Tag: statistics

JAMA. 2024 Mar 19;331(11):959-971. doi: 10.1001/jama.2024.0276.

ABSTRACT

IMPORTANCE: Child maltreatment is associated with serious negative physical, psychological, and behavioral consequences.

OBJECTIVE: To review the evidence on primary care-feasible or referable interventions to prevent child maltreatment to inform the US Preventive Services Task Force.

DATA SOURCES: PubMed, Cochrane Library, and trial registries through February 2, 2023; references, experts, and surveillance through December 6, 2023.

STUDY SELECTION: English-language, randomized clinical trials of youth through age 18 years (or their caregivers) with no known exposure or signs or symptoms of current or past maltreatment.

DATA EXTRACTION AND SYNTHESIS: Two reviewers assessed titles/abstracts, full-text articles, and study quality, and extracted data; when at least 3 similar studies were available, meta-analyses were conducted.

MAIN OUTCOMES AND MEASURES: Directly measured reports of child abuse or neglect (reports to Child Protective Services or removal of the child from the home); proxy measures of abuse or neglect (injury, visits to the emergency department, hospitalization); behavioral, developmental, emotional, mental, or physical health and well-being; mortality; harms.

RESULTS: Twenty-five trials (N = 14 355 participants) were included; 23 included home visits. Evidence from 11 studies (5311 participants) indicated no differences in likelihood of reports to Child Protective Services within 1 year of intervention completion (pooled odds ratio, 1.03 [95% CI, 0.84-1.27]). Five studies (3336 participants) found no differences in removal of the child from the home within 1 to 3 years of follow-up (pooled risk ratio, 1.06 [95% CI, 0.37-2.99]). The evidence suggested no benefit for emergency department visits in the short term (<2 years) and hospitalizations. The evidence was inconclusive for all other outcomes because of the limited number of trials on each outcome and imprecise results. Among 2 trials reporting harms, neither reported statistically significant differences. Contextual evidence indicated (1) widely varying practices when screening, identifying, and reporting child maltreatment to Child Protective Services, including variations by race or ethnicity; (2) widely varying accuracy of screening instruments; and (3) evidence that child maltreatment interventions may be associated with improvements in some social determinants of health.

CONCLUSION AND RELEVANCE: The evidence base on interventions feasible in or referable from primary care settings to prevent child maltreatment suggested no benefit or insufficient evidence for direct or proxy measures of child maltreatment. Little information was available about possible harms. Contextual evidence pointed to the potential for bias or inaccuracy in screening, identification, and reporting of child maltreatment but also highlighted the importance of addressing social determinants when intervening to prevent child maltreatment.

PMID:38502070 | DOI:10.1001/jama.2024.0276

Neuro Oncol. 2024 Mar 19:noae053. doi: 10.1093/neuonc/noae053. Online ahead of print.

ABSTRACT

BACKGROUND: Standard treatment for patients with newly diagnosed glioblastoma includes surgery, radiotherapy (RT) and temozolomide (TMZ) chemotherapy (TMZ/RT→TMZ). The proteasome has long been considered a promising therapeutic target because of its role as a central biological hub in tumor cells. Marizomib is a novel pan-proteasome inhibitor that crosses the blood brain barrier.

METHODS: EORTC 1709/CCTG CE.8 was a multicenter, randomized, controlled, open label phase 3 superiority trial. Key eligibility criteria included newly diagnosed glioblastoma, age > 18 years and Karnofsky performance status > 70. Patients were randomized in a 1:1 ratio. The primary objective was to compare overall survival (OS) in patients receiving marizomib in addition to TMZ/RT→TMZ with patients receiving only standard treatment in the whole population, and in the subgroup of patients with MGMT promoter-unmethylated tumors.

RESULTS: The trial was opened at 82 institutions in Europe, Canada and the US. A total of 749 patients (99.9% of planned 750) were randomized. OS was not different between the standard and the marizomib arm (median 17 vs 16.5 months; HR=1.04; p=0.64). PFS was not statistically different either (median 6.0 vs. 6.3 months; HR=0.97; p=0.67). In patients with MGMT promoter-unmethylated tumors, OS was also not different between standard therapy and marizomib (median 14.5 vs 15.1 months, HR=1.13; p=0.27). More CTCAE grade 3/4 treatment-emergent adverse events were observed in the marizomib arm than in the standard arm.

CONCLUSIONS: Adding marizomib to standard temozolomide-based radiochemotherapy resulted in more toxicity, but did not improve OS or PFS in patients with newly diagnosed glioblastoma.

