Developing a Clinico-Molecular Test for Individualized Treatment of Ovarian Cancer: The interplay of Precision Medicine Informatics with Clinical and Health Economics Dimensions.

We report recent progress in the development of a precision test for individualized use of the VEGF-A targeting drug bevacizumab for treating ovarian cancer. We discuss the discovery model stage (i.e., past feasibility modeling and before conversion to the production test). Main results: (a) Informatics modeling plays a critical role in supporting driving clinical and health economic requirements. (b) The novel computational models support the creation of a precision test with sufficient predictivity to reduce healthcare system costs up to $30 billion over 10 years, and make the use of bevacizumab affordable without loss of length or quality of life.

Assessment of the Intraoperative Consultation Service Rendered by General Pathologists in a Scenario Where a Well-Defined Decision Algorithm Is Followed.

OBJECTIVES: Intraoperative consultation (IOC) remains an area of general practice even within subspecialized pathology departments. This study assesses the IOCs rendered in a general pathology setting where surgeons integrate these results in a well-defined algorithm, developed with the input of specialized pathologists. METHODS: The surgical decisions to perform lymphadenectomy in patients with endometrial adenocarcinoma operated on at our institution between January 2003 and June 2015 as a result of the IOC assessment of tumor size, histologic grade, and depth of invasion in the hysterectomy specimen were analyzed. RESULTS: Frozen section (FS) was examined in 801 cases. In comparison to permanent section analysis, FS International Federation of Gynecology and Obstetrics (FIGO) grade had an overall accuracy of 0.95 (95% confidence interval [CI], 0.93-0.98). The FS depth of invasion had an overall accuracy of 0.92 (95% CI, 0.89-0.94). FIGO grade was not documented in 47.8%, the depth of myometrial invasion in 45.2%, and tumor size in 41.8% of the pathology reports. CONCLUSIONS: The high omission rate of the needed parameters by the general pathologists would question their overall understanding of the paradigm shift intended by this algorithm. Possible explanations of this phenomenon and potential solutions are discussed.