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PubMed1988

Mathematical and statistical strategies for biomarker research of aging.

The continuing revolution in personal computers has placed computing power rivaling that of some computational laboratories on the desktops of many investigators. Contained in this article are some suggestions for taking advantage of this enhanced computing power in analyzing data in which an investigator does not have control over his sample. Sample reuse methods, called the jackknife and the bootstrap, are discussed, along with possible applications of time-series methods. Some suggestions for getting help from mathematical scientists are also included.

Aging↗

PubMed1990

An application of the LFP survival model to smoking cessation data.

We use a limited failure population (LFP) model based on the Weibull distribution to model the times from initial abstinence to return to smoking for subjects enrolled in programmes to help them stop smoking. The model contains a third parameter that corresponds to the proportion of subjects who permanently abstain from smoking. The data are subject to both right and interval censoring. Furthermore, subjects receive treatment in groups, and individuals in the same group may provide correlated outcomes. Use of a maximum likelihood estimation procedure which assumes independent outcomes provides reasonable parameter estimates, but the corresponding standard errors tend to be too small, which results in tests with inflated type I error levels and confidence intervals that tend to be too narrow. We use a bootstrap procedure to obtain more reasonable values for the standard errors and to construct confidence intervals that more nearly achieve the stated coverage probabilities.

Confidence Intervals↗

PubMed2026

Multiregion profiling of genomic and transcriptional heterogeneity in head and neck squamous-cell carcinoma.

BACKGROUND: Intratumoral heterogeneity (ITH) is thought to contribute to tumour evolution and treatment resistance but its biological and clinical significance in localised head and neck squamous-cell carcinoma (HNSCC) remains incompletely understood. PATIENTS AND METHODS: In the prospective SCANDARE study, we analysed 87 patients with resectable HNSCC treated with upfront surgery. Two to five spatially distinct tumour regions per patient underwent pathological evaluation, targeted DNA sequencing, and bulk RNA sequencing. Genomic ITH (gITH) was quantified using clonal deconvolution and Shannon diversity indices, whereas transcriptional heterogeneity (tITH) was assessed using the intratumour expression distance metric. Associations between ITH, molecular features, tumour microenvironment composition, and clinical outcomes were explored using multivariable statistical models. RESULTS: Pathology-based spatial heterogeneity showed limited prognostic value. gITH was common, with 37% of tumours displaying regionally heterogeneous pathogenic variants, including spatially actionable alterations in 10% of patients. In an initial multivariable Cox model, higher gITH was associated with shorter disease-free survival. However, after Ridge-penalised modelling and bootstrap internal validation, the effect size was attenuated [corrected hazard ratio 1.42, 95% confidence interval (CI) 0.91-2.75]. The overall model retained moderate discriminative performance (optimism-corrected C-index 0.69, 95% CI 0.59-0.79). gITH was associated with tumour cellularity, reduced estimated endothelial cell infiltration, and alterations in KMT2C and PIK3CA. tITH differed according to human papillomavirus (HPV) status, with lower tITH in HPV-positive tumours, and was associated with distinct biological pathways and genomic alterations. Genomic and tITH were not correlated. CONCLUSIONS: This prospective multiregion study provides a comprehensive characterisation of genomic and tITH in localised HNSCC. Our findings highlight substantial spatial molecular diversity within primary tumours and suggest potential associations between heterogeneity, tumour biology, and clinical outcome that warrant validation in independent cohorts.

head and neck squamous-cell carcinoma (HNSCC)↗

PubMed2026

Differential cell signaling testing for cell-cell communication inference from single-cell data by dominoSignal.

MOTIVATION: Algorithms for ligand-receptor network inference have emerged as commonly used tools to estimate cell-cell communication from reference single-cell data. Many studies employ these algorithms to compare signaling between conditions and lack methods to statistically identify signals that are significantly different. We previously developed the cell communication inference algorithm Domino, which considers ligand and receptor gene expression in association with downstream transcription factor activity scoring. We developed the dominoSignal software to innovate upon Domino and extend its functionality to test statistically differential cellular signaling. RESULTS: This new functionality includes the compilation of active signals as linkages from multiple subjects in a single-cell data set and testing condition-dependent signaling linkage. The software is applicable for analysis of single-cell data sets with multiple subjects as biological replicates as well as with bootstrapped replicates from data sets with few or pooled subjects. We use simulation studies to benchmark the number of subjects in compared groups and cells within an annotated cell type sufficient to accurately identify differential linkages. We demonstrate the application of the Differential Cell Signaling Test (DCST) in the dominoSignal software to investigate consequences of cancer cell phenotypes and immunotherapy on cell-cell communication in tumor microenvironments. These applications in cancer studies demonstrate the ability of differential cell signaling analysis to infer changes to cell communication networks from therapeutic or experimental perturbations, which is broadly applicable across biological systems. AVAILABILITY: dominoSignal is available through Bioconductor at https://www.bioconductor.org/packages/release/bioc/html/dominoSignal.html.

