Aim: To discover unknown factors associated with carcinoid syndrome (CS) with the goal of earlier diagnosis of CS.
Methods: In this retrospective case-control study using United States administrative claims, patients (≥ 18 years) newly-diagnosed with gastrointestinal neuroendocrine tumors (GI NETs) without CS (controls) were exactly matched to patients with CS (cases) based on NET diagnosis date at a 3-to-1 ratio. Study index date was first CS diagnosis (controls: same distance from NET diagnosis as cases). The most observed conditions, excluding CS-associated symptoms/diagnoses, during the year before index date were assessed. Forward-stepwise logistic regression models were used to derive predictors, and were validation within another claims database.
Results: In the development database, 1004 patients with GI NETs were identified; 251 (25%) had CS and 753 (75%) were controls. In the validation database, 724 patients with GI NETs were identified; 181 (25%) had CS and 543 (75%) were controls. A total of 33 common diagnoses (excluding conditions already known to be associated with CS) in the development database were entered in forward step-wise logistic regression models. In the final, validated logistic regression model, three factors prior to CS diagnosis were found consistently associated with higher risks for CS, including liver disorder [odds ratio (95%CI): 3.38 (2.07-5.51)], enlargement of lymph nodes [2.13 (1.10-4.11)], and abdominal mass [3.79 (1.87-7.69)].
Conclusion: GI NET patients with CS were 2-4 times as likely to have preexisting diagnoses (i.e., liver disorder, enlarged lymph nodes, abdominal mass) than non-CS patients.
Keywords: Carcinoid syndrome; Data mining; Gastrointestinal neuroendocrine tumors; Predictive factors.