Category: Statistics

Clin Pharmacol Ther. 2021 Mar 5. doi: 10.1002/cpt.2224. Online ahead of print.

ABSTRACT

Cell and gene therapies have shown enormous promise across a range of diseases in recent years. Numerous adoptive cell therapy modalities as well as systemic and direct-to-target tissue gene transfer administrations are currently in clinical development. The clinical trial design, development, reporting, and analysis of novel cell and gene therapies can differ significantly from established practices for small molecule drugs and biologics. Here we discuss important quantitative considerations and key competencies for drug developers in preclinical requirements, trial design, and lifecycle planning for gene therapies. We argue that the unique development path of gene therapies requires practicing quantitative drug developers-statisticians, pharmacometricians, pharmacokineticists, epidemiologists, and medical and translational science leads-to exercise active collaboration and cross-functional learning across development stages.

PMID:33666225 | DOI:10.1002/cpt.2224

Elife. 2021 Mar 5;10:e64206. doi: 10.7554/eLife.64206. Online ahead of print.

ABSTRACT

Establishing how many people have been infected by SARS-CoV-2 remains an urgent priority for controlling the COVID-19 pandemic. Serological tests that identify past infection can be used to estimate cumulative incidence, but the relative accuracy and robustness of various sampling strategies has been unclear. We developed a flexible framework that integrates uncertainty from test characteristics, sample size, and heterogeneity in seroprevalence across subpopulations to compare estimates from sampling schemes. Using the same framework and making the assumption that seropositivity indicates immune protection, we propagated estimates and uncertainty through dynamical models to assess uncertainty in the epidemiological parameters needed to evaluate public health interventions, and found that sampling schemes informed by demographics and contact networks outperform uniform sampling. The framework can be adapted to optimize serosurvey design given test characteristics and capacity, population demography, sampling strategy, and modeling approach, and can be tailored to support decision-making around introducing or removing interventions.

PMID:33666169 | DOI:10.7554/eLife.64206

Front Vet Sci. 2021 Feb 16;8:591961. doi: 10.3389/fvets.2021.591961. eCollection 2021.

ABSTRACT

RNA is considered as an indicator of the dynamic genetic expression changes in a cell. RNAScope is a commercially available in situ hybridization assay for the detection of RNA in formalin-fixed paraffin-embedded tissue. In this work, we describe the use of RNAScope as a sensitive and specific method for the evaluation of c-KIT messenger RNA (mRNA) in canine mast cell tumor. We investigated the expression of c-KIT mRNA with RNAscope in 60 canine mast cell tumors (MCTs), comparing it with the histological grade and KIT immunohistochemical expression patterns. Our results showed an overall good expression of c-KIT mRNA in neoplastic cells if compared with control probes. We also observed a statistically significant correlation between histological grade and c-KIT mRNA expression. No correlations were found between KIT protein immunohistochemical distribution pattern and c-KIT mRNA expression or histological grade. Our results provide a reference basis to better understand c-KIT mRNA expression in canine MCTs and strongly encourage further studies that may provide useful information about its potential and significant role as a prognostic and predictive biological marker for canine MCTs clinical outcome.

PMID:33665215 | PMC:PMC7921150 | DOI:10.3389/fvets.2021.591961

Gynecol Oncol Rep. 2021 Feb 12;36:100730. doi: 10.1016/j.gore.2021.100730. eCollection 2021 May.

