Category: Statistics

J Psychiatr Res. 2026 Jul 21;201:641-650. doi: 10.1016/j.jpsychires.2026.07.020. Online ahead of print.

ABSTRACT

BACKGROUND: Anorexia nervosa (AN) is a severe psychiatric disorder frequently associated with affective disturbances, particularly depression, and marked deficits in emotional awareness. Alexithymia has been identified as a core vulnerability factor in AN, however, its relationship with eating disorder symptomatology appears complex and may be influenced by depressive mood. Despite growing interest in transdiagnostic emotional processes, the mediating role of depression in the association between alexithymia and eating symptoms remains insufficiently explored, especially in young women and using comprehensive psychopathological assessment tools.

OBJECTIVES: The present study aimed to examine differences in alexithymia, emotion regulation, mood, personality-related psychopathology, and eating disorder symptoms between young women with and without restrictive AN; to investigate associations among these dimensions within each group; and to test the mediating role of depression in the relationship between alexithymia and eating disorder symptomatology.

METHODS: The sample consisted of 47 young women with restrictive AN and 48 non-clinical controls aged 16-30 years. Participants completed the Toronto Alexithymia Scale (TAS-20), Profile of Mood States (POMS), Emotion Regulation Questionnaire (ERQ), Minnesota Multiphasic Personality Inventory-2 (MMPI-2) and Eating Disorder Inventory-3 (EDI-3). Group comparisons were performed between the clinical and control groups. Correlational analyses and mediation models were conducted separately within each group.

RESULTS: Compared to controls, patients with AN showed significantly higher levels of psychopathology, depressive mood, alexithymia, and expressive suppression. Correlational analyses revealed partially different patterns across groups. Mediation analyses indicated that, in the clinical group, the association between alexithymia and eating disorder symptoms was fully accounted for by depressive symptoms, whereas in the control group both direct and indirect associations remained statistically significant.

CONCLUSIONS: These findings suggest that depressive symptoms may partially account for the observed association between alexithymia and eating disorder symptoms in AN. However, the cross-sectional design precludes causal inferences. Nevertheless, the results highlight the clinical relevance of assessing emotional awareness and depressive symptoms in young women with AN.

PMID:42503289 | DOI:10.1016/j.jpsychires.2026.07.020

Int J Pediatr Otorhinolaryngol. 2026 Jul 20;208:112954. doi: 10.1016/j.ijporl.2026.112954. Online ahead of print.

ABSTRACT

AIMS: This systematic review and meta-analysis aimed to evaluate the efficacy and safety of press-needle therapy for allergic rhinitis in children.

METHODS: We comprehensively searched for relevant randomized controlled trials (RCTs) on press-needle therapy for pediatric AR. After strict screening of literature, data extraction and assessment of methodological quality, meta-analysis was performed using appropriate statistical methods. A random-effects model was adopted to synthesize the results, considering differences in follow-up duration and intervention period among included studies. Pre-specified further analyses were conducted for the primary outcome to compare press-needle plus medication vs medication alone, press-needle alone vs medication alone, and press-needle plus medication vs press-needle alone. The primary and secondary outcome measures included clinical efficacy, symptom and sign score, Visual Analogue Scale (VAS) score, Total Nasal Symptom Score (TNSS), Pediatric Rhinoconjunctivitis Quality of Life Questionnaire (PRQLQ) score, Eosinophil Ratio (EOSR), serum immunoglobulin E (IgE) levels, adverse drug reactions (ADRs) and recurrence rate.

RESULTS: 24 RCTs with 1625 participants were included. Press-needle therapy significantly improved clinical efficacy (OR = 3.75, 95 CI: 2.59-5.42; I² = 0%). Further analysis showed that press-needle plus medication was superior to medication alone (OR = 4.60, 95% CI: 3.08-6.86), whereas press-needle monotherapy did not show a significant advantage over medication alone. Significant reductions were observed in VAS (SMD = -1.30), TNSS (SMD = -0.74), PRQLQ (SMD = -1.16), and serum IgE (SMD = -2.06; based on only 3 studies, I² = 96%, interpret with caution). No significant differences were found in symptom and sign score, EOSR, or ADRs. Recurrence rate was significantly lower in the intervention group (OR = 0.37, 95% CI: 0.23-0.61).

