Tag: statistics

PLoS Comput Biol. 2024 Feb 22;20(2):e1011878. doi: 10.1371/journal.pcbi.1011878. Online ahead of print.

ABSTRACT

Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model with N alleles, which maps genotype to fitness, allows comparisons between N genotypes simultaneously, but does not encode continuous drug response data. In clinical settings, there may be a wide range of drug concentrations selecting for a variety of genotypes in both cancer and infectious diseases. Therefore, there is a need for a more robust model of the pathogen response to therapy to predict resistance and design new therapeutic approaches. Fitness seascapes, which model genotype-by-environment interactions, permit multiple MSW comparisons simultaneously by encoding genotype-specific dose-response data. By comparing dose-response curves, one can visualize the range of drug concentrations where one genotype is selected over another. In this work, we show how N-allele fitness seascapes allow for N * 2N-1 unique MSW comparisons. In spatial drug diffusion models, we demonstrate how fitness seascapes reveal spatially heterogeneous MSWs, extending the MSW model to more fully reflect the selection of drug resistant genotypes. Furthermore, using synthetic data and empirical dose-response data in cancer, we find that the spatial structure of MSWs shapes the evolution of drug resistance in an agent-based model. By simulating a tumor treated with cyclic drug therapy, we find that mutant selection windows introduced by drug diffusion promote the proliferation of drug resistant cells. Our work highlights the importance and utility of considering dose-dependent fitness seascapes in evolutionary medicine.

PMID:38386690 | DOI:10.1371/journal.pcbi.1011878

PLoS Negl Trop Dis. 2024 Feb 22;18(2):e0011986. doi: 10.1371/journal.pntd.0011986. Online ahead of print.

ABSTRACT

BACKGROUND: Trachoma recrudescence after elimination as a public health problem has been reached is a concern for control programs globally. Programs typically conduct district-level trachoma surveillance surveys (TSS) ≥ 2 years after the elimination threshold is achieved to determine whether the prevalence of trachomatous inflammation-follicular (TF) among children ages 1 to 9 years remains <5%. Many TSS are resulting in a TF prevalence ≥5%. Once a district returns to TF ≥5%, a program typically restarts costly mass drug administration (MDA) campaigns and surveys at least twice, for impact and another TSS. In Amhara, Ethiopia, most TSS which result in a TF ≥5% have a prevalence close to 5%, making it difficult to determine whether the result is due to true recrudescence or to statistical variability. This study’s aim was to monitor recrudescence within Amhara by waiting to restart MDA within 2 districts with a TF prevalence ≥5% at TSS, Metema = 5.2% and Woreta Town = 5.1%. The districts were resurveyed 1 year later using traditional and alternative indicators, such as measures of infection and serology, a “wait and watch” approach.

METHODS/PRINCIPAL FINDINGS: These post-surveillance surveys, conducted in 2021, were multi-stage cluster surveys whereby certified graders assessed trachoma signs. Children ages 1 to 9 years provided a dried blood spot and children ages 1 to 5 years provided a conjunctival swab. TF prevalence in Metema and Woreta Town were 3.6% (95% Confidence Interval [CI]:1.4-6.4) and 2.5% (95% CI:0.8-4.5) respectively. Infection prevalence was 1.2% in Woreta Town and 0% in Metema. Seroconversion rates to Pgp3 in Metema and Woreta Town were 0.4 (95% CI:0.2-0.7) seroconversions per 100 child-years and 0.9 (95% CI:0.6-1.5) respectively.

CONCLUSIONS/SIGNIFICANCE: Both study districts had a TF prevalence <5% with low levels of Chlamydia trachomatis infection and transmission, and thus MDA interventions are no longer warranted. The wait and watch approach represents a surveillance strategy which could lead to fewer MDA campaigns and surveys and thus cost savings with reduced antibiotic usage.

PMID:38386689 | DOI:10.1371/journal.pntd.0011986

PLoS One. 2024 Feb 22;19(2):e0297874. doi: 10.1371/journal.pone.0297874. eCollection 2024.