ABSTRACT

Forgoing hysterectomy as part of borderline ovarian tumor (BOT) staging is considered appropriate for fertility preservation. We evaluated whether forgoing hysterectomy may also be acceptable in non-fertility-sparing surgery by evaluating the frequency of uterine involvement and the rate of recurrence involving the uterus. A review of all BOTs at one institution over ten years (2009-2019) was performed. Patients with hysterectomy prior to BOT diagnosis were excluded. Data were abstracted from electronic medical records. Bivariate statistics were used to compare groups. 129 patients with BOT on final pathology were identified. 67 cases included hysterectomy. Reasons for no hysterectomy (n = 62) included fertility preservation (40), benign intraoperative frozen pathology (4), patient preference (3), comorbidities (7), and unknown (8). Four of 67 (6.0%) uterine specimens had non-invasive serosal implants, of which two had grossly visible uterine involvement and all four had grossly visible extrauterine peritoneal disease. 12 of 129 (9.3%) patients had documented recurrence, of which all had uterine preservation at the time of initial surgery. Of the 12 recurrences with uterus in situ, none were documented to involve the uterus, and all were composed of non-invasive implants. In patients with BOT grossly confined to ovaries at the time of surgery, we found no cases of uterine involvement. We found no cases in which microscopic uterine serosal involvement changed stage and no cases of recurrence involving the uterus. Hysterectomy may be able to be safely excluded from non-fertility-sparing surgery for BOTs, particularly when disease is grossly confined to the ovaries.

PMID:33665295 | PMC:PMC7900677 | DOI:10.1016/j.gore.2021.100730

Front Pediatr. 2021 Feb 16;9:632573. doi: 10.3389/fped.2021.632573. eCollection 2021.

ABSTRACT

Objective: There are mutual influences between intestine and lung, that propose a concept of the gut-lung axis, but the mechanism is still unclear. Microbial colonization in early life plays an important role in regulating intestinal and lung function. In order to explore the characteristics of early microbiota on the gut-lung axis, we studied the correlation between intestinal and pharyngeal microbiota on day 1 and day 28 after birth in premature neonates. Methods: Thirteen neonates born at 26-32 weeks gestational age (GA) hospitalized at the neonatal intensive care unit (NICU) of the West China Second Hospital of Sichuan University were enrolled in this study. Stool samples and pharyngeal swabs samples were collected from each neonate on the first day (T1) and the 28th day (T28) after birth. Total bacterial DNA was extracted and sequenced using the Illumina MiSeq Sequencing System based on the V3-V4 hyper-variable regions of the 16S rRNA gene. Based on the sequencing results, the composition of the intestinal and pharyngeal microbiota was compared and analyzed. Results: At T1, the difference in microbial composition between intestine and pharynx was not statistically significant. The intestinal microbiota was mainly composed of Unidentified Enterobacteriaceae, Ralstonia, Streptococcus, Fusobacterium, Ureaplasma, etc. The pharyngeal microbiota was mainly composed of Ureaplasma, Bacteroides, Fusobacterium, etc. Ureaplasma and Fusobacterium were detected in both intestine and pharynx. At T28, there was a significant difference in microbial composition between intestine and pharynx (p < 0.001). The intestinal microbiota was mainly composed of Unidentified Clostridiales, Klebsiella, Unidentified Enterobacteriaceae, Enterobacter, Streptococcus, etc. Pharyngeal microbiota was mainly composed of Streptococcus, Rothia, etc. Streptococcus was detected in both intestine and pharynx. Conclusions: The intestine and pharynx of premature neonates have a unique microbial composition, and share some common microbiota. Whether these microbiotas play a role in the mechanism of gut-lung crosstalk needs further study.

PMID:33665178 | PMC:PMC7920978 | DOI:10.3389/fped.2021.632573

Front Bioeng Biotechnol. 2021 Feb 16;8:536957. doi: 10.3389/fbioe.2020.536957. eCollection 2020.

