A nonlinear correlation measure with applications to gene expression data.

Nonlinear correlation exists in many types of biomedical data. Several types of pairwise gene expression in humans and other organisms show nonlinear correlation across time, e.g.

Acetyl Coenzyme A Synthase 2 Acts as a Prognostic Biomarker Associated with Immune Infiltration in Cervical Squamous Cell Carcinoma.

Cervical squamous cell carcinoma (CESC) is one of the most common malignant tumors in women worldwide with a low survival rate. Acetyl coenzyme A synthase 2 (ACSS2) is a conserved nucleosidase that converts acetate to acetyl-CoA for energy production. Our research intended to identify the correlations of ACSS2 with clinical prognosis and tumor immune infiltration in CESC.

UBE2C Drives Human Cervical Cancer Progression and Is Positively Modulated by mTOR.

Cervical cancer is a common gynecological malignancy, accounting for 10% of all gynecological cancers. Recently, targeted therapy for cervical cancer has shown unprecedented advantages. Several studies have shown that ubiquitin conjugating enzyme E2 (UBE2C) is highly expressed in a series of tumors, and participates in the progression of these tumors.

Sequential adaptive variables and subject selection for GEE methods.

Modeling correlated or highly stratified multiple-response data is a common data analysis task in many applications, such as those in large epidemiological studies or multisite cohort studies. The generalized estimating equations method is a popular statistical method used to analyze these kinds of data, because it can manage many types of unmeasured dependence among outcomes. Collecting large amounts of highly stratified or correlated response data is time-consuming; thus, the use of a more aggressive sampling strategy that can accelerate this process-such as the active-learning methods found in the machine-learning literature-will always be beneficial.

Sample size determination and treatment screening in two-stage phase II clinical trials via ROC curve.

In pharmaceutical-related research, we usually use clinical trials methods to identify valuable treatments and compare their efficacy with that of a standard control therapy. Although clinical trials are essential for ensuring the efficacy and postmarketing safety of a drug, conducting clinical trials is usually costly and time-consuming. Moreover, to allocate patients to the little therapeutic effect treatments is inappropriate due to the ethical and cost imperative.

Influence Analysis for the Area Under the Receiver Operating Characteristic Curve.

Classification measures play essential roles in the assessment and construction of classifiers. Hence, determining how to prevent these measures from being affected by individual observations has become an important problem. In this paper, we propose several indexes based on the influence function and the concept of local influence to identify influential observations that affect the estimate of the area under the receiver operating characteristic curve (AUC), an important and commonly used measure.

Obesity and inflammatory biomarkers in women with polycystic ovary syndrome.

Objective: To evaluate the roles of obesity and inflammatory biomarkers associated with medical complications in women with PCOS.

Study Design: Retrospective, BMI-matched study. A total of 330 patients, including 165 women with PCOS and 165 women without PCOS, were evaluated.

Assessing the predictive power of newly added biomarkers.

As medical research and technology advance, there are always new biomarkers found and predictive models proposed for improving the diagnostic performance of diseases. Therefore, in addition to the existing biomarkers and predictive models, how to assess new biomarkers becomes an important research problem. Many classification performance measures, which are usually based on the performance on the whole cut-off values, were applied directly to this type of problems.

Adiponectin and leptin in overweight/obese and lean women with polycystic ovary syndrome.

Aim: The objective of this study was to evaluate the adiponectin and leptin levels in overweight/obese and lean women with polycystic ovary syndrome (PCOS).

Design: This was a retrospective study.

Patients: Of the 422 studied patients, 224 women with PCOS and 198 women without PCOS were evaluated.

Cluster analysis of cardiovascular and metabolic risk factors in women of reproductive age.

Objective: To study the association between endocrine disturbances and metabolic complications in women seeking gynecologic care.

Design: Retrospective study, cluster analysis.

Setting: Outpatient clinic, university medical center.

Hyperhomocysteinaemia is associated with biochemical hyperandrogenaemia in women with reproductive age.

Objective: Hyperhomocysteinaemia is a well-established risk factor for cardiovascular disease. This study investigated the relationship between hyperhomocysteinaemia and factors related to polycystic ovary syndrome (PCOS).

Study Design: Case-control study.

Maximizing an ROC-type measure via linear combination of markers when the gold reference is continuous.

Effectively combining many classification instruments or diagnostic measurements together to improve the classification accuracy of individuals is a common idea in disease diagnosis or classification. These ensemble-type diagnostic methods can be constructed with respect to different kinds of performance criterions. Among them, the receiver operating characteristic (ROC) curve is the most popular criterion, which, together with some indexes derived from it, is commonly used to evaluate and summarize the performance of a classification instrument, such as a biomarker or a classifier.

Sequential analysis of longitudinal data in a prospective nested case-control study.

The nested case-control design is a relatively new type of observational study whereby a case-control approach is employed within an established cohort. In this design, we observe cases and controls longitudinally by sampling all cases whenever they occur but controls at certain time points. Controls can be obtained at time points randomly scheduled or prefixed for operational convenience.

A parsimonious threshold-independent protein feature selection method through the area under receiver operating characteristic curve.

Motivation: Protein expression profiling for differences indicative of early cancer holds promise for improving diagnostics. Due to their high dimensionality, statistical analysis of proteomic data from mass spectrometers is challenging in many aspects such as dimension reduction, feature subset selection as well as construction of classification rules. Search of an optimal feature subset, commonly known as the feature subset selection (FSS) problem, is an important step towards disease classification/diagnostics with biomarkers.