Association between patient medications and postoperative outcomes in early-stage non-small cell lung cancer.

Background: Currently, there is no consensus on how to comprehensively assess comorbidities in lung cancer patients in the clinical setting. Prescription medications may be a preferred comorbidity assessment tool and provide a simple mechanism for predicting postoperative outcomes for lung cancer. We examined the relationship between prescription medications and postoperative outcomes for early-stage non-small cell lung cancer (NSCLC).

Prescription Medications and Overall Survival in Metastatic Hormone Sensitive Prostate Cancer.

Background/aim: With new therapies for metastatic prostate cancer, patients are living longer, increasing the need for better understanding of the impact of comorbid disease. Prescription medications may risk-stratify patients independent of established methods, such as the Charlson Comorbidity Index (CCI) and guide treatment selection.

Patients And Methods: In a nationwide retrospective study of US Veterans, we used multivariable logistic regression and Cox proportional hazard modeling to evaluate the association between number and class of prescription medications and overall survival (OS) with age, race, body-mass index, prostate specific antigen (PSA), and Charlson comorbidities as covariates in veterans treated for de novo metastatic hormone sensitive prostate cancer (mHSPC) between 2010-2021.

Inhaled medications for chronic obstructive pulmonary disease predict surgical complications and survival in stage I non-small cell lung cancer.

Background: Lung function is routinely assessed prior to surgical resection for non-small cell lung cancer (NSCLC). Further assessment of chronic obstructive pulmonary disease (COPD) using inhaled COPD medications to determine disease severity, a readily available metric of disease burden, may predict postoperative outcomes and overall survival (OS) in lung cancer patients undergoing surgery.

Methods: We retrospectively evaluated clinical stage I NSCLC patients receiving surgical treatment within the Veterans Health Administration from 2006-2016 to determine the relationship between number and type of inhaled COPD medications (short- and long-acting beta2-agonists, muscarinic antagonists, or corticosteroids prescribed within 1 year before surgery) and postoperative outcomes including OS using multivariable models.

Predicting Readmission Charges Billed by Hospitals: Machine Learning Approach.

Background: The Centers for Medicare and Medicaid Services projects that health care costs will continue to grow over the next few years. Rising readmission costs contribute significantly to increasing health care costs. Multiple areas of health care, including readmissions, have benefited from the application of various machine learning algorithms in several ways.

Big Data Application in Biomedical Research and Health Care: A Literature Review.

Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data.