Please assess the completion status of the following clinical trial:

Trial Title: A Study of Tarceva (Erlotinib) in First Line in Patients With Locally Advanced or Metastatic Lung Adenocarcinoma With EGFR Mutations

Study Design Characteristics:
- Allocation: None
- Intervention Model: SINGLE_GROUP
- Observational Model: None
- Primary Purpose: TREATMENT
- Time Perspective: None
- Masking: NONE
- Phase: PHASE4
- Number of Arms: 1.0

Eligibility Criteria:
Inclusion Criteria:~* Adult patients, \>/= 18 years of age~* Histologically or cytologically documented, inoperable, locally advanced, recurrent or metastatic (Stage IIIB or Stage IV) lung adenocarcinoma~* Non-small cell lung cancer with an EGFR activating mutation~* Patients must have evidence of disease, but measurable disease is not mandatory~* Eastern Cooperative Oncology Group (ECOG) performance status 0-2~* Adequate renal and liver function~Exclusion Criteria:~* Prior chemotherapy or other systemic anti-cancer treatment. Neoadjuvant/adjuvant chemotherapy is allowed if completed within 6 months prior to enrolment. Prior radiochemotherapy is allowed if completed more than 6 months before start of study treatment~* Prior therapy with systemic anti-tumour therapy with HER1/EGFR inhibitors~* Any other malignancies within 5 years, except for adequately treated carcinoma in situ of the cervix or basal or squamous cell skin carcinoma~* Brain metastasis or spinal cord compression not yet definitely treated with surgery and/or radiation~* Patients unable to take oral medication or requiring intravenous alimentation, with prior surgical procedures affecting absorption or active peptic ulcer disease~* Any significant ophthalmologic abnormality, especially those likely to increase the risk of corneal epithelial lesions; the use of contact lenses is not recommended during the study~* Pregnant or breast-feeding women

- Gender: ALL
- Minimum Age: 18 Years
- Maximum Age: None
- Healthy Volunteers: f

Study Arms:
- Single Arm (Type: EXPERIMENTAL): None

Based on this trial design, predict the completion outcome and termination type (if applicable).