INTEGRATION OF MULTI-PLATFORM HIGH-DIMENSIONAL OMIC DATA

The development of high-throughput biotechnologies have made data accessible from different platforms, including RNA sequencing, copy number variation, DNA methylation, protein lysate arrays, etc. The high-dimensional omic data derived from different technological platforms have been extensively used to facilitate comprehensive understanding of disease mechanisms and to determine personalized health treatments. Although vital to the progress of clinical research, the high dimensional multi-platform data impose new challenges for data analysis. Numerous studies have been proposed to integrate multi-platform omic data; however, few have efficiently and simultaneously addressed the problems that arise from high dimensionality and complex correlations. In my dissertation, I propose a statistical framework of shared informative factor model (SIFORM) that can jointly analyze multi-platform omic data and explore their associations with a disease phenotype. The common disease- associated sample characteristics across different data types can be captured through the shared structure space, while the corresponding weights of genetic variables directly index the strengths of their association with the phenotype. I compare the performance of the proposed method with several popular regularized regression methods and canonical correlation analysis (CCA)-based methods through extensive simulation studies and two lung adenocarcinoma applications. The two lung adenocarcinoma applications jointly explore the associations of mRNA expression and protein expression with smoking status and survival using The Cancer Genome Atlas (TCGA) datasets. The simulation studies demonstrate the superior performance of SIFORM in terms of biomarker detection accuracy. In lung cancer applications, SIFORM identifies many biomarkers that belong to key pathways for lung tumorigenesis. It also discovers potential prognostic biomarkers for lung cancer patients survival and some biomarkers that reveal different tumorigenesis mechanisms between light smokers and heavy smokers. To improve the prediction accuracy and interpretability of the proposed model, I extend it to PSIFORM by incorporating existing biological pathway information to current statistical framework. I adopt a network-based regularization to ensure that the neighboring genes in the same pathway tend to be selected (or eliminated) simultaneously. Through simulation studies and a TCGA kidney cancer application, I show that PSIFORM outperforms its competitors in both variable selection and prediction. The statistical framework of PSIFORM also has a great potential in incorporating the hierarchical order across the multi-platform omic measurements

A simulation model of colorectal cancer surveillance and recurrence

BACKGROUND: Approximately one-third of those treated curatively for colorectal cancer (CRC) will experience recurrence. No evidence-based consensus exists on how best to follow patients after initial treatment to detect asymptomatic recurrence. Here, a new approach for simulating surveillance and recurrence among CRC survivors is outlined, and development and calibration of a simple model applying this approach is described. The model’s ability to predict outcomes for a group of patients under a specified surveillance strategy is validated. METHODS: We developed an individual-based simulation model consisting of two interacting submodels: a continuous-time disease-progression submodel overlain by a discrete-time Markov submodel of surveillance and re-treatment. In the former, some patients develops recurrent disease which probabilistically progresses from detectability to unresectability, and which may produce early symptoms leading to detection independent of surveillance testing. In the latter submodel, patients undergo user-specified surveillance testing regimens. Parameters describing disease progression were preliminarily estimated through calibration to match five-year disease-free survival, overall survival at years 1–5, and proportion of recurring patients undergoing curative salvage surgery from one arm of a published randomized trial. The calibrated model was validated by examining its ability to predict these same outcomes for patients in a different arm of the same trial undergoing less aggressive surveillance. RESULTS: Calibrated parameter values were consistent with generally observed recurrence patterns. Sensitivity analysis suggested probability of curative salvage surgery was most influenced by sensitivity of carcinoembryonic antigen assay and of clinical interview/examination (i.e. scheduled provider visits). In validation, the model accurately predicted overall survival (59% predicted, 58% observed) and five-year disease-free survival (55% predicted, 53% observed), but was less accurate in predicting curative salvage surgery (10% predicted; 6% observed). CONCLUSIONS: Initial validation suggests the feasibility of this approach to modeling alternative surveillance regimens among CRC survivors. Further calibration to individual-level patient data could yield a model useful for predicting outcomes of specific surveillance strategies for risk-based subgroups or for individuals. This approach could be applied toward developing novel, tailored strategies for further clinical study. It has the potential to produce insights which will promote more effective surveillance—leading to higher cure rates for recurrent CRC

Barriers to hospital deliveries among ethnicminority women with religious beliefs in China:A descriptive study using interviews and survey data

Background: China has made great progress in improving hospital delivery-the coverage of hospital delivery has increased to above 95% in most regions- some regions lag behind owing to geographic and economic inequality, particularly the poor ethnic minority areas of the Sichuan Province. This study explores factors which may influence hospital delivery from multiple perspectives, with implications for practice and policy. Methods: A framework analysis approach was used to identify and categorize the main barriers and levers to hospital delivery. Our analysis draws on basic information from the sampled counties (Butuo and Daofu). Results: The hospital delivery rate was below 50% in the two sampled areas. In both areas, the “New Rural Cooperative Medical Scheme” and “Rural hospital delivery subsidy” were introduced, but only Butuo county had a transportation subsidy policy. Socioeconomically disadvantaged women in both counties who delivered their babies in hospitals could also apply for financial assistance. A lack of transport was among the main reasons for low hospital delivery rates in these two counties. Furthermore, while the hospital delivery costs could be mostly covered by “New Rural Cooperative Medical Scheme” or “Rural Hospital Delivery Subsidy”, reimbursement was not guaranteed. People in Daofu county might be affected by their Buddhism religion for hospital delivery. Women in Butuo following the Animism religion would refuse delivery in hospitals because of language barriers. Traditional lay beliefs were the main factor that influenced hospital delivery; their understandings of reproductive health varied, and many believed that childbirth should not be watched by strangers and that a home delivery was safe. Conclusions: This study has highlighted a number of barriers and levers to hospital delivery in rural poor ethnic minority areas which could inform and improve the access and rate of hospital delivery rate; thereby reducing health inequalities in maternal and child health in China