PMID:38502052 | DOI:10.1093/neuonc/noae053

World J Surg. 2024 Mar 19. doi: 10.1002/wjs.12127. Online ahead of print.

ABSTRACT

BACKGROUND: Inferior vena cava (IVC) resection is essential for complete (R0) excision of some malignancies. However, the optimal material for IVC reconstruction remains unclear. Our objective is to demonstrate the efficacy, safety, and advantages of using Non-Fascial Autologous Peritoneum (NFAP) for IVC reconstruction. To conduct a literature review of surgical strategies for tumors involving the IVC.

METHODS: We reviewed all IVC reconstructions performed at our institution between 2015 and 2023. Preoperative, operative, postoperative, and follow-up data were collected and analyzed.

RESULTS: A total of 33 consecutive IVC reconstructions were identified: seven direct sutures, eight venous homografts (VH), and 18 NFAP. With regard to NFAP, eight tubular (mean length, 12.5 cm) and 10 patch (mean length, 7.9 cm) IVC reconstructions were performed. Resection was R0 in 89% of the cases. Two patients had Clavien-Dindo grade I complications, 2 grade II, 2 grade III and 2 grade V complications. The only graft-related complication was a case of early partial thrombosis, which was conservatively treated. At a mean follow-up of 25.9 months, graft patency was 100%. There were seven recurrences and six deaths. Mean overall survival (OS) was 23.4 months and mean disease-free survival (DFS) was 14.4 months. According to our results, no statistically significant differences were found between NFAP and VH.

CONCLUSIONS: NFAP is a safe and effective alternative for partial or complete IVC reconstruction and has many advantages over other techniques, including its lack of cost, wide and ready availability, extreme handiness, and versatility. Further comparative studies are required to determine the optimal technique for IVC reconstruction.

PMID:38502051 | DOI:10.1002/wjs.12127

Stat Methods Med Res. 2024 Mar 19:9622802241238998. doi: 10.1177/09622802241238998. Online ahead of print.

ABSTRACT

The empirical likelihood is a powerful nonparametric tool, that emulates its parametric counterpart-the parametric likelihood-preserving many of its large-sample properties. This article tackles the problem of assessing the discriminatory power of three-class diagnostic tests from an empirical likelihood perspective. In particular, we concentrate on interval estimation in a three-class receiver operating characteristic analysis, where a variety of inferential tasks could be of interest. We present novel theoretical results and tailored techniques studied to efficiently solve some of such tasks. Extensive simulation experiments are provided in a supporting role, with our novel proposals compared to existing competitors, when possible. It emerges that our new proposals are extremely flexible, being able to compete with contestants and appearing suited to accommodating several distributions, such, for example, mixtures, for target populations. We illustrate the application of the novel proposals with a real data example. The article ends with a discussion and a presentation of some directions for future research.

PMID:38502023 | DOI:10.1177/09622802241238998

Stat Methods Med Res. 2024 Mar 19:9622802241231496. doi: 10.1177/09622802241231496. Online ahead of print.

ABSTRACT

Assessing heterogeneity between studies is a critical step in determining whether studies can be combined and whether the synthesized results are reliable. The $I^2$ statistic has been a popular measure for quantifying heterogeneity, but its usage has been challenged from various perspectives in recent years. In particular, it should not be considered an absolute measure of heterogeneity, and it could be subject to large uncertainties. As such, when using $I^2$ to interpret the extent of heterogeneity, it is essential to account for its interval estimate. Various point and interval estimators exist for $I^2$. This article summarizes these estimators. In addition, we performed a simulation study under different scenarios to investigate preferable point and interval estimates of $I^2$. We found that the Sidik-Jonkman method gave precise point estimates for $I^2$ when the between-study variance was large, while in other cases, the DerSimonian-Laird method was suggested to estimate $I^2$. When the effect measure was the mean difference or the standardized mean difference, the $Q$-profile method, the Biggerstaff-Jackson method, or the Jackson method was suggested to calculate the interval estimate for $I^2$ due to reasonable interval length and more reliable coverage probabilities than various alternatives. For the same reason, the Kulinskaya-Dollinger method was recommended to calculate the interval estimate for $I^2$ when the effect measure was the log odds ratio.

PMID:38502022 | DOI:10.1177/09622802241231496

Stat Methods Med Res. 2024 Mar 19:9622802241236954. doi: 10.1177/09622802241236954. Online ahead of print.