Cell Communication↗

PubMed2025

Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic data of ovarian cancer.

To unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell-cell communication between tumor and immune/stromal cells in the tumor microenvironment. Central to this communication are interactions between secreted ligands and cell-surface receptors, creating a highly connected signaling network among cells. Recent advancements in in situ-omics profiling, particularly spatial transcriptomic (ST) technology, provide unique opportunities to directly characterize ligand-receptor signaling networks that power cell-cell communication. In this paper, we propose a novel statistical method, LRnetST, to characterize the ligand-receptor interaction networks between adjacent tumor and immune/stroma cells based on ST data. LRnetST utilizes a directed acyclic graph model with a novel approach to handle the zero-inflated distributions of ST data. It also leverages existing ligand-receptor regulation databases as prior information, and employs a bootstrap aggregation strategy to achieve robust network estimation. Application of LRnetST to ST data of high-grade serous ovarian tumor samples revealed both common and distinct ligand-receptor regulations across different tumors. Some of these interactions were validated through both a MERFISH dataset and a CosMx SMI dataset of independent ovarian tumor samples. These results cast light on biological processes relating to the communication between tumor and immune/stromal cells in ovarian tumors. An open-source R package of LRnetST is available on GitHub at https://github.com/jie108/LRnetST.

Humans↗

PubMed1986

Variability of evolutionary rates of DNA.

A statistical analysis of DNA sequences from four nuclear loci and five mitochondrial loci from different orders of mammals is described. A major aim of the study is to describe the variation in the rate of molecular evolution of proteins and DNA. A measure of rate variability is the statistic R, the ratio of the variance in the number of substitutions to the mean number. For proteins, R is found to be in the range 0.16 less than R less than 35.55, thus extending in both directions the values seen in previous studies. An analysis of codons shows that there is a highly significant excess of double substitutions in the first and second positions, but not in the second and third or first and third positions. The analysis of the dynamics of nucleotide evolution showed that the ergodic Markov chain models that are the basis of most published formulas for correcting for multiple substitutions are incompatible with the data. A bootstrap procedure was used to show that the evolution of the individual nucleotides, even the third positions, show the same variation in rates as seen in the proteins. It is argued that protein and silent DNA evolution are uncoupled, with the evolution at both levels showing patterns that are better explained by the action of natural selection than by neutrality. This conclusion is based primarily on a comparison of the nuclear and mitochondrial results.

Animals↗

PubMed1992

Analysis of aberrations in public health surveillance data: estimating variances on correlated samples.

The detection of unusual patterns in health data presents an important challenge to health workers interested in early identification of epidemics or important risk factors. A useful procedure for detection of aberrations is the ratio of a current report to some historic baseline. This work addresses the problem of finding the variance of such a ratio when the surveillance reports are correlated. Results show that, when estimating this variance or the variance of the sample mean from a series of observations with an estimated correlation structure, bootstrap and jackknife estimates may be overly optimistic. The delta method or a classical method may be more useful when such model dependence is inappropriate.

Analysis of Variance↗

PubMed1989

Bootstrap investigation of the stability of a Cox regression model.

We describe a bootstrap investigation of the stability of a Cox proportional hazards regression model resulting from the analysis of a clinical trial of azathioprine versus placebo in patients with primary biliary cirrhosis. We have considered stability to refer both to the choice of variables included in the model and, more importantly, to the predictive ability of the model. In stepwise Cox regression analyses of 100 bootstrap samples using 17 candidate variables, the most frequently selected variables were those selected in the original analysis, and no other important variable was identified. Thus there was no reason to doubt the model obtained in the original analysis. For each patient in the trial, bootstrap confidence intervals were constructed for the estimated probability of surviving two years. It is shown graphically that these intervals are markedly wider than those obtained from the original model.

Azathioprine↗

PubMed1989

Comparison of correlated correlations.