CONCLUSION: Press-needle therapy, primarily as an adjunct to pharmacotherapy, may be a well-tolerated and potentially effective option for pediatric AR, improving clinical response, symptoms, quality of life, and recurrence without increasing adverse events. Evidence for press-needle monotherapy and for immunological outcomes (IgE, EOSR) remains limited. Multi-center, three-arm RCTs with standardized protocols and long-term follow-up are needed to isolate its independent effect.

SYSTEMATIC REVIEW REGISTRATION: The protocols for this meta-analysis were registered in the International Prospective Register of Systematic Reviews (PROSPERO, https://www.crd.york.ac.uk/PROSPERO/view/CRD420261307545.).

PMID:42503260 | DOI:10.1016/j.ijporl.2026.112954

J Magn Reson Imaging. 2026 Jul 26. doi: 10.1002/jmri.70445. Online ahead of print.

ABSTRACT

BACKGROUND: Nasopharyngeal carcinoma (NPC) can be detected early on MRI, but adoption for screening is limited by a shortage of experienced specialists. MRI artificial intelligence (AI) algorithms for diagnosing NPC in the literature may address this, but most studies focus on routine clinical care, and their applicability in screening requires close examination.

PURPOSE: To (i) evaluate the diagnostic performance of AI for NPC detection, (ii) analyze the impact of study protocols, and (iii) assess the applicability of existing studies to NPC screening.

STUDY TYPE: Systematic review.

POPULATION: Thirty-eight studies were included, including a total of 23,398 patients (20,693 NPC and 2705 non-NPC).

FIELDSTRENGTH: 1.5 T to 3.0 T.

ASSESSMENT: Following PRISMA guidelines, PubMed, Scopus, and Embase records from January 1, 2009 to August 16, 2025 were screened by two independent reviewers for studies on NPC detection, localization, and/or diagnosis using MRI. Included studies were reviewed for applicability and risk of bias. Lesion-localization performance (Dice similarity score [DSC]) and NPC vs. non-NPC discrimination (sensitivity/specificity) were extracted and summarized. Subgroup analyses assessed the impact of intravenous contrast on AI performance.

STATISTICAL TESTS: Meta-analysis used standard random-effects univariate restricted maximum likelihood model and hierarchical summary receiver operator characteristics for performance pooling and subgroup analysis, taking p value < 0.05 as significance.

RESULTS: Pooled performance from 30 localization and 6 discrimination studies was DSC = 0.80 (CI: 0.78-0.82) and sensitivity/specificity = 97.1% (CI: 88.0%-99.3%)/87.8% (CI: 78.9%-93.2%), respectively. Intravenous contrast did not significantly affect AI performance for either task (p > 0.05). Only seven studies were fully applicable to screening.

DATA CONCLUSION: AI-driven NPC screening using MRI is feasible at high sensitivity. Using non-contrast MRI did not significantly impact AIs’ performance. However, applicability and the suboptimal ratio of NPC: non-NPC patients remain the weaknesses of existing studies, warranting further investigation with cohorts that better reflect the screening scenario.

SYSTEMATIC REVIEW REGISTRATION: The systematic review protocol of this system is registered with the Inplasy registry (Ref. INPLASY202570076).

PMID:42503234 | DOI:10.1002/jmri.70445

Cancer Med. 2026 Jul;15(7):e72116. doi: 10.1002/cam4.72116.

ABSTRACT

PURPOSE: Infectious complications in patients with cancer are contributors to hospitalisations, treatment disruption, and mortality. This study aimed to develop machine learning (ML) models for risk stratification of infection-related hospitalisations (IRHs) among patients with cancer.

METHODS: Adult patients diagnosed with and treated for lymphoma, multiple myeloma (MM), chronic lymphocytic leukaemia (CLL), colorectal, or lung cancer from 2013 to 2023 in the North Denmark Region were included. Data from national cancer registries and patient health records were used. Serious infections were defined as sepsis, positive blood culture, intensive care admission, or death during hospitalisation. Models were developed using multiple ML methodologies across three different data setups: ML-using data up to hospital admission; ML₄₈-using data up to 48 h after admission; and ML_48,reduced-a pruned version of ML₄₈ with fewer features. Data were split into training, validation and held-out test sets.

