Generalized survival models as a tool for medical research

In medical research, many studies with the time-to-event outcomes investigate the effect of an exposure (or treatment) on patients’ survival. For the analysis of time-to-event or survival data, model-based approaches have been commonly applied. In this thesis, a class of regression models on the survival scale, termed generalized survival models (GSMs previously described in Appendix A of [1]), and full likelihood-based estimation methods were presented along with four papers. The overall aim was to provide a rich and coherent framework for modelling either independent or correlated survival data. Our main contributions to GSMs and related estimation approaches were as follows: First, we refined the mathematical and statistical backgrounds of the model components, including the link function, log-time, and smooth univariate functions. Second, we broadened the class to include generalized additive functional forms for representing covariate effects, such as non-linear forms, time-dependent effects, joint time-dependent and non-linear effects for age, and multivariate regression splines. Third, we introduced the thin plate regression splines [2], which can use knot free bases, as an alternative regression tool to knot-based regression splines into GSMs. Fourth, under a penalized likelihood framework, we integrated the process of parametric estimation and model selection for the number of spline basis functions. These refinements, extensions, and related assessments were undertaken in the first three papers. These newly proposed features of GSMs and estimation methods were implemented and integrated into the rstpm2 package in R. This thesis consists of four research papers for modeling either independent or correlated survival data, together with either overall or net survival to be the measure of interest. In Paper I, the outcomes under study were independent time-to-death due to any cause (or time-to-any recurrence of disease). Parametric and penalized GSMs were introduced with extensions, simulation studies and applications. In Paper II, the outcome of interest was correlated time-to-some specific event due to any cause, such as time-to-event data collected from patients in the same clinics. It is reasonable to consider that the subjects within a cluster may share some unmeasured environmental or genetic risk factors, which are commonly modeled by a random effect b (or frailty U) and assumed to be independent of given baseline covariates. In this paper, GSMs with novel extensions were proposed to analyze correlated time-to-event data. In Paper III, we extended GSMs with novel features for relative survival analysis; the outcome of interest was time-to-death due to the disease under study. In Paper IV, we analyzed time-to-repeated event within the same subject using the proposed methods in Paper II and described the time-dependent cumulative risks of subsequent outcomes for men in different states since study entry. In summary, these proposed methods performed well in extensive simulation studies under the investigated setting, with good point estimates and coverage probabilities. Through the analysis of example data sets, similar results can also be observed using the proposed methods and other well-established approaches, under proportional hazards or proportional odds models settings. Moreover, novel features were also illustrated in both simulations and applications. Generally, the combination of GSMs and full-likelihood based estimation methods can provide alternative tools for the analysis of survival data in medical research

Age-period-cohort analysis of gender differential trends in incidence and mortality of non-Hodgkin lymphoma in China, 1990-2019

BackgroundNon-Hodgkin lymphoma (NHL) is one of the dominant malignancies in the hematological system. This study estimated secular trends in NHL incidence and mortality from 1990 to 2019 and provided comprehensive evaluations of potential age, period, and cohort effects.MethodsAge-period-cohort (APC) model was used to analyze changes in NHL incidence and mortality with age, period, and birth cohort effects based on data from the Global Burden of Disease Study 2019.ResultsThe age-standardized incidence rates (ASIR) of NHL rose by 144.6% and age-standardized mortality rate (ASMR) rose by 27.5% from 1990 to 2019. Local drift for incidence was greater than 0 (p< 0.05) for both genders in each age group. Local drift for mortality rates were greater than 0 (p< 0.05) for males aged 20 to 89 years and females aged 60 to 84 years and less than 0 (p< 0.05) for females aged 20 to 50 years. Period rate ratio (RR) and cohort RR of NHL incidence in China showed an increasing trend, while the trend of male and female mortality was not consistent.ConclusionsNHL incidence and mortality rates have been increasing in China over the past three decades. Males and older individuals were at high risk for NHL. Thus, attention to the prevention and therapy of NHL would be essential to lessen the disease burden of NHL