We consider a problem where kappa highly correlated variables are available, each being a candidate for predicting a dependent variable. Only one of the kappa variables can be chosen as a predictor and the question is whether there are significant differences in the quality of the predictors. We review several tests derived previously and propose a method based on the bootstrap. The motivating medical problem was to predict 24 hour proteinuria by protein-creatinine ratio measured at either 08:00, 12:00 or 16:00. The tests which we discuss are illustrated by this example and compared using a small Monte Carlo study.

Humans↗

PubMed2025

A prediction model for metachronous colorectal cancer: development and validation.

BACKGROUND: Being able to estimate the risk of metachronous disease in a patient with colorectal cancer (CRC) could enable risk-appropriate surveillance. The aim of this study was to develop a risk-prediction model to estimate individual 10-year risk of metachronous disease following a CRC diagnosis. METHODS: A population-based cohort of patients with CRC was recruited soon after diagnosis between 1997 and 2012 from the United States, Canada, and Australia. Cox regression with the least absolute shrinkage and selection operator penalization was used to identify factors that predicted the risk of a new primary CRC diagnosed at least 1 year after the initial CRC diagnosis. Potential predictors included demography, anthropometry, lifestyle factors, comorbidities, personal and family cancer history, medication use, age at diagnosis, and pathological features of the first CRC. Internal validation through bootstrapping was used to evaluate the discrimination and calibration. RESULTS: We included 6085 CRC cases; 138 (2.3%) of these cases were diagnosed with metachronous disease over a median of 12 years (IQR = 5-17 years). Metachronous CRC risk was predicted by body mass index; smoking status; level of physical activity; family history of cancer and synchronous CRC; stage, grade, histological type, and DNA mismatch repair status; and age at diagnosis of the first CRC. The model was valid with a C statistic of 0.65 (95% CI = 0.63 to 0.68) and a calibration slope of 0.873 (SD = 0.087). CONCLUSIONS: Metachronous CRC can be predicted with reasonable accuracy using a prediction model that consists of clinical variables collected as part of routine practice.

Humans↗

PubMed1979

A funny thing happened to us on the way to the latent entities.

Inferred latent entities, whether those of psychoanalysis, factor analysis, or cluster analysis, have declined in value for many clinical psychologists, both as tools of practice and as objects of theoretical interest. Behavior modification, rational-emotive therapy, crisis intervention, psycho-pharmacology, and actuarial prediction all tend to minimize reliance on latent entities in favor of purely dispositional concepts. Behavior genetics is, however, a powerful movement to the contrary. As regards categorical entities (types, taxa, syndromes, diseases), history reveals no impressive examples of their discovery by cluster algorithms; whereas organic medicine and psychopathology have both discovered many taxonic entities without reliance on formal (statistical) cluster methods. I offer eight reasons for this strange condition, with associated suggestions for ameliorating it. Adopting a realist instead of a fictionist approach to taxonomy, I give high priority to theory-based mathematical derivation of quantitative consistency tests for all taxometric results. I urge a large scale cooperative survey of taxometric methods based on Monte Carlo runs, biological pseudoproblems where the true axon is independently known, and live problem in genetics, organic medicine, and psychopathology. An empirical example of taxometric bootstrapping and consistency testing was presented from my own current research on schizotypy.

Humans↗

PubMed2026

Associations Between Short Video Exposure, Empathy and Attitudes Toward End-Of-Life Care Among Nursing Students: A Cross-Sectional Study.

AIM: This cross-sectional study examined the associations between short video exposure, nursing students' empathy, and attitudes toward end-of-life (EOL) care, and tested whether perceived impact is statistically consistent with an indirect pathway in these relationships. DESIGN: A descriptive cross-sectional study. METHODS: In total, 534 undergraduate nursing students were included. Data were collected using a self-designed questionnaire, including the Attitudes Toward Care of the Dying Scale and the Jefferson Scale of Empathy-Health Professions Student version for empathy assessment. Statistical analysis for correlation and mediation analysis (PROCESS macro) was performed. RESULTS: 85.96% of students watch short videos for more than 30 min daily, with more than 60% of them viewing EOL-related content. Students with prior caregiving experience or formal palliative care education showed significantly higher empathy and more positive attitudes (p < 0.05). Exposure to medical and EOL-related short videos was positively correlated with perceived impact, empathy, and positive EOL attitudes, with effect sizes ranging from very weak to modest (r = 0.10 to 0.27). The data were consistent with an indirect pathway between short video exposure and empathy via perceived impact (indirect effect = 0.04; 95% bootstrap CI [0.01, 0.08]). However, for EOL attitudes, short video exposure showed a direct association rather than an indirect pathway via perceived impact (direct effect = 0.09, p < 0.01). CONCLUSION: In this cross-sectional study, short video exposure was modestly associated with nursing students' empathy, with data consistent with an indirect pathway via perceived impact; the observed associations explained only approximately 1% to 7% of the variance in the outcome variables. However, reshaping EOL attitudes may require more systematic education beyond brief video exposure. These findings are hypothesis-generating and await validation through longitudinal and experimental research using standardized video content. IMPLICATIONS FOR NURSING PRACTICE: Nursing educators should consider integrating curated short video content into palliative care curricula to enhance students' empathy and perceived impact of end-of-life education. However, brief video exposure alone may be insufficient to reshape deeper end-of-life attitudes, suggesting the need for comprehensive, multi-modal educational strategies.