ABSTRACT

Temporal multi-omics data can provide information about the dynamics of disease development and therapeutic response. However, statistical analysis of high-dimensional time-series data is challenging. Here we develop a novel approach to model temporal metabolomic and transcriptomic data by combining machine learning with metabolic models. ADAPT (Analysis of Dynamic Adaptations in Parameter Trajectories) performs metabolic trajectory modeling by introducing time-dependent parameters in differential equation models of metabolic systems. ADAPT translates structural uncertainty in the model, such as missing information about regulation, into a parameter estimation problem that is solved by iterative learning. We have now extended ADAPT to include both metabolic and transcriptomic time-series data by introducing a regularization function in the learning algorithm. The ADAPT learning algorithm was (re)formulated as a multi-objective optimization problem in which the estimation of trajectories of metabolic parameters is constrained by the metabolite data and refined by gene expression data. ADAPT was applied to a model of hepatic lipid and plasma lipoprotein metabolism to predict metabolic adaptations that are induced upon pharmacological treatment of mice by a Liver X receptor (LXR) agonist. We investigated the excessive accumulation of triglycerides (TG) in the liver resulting in the development of hepatic steatosis. ADAPT predicted that hepatic TG accumulation after LXR activation originates for 80% from an increased influx of free fatty acids. The model also correctly estimated that TG was stored in the cytosol rather than transferred to nascent very-low density lipoproteins. Through model-based integration of temporal metabolic and gene expression data we discovered that increased free fatty acid influx instead of de novo lipogenesis is the main driver of LXR-induced hepatic steatosis. This study illustrates how ADAPT provides estimates for biomedically important parameters that cannot be measured directly, explaining (side-)effects of pharmacological treatment with LXR agonists.

PMID:33665185 | PMC:PMC7921164 | DOI:10.3389/fbioe.2020.536957

Front Med (Lausanne). 2021 Feb 16;8:608941. doi: 10.3389/fmed.2021.608941. eCollection 2021.

ABSTRACT

Background: Lower serum lipid metabolism might be associated with the decline of activity of daily living in the extreme longevity group. However, studies on models and possible paths of this correlation between total cholesterol (TC) and disability in centenarians are scarce. The aim of this study was to verify this correlation and explore the mediating effect of BMI and blood pressure on this relationship in Hainan centenarians. Methods: We conducted a cross-sectional analysis of 1002 centenarians from the China Hainan Centenarians Cohort Study (CHCCS). Data on demographics, anthropometry data, lifestyle, and TC levels were collected through interviews, physical examinations, and laboratory tests. The Barthel index and Lawton index, measuring the disability status, were used to estimate the activity of daily living (ADL) and instrumental activity of daily living (IADL). A multivariable logistic regression model was used to explore the correlation between disability and TC levels. Mediation analyses were used to explore the both direct and indirect effects of TC level on disability. Results: After adjusting for covariates, with 1 mmol/L increment in TC, the adjusted odds ratios (ORs) of ADL severe disability and ADL moderate & severe disability were 0.789(95%CI: 0.650-0.959) and 0.822(95%CI: 0. 0.699-0.966), respectively. There was a significant declining trend in the prevalence of different types of disability with increment in TC. The correlation was more pronounced among Hainan female centenarians. In the analysis of mediating effect among the female population, BMI significantly mediated the effect of TC levels on different types of disability. BMI and SBP, as chain mediators, multiply and chain mediated the effect of TC levels on IADL. Conclusion: Low TC levels might be correlated with a higher frequency of disability in female centenarians, and this correlation might be mediated by BMI and blood pressure.

PMID:33665198 | PMC:PMC7921456 | DOI:10.3389/fmed.2021.608941

Integr Med Res. 2021 Sep;10(3):100715. doi: 10.1016/j.imr.2021.100715. Epub 2021 Jan 9.

ABSTRACT

BACKGROUND: Danggwijagyaksan (DJS) has been one of the most widely used herbal medicines for gynecological disorders in traditional East Asian medicine. Several clinical studies about DJS have shown improvement in menopausal symptoms. This pilot study aimed to evaluate the efficacy, safety and feasibility of DJS for treating climacteric syndrome with a blood-deficiency-dominant pattern.

METHODS: This was a randomized, double-blind, placebo-controlled pilot trial. A group of 45-to 60-year-old women with climacteric syndrome were registered for the trial. The participants received treatment over a 4-week period and were then followed for 4 weeks. The primary outcome measure was the mean change in the Menopause Rating Scale (MRS). Secondary outcome measures included the World Health Organization Quality of Life-BREF (WHOQOL-BREF), the Blood-Deficiency Scoring System (BDSS), lean body mass, and serum hormone levels, including follicle-stimulating hormone (FSH) and estradiol (E₂) levels.

