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Mining cancer-specific disease comorbidities from a large observational health database.

Chen Y, Xu R - Cancer Inform (2014)

Bottom Line: We stratified 3,354,043 patients based on age and gender, and developed a network-based approach to extract comorbidity patterns from each patient group.We applied our comorbidity mining approach on colorectal cancer and detected its comorbid associations with metabolic syndrome components, diabetes, and osteoporosis.Our results not only confirmed known cancer comorbidities but also generated novel hypotheses, which can illuminate the common pathophysiology between cancers and their co-occurring diseases.

View Article: PubMed Central - PubMed

Affiliation: Division of Medical Informatics, Case Western Reserve University, Cleveland, OH, USA.

ABSTRACT
Cancer comorbidities often reflect the complex pathogenesis of cancers and provide valuable clues to discover the underlying genetic mechanisms of cancers. In this study, we systematically mine and analyze cancer-specific comorbidity from the FDA Adverse Event Reporting System. We stratified 3,354,043 patients based on age and gender, and developed a network-based approach to extract comorbidity patterns from each patient group. We compared the comorbidity patterns among different patient groups and investigated the effect of age and gender on cancer comorbidity patterns. The results demonstrated that the comorbidity relationships between cancers and non-cancer diseases largely depend on age and gender. A few exceptions are depression, anxiety, and metabolic syndrome, whose comorbidity relationships with cancers are relatively stable among all patients. Literature evidences demonstrate that these stable cancer comorbidities reflect the pathogenesis of cancers. We applied our comorbidity mining approach on colorectal cancer and detected its comorbid associations with metabolic syndrome components, diabetes, and osteoporosis. Our results not only confirmed known cancer comorbidities but also generated novel hypotheses, which can illuminate the common pathophysiology between cancers and their co-occurring diseases.

No MeSH data available.


Related in: MedlinePlus

Comorbidity relationships between nervous system diseases and cancers among five age groups.
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f5-cin-suppl.1-2014-037: Comorbidity relationships between nervous system diseases and cancers among five age groups.

Mentions: We extracted 14 nervous system diseases from the top-ranked comorbidities in all age groups. Among them, anxiety, depression, and epilepsy are associated with cancers at most age levels; schizophrenia and bipolar disease tend to co-occur with cancers among patients younger than 60 years (Fig. 5). Gender has little impact on the comorbidity patterns of these diseases. Note that other mental problems, such as Alzheimer’s disease and Parkinson’s disease, do not have strong associations with cancers in any patient group, although both diseases are common among elderly patients in our data. Previous studies have demonstrated that they are inverse cancer comorbidities.28,29


Mining cancer-specific disease comorbidities from a large observational health database.

Chen Y, Xu R - Cancer Inform (2014)

Comorbidity relationships between nervous system diseases and cancers among five age groups.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4216041&req=5

f5-cin-suppl.1-2014-037: Comorbidity relationships between nervous system diseases and cancers among five age groups.
Mentions: We extracted 14 nervous system diseases from the top-ranked comorbidities in all age groups. Among them, anxiety, depression, and epilepsy are associated with cancers at most age levels; schizophrenia and bipolar disease tend to co-occur with cancers among patients younger than 60 years (Fig. 5). Gender has little impact on the comorbidity patterns of these diseases. Note that other mental problems, such as Alzheimer’s disease and Parkinson’s disease, do not have strong associations with cancers in any patient group, although both diseases are common among elderly patients in our data. Previous studies have demonstrated that they are inverse cancer comorbidities.28,29

Bottom Line: We stratified 3,354,043 patients based on age and gender, and developed a network-based approach to extract comorbidity patterns from each patient group.We applied our comorbidity mining approach on colorectal cancer and detected its comorbid associations with metabolic syndrome components, diabetes, and osteoporosis.Our results not only confirmed known cancer comorbidities but also generated novel hypotheses, which can illuminate the common pathophysiology between cancers and their co-occurring diseases.

View Article: PubMed Central - PubMed

Affiliation: Division of Medical Informatics, Case Western Reserve University, Cleveland, OH, USA.

ABSTRACT
Cancer comorbidities often reflect the complex pathogenesis of cancers and provide valuable clues to discover the underlying genetic mechanisms of cancers. In this study, we systematically mine and analyze cancer-specific comorbidity from the FDA Adverse Event Reporting System. We stratified 3,354,043 patients based on age and gender, and developed a network-based approach to extract comorbidity patterns from each patient group. We compared the comorbidity patterns among different patient groups and investigated the effect of age and gender on cancer comorbidity patterns. The results demonstrated that the comorbidity relationships between cancers and non-cancer diseases largely depend on age and gender. A few exceptions are depression, anxiety, and metabolic syndrome, whose comorbidity relationships with cancers are relatively stable among all patients. Literature evidences demonstrate that these stable cancer comorbidities reflect the pathogenesis of cancers. We applied our comorbidity mining approach on colorectal cancer and detected its comorbid associations with metabolic syndrome components, diabetes, and osteoporosis. Our results not only confirmed known cancer comorbidities but also generated novel hypotheses, which can illuminate the common pathophysiology between cancers and their co-occurring diseases.

No MeSH data available.


Related in: MedlinePlus