ABSTRACT

Observational data (e.g. electronic health records) has become increasingly important in evidence-based research on dynamic treatment regimes, which tailor treatments over time to patients based on their characteristics and evolving clinical history. It is of great interest for clinicians and statisticians to identify an optimal dynamic treatment regime that can produce the best expected clinical outcome for each individual and thus maximize the treatment benefit over the population. Observational data impose various challenges for using statistical tools to estimate optimal dynamic treatment regimes. Notably, the task becomes more sophisticated when the clinical outcome of primary interest is time-to-event. Here, we propose a matching-based machine learning method to identify the optimal dynamic treatment regime with time-to-event outcomes subject to right-censoring using electronic health record data. In contrast to the established inverse probability weighting-based dynamic treatment regime methods, our proposed approach provides better protection against model misspecification and extreme weights in the context of treatment sequences, effectively addressing a prevalent challenge in the longitudinal analysis of electronic health record data. In simulations, the proposed method demonstrates robust performance across a range of scenarios. In addition, we illustrate the method with an application to estimate optimal dynamic treatment regimes for patients with advanced non-small cell lung cancer using a real-world, nationwide electronic health record database from Flatiron Health.

PMID:38502008 | DOI:10.1177/09622802241236954

Aliment Pharmacol Ther. 2024 Mar 19. doi: 10.1111/apt.17950. Online ahead of print.

ABSTRACT

BACKGROUND: Results of studies evaluating the effect of viral eradication following direct-acting antiviral (DDA) therapy on skeletal muscle mass of patients with chronic hepatitis C (CHC) are scarce.

AIM: To assess the components of sarcopenia (low muscle mass, low muscle strength and low physical performance) in a cohort of CHC individuals before and after DAA therapy.

METHODS: We performed a longitudinal study of patients with CHC who underwent body composition assessment before (T0), and at 12 (T1) and 48 (T2) weeks after DDA therapy. Bioelectrical Impedance Analysis was used to assess skeletal mass muscle (SM) and phase angle (PhA). SM index (SMI) was calculated by dividing the SM by squared height. Muscle function was evaluated by hand grip strength (HGS) and timed up-and-go (TUG) test. Mixed-effects linear regression models were fitted to SMI, HGS and physical performance and were used to test the effect of HCV eradication by DAA.

RESULTS: 62 outpatients (mean age, 58.6 ± 10.8 years; 58% with compensated cirrhosis) were included. Significant decreases in liver fibrosis markers and an increase of 0.20 and 0.22 kg/m² in the SMI were observed at T1 and T2. Following DAA therapy, an increase of one unit of PhA was associated with a reduction of 0.38 min in TUG.

CONCLUSION: HCV eradication with DAA therapy was associated with a dynamic reduction of non-invasive markers of liver fibrosis and increased muscle mass in 62 patients with CHC who had an undetectable HCV load at 12 weeks after completion of antiviral treatment.

PMID:38501893 | DOI:10.1111/apt.17950

Microsc Res Tech. 2024 Mar 19. doi: 10.1002/jemt.24550. Online ahead of print.

ABSTRACT

This manuscript proposes thermal images using PCSAN-Net-DBOA Initially, the input images are engaged from the database for mastology research with infrared image (DMR-IR) dataset for breast cancer classification. The adaptive distorted Gaussian matched-filter (ADGMF) was used in removing noise and increasing the quality of infrared thermal images. Next, these preprocessed images are given into one-dimensional quantum integer wavelet S-transform (OQIWST) for extracting Grayscale statistic features like standard deviation, mean, variance, entropy, kurtosis, and skewness. The extracted features are given into the pyramidal convolution shuffle attention neural network (PCSANN) for categorization. In general, PCSANN does not show any adaption optimization techniques to determine the optimal parameter to offer precise breast cancer categorization. This research proposes the dung beetle optimization algorithm (DBOA) to optimize the PCSANN classifier that accurately diagnoses breast cancer. The BCD-PCSANN-DBO method is implemented using Python. To classify breast cancer, performance metrics including accuracy, precision, recall, F1 score, error rate, RoC, and computational time are considered. Performance of the BCD-PCSANN-DBO approach attains 29.87%, 28.95%, and 27.92% lower computation time and 13.29%, 14.35%, and 20.54% greater RoC compared with existing methods like breast cancer diagnosis utilizing thermal infrared imaging and machine learning approaches(BCD-CNN), breast cancer classification from thermal images utilizing Grunwald-Letnikov assisted dragonfly algorithm-based deep feature selection (BCD-VGG16) and Breast cancer detection in thermograms using deep selection based on genetic algorithm and Gray Wolf Optimizer (BCD-SqueezeNet), respectively. RESEARCH HIGHLIGHTS: The input images are engaged from the breast cancer dataset for breast cancer classification. The ADQMF was used in removing noise and increasing the quality of infrared thermal images. The extracted features are given into the PCSANN for categorization. DBOA is proposed to optimize PCSANN classifier that classifies breast cancer precisely. The proposed BCD-PCSANN-DBO method is implemented using Python.

