title: IDENTIFICATION OF POTENTIAL MARKERS FOR CUSHING DISEASE.
abstract: OBJECTIVE
  Cushing disease (CD) causes a wide variety of nonspecific symptoms, which may result in delayed diagnosis. It may be possible to uncover unusual combinations of otherwise common symptoms using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. Our aim was to identify and evaluate dyads of clinical symptoms or conditions associated with CD.
  
  
  METHODS
  We conducted a matched case-control study using a commercial healthcare insurance claims database designed to compare the relative risk (RR) of individual conditions and dyad combinations of conditions among patients with CD versus matched non-CD controls.
  
  
  RESULTS
  With expert endocrinologist input, we isolated 10 key conditions (localized adiposity, hirsutism, facial plethora, polycystic ovary syndrome, abnormal weight gain, hypokalemia, deep venous thrombosis, muscle weakness, female balding, osteoporosis) with RRs varying from 5.3 for osteoporosis to 61.0 for hirsutism (and infinite RR for localized adiposity). The RRs of dyads of these conditions ranged from 4.1 for psychiatric disorders/serious infections to 128.0 for hirsutism/fatigue in patients with versus without CD. Construction of uncommon dyads resulted in further increases in RRs beyond single condition analyses; for example, osteoporosis alone had an RR of 5.3, which increased to 8.3 with serious infections and to 52.0 with obesity.
  
  
  CONCLUSIONS
  This study demonstrated that RR of any one of 10 key conditions selected by expert opinion was ≥5 times greater in CD compared to non-CD, and nearly all dyads had RR≥5. An uncommon dyad of osteoporosis and obesity had an RR of 52.0. If clinicians consider the diagnosis of CD when the highest-risk conditions are seen, identification of this rare disease may improve.
authors.forename: Michael S
authors.initials: MS
authors.lastname: Broder
authors.forename: Eunice
authors.initials: E
authors.lastname: Chang
authors.forename: Dasha
authors.initials: D
authors.lastname: Cherepanov
authors.forename: Maureen P
authors.initials: MP
authors.lastname: Neary
authors.forename: William H
authors.initials: WH
authors.lastname: Ludlam
mesh_terms: D050154:Adiposity; D000328:Adult; D000505:Alopecia / Q000453:epidemiology; D015415:Biomarkers / Q000032:analysis*; D016022:Case-Control Studies; D015897:Comorbidity; D016208:Databases, Factual / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018908:Muscle Weakness / Q000453:epidemiology; D010024:Osteoporosis / Q000453:epidemiology; D047748:Pituitary ACTH Hypersecretion / Q000175:diagnosis* / Q000453:epidemiology*; D011085:Polycystic Ovary Syndrome / Q000453:epidemiology; D012189:Retrospective Studies; D014481:United States / Q000453:epidemiology; D015430:Weight Gain
chemical_list: D015415:Biomarkers