ABSTRACT

Bayes factors for composite hypotheses have difficulty in encoding vague prior knowledge, as improper priors cannot be used and objective priors may be subjectively unreasonable. To address these issues I revisit the posterior Bayes factor, in which the posterior distribution from the data at hand is re-used in the Bayes factor for the same data. I argue that this is biased when calibrated against proper Bayes factors, but propose adjustments to allow interpretation on the same scale. In the important case of a regular normal model, the bias in log scale is half the number of parameters. The resulting empirical Bayes factor is closely related to the widely applicable information criterion. I develop test-based empirical Bayes factors for several standard tests and propose an extension to multiple testing closely related to the optimal discovery procedure. When only a P-value is available, an approximate empirical Bayes factor is 10p. I propose interpreting the strength of Bayes factors on a logarithmic scale with base 3.73, reflecting the sharpest distinction between weaker and stronger belief. This provides an objective framework for interpreting statistical evidence, and realises a Bayesian/frequentist compromise.

PMID:38386684 | DOI:10.1371/journal.pone.0297874

PLoS One. 2024 Feb 22;19(2):e0298810. doi: 10.1371/journal.pone.0298810. eCollection 2024.

ABSTRACT

INTRODUCTION: The novel coronavirus SARS-CoV-2 causes Coronavirus Disease 2019 (COVID-19). Vaccination has been identified as one of the most effective strategies for combating COVID-19. Positive perceptions and attitudes of HCPs towards the COVID-19 vaccination are essential to vaccine uptake and adherence. However, the perceptions and attitudes of HCPs towards the COVID-19 vaccination remain largely unexplored. We therefore assessed healthcare professionals’ perceptions, attitudes, and predictors of their attitudes towards COVID-19 vaccination in the Wa Municipality, Upper West Region of Ghana.

METHODS: In 2023, from January 16th to February 28th, we administered a multi-centre e-survey to a cross-section of 403 healthcare professionals in Wa Municipality of the Upper West Region, Ghana. We used STATA version 13 to analyze the data. Frequencies, percentages, and composite scores were used to assess perceptions and attitudes towards the COVID-19 vaccination. Hierarchical binary logistic regression modeling was then used to determine the predictors of attitudes towards the COVID-19 vaccination.

RESULTS: The healthcare professionals had positive perceptions [6.00; IQR = 4.00-7.00] and attitudes [5.00; IQR = 4.00-5.00] towards theCOVID-19 vaccination. Positive perception [aOR = 1.81; 95% CI = 1.14-2.87, p < 0.05], female sex [aOR = 0.58; 95% CI = 0.35-0.97, p < 0.05], marital status [aOR = 1.94; 95% CI = 1.20-3.12; p < 0.01], having a bachelor’s degree or higher [aOR = 2.03; 95% CI = 1.01-4.12; p < 0.05], and working in the Wa North sub-Municipal area [aOR = 0.22; 95% CI = 0.05-0.96; p < 0.05] were statistically significantly associated with attitudes towards COVID-19 vaccination.

CONCLUSION: The healthcare professionals’ perceptions and attitudes towards the COVID-19 vaccination were positive but suboptimal. We recommend regular education on COVID-19 vaccine benefits, safety, and efficacy. Enabling the work environment and addressing vaccine availability and accessibility for healthcare professionals should also be prioritized. These measures should particularly focus on female, single healthcare professionals who possess below a bachelor’s degree and are working in the Wa North sub-municipal area.

PMID:38386682 | DOI:10.1371/journal.pone.0298810

Stat Med. 2024 Mar 15;43(6):1170-1193. doi: 10.1002/sim.9999. Epub 2024 Jan 20.

ABSTRACT

This research introduces a multivariate $\tau$ -inflated beta regression ( $\tau$ -IBR) modeling approach for the analysis of censored recurrent event data that is particularly useful when there is a mixture of (a) individuals who are generally less susceptible to recurrent events and (b) heterogeneity in duration of event-free periods amongst those who experience events. The modeling approach is applied to a restructured version of the recurrent event data that consists of censored longitudinal times-to-first-event in $\tau$ length follow-up windows that potentially overlap. Multiple imputation (MI) and expectation-solution (ES) approaches appropriate for censored data are developed as part of the model fitting process. A suite of useful analysis outputs are provided from the $\tau$ -IBR model that include parameter estimates to help interpret the (a) and (b) mixture of event times in the data, estimates of mean $\tau$ -restricted event-free duration in a $\tau$ -length follow-up window based on a patient’s covariate profile, and heat maps of raw $\tau$ -restricted event-free durations observed in the data with censored observations augmented via averages across MI datasets. Simulations indicate good statistical performance of the proposed $\tau$ -IBR approach to modeling censored recurrent event data. An example is given based on the Azithromycin for Prevention of COPD Exacerbations Trial.