Antibiotic Stewardship in Retail Pharmacies and the Access-Excess Challenge in China:A Policy Review

In China, efforts to restrict excessive antibiotic consumption may prevent sufficient access to these life-saving drugs among the most deprived in society because of the weak primary health care system. This makes antibiotic stewardship in the retail pharmacy sector a particular challenge. We conducted an analysis to examinate policies on antibiotic sales in retail pharmacies in China and how tensions between ‘excess’ and ‘access’ are managed. The analysis was guided by the Walt and Gilson health policy analysis triangle to systematically analyse policies based on the content of policies, contexts, governance processes, and actors. Nine research studies and 25 documents identified from national and international sources were extracted, grouped into categories, and examined within and across records and categories. As of 2020, eight key policies have been introduced in China that focus on two areas: dispending prescribed medicines or antimicrobials with a prescription and having a licensed pharmacist present in the retail pharmacies, with approaches having changed over time. Inappropriate sales of antibiotics are still common in retail pharmacies, which can be linked to the lack of consistency and enforcement of published policies, the profit-driven nature of retail pharmacies, and the displacement of the demand for antibiotics from clinical into less regulated settings

Use of the Cassette-Dosing Approach to Assess Brain Penetration in Drug Discovery

ABSTRACT: The objective of the present study was to examine the cassette dosing method in determination of brain-to-plasma concentration ratio (area under the concentration-time profiles for plasma/area under the concentration-time profiles for brain, K p ). Eleven model compounds, amprenavir, citalopram, digoxin, elacridar, imatinib, (3S,6S,12aS)-1,2,3,4,6,7,12,12a-octahydro-9-methoxy-6-(2-methylpropyl)-1,4-dioxopyrazino[1,2:1,6]pyrido[3,4-b]indole-3-propanoic acid 1,1-dimethylethyl ester (Ko143), loperamide, prazosin, quinidine, sulfasalazine, and verapamil, were selected to compare their K p determined from discrete dosing in wild-type mice and their K p from cassette dosing in wild-type, Mdr1a/1b(؊/؊), Bcrp1(؊/؊), and Mdr1a/1b(؊/؊)/Bcrp1(؊/؊) mice at 1 to 3 mg/kg. The mice brain and plasma were collected at 0.25, 1, and 3 h and were analyzed using high-performance liquid chromatography-tandem mass spectrometry methods. The K p determined from discrete dosing versus cassette dosing in the wild-type mice were within 2-fold for all the compounds except sulfasalazine and Ko143. The brain concentrations of sulfasalazine and Ko143 and the plasma concentrations of Ko143 were below the lower limit of quantitation. In addition, the K p values estimated by mass spectrometry responses, namely the ratio of compound peak area to internal standard peak area, were within 2-fold of the K p observed from the actual concentrations. Furthermore, the ratios of K p in Mdr1a/1b(؊/؊), Bcrp1(؊/؊), and Mdr1a/1b(؊/؊)/ Bcrp1(؊/؊) mice versus the K p in the wild-type mice from cassette dosing were consistent with the ones reported in the literature where the compounds were dosed discretely. These results demonstrate that drug-drug interactions at the blood-brain barrier are unlikely at a subcutaneous dose of 1 to 3 mg/kg and support the use of the cassette dosing approach to assess brain penetration in drug discovery

Optimizing DUS testing for Chimonanthus praecox using feature selection based on a genetic algorithm

Chimonanthus praecox is a famous traditional flower in China with high ornamental value. It has numerous varieties, yet its classification is highly disorganized. The distinctness, uniformity, and stability (DUS) test enables the classification and nomenclature of various species; thus, it can be used to classify the Chimonanthus varieties. In this study, flower traits were quantified using an automatic system based on pattern recognition instead of traditional manual measurement to improve the efficiency of DUS testing. A total of 42 features were quantified, including 28 features in the DUS guidelines and 14 new features proposed in this study. Eight algorithms were used to classify wintersweet, and the random forest (RF) algorithm performed the best when all features were used. The classification accuracy of the outer perianth was the highest when the features of the different parts were used for classification. A genetic algorithm was used as the feature selection algorithm to select a set of 22 reduced core features and improve the accuracy and efficiency of the classification. Using the core feature set, the classification accuracy of the RF model improved to 99.13%. Finally, K-means was used to construct a pedigree cluster tree of 23 varieties of wintersweet; evidently, wintersweet was clustered into a single class, which can be the basis for further study of genetic relationships among varieties. This study provides a novel method for DUS detection, variety identification, and pedigree analysis

