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Long-term survival of patients with advanced melanoma treated with BRAF-MEK inhibitors.

Melanoma research | 2022

Recent results of patients with advanced melanoma treated with first-line BRAF-MEK inhibitors in clinical trials showed 5-year survival in one-third of patients with a median overall survival (OS) of more than 2 years. This study aimed to investigate these patients' real-world survival and identify the characteristics of long-term survivors. The study population consisted of patients with advanced cutaneous melanoma with a BRAF-V600 mutated tumor who were treated with first-line BRAF-MEK inhibitors between 2013 and 2017. Long-term survival was defined as a minimum OS of 2 years from start therapy. The median progression-free survival (mPFS) and median OS (mOS) of real-world patients ( n  = 435) were respectively 8.0 (95% CI, 6.8-9.4) and 11.7 (95% CI, 10.3-13.5) months. Two-year survival was reached by 28% of the patients, 22% reached 3-year survival and 19% reached 4-year survival. Real-world patients often had brain metastases (41%), stage IV M1c disease (87%), ECOG PS ≥2 (21%), ≥3 organ sites (62%) and elevated LDH of ≥250 U/I (49%). Trial-eligible real-world patients had an mOS of 17.9 months. Patients surviving more than 2 years ( n  = 116) more often had an ECOG PS ≤1 (83%), normal LDH (60%), no brain metastases (60%), no liver metastases (63%) and <3 organ sites (60%). Long-term survival of real-world patients treated with first-line BRAF-MEK inhibitors is significantly lower than that of trial patients, which is probably explained by poorer baseline characteristics of patients treated in daily practice. Long-term survivors generally had more favorable characteristics with regard to age, LDH level and metastatic sites, compared to patients not reaching long-term survival.

Pubmed ID: 35703270 RIS Download

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ggplot2 (tool)

RRID:SCR_014601

Open source software package for statistical programming language R to create plots based on grammar of graphics. Used for data visualization to break up graphs into semantic components such as scales and layers.

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