Auspex Diagnostics articles

Abstract

We developed a series of models to predict the likelihood of recurrence and the response to chemotherapy for the personalized treatment of stage I and II colorectal cancer patients. A recurrence prediction model was developed from 235 stage I/II patients. The model successfully distinguished between high-risk and low-risk groups, with a hazard ratio of recurrence of 4.66 (p < 0.0001). More importantly, the model was accurate for

Background

Combination chemotherapy using fluorouracil, leucovorin with or without oxaliplatin (5-FU and FOLFOX) are standard treatment for locally advanced colon cancer. However, about half of the patients developed recurrence. The objective of this study was to use gene profiling to predict treatment efficacy for colon cancer patients (stages 1-3). We developed three prediction models: the first determines the likelihood of recurrence after curative resection while

Purpose

The incidence and mortality rates of cervical cancer are declining in the United States; however, worldwide, cervical cancer is still one of the leading causes of death in women, second only to breast cancer. This disparity is at least partially explained by the absence of or comparatively ineffective screening programs in the developing world. Recent advances in expression genomics have enabled the use of DNA microarray to profile gene expression of various c

Abstract

Lung cancer mortality remains high even after successful resection. Adjuvant treatment benefits stage II and III patients, but not stage I patients, and most studies fail to predict recurrence in stage I patients. Our study included 211 lung adenocarcinoma patients (stages I–IIIA; 81% stage I) who received curative resections at Taipei Veterans General Hospital between January 2001 and December 2012. We generated a prediction model using 153 samples, wi

Abstract

Background: Five-year survival for stage I-II lung cancer is quite low even after complete surgical resection. Current guidelines recommend adjuvant treatment only for selected patients with stage II or higher disease. A prediction model that identifies patients at high risk of recurrence who may benefit from adjuvant treatment is greatly needed. Many existing prediction models include a small number of genes that were found to be significant