Humans↗

PubMedDate not supplied

Circannual bootstrapping complements pattern discrimination in the assessment of endocrine markers for an expansive personality (EP).

The bootstrap distribution of the difference in the circannual mesor of DHEA-S, TSH and LH between healthy adult women of a lowly or highly expansive personality, assessed by scale 9 of an abbreviated Minnesota Multiphasic Personality Inventory, validates the potential classifying role of these hormones, originally singled out by methods of pattern discrimination.

Adult↗

PubMed1986

Rapid estimation of hospitalization charges from a brief medical record review. Evaluation of a multivariate prediction model.

In settings where an itemized hospital bill is not generated, estimation of hospitalization charges for research or administrative purposes can be a laborious task. This article examines the extent to which the number of hospital days spent outside an intensive care unit (ICU), number of days in an ICU, number of laboratory tests performed, number of x-rays, and number of surgeries can be used in a multiple regression equation to impute inpatient charges for a sample of 103 hospitalizations at a Veterans Administration hospital. These predictor variables, all of which are readily ascertained in a brief medical record review, accounted for about 97% of the variance in imputed hospital charges. The bootstrap method was applied for validation of the prediction equation. Application of the method described here may be of value to researchers concerned with hospital charge estimation in non-fee-for-service settings.

Aged↗

PubMed1991

The unseen sample in cohort studies: estimation of its size and effect. Multicenter AIDS Cohort Study.

Recruitment of disease-free subjects into cohort studies and measurement of their time from exposure/infection to disease selectively excludes individuals (the unseen sample) who had earlier exposure and who have shorter times to disease. The unseen and observed samples may differ in other characteristics in addition to incubation period and exposure/infection time. For data with known truncation times, we develop non-parametric maximum likelihood estimates of the size, exposure/infection dates and distribution of incubation time in the unseen sample. We provide procedures to estimate and compensate for the biasing effects due to exclusion of the unseen sample in descriptive and survival analysis. We give consistency properties of these estimates and assess variability using bootstrap methods. One can use imputation to derive the above estimates from data with unknown truncation times that have been estimated parametrically. Application is made to an AIDS cohort study of over 5000 homosexual men. Important estimates obtained from this application are the annual seroconversion rates from 1978 to 1983, not otherwise obtainable in this study population.

Acquired Immunodeficiency Syndrome↗

PubMed1991

Thymic peptides, stress, and depressive symptoms in older men: a comparison of different statistical techniques for small samples.

Thymic peptides play an important role in aging and immune regulation, but little is known about their relationship to psychosocial factors. One thymic fraction, thymosin-alpha 1 (TSN-alpha 1) may be of particular interest given its hypothesized role in the differentiation of immature T cells into functional, mature T cells. We examined the relationships among stress, psychological symptoms, and TSN-alpha 1 levels in two conditions; before and after a glucose challenge test. The sample consisted of 18 men, aged 48-80, participants in the Normative Aging Study. While none of the correlations reached significance in the baseline condition, life events and depressive symptoms were significantly correlated with TSN-alpha 1 in the postchallenge condition (r's = .57, and .62, respectively). Hierarchical regression analyses with cross-product interaction terms suggested that individuals who were high in both life events and depression showed the highest levels of postchallenge TSN-alpha 1, with the psychosocial variables accounting for 65% of the variance. Given the small sample size, we replicated these analyses using jackknife and bootstrap techniques, which generally confirmed these findings. Thus, these preliminary results suggest that psychosocial factors may be related to abnormal TSN-alpha 1 responses to a challenge.

Aged↗

PubMed2025

S-GMAS: Genome-Wide Mediation Analysis With Brain Subcortical Shape Mediators.