Intracranial Efficacy and Survival With Tucatinib Plus Trastuzumab and Capecitabine for Previously Treated HER2-Positive Breast Cancer With Brain Metastases in the HER2CLIMB Trial

PURPOSE: In the HER2CLIMB study, patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer with brain metastases (BMs) showed statistically significant improvement in progression-free survival (PFS) with tucatinib. We describe exploratory analyses of intracranial efficacy and survival in participants with BMs. PATIENTS AND METHODS: Patients were randomly assigned 2:1 to tucatinib or placebo, in combination with trastuzumab and capecitabine. All patients underwent baseline brain magnetic resonance imaging; those with BMs were classified as active or stable. Efficacy analyses were performed by applying RECIST 1.1 criteria to CNS target lesions by investigator assessment. CNS-PFS (intracranial progression or death) and overall survival (OS) were evaluated in all patients with BMs. Confirmed intracranial objective response rate (ORR-IC) was evaluated in patients with measurable intracranial disease. RESULTS: There were 291 patients with BMs: 198 (48%) in the tucatinib arm and 93 (46%) in the control arm. The risk of intracranial progression or death was reduced by 68% in the tucatinib arm (hazard ratio [HR], 0.32; 95% CI, 0.22 to 0.48; CONCLUSION: In patients with HER2-positive breast cancer with BMs, the addition of tucatinib to trastuzumab and capecitabine doubled ORR-IC, reduced risk of intracranial progression or death by two thirds, and reduced risk of death by nearly half. To our knowledge, this is the first regimen to demonstrate improved antitumor activity against BMs in patients with HER2-positive breast cancer in a randomized, controlled trial

Inequality of Paediatric Workforce Distribution in China

Child health has been addressed as a priority at both global and national levels for many decades. In China, difficulty of accessing paediatricians has been of debate for a long time, however, there is limited evidence to assess the population- and geography-related inequality of paediatric workforce distribution. This study aimed to analyse the inequality of the distributions of the paediatric workforce (including paediatricians and paediatric nurses) in China by using Lorenz curve, Gini coefficient, and Theil L index, data were obtained from the national maternal and child health human resource sampling survey conducted in 2010. In this study, we found that the paediatric workforce was the most inequitable regarding the distribution of children <7 years, the geographic distribution of the paediatric workforce highlighted very severe inequality across the nation, except the Central region. For different professional types, we found that, except the Central region, the level of inequality of paediatric nurses was higher than that of the paediatricians regarding both the demographic and geographic distributions. The inner-regional inequalities were the main sources of the paediatric workforce distribution inequality. To conclude, this study revealed the inadequate distribution of the paediatric workforce in China for the first time, substantial inequality of paediatric workforce distribution still existed across the nation in 2010, more research is still needed to explore the in-depth sources of inequality, especially the urban-rural variance and the inner- and inter-provincial differences, and to guide national and local health policy-making and resource allocation

Intracranial Efficacy and Survival With Tucatinib Plus Trastuzumab and Capecitabine for Previously Treated HER2-Positive Breast Cancer With Brain Metastases in the HER2CLIMB Trial.

PurposeIn the HER2CLIMB study, patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer with brain metastases (BMs) showed statistically significant improvement in progression-free survival (PFS) with tucatinib. We describe exploratory analyses of intracranial efficacy and survival in participants with BMs.Patients and methodsPatients were randomly assigned 2:1 to tucatinib or placebo, in combination with trastuzumab and capecitabine. All patients underwent baseline brain magnetic resonance imaging; those with BMs were classified as active or stable. Efficacy analyses were performed by applying RECIST 1.1 criteria to CNS target lesions by investigator assessment. CNS-PFS (intracranial progression or death) and overall survival (OS) were evaluated in all patients with BMs. Confirmed intracranial objective response rate (ORR-IC) was evaluated in patients with measurable intracranial disease.ResultsThere were 291 patients with BMs: 198 (48%) in the tucatinib arm and 93 (46%) in the control arm. The risk of intracranial progression or death was reduced by 68% in the tucatinib arm (hazard ratio [HR], 0.32; 95% CI, 0.22 to 0.48; P < .0001). Median CNS-PFS was 9.9 months in the tucatinib arm versus 4.2 months in the control arm. Risk of death was reduced by 42% in the tucatinib arm (OS HR, 0.58; 95% CI, 0.40 to 0.85; P = .005). Median OS was 18.1 versus 12.0 months. ORR-IC was higher in the tucatinib arm (47.3%; 95% CI, 33.7% to 61.2%) versus the control arm (20.0%; 95% CI, 5.7% to 43.7%; P = .03).ConclusionIn patients with HER2-positive breast cancer with BMs, the addition of tucatinib to trastuzumab and capecitabine doubled ORR-IC, reduced risk of intracranial progression or death by two thirds, and reduced risk of death by nearly half. To our knowledge, this is the first regimen to demonstrate improved antitumor activity against BMs in patients with HER2-positive breast cancer in a randomized, controlled trial