Cluster randomised controlled trial to assess a tailored intervention to reduce antibiotic prescribing in rural China:study protocol

INTRODUCTION: Up to 80% of patients with respiratory tract infections (RTI) attending healthcare facilities in rural areas of China are prescribed antibiotics, many of which are unnecessary. Since 2009, China has implemented several policies to try to reduce inappropriate antibiotic use; however, antibiotic prescribing remains high in rural health facilities. METHODS AND ANALYSIS: A cluster randomised controlled trial will be carried out to estimate the effectiveness and cost effectiveness of a complex intervention in reducing antibiotic prescribing at township health centres in Anhui Province, China. 40 Township health centres will be randomised at a 1:1 ratio to the intervention or usual care arms. In the intervention group, practitioners will receive an intervention comprising: (1) training to support appropriate antibiotic prescribing for RTI, (2) a computer-based treatment decision support system, (3) virtual peer support, (4) a leaflet for patients and (5) a letter of commitment to optimise antibiotic use to display in their clinic. The primary outcome is the percentage of antibiotics (intravenous and oral) prescribed for RTI patients. Secondary outcomes include patient symptom severity and duration, recovery status, satisfaction, antibiotic consumption. A full economic evaluation will be conducted within the trial period. Costs and savings for both clinics and patients will be considered and quality of life will be measured by EuroQoL (EQ-5D-5L). A qualitative process evaluation will explore practitioner and patient views and experiences of trial processes, intervention fidelity and acceptability, and barriers and facilitators to implementation. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Biomedical Research Ethics Committee of Anhui Medical University (Ref: 20180259); the study has undergone due diligence checks and is registered at the University of Bristol (Ref: 2020-3137). Research findings will be disseminated to stakeholders through conferences and peer-reviewed journals in China, the UK and internationally. TRIAL REGISTRATION NUMBER: ISRCTN30652037

Integrative Analysis of Transcriptome and GWAS Data to Identify the Hub Genes Associated With Milk Yield Trait in Buffalo

The mammary gland is the production organ in mammals that is of great importance for milk production and quality. However, characterization of the buffalo mammary gland transcriptome and identification of the valuable candidate genes that affect milk production is limited. Here, we performed the differential expressed genes (DEGs) analysis of mammary gland tissue on day 7, 50, 140, and 280 after calving and conducted gene-based genome-wide association studies (GWAS) of milk yield in 935 Mediterranean buffaloes. We then employed weighted gene co-expression network analysis (WGCNA) to identify specific modules and hub genes related to milk yield based on gene expression profiles and GWAS data. The results of the DEGs analysis showed that a total of 1,420 DEGs were detected across different lactation points. In the gene-based analysis, 976 genes were found to have genome-wide association (P ≤ 0.05) that could be defined as the nominally significant GWAS geneset (NSGG), 9 of which were suggestively associated with milk yield (P < 10−4). Using the WGCNA analysis, 544 and 225 genes associated with milk yield in the turquoise module were identified from DEGs and NSGG datasets, respectively. Several genes (including BNIPL, TUBA1C, C2CD4B, DCP1B, MAP3K5, PDCD11, SRGAP1, GDPD5, BARX2, SCARA3, CTU2, and RPL27A) were identified and considered as the hub genes because they were involved in multiple pathways related to milk production. Our findings provide an insight into the dynamic characterization of the buffalo mammary gland transcriptome, and these potential candidate genes may be valuable for future functional characterization of the buffalo mammary gland