Clinical and molecular characteristics associated with survival among cancer patients receiving first-line anti-PD-1/PD-L1-based therapies. (17th August 2020)

• Record Type: Journal Article
• Authors: Zhou, Yaojie; Wang, Chengdi; Jiang, Yuting; Ren, Pengwei; Shao, Jun; Tuersun, Paierhati; Li, Weimin
• Is Part Of: Biomarkers. Volume 25:Number 6(2020)
• Page Start: 441
• Page End: 448
• Publication Date: 2020-08-17
• Subjects: Immune checkpoint inhibitors -- biomarker -- PD-1 inhibitor -- PD-L1 inhibitor -- cancer; Biochemical markers -- Periodicals; 610.28
• DOI: 10.1080/1354750X.2020.1794042
• Languages: English
• ISSNs: 1354-750X

Abstract

Abstract: Background: Anti-PD-1/PD-L1-based therapy has emerged recently, and we aimed to figure out the latent value of different clinical and molecular factors to predict the efficacy of immune checkpoint inhibitors (ICIs) therapy compared with non-immunotherapy in the first-line setting. Methods: We assessed the clinical outcomes of 8711 patients in 13 trials receiving anti-PD-1/PD-L1-based therapy or non-immunotherapy as first-line treatment, and different predictors were investigated. Results: Overall, compared with non-immunotherapy, anti-PD-1/PD-L1-based therapy reduced the risk of death by 31% (HR 0.69, 95%CI: 0.60–0.79) for all cancers. Stratified analysis showed that the progression-free survival (PFS) benefit from anti-PD-1/PD-L1-based therapy existed in all three PD-L1 status subgroups (tumour proportion score, TPS ≥50%: HR 0.54, 95%CI: 0.38–0.78; TPS 1–49%: HR 0.56, 95%CI: 0.46–0.68; TPS <1%: HR 0.82, 95%CI: 0.73–0.91; interaction, p < 0.01). ICI therapy also prolonged PFS in males (HR 0.64, 95%CI: 0.50–0.83) and younger patients (HR 0.70, 95%CI: 0.52–0.93), and they might prolong overall survival (OS) in patients without brain metastasis (HR 0.54, 95%CI: 0.41–0.71). Conclusion: PD-L1 expression level alone is imperfect to predict the efficacy of anti-PD-1/PD-L1-based therapies as first-line cancer treatment. Meanwhile, sex, age, and status of brain metastases might also be predictive parameters for the selection of cancer patients.