背景:抗PD-1单药治疗的晚期黑色素瘤患者之间的最佳反应和生存结果差异很大,根据患者从所述治疗中获益的可能性,提供需要对患者进行最佳分层的风险模型。方法:我们对2016年4月至2018年5月在北京大学肿瘤医院接受抗PD-1单药治疗的89例晚期黑色素瘤患者进行了回顾性分析。临床人口统计学特征,基线和早期治疗(抗PD-1单药治疗开始后中位0.6个月)常规实验室变量,包括全血细胞计数和一般化学,在单变量和多变量logistic和Cox比例风险模型中提取并分析最佳反应/生存数据.结果:经过三轮筛查,与PFS较差相关的危险因素包括治疗前中性粒细胞较高,衍生中性粒细胞-淋巴细胞比率(dNLR),低治疗前血红蛋白,和低早期/治疗前的嗜酸性粒细胞的倍数变化;那些有较差的OS包括高治疗前的中性粒细胞,嗜酸性粒细胞,PLT,LDH和中性粒细胞的早期/治疗前倍数变化;最佳反应较差的患者包括高治疗前NLR和早期/治疗前LDH倍数变化.风险模型(量表:低,中位数低,中位数高,和高风险)是基于这些风险因素作为二分变量和M期(与无远处转移)的PFS(HR1.976,95%CI,1.507-2.592,P<0.001),OS(HR2.348,95%CI,1.688-3.266),和无应答者(OR3.586,95%CI,1.668-7.713,P=0.001),分别。对于低的患者,中位数低,中位数高,和发展疾病进展(PD)的高风险,六个月PFS率为64.3%(95%CI,43.5-95.0%),37.5%(95%CI,22.4-62.9%),9.1%(95%CI,3.1-26.7%),0%,分别。对于OS风险低的患者,中位数低,中位数高,高,12个月的OS率为82.5%(95%CI,63.1-100%),76.6%(95%CI,58.4-100%),42.1%(95%CI,26.3-67.3%),和23.9%(95%CI,11.1-51.3%),分别。对于风险低的患者,中位数低,中位数高,作为一个没有反应的人,客观缓解率为50.0%(95%CI,15.7-84.3%),27.8%(95%CI,9.7-53.5%),10.3%(95%CI,2.9-24.2%),0%,分别。结论:基于临床人口统计学特征和易于获得的常规测试的实验室生物标志物的风险评分模型可能有助于亚洲抗PD-1单药治疗晚期黑色素瘤患者的最佳反应和生存结果预测以及个性化治疗决策。
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.