PMID:38386367 | DOI:10.1002/sim.9999

Biometrics. 2024 Jan 29;80(1):ujad035. doi: 10.1093/biomtc/ujad035.

ABSTRACT

In clinical studies of chronic diseases, the effectiveness of an intervention is often assessed using “high cost” outcomes that require long-term patient follow-up and/or are invasive to obtain. While much progress has been made in the development of statistical methods to identify surrogate markers, that is, measurements that could replace such costly outcomes, they are generally not applicable to studies with a small sample size. These methods either rely on nonparametric smoothing which requires a relatively large sample size or rely on strict model assumptions that are unlikely to hold in practice and empirically difficult to verify with a small sample size. In this paper, we develop a novel rank-based nonparametric approach to evaluate a surrogate marker in a small sample size setting. The method developed in this paper is motivated by a small study of children with nonalcoholic fatty liver disease (NAFLD), a diagnosis for a range of liver conditions in individuals without significant history of alcohol intake. Specifically, we examine whether change in alanine aminotransferase (ALT; measured in blood) is a surrogate marker for change in NAFLD activity score (obtained by biopsy) in a trial, which compared Vitamin E ($n=50$) versus placebo ($n=46$) among children with NAFLD.

PMID:38386359 | DOI:10.1093/biomtc/ujad035

JAMA Ophthalmol. 2024 Feb 22. doi: 10.1001/jamaophthalmol.2023.6917. Online ahead of print.

ABSTRACT

IMPORTANCE: Large language models (LLMs) are revolutionizing medical diagnosis and treatment, offering unprecedented accuracy and ease surpassing conventional search engines. Their integration into medical assistance programs will become pivotal for ophthalmologists as an adjunct for practicing evidence-based medicine. Therefore, the diagnostic and treatment accuracy of LLM-generated responses compared with fellowship-trained ophthalmologists can help assess their accuracy and validate their potential utility in ophthalmic subspecialties.

OBJECTIVE: To compare the diagnostic accuracy and comprehensiveness of responses from an LLM chatbot with those of fellowship-trained glaucoma and retina specialists on ophthalmological questions and real patient case management.

DESIGN, SETTING, AND PARTICIPANTS: This comparative cross-sectional study recruited 15 participants aged 31 to 67 years, including 12 attending physicians and 3 senior trainees, from eye clinics affiliated with the Department of Ophthalmology at Icahn School of Medicine at Mount Sinai, New York, New York. Glaucoma and retina questions (10 of each type) were randomly selected from the American Academy of Ophthalmology’s Commonly Asked Questions. Deidentified glaucoma and retinal cases (10 of each type) were randomly selected from ophthalmology patients seen at Icahn School of Medicine at Mount Sinai-affiliated clinics. The LLM used was GPT-4 (version dated May 12, 2023). Data were collected from June to August 2023.

MAIN OUTCOMES AND MEASURES: Responses were assessed via a Likert scale for medical accuracy and completeness. Statistical analysis involved the Mann-Whitney U test and the Kruskal-Wallis test, followed by pairwise comparison.

RESULTS: The combined question-case mean rank for accuracy was 506.2 for the LLM chatbot and 403.4 for glaucoma specialists (n = 831; Mann-Whitney U = 27976.5; P < .001), and the mean rank for completeness was 528.3 and 398.7, respectively (n = 828; Mann-Whitney U = 25218.5; P < .001). The mean rank for accuracy was 235.3 for the LLM chatbot and 216.1 for retina specialists (n = 440; Mann-Whitney U = 15518.0; P = .17), and the mean rank for completeness was 258.3 and 208.7, respectively (n = 439; Mann-Whitney U = 13123.5; P = .005). The Dunn test revealed a significant difference between all pairwise comparisons, except specialist vs trainee in rating chatbot completeness. The overall pairwise comparisons showed that both trainees and specialists rated the chatbot’s accuracy and completeness more favorably than those of their specialist counterparts, with specialists noting a significant difference in the chatbot’s accuracy (z = 3.23; P = .007) and completeness (z = 5.86; P < .001).

