Inferring breast cancer concomitant diagnosis and comorbidities from the Nationwide Inpatient Sample using social network analysis

Abstract

Breast cancer is a complex disease and may be accompanied by other multiple health conditions. The present study investigates associations between diagnosis codes in breast cancer patients using the Nationwide Inpatient Sample data. Concomitant diagnoses codes are identified by statistically significant associations between the diagnoses codes in a given breast cancer patient. These are subsequently represented in the form of a network (Breast Cancer Concomitant Diagnosis Network (BCCDN)). In contrast to more classical approaches, BCCDN provides system-level insights and convenient visualization reflected by the complex wiring patterns between the diagnoses codes. Social network analysis is used to investigate highly connected codes in the BCCDN network, and their variation across three different populations: (i) the deceased breast cancer population (ii) the elderly breast cancer population (age>65 years) and (iii) the adult breast cancer population (age <=65 years). BCCDNs were investigated across years 2005 and 2006 in order to identify associations that are robust to the stratified sampling and population heterogeneity as well as possible errors in documentation characteristic of observational healthcare data. The results presented validate known chronic comorbidities and their persistence across the deceased and elderly breast cancer population. They also provide novel associations and potential comorbidities in breast cancer patients that may warrant a more detailed investigation.