Diagnostic evaluation of patients with a high suspicion of malignancy: Comorbidities and clinical predictors of cancer

Background: The diagnosis of cancer is based on the demonstration of malignant cells obtained via biopsy or needle aspiration. For some patients, diagnostic options may be limited either because of tumor location, underlying comorbid conditions, or lack of access to care. Methods: 275 of 282 consecutive patients presenting to the University of Texas M.D. Anderson Cancer Center with a suspicion of cancer between April 1, 2000 and January 23, 2003 were evaluated retrospectively. We analyzed differences in means of diagnosis, complication rates, clinical characteristics, and comorbid medical conditions between patients with and without a cancer diagnosis. Logistic regression analysis was used to determine the independent predictors of a diagnosis of cancer. Results: 179 (65%) patients had a cancer diagnosis. Endoscopic ultrasonography with fine needle aspiration (EUS/FNA) and image-guided percutaneous biopsy (IGPB) were the most commonly used diagnostic techniques. Complications occurred in 6% of all cases. Independent predictors of a cancer diagnosis included age of 50 years or older, jaundice, weight loss, percentage of monocytes greater than 7, and platelet count greater than 440 × 10⁹/L; the ROC statistic was 0.796 (CI, 0.738-0.854; P < 0.001). Controlling for age, there was no difference in comorbidity between patients with and without a cancer diagnosis. Conclusions: EUS/FNA and IGPB play an important role in the diagnosis of certain types of malignancy and are associated with a low risk for complications. Advanced age, prior history of malignancy, weight loss, abnormally high percentage of monocytes, and thrombocytosis may be predictive of a cancer diagnosis in patients with suspected malignancy. Comorbid medical conditions are common among patients and occur at rates similar to the general population. Further study is necessary to determine organ-specific predictors of malignancy and to better understand the relationship between cancer and coexisting medical conditions.