CONCLUSIONS AND RELEVANCE: This study accentuates the comparative proficiency of LLM chatbots in diagnostic accuracy and completeness compared with fellowship-trained ophthalmologists in various clinical scenarios. The LLM chatbot outperformed glaucoma specialists and matched retina specialists in diagnostic and treatment accuracy, substantiating its role as a promising diagnostic adjunct in ophthalmology.

PMID:38386351 | DOI:10.1001/jamaophthalmol.2023.6917

JAMA Oncol. 2024 Feb 22. doi: 10.1001/jamaoncol.2023.6969. Online ahead of print.

ABSTRACT

IMPORTANCE: The COVID-19 pandemic disrupted the normal course of cancer screening and detection in the US. A nationwide analysis of the extent of this disruption using cancer registry data has not been conducted.

OBJECTIVE: To assess the observed and expected cancer rate trends for March through December 2020 using data from all 50 US states and the District of Columbia.

DESIGN, SETTINGS, AND PARTICIPANTS: This was a population-based cross-sectional analysis of cancer incidence trends using data on cases of invasive cancer diagnosis reported to the US Cancer Statistics from January 1, 2018, through December 31, 2020. Data analyses were performed from July 6 to 28, 2023.

EXPOSURE(S): Age, sex, race, urbanicity, and state-level response to the COVID-19 pandemic at the time of cancer diagnosis.

MAIN OUTCOMES AND MEASURES: Used time-series forecasting methods to calculate expected cancer incidence rates for March 1 through December 31, 2020, from prepandemic trends (January 2018-February 2020). Measured relative difference between observed and expected cancer incidence rates and numbers of potentially missed cancer cases.

RESULTS: This study included 1 297 874 cancer cases reported in the US from March 1 through December 31, 2020, with an age-adjusted incidence rate of 326.5 cases per 100 000 population. Of the observed cases, 657 743 (50.7%) occurred in male patients, 757 106 (58.3%) in persons 65 years or older, and 1 066 566 (82.2%) in White individuals. Observed rates of all-sites cancer incidence in the US were 28.6% (95% prediction interval [PI], 25.4%-31.7%) lower than expected during the height of the COVID-19 pandemic response (March-May 2020); 6.3% (95% PI, 3.8%-8.8%) lower in June to December 2020; and overall, 13.0% (95% PI, 11.2%-14.9%) lower during the first 10 months of the pandemic. These differences indicate that there were potentially 134 395 (95% PI, 112 544-156 680) undiagnosed cancers during that time frame. Prostate cancer accounted for the largest number of potentially missed cases (22 950), followed by female breast (16 870) and lung (16 333) cancers. Screenable cancers saw a total rate reduction of 13.9% (95% PI, 12.2%-15.6%) compared with the expected rate. The rate of female breast cancer showed evidence of recovery to previous trends after the first 3 months of the pandemic, but levels remained low for colorectal, cervical, and lung cancers. From March to May 2020, states with more restrictive COVID-19 responses had significantly greater disruptions, yet by December 2020, these differences were nonsignificant for all sites except lung, kidney, and pancreatic cancer.

CONCLUSIONS AND RELEVANCE: This cross-sectional analysis of cancer incidence trends found a substantial disruption to cancer diagnoses in the US during the first 10 months of the COVID-19 pandemic. The overall and differential findings can be used to inform where the US health care system should be looking to make up ground in cancer screening and detection.

PMID:38386344 | DOI:10.1001/jamaoncol.2023.6969

JAMA Netw Open. 2024 Feb 5;7(2):e240201. doi: 10.1001/jamanetworkopen.2024.0201.

ABSTRACT

IMPORTANCE: Various psychopathology may follow trauma; however, sex differences in these ranging manifestations of posttraumatic psychopathology remain understudied.

OBJECTIVE: To investigate sex-specific incidence of posttraumatic psychopathology.

DESIGN, SETTING, AND PARTICIPANTS: This population-based cohort study of Danish national health registries included a cohort of individuals who experienced a potentially traumatic event (PTE) from 1994 to 2016. Individuals were further categorized by presence of any pretrauma psychopathology. A comparison group of individuals who experienced a nontraumatic stressor (nonsuicide death of a first-degree relative) was examined as a reference cohort.

EXPOSURES: At least 1 of 8 PTEs (eg, physical assault, transportation accident) derived through health registry International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes, with additional qualifiers to improve classification accuracy.