RESULTS: Among 9874 patients 2661 IRHs occurred, including 691 (21.5%) serious infections. On the held-out test set, ML achieved the best performance (ROC-AUC: 0.79) versus ML₄₈ (0.76), with ML₄₈ having higher specificity at matched sensitivity (50.9% vs 44.9% for sensitivity ~85%). ML_48,reduced reached a ROC-AUC of 0.75 (specificity 46.5% at sensitivity ~85%). Subgroup analysis showed the best performance for lymphoma (ROC-AUC: 0.86) and lowest for lung cancer (ROC-AUC: 0.73). The model performed better in patients with ECOG score 0-1 compared to ≥ 2 (ROC-AUC 0.88 vs. 0.77). SHAP analysis identified previous blood cultures, carbamide, and neutrophil counts as key predictive features across all models.

CONCLUSION: The ML models showed moderate performance in risk stratification of IRHs in patients with cancer. Such models could provide decision support in hospitalisation decisions and discharge.

PMID:42503233 | DOI:10.1002/cam4.72116

Chem Biodivers. 2026 Jul;23(7):e71511. doi: 10.1002/cbdv.71511.

ABSTRACT

The present study investigates the phytochemical composition, antioxidant potential, and preliminary in silico interactions of the methanolic root extract of Antigonon leptopus. Qualitative phytochemical screening suggested the presence of alkaloids, flavonoids, phenolics, tannins, saponins, and terpenoids. The extract exhibited moderate free radical scavenging activity in the DPPH assay, with an IC₅₀ value of 142.45 ± 3.05 µg/mL, compared with ascorbic acid (IC₅₀ = 18.09 ± 0.51 µg/mL). Statistical analysis using Student’s t-test indicated a significant difference between the extract and standard (p < 0.001). In addition, the extract exhibited a ferric reducing antioxidant power (FRAP) of 278.12 ± 0.65 µM Fe^{2 +}/g dry extract and contained appreciable levels of total phenolics (394.50 ± 3.77 mg GAE/g dry extract) and total flavonoids (55.33 ± 1.16 mg QE/g dry extract), suggesting that polyphenolic constituents contribute to the observed antioxidant activity. Molecular docking was conducted as an exploratory approach to predict potential interactions of selected phytochemicals with NADPH oxidase 2 (NOX2), but these results are considered preliminary and require further experimental validation. Overall, the findings suggest that A. leptopus roots contain bioactive secondary metabolites with moderate antioxidant activity, warranting further in-depth biological and mechanistic studies.

PMID:42503198 | DOI:10.1002/cbdv.71511

Stat Med. 2026 Aug;45(18-19):e70637. doi: 10.1002/sim.70637.

ABSTRACT

While randomized clinical trials (RCTs) are widely regarded as the gold standard for estimating average treatment effects, their external validity is often constrained by limited sample sizes and restrictive inclusion/exclusion criteria, which may compromise the generalizability of findings to broader real-world populations. Conversely, observational studies typically consist of representative real-world samples but are susceptible to bias due to unmeasured confounders, undermining their internal validity. To address the limitation, sensitivity analysis is often used to estimate bounds for the average treatment effect (ATE) without relying on stringent assumptions of other existing methods. This article introduces a novel synthesis sensitivity analysis estimator that enhances sensitivity analysis in observational studies by incorporating RCT data, even when limited covariate overlap exists between datasets due to differential inclusion/exclusion criteria. We show that the proposed estimator will give a tighter bound when a “separability” condition holds for the sensitivity parameter. Theoretical proofs and simulations show that this method provides a tighter bound than the sensitivity analysis using only observational study data. We apply this method to combine observational study data on drug effectiveness comparison with a partially overlapping RCT data, yielding tighter average treatment effect bounds.

PMID:42503171 | DOI:10.1002/sim.70637

Orv Hetil. 2026 Jul 26;167(30):1207-1212. doi: 10.1556/650.2026.33610. Print 2026 Jul 26.

ABSTRACT

INTRODUCTION: Adolescence is of particular importance in the prevention of non-communicable chronic diseases, as health behavior patterns established during this life stage may influence adult morbidity in the long term. The healthcare system and societal burden of chronic diseases justify the development of prevention programs initiated early in life and adapted to the needs of the target population.

OBJECTIVE: The aim of our study was to assess program awareness, health behavior characteristics and perceptions of prevention programs among the target population of the “Youth for a Healthy Future” (YHF) program.

METHOD: A cross-sectional quantitative questionnaire-based study was conducted in 2025 using convenience sampling. The 26-item online questionnaire was completed by 427 examined individuals; data processing was performed using IBM SPSS Statistics 30.0 software. In addition to descriptive statistics, cross-tabulation, Pearson’s χ² test and Cramér’s association coefficient were applied.

