The MelFo Study UK: Effects of a reduced-frequency, stage-adjusted follow-up schedule for cutaneous melanoma 1B to 2C patients after 3-years

Background: Evidence-based guidelines for follow-up treatment of American Joint Committee on Cancer (AJCC) stages 1B to 2C melanoma patients are lacking. The MELanoma FOllow-up study is an international phase 3 randomized trial, and the 3-year interim data were recently reported from the Netherlands. The study was undertaken concurrently with a British cohort for comparison and validation of the Dutch study. Methods: The study enrolled and stratified 207 patients by AJCC stage. The conventional schedule group (CSG; n = 103) cohort was reviewed as per UK guidelines. The experimental schedule group (ESG; n = 104) cohort was reviewed in a reduced-frequency nurse-led, consultant-supervised clinic. Quality of life (QoL) was measured at baseline (T1), a 1 year (T2), and at 3 years (T3) using the State-Trait Anxiety Inventory, the Cancer Worry Scale, the Impact-of-Event Scale, and the Mental and Physical Component scales (PCS/MCS) of the RAND-36. Results: Of the 207 QoL questionnaires, 170 (82.1%) were completed at T3. Both cohorts expressed high satisfaction (' 93%) with their regimens. At T3, no significant group effect was found on any patient-reported outcome measures scores, indicating no QoL difference between the follow-up protocols. Recurrence had developed in 33 patients Conventional follow-up (CFU), 16 [15.5%]; Experimental follow-up (EFU), 17 [16.3%]. Self-examination was the method of detection for 12 ESG patients (70.6%) and 11 CSG patients (68.8%). The melanoma-specific survival was identical. Conclusion: The UK 3-year data were consistent with the previous Dutch report. The reduced follow-up strategy was shown to be safe, with significant resource usage benefits for national cancer services. Patient anxiety levels were not increased by a less-intensive follow-up regimen, and acceptance was high. The study data indicate that patient self-examination is very effective for recurrence detection