Yu Yishan, Wang Linlin, Cao Shufen, Gao Siming, Wang Weili, Mulvihill Lianne, Machtay Mitchell, Fu Pingfu, Yu Jinming, Kong Feng-Ming Spring
School of Medicine, Shandong University, Jinan, China.
Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Transl Lung Cancer Res. 2020 Dec;9(6):2315-2327. doi: 10.21037/tlcr-20-666.
Few small sample size studies have reported lymphocyte count was prognostic for survival in small-cell lung cancer (SCLC). This study aimed to validate this finding, to build prediction model for overall survival (OS) and to study whether novel models that combine lymphocyte-related variables can predict OS more accurately than a conventional model using clinical factors alone in a large cohort of limited-stage SCLC patients.
This study enrolled 544 limited-stage SCLC patients receiving definitive chemo-radiation with pre-radiotherapy lymphocyte-related variables including absolute lymphocyte count (ALC), platelet-to-lymphocyte ratio (P/L ratio), neutrophil-to-lymphocyte ratio (N/L ratio), and lymphocyte-to-monocyte ratio (L/M ratio). The primary endpoint was OS. These patients were randomly divided into a training dataset (n=274) and a validation dataset (n=270). Multivariate survival models were built in the training dataset, and the performance of these models were further tested in the validation dataset using the concordance index (C-index).
The median follow-up time was 36 months for all patients. In the training dataset, univariate analysis showed that ALC (P=0.020) and P/L ratio (P=0.023) were significantly correlated with OS, while L/M ratio (P=0.091) and N/L ratio (P=0.436) were not. Multivariate modeling demonstrated the significance of ALC (P=0.063) and P/L ratio (P=0.003), and the improvement for OS prediction in combined models with the addition of ALC (C-index =0.693) or P/L ratio (C-index =0.688) over the conventional model (C-index =0.679). The validation dataset analysis confirmed a modest improvement of C-index with the addition of ALC or P/L ratio. All these models showed reasonable discriminations and calibrations.
This study validated the significant value of pre-radiotherapy ALC and P/L ratio on OS in limited-stage SCLC. The combined model with ALC or P/L ratio showed additional OS prediction values than the conventional model with clinical factors alone.
很少有小样本量研究报道淋巴细胞计数对小细胞肺癌(SCLC)的生存具有预后价值。本研究旨在验证这一发现,构建总生存(OS)预测模型,并研究在一大群局限期SCLC患者中,将淋巴细胞相关变量相结合的新模型是否比仅使用临床因素的传统模型能更准确地预测OS。
本研究纳入了544例接受根治性放化疗的局限期SCLC患者,收集放疗前淋巴细胞相关变量,包括绝对淋巴细胞计数(ALC)、血小板与淋巴细胞比值(P/L比值)、中性粒细胞与淋巴细胞比值(N/L比值)以及淋巴细胞与单核细胞比值(L/M比值)。主要终点为OS。这些患者被随机分为训练数据集(n = 274)和验证数据集(n = 270)。在训练数据集中构建多因素生存模型,并在验证数据集中使用一致性指数(C指数)进一步测试这些模型的性能。
所有患者的中位随访时间为36个月。在训练数据集中,单因素分析显示ALC(P = 0.020)和P/L比值(P = 0.023)与OS显著相关,而L/M比值(P = 0.091)和N/L比值(P = 0.436)与OS无关。多因素建模显示ALC(P = 0.063)和P/L比值(P = 0.003)具有显著性,并且在联合模型中加入ALC(C指数 = 0.693)或P/L比值(C指数 = 0.688)后,与传统模型(C指数 = 0.679)相比,OS预测有所改善。验证数据集分析证实,加入ALC或P/L比值后C指数有适度提高。所有这些模型均显示出合理的区分度和校准度。
本研究验证了放疗前ALC和P/L比值对局限期SCLC患者OS的重要价值。与仅包含临床因素的传统模型相比,包含ALC或P/L比值的联合模型显示出额外的OS预测价值。