of the U-SCAN registry (Coronary Intravascular Ultrasound for Calcified Nodule), 348 patients with CNs identified by intravascular ultrasound who underwent percutaneous coronary intervention were analyzed. We excluded patients with in-stent restenosis, use of alternative debulking devices, failed device passage without RA, and poor image quality. The final analysis included 209 patients, stratified by RA use. Multivariable Cox proportional hazards models were used to identify predictors of TLR and assess treatment interactions across subgroups.

RESULTS: Among 209 patients, 79 patients (37.8%) underwent RA. During a median follow-up of 2.1 years (interquartile range, 0.4-4.9), TLR was required in 20 of 79 patients (25.3%) in the RA group and 41 of 130 patients (31.5%) in the non-RA group. After adjustment, RA independently predicted reduced TLR (hazard ratio, 0.34 [95% CI, 0.19-0.62], P<0.001). In addition, intravascular ultrasound-derived calcification features, including greater lumen area stenosis, longer CN length, smaller final minimum lumen area, and adjacent circumferential calcification, were significantly associated with TLR. Notably, the benefit of RA on TLR was pronounced in patients with contralateral calcification (8.6% versus 51.6%, P<0.001). In contrast, without this feature, the TLR rate was higher in the RA group (38.6% versus 25.3%, P=0.11), resulting in a statistically significant interaction (P_interaction<0.001).

CONCLUSIONS: In patients with CNs, RA was associated with a reduced long-term risk of TLR. The presence of contralateral calcification identifies a subgroup deriving substantial benefit, supporting a more selective, morphology-guided approach to treatment.

REGISTRATION: URL: https://jrct.mhlw.go.jp/; Unique identifier: jRCT1050240037.

PMID:41669840 | DOI:10.1161/CIRCINTERVENTIONS.125.015932

Circulation. 2026 Feb 11. doi: 10.1161/CIR.0000000000001401. Online ahead of print.

ABSTRACT

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate established cardiovascular risk factors and have evolved over time from the Framingham Risk Model to the pooled cohort equations to the PREVENT (Predicting Risk of CVD Events) equations. Recent scientific (ie, genomics, proteomics, metabolomics) and methodologic (ie, artificial intelligence) advances have led to a proliferation of novel models, biomarkers, and tools for potential use in risk prediction. In parallel, the growing armamentarium of preventive therapies, some with considerable cost, underscores the need for more accurate and precise risk assessment to prioritize those at highest risk who will derive the greatest absolute benefit. Accompanying the considerable enthusiasm for the potential of newer approaches to improve risk prediction is the need for rigorous evaluation and assessment of their performance (ie, accuracy, precision, incremental performance when added to contemporary multivariable risk models or established risk factors) and clinical utility (ie, actionability, scalability, generalizability) before adoption in clinical practice. Additional considerations in risk tool evaluation include reproducibility, cost-value considerations (including impact on downstream health care costs), and implications for health equity. This scientific statement defines a standardized framework for general considerations in risk prediction, statistical assessment of predictive utility, and critical appraisal of clinical utility and readiness. This scientific statement is intended to support clinicians, researchers, and policymakers in how best to evaluate current and emerging risk prediction tools and ultimately improve the prevention of cardiovascular disease in diverse populations.

PMID:41669831 | DOI:10.1161/CIR.0000000000001401

Stroke. 2026 Feb 11. doi: 10.1161/STROKEAHA.125.054876. Online ahead of print.

ABSTRACT

The CREST-2 (Carotid Revascularization and Medical Management for Asymptomatic Carotid Stenosis Trials) comprised 2 parallel randomized trials in asymptomatic carotid stenosis comparing medical management alone with medical management plus carotid artery stenting or carotid endarterectomy. Carotid stenting achieved a modest but statistically significant 4-year reduction in primary events, whereas carotid endarterectomy did not. This commentary examines methodological features that may have favored the revascularization arms, including omission of peri-procedural myocardial infarction and major hemorrhage as end points; allowing operator-team members to perform neurological assessments; highly selective credentialing of carotid stenting operators; and a primary analysis that weighted early and late events equally. Taken together, these methodological features and ongoing advances in contemporary medical therapy suggest that carotid stenting, carotid endarterectomy, and medical management may yield similar outcomes in clinical practice.

PMID:41669830 | DOI:10.1161/STROKEAHA.125.054876

J Cosmet Dermatol. 2026 Feb;25(2):e70716. doi: 10.1111/jocd.70716.

