Data_Sheet_1_Risk Models for Advanced Melanoma Patients Under Anti-PD-1 Monotherapy—Ad hoc Analyses of Pooled Data From Two Clinical Trials.docx (40.87 kB)
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Data_Sheet_1_Risk Models for Advanced Melanoma Patients Under Anti-PD-1 Monotherapy—Ad hoc Analyses of Pooled Data From Two Clinical Trials.docx

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posted on 20.05.2021, 15:09 authored by Xue Bai, Jie Dai, Caili Li, Chuanliang Cui, Lili Mao, Xiaoting Wei, Xinan Sheng, Zhihong Chi, Xieqiao Yan, Bixia Tang, Bin Lian, Xuan Wang, Li Zhou, Siming Li, Yan Kong, Zhonghui Qi, Huayan Xu, Rong Duan, Jun Guo, Lu Si

Background: The best response and survival outcomes between advanced melanoma patients treated with the anti-PD-1 monotherapy vary greatly, rendering a risk model in need to optimally stratify patients based on their likelihood to benefit from the said treatment.

Methods: We performed an ad hoc analysis of 89 advanced melanoma patients treated with the anti-PD-1 monotherapy from two prospective clinical trials at the Peking University Cancer Hospital from April 2016 to May 2018. Clinicodemographical characteristics, baseline and early-on-treatment (median 0.6 months after anti-PD-1 monotherapy initiation) routine laboratory variables, including complete blood count and general chemistry, and best response/survival data were extracted and analyzed in both univariate and multivariate logistic and Cox proportional hazard models.

Results: After three rounds of screening, risk factors associated with a poorer PFS included a high pre-treatment neutrophil, derived neutrophil-lymphocyte ratio (dNLR), low pre-treatment hemoglobin, and low early-on-/pre-treatment fold change of eosinophil; those with a poorer OS included a high pre-treatment neutrophil, eosinophil, PLT, early-on/pre-treatment fold change of LDH and neutrophil; and those with a poorer best response included a high pre-treatment NLR and early-on-/pre-treatment LDH fold change. Risk models (scale: low, median-low, median high, and high risk) were established based on these risk factors as dichotomous variables and M stage (with vs. without distant metastasis) for PFS (HR 1.976, 95% CI, 1.507–2.592, P < 0.001), OS (HR 2.348, 95% CI, 1.688–3.266), and non-responder (OR 3.586, 95% CI, 1.668–7.713, P = 0.001), respectively. For patients with low, median-low, median-high, and high risks of developing disease progression (PD), six-month PFS rates were 64.3% (95% CI, 43.5–95.0%), 37.5% (95% CI, 22.4–62.9%), 9.1% (95% CI, 3.1–26.7%), and 0%, respectively. For patients with OS risks of low, median-low, median-high, and high, OS rates at 12 months were 82.5% (95% CI, 63.1–100%), 76.6% (95% CI, 58.4–100%), 42.1% (95% CI, 26.3–67.3%), and 23.9% (95% CI, 11.1–51.3%), respectively. For patients with risks of low, median-low, median-high, and high of being a non-responder, objective response rates were 50.0% (95% CI, 15.7–84.3%), 27.8% (95% CI, 9.7–53.5%), 10.3% (95% CI, 2.9–24.2%), and 0%, respectively.

Conclusion: A risk scoring model based on the clinicodemographical characteristics and easily obtainable routinely tested laboratory biomarkers may facilitate the best response and survival outcome prediction and personalized therapeutic decision making for the anti-PD-1 monotherapy treated advanced melanoma patients in Asia.

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