PMID:38501825 | DOI:10.1002/jemt.24550

Microbiol Spectr. 2024 Mar 19:e0365023. doi: 10.1128/spectrum.03650-23. Online ahead of print.

ABSTRACT

Anaerobic microbes play crucial roles in environmental processes, industry, and human health. Traditional methods for monitoring the growth of anaerobes, including plate counts or subsampling broth cultures for optical density measurements, are time and resource-intensive. The advent of microplate readers revolutionized bacterial growth studies by enabling high-throughput and real-time monitoring of microbial growth kinetics. Yet, their use in anaerobic microbiology has remained limited. Here, we present a workflow for using small-footprint microplate readers and the Growthcurver R package to analyze the kinetic growth metrics of anaerobic bacteria. We benchmarked the small-footprint Cerillo Stratus microplate reader against a BioTek Synergy HTX microplate reader in aerobic conditions using Escherichia coli DSM 28618 cultures. The growth rates and carrying capacities obtained from the two readers were statistically indistinguishable. However, the area under the logistic curve was significantly higher in cultures monitored by the Stratus reader. We used the Stratus to quantify the growth responses of anaerobically grown E. coli and Clostridium bolteae DSM 29485 to different doses of the toxin sodium arsenite. The growth of E. coli and C. bolteae was sensitive to arsenite doses of 1.3 µM and 0.4 µM, respectively. Complete inhibition of growth was achieved at 38 µM arsenite for C. bolteae and 338 µM in E. coli. These results show that the Stratus performs similarly to a leading brand of microplate reader and can be reliably used in anaerobic conditions. We discuss the advantages of the small format microplate readers and our experiences with the Stratus.

IMPORTANCE: We present a workflow that facilitates the production and analysis of growth curves for anaerobic microbes using small-footprint microplate readers and an R script. This workflow is a cost and space-effective solution to most high-throughput solutions for collecting growth data from anaerobic microbes. This technology can be used for applications where high throughput would advance discovery, including microbial isolation, bioprospecting, co-culturing, host-microbe interactions, and drug/toxin-microbial interactions.

PMID:38501820 | DOI:10.1128/spectrum.03650-23

Acta Oncol. 2024 Mar 19;63:83-94. doi: 10.2340/1651-226X.2024.24970.

ABSTRACT

BACKGROUND: Surveillance of incidence and survival of central nervous system tumors is essential to monitor disease burden and epidemiological changes, and to allocate health care resources. Here, we describe glioma incidence and survival trends by histopathology group, age, and sex in the Norwegian population.

MATERIAL AND METHODS: We included patients with a histologically verified glioma reported to the Cancer Registry of Norway from 2002 to 2021 (N = 7,048). Population size and expected mortality were obtained from Statistics Norway. Cases were followed from diagnosis until death, emigration, or 31 December 2022, whichever came first. We calculated age-standardized incidence rates (ASIR) per 100,000 person-years and age-standardized relative survival (RS). Results: The ASIR for histologically verified gliomas was 7.4 (95% CI: 7.3-7.6) and was higher for males (8.8; 95% CI: 8.5-9.1) than females (6.1; 95% CI: 5.9-6.4). Overall incidence was stable over time. Glioblastoma was the most frequent tumor entity (ASIR = 4.2; 95% CI: 4.1-4.4). Overall, glioma patients had a 1-year RS of 63.6% (95% CI: 62.5-64.8%), and a 5-year RS of 32.8% (95% CI: 31.6-33.9%). Females had slightly better survival than males. For most entities, 1- and 5-year RS improved over time (5-year RS for all gliomas 29.0% (2006) and 33.1% (2021), p < 0.001). Across all tumor types, the RS declined with increasing age at diagnosis.

INTERPRETATION: The incidence of gliomas has been stable while patient survival has increased over the past 20 years in Norway. As gliomas represent a heterogeneous group of primary CNS tumors, regular reporting from cancer registries at the histopathology group level is important to monitor disease burden and allocate health care resources in a population.

PMID:38501768 | DOI:10.2340/1651-226X.2024.24970