RESULTS: The sample comprised 46% boys and 52.0% girls; the mean age was 18.0 years (SD = 1.73). The YHF program was known by 16% of respondents, and 29 examined individuals reported direct participation. Regular smoking was reported by 16% and occasional smoking by 17% of respondents. A significant association was found between school type and smoking status (χ² = 36.798; p<0.001; Cramér’s V = 0.29): a lower smoking rate was observed among grammar school students, whereas regular smoking was more frequent among vocational secondary school and technical school students. Awareness of the YHF program was also associated with school type (χ² = 12.070; p = 0.002; Cramér’s V = 0.17), with higher awareness among grammar school students. Among barriers to participation, insufficient information was reported by 61% of respondents, lack of free or discounted participation by 58%, and the insufficiently practical nature of programs by 38%. Among future program topics, stress management, mental health and sports events attracted the greatest interest.

CONCLUSION: Based on our findings, improving the reach of the YHF program and similar prevention initiatives requires more targeted communication, program structures better adapted to differences by school type and sex, and a stronger emphasis on practical and interactive program elements. Due to the cross-sectional design, causal conclusions cannot be drawn; however, the results may provide a basis for future longitudinal and controlled studies. Orv Hetil. 2026; 167(30): 1207-1212.

PMID:42503164 | DOI:10.1556/650.2026.33610

Phys Rev Lett. 2026 Jul 10;137(2):027101. doi: 10.1103/3ck1-gzzf.

ABSTRACT

We study mean-field Ising models in which the coupling depends on the magnetization via a feedback function. We identify mixed phases (MPs) and show that they can be stable at zero temperature for sufficiently strong feedback. Moreover, stable MPs are always superstable, meaning that perturbations decay linearly in time. Feedback Ising models (FIMs) provide a useful framework for phase transformations between aligned phases via stable and unstable intermediate phases in multistable systems. We also analyze the dynamical behavior of FIMs driven by a varying magnetic field and discuss basic properties of finite-dimensional FIMs.

PMID:42503150 | DOI:10.1103/3ck1-gzzf

Phys Rev Lett. 2026 Jul 10;137(2):021405. doi: 10.1103/pqcz-cvsv.

ABSTRACT

Gravitational-wave signals are typically interpreted under the vacuum hypothesis, i.e., assuming negligible influence from the astrophysical environment. This assumption is expected to break down for low-frequency sources such as extreme mass ratio inspirals (EMRIs), which are prime targets for the Laser Interferometer Space Antenna (LISA) and are expected to form, at least in part, in dense environments such as active galactic nuclei or dark-matter spikes or cores. Modeling environmental effects parametrically is challenging due to the large uncertainties in their underlying physics. We propose a nonparametric test for environmental effects in EMRIs, based on assessing the self-consistency of vacuum parameter posteriors inferred from different portions of the signal. Our results demonstrate that this test can reveal statistically significant inconsistencies from vacuum signals-arising from, e.g., incomplete modeling, environmental effects, or deviations from general relativity-without introducing additional parameters or assumptions about the underlying physics.

PMID:42503148 | DOI:10.1103/pqcz-cvsv

Phys Rev Lett. 2026 Jul 10;137(2):021410. doi: 10.1103/5hvn-3lmh.

ABSTRACT

We introduce accelerated sequential posterior inference via reuse (ASPIRE), a broadly applicable framework that transforms existing posterior samples and Bayesian evidence estimates into unbiased results under alternative models without rerunning the original analysis. ASPIRE combines normalizing flows with a generalized sequential Monte Carlo (SMC) scheme, enabling efficient updates of existing results and reducing total likelihood evaluations and wall times by factors of up to 5.8 and 5.5, respectively, with larger gains per posterior sample. This addresses a growing problem in gravitational-wave astronomy, where events must be repeatedly reanalyzed under different models or physical hypotheses. We show that ASPIRE reproduces full Bayesian results when switching waveform models or adding physical effects such as spin precession and orbital eccentricity. With this statistical robustness, ASPIRE turns repeated reanalyses into fast, reliable updates-paving the way for systematic studies of waveform systematics, scalable reanalyses across large event catalogs, and broadly applicable Bayesian reanalysis across other scientific domains.

PMID:42503147 | DOI:10.1103/5hvn-3lmh