A predictive model for recurrence in patients with glottic cancer implemented in a mobile application for Android.

OBJECTIVES: The existing predictive models of laryngeal cancer recurrence present limitations for clinical practice. Therefore, we constructed, internally validated and implemented in a mobile application (Android) a new model based on a points system taking into account the internationally recommended statistical methodology. MATERIALS AND METHODS: This longitudinal prospective study included 189 patients with glottic cancer in 2004-2016 in a Spanish region. The main variable was time-to-recurrence, and its potential predictors were: age, gender, TNM classification, stage, smoking, alcohol consumption, and histology. A points system was developed to predict five-year risk of recurrence based on a Cox model. This was validated internally by bootstrapping, determining discrimination (C-statistics) and calibration (smooth curves). RESULTS: A total of 77 patients presented recurrence (40.7%) in a mean follow-up period of 3.4 ±â€¯3.0 years. The factors in the model were: age, lymph node stage, alcohol consumption and stage. Discrimination and calibration were satisfactory. CONCLUSION: A points system was developed to obtain the probability of recurrence of laryngeal glottic cancer in five years, using five clinical variables. Our system should be validated externally in other geographical areas.