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Clinical physicians commonly find pulmonary nodules difficult to interpret when these are found in radiographic images. This finding requires special skills to use the correct diagnostic method to properly distinguish between malignant and benign nodules. Prompt identification of a nodule or tumor is necessary so treatment strategies essential for prognosis can be implemented. Over the past few years, the Mayo Clinic lung cancer probability formula has been validated by several researchers to determine if this equation is an effective tool in helping to identify lung cancer. The purpose of this study is to verify whether this formula is applicable to patients living in Asian countries where tuberculosis (TB) is prevalent. 

Between 2012 and 2014, we retrospectively collected and reviewed the medical records of 54 patients in Bangkok Hospital Medical Center who tested positive with lung nodules or mass, measuring 4.5- 88 mm in diameter as reported from their chest computed tomography (CT) scan. Data gathered included: patient age, gender (male or female), race (Asian or Non-Asian), smoking history (smoker, previous smoker or never having smoked), extrathoracic cancer for more than 5 years prior to the consultation, lung nodule or tumor location (upper, middle, lower), spiculated morphology and final definite tissue diagnosis as collected through Fiberoptic bronchoscopy (FOB), Endobronchial Ultrasound (EBUS), Electromagnetic Navigation Bronchoscopy (ENB) and Video Assisted Thoracoscopic Surgery (VATS). We evaluated the accuracy of the Mayo Clinic formula for estimating the probability of lung cancer by computing then comparing the lung cancer probability result versus the final diagnosis. 

For the 54 patients with a confirmed final diagnosis, lung cancer was found in 16 patients, tuberculosis with non-tuberculous mycobacteria (NTM) infection in 24 patients, 11 cases were diagnosed with lung cancer with tuberculosis and 3 cases appeared to be a benign tumor. In the first category, in patients diagnosed with lung cancer, the result from the Mayo Clinic formula was 74.7%. In Category 2 (TB and NTM infection), lung cancer probability was 27.8%, in category 3 (lung cancer and TB) the probability was 76% and in category 4 (benign) the probability was 17.9%. 

The Mayo Clinic formula is an effective and useful tool in predicting lung cancer probability even among Asian communities where there is high incidence of tuberculosis. However, we must also consider that this formula though beneficial, should not be the sole basis of diagnosis when screening for lung cancer.

chest CT scan, lung cancer, mayo clinic formula, non-tuberculous myobacterium, pulmonary nodules, tuberculosis

10.31524/bkkmedj.2017.09.006