ABSTRACT

BACKGROUND: Calcium hydroxyapatite (CaHA) is a well-established biostimulatory filler approved for hand rejuvenation. Recent approaches have explored dilution with polymicronutrient (PMN) solutions to enhance cellular metabolism and extracellular matrix (ECM) regeneration.

AIMS: To evaluate the biological and clinical effects of CaHA diluted in a PMN solution (CaHA + PMN) compared with the conventional CaHA diluted in saline solution (CaHA + SS) for hand rejuvenation.

METHODS: An in vitro study was conducted to assess fibroblast proliferation and gene expression of ECM components (COL1A1, COL3A1, and ELN) after exposure to CaHA diluted with PMN or SS. A prospective, split-hand, double-blind clinical trial (n = 22) compared both formulations regarding Hand Grading Scale (HGS), Global Aesthetic Improvement Scale (GAIS), skin hydration (corneometry), and dermal thickness (ultrasound imaging) at baseline, 15 and 90 days after treatment.

RESULTS: In vitro, CaHA + PMN induced greater fibroblast proliferation and upregulated COL1A1 and ELN gene expression compared to CaHA + SS. Clinically, both treatments led to significant improvement from baseline in HGS (p < 0.001), skin hydration and dermal/hypodermal thickness, with no statistically significant differences between-group. Investigator-assessed GAIS and patient-reported satisfaction on a 5-point Likert scale also showed improvement in both groups.

CONCLUSION: Both treatments demonstrated comparable clinical outcomes, suggesting that the strong biostimulating effect of CaHA may have overshadowed potential additive effects of PMN. Nonetheless, in vitro findings confirmed enhanced biological activity with CaHA + PMN, supporting its investigation as a complementary strategy in future studies.

PMID:41669823 | DOI:10.1111/jocd.70716

Anal Methods. 2026 Feb 11. doi: 10.1039/d5ay02096d. Online ahead of print.

ABSTRACT

Saracatinib (AZD-0530; SRB) is a pharmaceutical agent produced by AstraZeneca and is currently undergoing clinical studies. It is classified as a dual-kinase inhibitor, exhibiting selective activity both as an Src inhibitor and a Bcr-Abl tyrosine kinase inhibitor. No metabolic stability study for SRB has been reported; hence, so the goal of the present study was to establish an ultra-fast, green, sensitive, and validated UPLC-MS/MS method for the quantification of SRB levels in human liver microsomes (HLMs) using different in silico software to support the practical outcomes. The validated approach was used to estimate the SRB metabolic stability in HLMs. In silico software tools were employed to predict the potential sites of metabolic lability and toxicity within the SRB structure. SRB and baricitinib, used as an internal standard (IS), were isolated from HLMs using protein precipitation with acetonitrile (ACN) as the extracting agent. Chromatographic separation was conducted utilizing a Luna 3 µm HILIC column (200 Å: 50 × 2 mm, Ea), with the mobile phase comprising 0.1% formic acid in ACN (85%) and 10 mM ammonium formate in water (15% at pH 3.2), and the total run time was 1.0 min. SRB and IS were analyzed utilizing the MRM mass analyzer mode. The approach was validated according to the latest FDA guidelines for bioanalytical method validation. The SRB calibration curve demonstrated significant sensitivity, with a range of statistical linearity from 1 to 4000 ng mL^-1. The intraday and interday accuracies of the four quality controls varied from -4.17% to 12.25% and -3.92% to 13.50%, respectively. The metabolic stability parameters, including the in vitro half-life (t_1/2) and intrinsic clearance (Cl_int) of SRB, were assessed at 17.24 min and 47.02 mL min^-1 kg^-1, respectively. In silico research indicated that slight structural modifications to the N-methyl piperazine ring in the drug design may enhance metabolic stability and safety compared with those of SRB.

PMID:41669815 | DOI:10.1039/d5ay02096d

Yi Chuan. 2026 Feb 20;48(2):158-176. doi: 10.16288/j.yczz.25-214.

ABSTRACT

Codon usage bias (CUB) refers to the non-random usage of synonymous codons during protein translation. It holds significant value for understanding species evolution, environmental adaptation, gene expression regulation, and population genetic diversity. In this review, we summarize the biological significance of codon usage bias, outline commonly used statistical approaches for its analysis, and provide a comprehensive overview of recent advances in codon usage research within the field of entomology. This work aims to offer new perspective and methodologies insights to support further in-depth studies of codon usage patterns in insects.

PMID:41669808 | DOI:10.16288/j.yczz.25-214