Verification of Mayo Clinic Formula to Determine Lung Cancer Probability among Patients Living in Tuberculosis Endemic Areas

Abstract

RATIONALE: Clinical physicians commonly find pulmonary nodules difficult tointerpret when these are found in radiographic images. This finding requires specialskills to use the correct diagnostic method to properly distinguish between malignantand benign nodules. Prompt identification of a nodule or tumor is necessary so treatmentstrategies essential for prognosis can be implemented. Over the past few years, the MayoClinic lung cancer probability formula has been validated by several researchers todetermine if this equation is an effective tool in helping to identify lung cancer. Thepurpose of this study is to verify whether this formula is applicable to patients living inAsian countries where tuberculosis (TB) is prevalent. MATERIALS AND METHODS: Between 2012 and 2014, we retrospectivelycollected and reviewed the medical records of 54 patients in Bangkok Hospital MedicalCenter who tested positive with lung nodules or mass, measuring 4.5- 88 mm in diameteras 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 than5 years prior to the consultation, lung nodule or tumor location (upper, middle, lower),spiculated morphology and final definite tissue diagnosis as collected through Fiberopticbronchoscopy (FOB), Endobronchial Ultrasound (EBUS), Electromagnetic NavigationBronchoscopy (ENB) and Video Assisted Thoracoscopic Surgery (VATS). We evaluatedthe accuracy of the Mayo Clinic formula for estimating the probability of lung cancerby computing then comparing the lung cancer probability result versus the final diagnosis. RESULTS: For the 54 patients with a confirmed final diagnosis, lung cancer was foundin 16 patients, tuberculosis with non-tuberculous mycobacteria (NTM) infection in 24patients, 11 cases were diagnosed with lung cancer with tuberculosis and 3 casesappeared to be a benign tumor. In the first category, in patients diagnosed with lungcancer, the result from the Mayo Clinic formula was 74.7%. In Category 2 (TB andNTM 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%. CONCLUSION: The Mayo Clinic formula is an effective and useful tool in predictinglung cancer probability even among Asian communities where there is high incidenceof tuberculosis. However, we must also consider that this formula though beneficial,should not be the sole basis of diagnosis when screening for lung cancer.