RESULTS: The MRS and BDSS scores decreased significantly in both groups, but the differences between two groups were not significant. The WHOQOL-BREF scores increased in the control group. No statistically meaningful differences in serum hormone levels or lean body mass were observed in both groups. There were no serious adverse events, and the laboratory tests were within the normal range. The recruitment rate, completion rate and medication adherence rate were over 90% in both groups, indicating high feasibility.

CONCLUSIONS: DJS showed clinical effectiveness in the treatment of climacteric syndrome with a blood-deficiency-dominant pattern. Additionally, DJS was shown to be safe and feasible for a large-scale study to confirm the efficacy of the treatment. Trial registration: Clinical Research Information Service (CRIS, https://cris.nih.go.kr): KCT0002387.

PMID:33665100 | PMC:PMC7903340 | DOI:10.1016/j.imr.2021.100715

Ann Glob Health. 2021 Feb 25;87(1):22. doi: 10.5334/aogh.3045.

ABSTRACT

BACKGROUND: Hepatitis B virus (HBV) infection disproportionally affects populations in sub-Saharan Africa. Lack of HBV awareness perpetuates disease burden in Africa.

OBJECTIVE: To promote HBV awareness in Tanzania using a systematic, measurable, and expandable approach to educating health care workers (HCW).

METHODS: We designed and implemented an HBV knowledge and teaching skills session in southern Tanzania to empower HCWs in leading education to promote disease awareness in their communities. Training was divided into two sessions: didactic and practical. A five-question anonymous survey was distributed in person immediately before and after the practical portion of the training to evaluate HBV knowledge as well as specific skills for teaching. Differences between responses before and after the sessions were evaluated by Chi-Square analysis. A sub-group of questions were further analyzed for differences based on HCW self-report of HBV serostatus awareness.

FINDINGS: 130 HCWs participated in the didactic lecture and 30 HCWs participated in both portions. A pre-post training five-question survey showed an increase in correct answers for all questions, with two showing statistical significance: HBV is silent (7% pre vs. 87% post; p < 0.0001), and repetition as key to promote awareness (63% pre vs. 100% post; p = 0.0002).

CONCLUSIONS: Our low-cost intervention is applicable to increase HBV awareness in low resource settings across Africa.

PMID:33665144 | PMC:PMC7908926 | DOI:10.5334/aogh.3045

Front Oncol. 2021 Feb 16;10:581347. doi: 10.3389/fonc.2020.581347. eCollection 2020.

ABSTRACT

BACKGROUND: This study aims to construct and validate a model based on convolutional neural networks (CNNs), which can fulfil the automatic segmentation of clinical target volumes (CTVs) of breast cancer for radiotherapy.

METHODS: In this work, computed tomography (CT) scans of 110 patients who underwent modified radical mastectomies were collected. The CTV contours were confirmed by two experienced oncologists. A novel CNN was constructed to automatically delineate the CTV. Quantitative evaluation metrics were calculated, and a clinical evaluation was conducted to evaluate the performance of our model.

RESULTS: The mean Dice similarity coefficient (DSC) of the proposed model was 0.90, and the 95th percentile Hausdorff distance (95HD) was 5.65 mm. The evaluation results of the two clinicians showed that 99.3% of the chest wall CTV slices could be accepted by clinician A, and this number was 98.9% for clinician B. In addition, 9/10 of patients had all slices accepted by clinician A, while 7/10 could be accepted by clinician B. The score differences between the AI (artificial intelligence) group and the GT (ground truth) group showed no statistically significant difference for either clinician. However, the score differences in the AI group were significantly different between the two clinicians. The Kappa consistency index was 0.259. It took 3.45 s to delineate the chest wall CTV using the model.

CONCLUSION: Our model could automatically generate the CTVs for breast cancer. AI-generated structures of the proposed model showed a trend that was comparable, or was even better, than those of human-generated structures. Additional multicentre evaluations should be performed for adequate validation before the model can be completely applied in clinical practice.

PMID:33665160 | PMC:PMC7921705 | DOI:10.3389/fonc.2020.581347