MAIN OUTCOMES AND MEASURES: Incidence of 9 categories of ICD-10 psychiatric disorders recorded in registries within 5 years of PTEs. The standardized morbidity ratios (SMRs) for psychopathology outcomes were also calculated to compare individuals experiencing PTEs with those experiencing a nontraumatic stressor.

RESULTS: This study included 1 398 026 individuals who had been exposed to trauma (475 280 males [34.0%]; 922 750 females [66.0%]). The group of males who had been exposed to trauma were evenly distributed across age, while most females in the trauma-exposed group were aged 16 to 39 years (592 385 [64.2%]). Males and females were equally distributed across income quartiles and predominantly single. Following PTEs, the most common diagnosis was substance use disorders for males (35 160 [7.4%]) and depressive disorders for females (29 255 [3.2%]); incidence proportions for these and other disorders were higher among males and females with any pretrauma psychopathology. Certain PTEs had elevated onset of various psychiatric disorders and some sex differences emerged. Following physical assault, associations were found with schizophrenia or psychotic disorders for males (SMR, 17.5; 95% CI, 15.9-19.3) and adult personality disorders for females (SMR, 16.3; 95% CI, 14.6-18.3). For noninterpersonal PTEs, males had larger SMRs for substance use, schizophrenia or psychotic disorders, and adult personality disorders (SMR, 43.4; 95% CI, 41.9-45.0), and females had larger SMRs for depressive disorders (SMR, 19.0; 95% CI, 18.6-19.4). Sex differences were also observed, particularly when considering pretrauma psychopathology. For example, among interpersonal PTEs, males were most likely to develop substance use disorders after physical assault, whereas females were more likely to develop various disorders, with stronger associations seen for females without pretrauma psychiatric diagnoses. Among noninterpersonal PTEs, exposure to toxic substance showed robust associations with psychopathology, particularly in those without pretrauma psychopathology, with sex-specific differences across psychiatric categories.

CONCLUSIONS AND RELEVANCE: Mental disorders after trauma were wide-ranging for males and females, and sex differences in patterns of posttraumatic psychopathology were more pronounced when accounting for pretrauma psychopathology. Findings provide new insights for sex-relevant PTEs and their mental health consequences. It also outlines future directions for advancing understanding of a constellation of posttraumatic psychopathology in males and females.

PMID:38386319 | DOI:10.1001/jamanetworkopen.2024.0201

Brain. 2024 Feb 22:awae058. doi: 10.1093/brain/awae058. Online ahead of print.

ABSTRACT

Neurodevelopmental disorders are major indications for genetic referral and have been linked to more than 1,500 loci including genes encoding transcriptional regulators. The dysfunction of transcription factors often results in characteristic syndromic presentations, however, at least half of these patients lack a genetic diagnosis. The implementation of machine learning approaches has the potential to aid in the identification of new disease genes and delineate associated phenotypes. Next generation sequencing was performed in seven affected individuals with neurodevelopmental delay and dysmorphic features. Clinical characterization included reanalysis of available neuroimaging datasets and 2D portrait image analysis with GestaltMatcher. The functional consequences of ZSCAN10 loss were modelled in mouse embryonic stem cells (mESC), including a knock-out and a representative ZSCAN10 protein truncating variant. These models were characterized by gene expression and Western blot analyses, chromatin immunoprecipitation and quantitative PCR (ChIP-qPCR), and immunofluorescence staining. Zscan10 knockout mouse embryos were generated and phenotyped. We prioritized bi-allelic ZSCAN10 loss-of-function variants in seven affected individuals from five unrelated families as the underlying molecular cause. RNA-Seq analyses in Zscan10-/- mESCs indicated dysregulation of genes related to stem cell pluripotency. In addition, we established in mESCs the loss-of-function mechanism for a representative human ZSCAN10 protein truncating variant by showing alteration of its expression levels and subcellular localization, interfering with its binding to DNA enhancer targets. Deep phenotyping revealed global developmental delay, facial asymmetry, and malformations of the outer ear as consistent clinical features. Cerebral MRI showed dysplasia of the semicircular canals as an anatomical correlate of sensorineural hearing loss. Facial asymmetry was confirmed as a clinical feature by GestaltMatcher and was recapitulated in the Zscan10 mouse model along with inner and outer ear malformations. Our findings provide evidence of a novel syndromic neurodevelopmental disorder caused by bi-allelic loss-of-function variants in ZSCAN10.

PMID:38386308 | DOI:10.1093/brain/awae058