Prostate cancer (PC) is the most common non-skin tumor in men and the second leading cause of death from cancer in Brazil. It accounts for 13.8% of deaths from cancer in males, similar to what happens with breast cancer in females, corresponding to 15.8% of cancer deaths in women. Mobile applications, software developed for smartphones and tablets used for many different purposes (games, communication, entertainment etc) have become important tools of mHealth (Mobile Health in Portuguese - mobile health) as they allow remote support to patients or self-promotion of health care. It has been used globally to assist in the treatment and control of various diseases such as diabetes, physical inactivity, and many others. In oncology there are several applications developed to assist in the monitoring and treatment of various cancers such as gastric and breast cancer. So far it has not developed an application for follow-up of patients with PC, to capture data on satisfaction of post-treatment patient regarding the comorbidity of surgery, and also loyalty and adherence of patients to follow-up in offices allowing a possible intervention it is done at the right time. Nor was made compared to assess whether there is benefit in using this application. Thus, the objective of this work is to develop an application for smartphones facing the postoperative follow-up of patients undergoing robotic radical prostatectomy and compare adherence to treatment compared to accompanied by traditional way patient. In addition, we will evaluate the progress of the IPSS, ICIQ and IIEF-5 compared to preoperatively in patients undergoing prostatectomy robotic radical.

Inclusion Criteria:

• patients having a diagnosis of prostate cancer who are undergoing robotic radical prostatectomy for treatment of the disease and who accept to participate in the study by signing the informed consent term.

Exclusion Criteria:

• Patients who refused to participate in the study

This is a prospective randomized controlled trial. We will select prospectively 100 patients diagnosed with prostate cancer. These patients will be divided into two groups using randomisation tables (www.random.org), which are: 1. Patients who will use the clinical application (n = 50) 2. Patients who do not use the application (n = 50 - group control).