Mediation analysis is widely utilized in neuroscience to investigate the role of brain image phenotypes in the neurological pathways from genetic exposures to clinical outcomes. However, it is still difficult to conduct mediation analyses with whole genome-wide exposures and brain subcortical shape mediators due to several challenges including (i) large-scale genetic exposures, that is, millions of single-nucleotide polymorphisms (SNPs); (ii) nonlinear Hilbert space for shape mediators; and (iii) statistical inference on the direct and indirect effects. To tackle these challenges, this paper proposes a genome-wide mediation analysis framework with brain subcortical shape mediators. First, to address the issue caused by the high dimensionality in genetic exposures, a fast genome-wide association analysis is conducted to discover potential genetic variants with significant genetic effects on the clinical outcome. Second, the square-root velocity function representations are extracted from the brain subcortical shapes, which fall in an unconstrained linear Hilbert subspace. Third, to identify the underlying causal pathways from the detected SNPs to the clinical outcome implicitly through the shape mediators, we utilize a shape mediation analysis framework consisting of a shape-on-scalar model and a scalar-on-shape model. Furthermore, the bootstrap resampling approach is adopted to investigate both global and spatial significant mediation effects. Finally, our framework is applied to the corpus callosum shape data from the Alzheimer's Disease Neuroimaging Initiative.

Humans↗

PubMed2026

Coagulation activation is associated with genomic-instability-related features in TP53-mutated AML and MDS: routine laboratory patterns beyond classical disseminated intravascular coagulation.

BACKGROUND: Disseminated intravascular coagulation (DIC) is a serious complication of acute myeloid leukemia (AML) associated with poor prognosis. In TP53-mutated AML and myelodysplastic syndrome (MDS), however, the classical ISTH criteria rarely identify overt DIC, although bleeding and thrombotic complications are well documented in acute leukaemia. We hypothesized that these patients exhibit a lower-grade, subclinical coagulation activation that is associated with the underlying genomic-instability-related features of TP53-mutant disease. METHODS: We retrospectively analyzed 107 consecutive patients with TP53-mutated AML (n = 52) or high-risk MDS (MDS, n = 55), median age 65 years, diagnosed and initially evaluated at our centre between 2018 and 2025. Seven routine coagulation markers and 46 co-mutated genes were evaluated for associations with overall survival (OS) using univariate and multivariable Cox regression, continuous dose-response modeling, and unsupervised k-means clustering. Internal validity was assessed by 1000 bootstrap resamples. RESULTS: Overt DIC according to ISTH criteria was rare (15%). Subclinical activation was common: 50% of patients had a D-dimer ≥1 μg/mL, 41% a fibrinogen ≥4 g/L, and 29% an INR ≥1.2. In univariate analysis, D-dimer, fibrinogen, INR, prothrombin time, and activated partial thromboplastin time were each associated with OS (HR 1.33-1.38 per SD; all p < 0.05). Complex karyotype correlated with higher D-dimer (median 1.39 vs. 0.60 μg/mL, p = 0.022) and fibrinogen (3.91 vs. 2.53 g/L, p = 0.007), while TP53 variant allele frequency (VAF) showed modest positive correlations with D-dimer (ρ = 0.21), INR (ρ = 0.27), and PT (ρ = 0.27; all p < 0.05). Clustering identified three coagulation phenotypes: Silent (51%), Thrombo-inflammatory (31%), and Consumption-like (18%), showing a graded but statistically non-significant gradient in molecular features and a stepwise decline in median OS (14, 10 and 8 months; log-rank p = 0.041). After adjustment for complex karyotype, TP53 VAF, and favorable co-mutation count, the Consumption-like phenotype was associated with a non-significant increased risk (HR 1.83, 95% CI 0.92-3.65, p = 0.084), whereas favorable co-mutation pathways remained independently protective (HR 0.56, 95% CI 0.35-0.90, p = 0.016). CONCLUSION: In TP53-mutated AML/MDS, coagulation activation intensity is associated with the degree of genomic instability. The three phenotypes may add biological resolution beyond classical DIC and cytogenetic risk groups, but represent laboratory patterns rather than validated bleeding or thrombosis prediction tools. However, after accounting for genomic features, phenotypes were not independent predictors of outcome, with complex karyotype, TP53 VAF, and favorable co-mutation count driving prognosis. Because treatment intensity and other clinical confounders were not available, these survival associations are hypothesis-generating. Coagulation profiling remains inexpensive, widely accessible, and offers a practical window into disease biology that warrants prospective validation.

TP53↗