PO.CL02.01 · 临床研究
增长最快病灶的生长速率比RECIST 1.1直径总和的生长速率更能预测生存:一项对84例NSCLC患者多线治疗的真实世界回顾性研究
Growth rate of fastest-growing lesion predicts survival better than growth rate of RECIST 1.1 sum of diameters: A real-world retrospective study of 84 NSCLC patients over multiple treatment lines
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摘要 Abstract
中文摘要
背景:多达5个靶病灶的直径总和(SoD)是用于实体瘤疗效评价标准(RECIST)分类的连续性指标。正如许多研究所证明的,基于RECIST的结局(如无进展生存期和缓解率)并不总是与总生存期很好地相关,这就需要探索评估疗效的替代方法,尤其是在新型疗法的背景下。许多研究已将SoD的变化速率与非小细胞肺癌(NSCLC)等实体瘤适应证的总生存期(OS)相关联。为检验患者的生存可能更强烈地受其反应最差或进展最快病灶影响这一假设,我们比较了SoD生长速率与增长最快靶病灶生长速率预测OS的能力。
方法:由一名放射科医生分析了84例在芬兰二级医疗机构接受治疗、基线突变状态各异(N=19例非20外显子EGFR突变、15例ALK重排、5例其他突变、44例无驱动突变)的成年(18岁及以上)III/IV期NSCLC患者的CT扫描,以识别并追踪每位患者多达5个靶病灶的直径。以两种方式分析了每条治疗线最后两次CT扫描的病灶直径(代表224个不同的患者-治疗线:78条一线、63条二线、99条三至六线、4条未知):EGRmax = 靶病灶(带符号的)指数生长速率(EGR)的最大值;EGRSoD = 靶病灶SoD的EGR。随后将EGRmax和EGRSoD值聚类为三个类别:低(L)、中(M)和高(H)。然后进行Kaplan-Meier(KM)和Cox比例风险(CPH)分析,以确定EGRmax或EGRSoD类别与OS的相关性。
结果:聚类分析(独立于OS)得出EGRmax的临界值为:L与M之间为0.06/月,M与H之间为0.25/月(结果为L/M/H类别中N=137/75/12个患者-治疗线),EGRSoD的临界值为:L与M之间为-0.015/月,M与H之间为0.095/月(结果为L/M/H中N=46/151/27个患者-治疗线)。在方向上,KM分析符合预期,较高的EGR与较低的OS相关。然而,KM分析显示EGRmax在L、M、H类别之间呈现一致的分离(中位OS分别为33、17.8和15.4个月),而EGRSoD的KM曲线在L和M之间重叠,仅在H时分离(中位OS分别为19.5、27.7和17个月)。相应地,CPH分析显示EGRmax具有一系列具有统计学意义的风险比(HRs)(M/L为HR = 1.97,H/L为3.28),而EGRSoD仅在H与L之间存在显著差异(M/L为HR = 0.98,H/L为1.99)。
结论:在这一涵盖多线治疗的NSCLC患者人群中,EGRmax似乎是比基于RECIST的EGRSoD更好的OS预测指标。
查看英文原文 English abstract
Background: Sum of Diameters (SoD) of up to 5 target lesions is the continuous metric used for Response Evaluation Criteria In Solid Tumors (RECIST) classifications. As demonstrated in many studies, RECIST based outcomes such as progression free survival and response rate do not always correlate well with overall survival, warranting the need to explore alternative ways of assessing response, particularly in the setting of novel therapies. Many studies have correlated SoD rates of change to overall survival (OS) in solid tumor indications such as non-small cell lung cancer (NSCLC). To test the hypothesis that a patient's survival could be influenced more strongly by their most poorly responding or quickly progressing lesion, we compared the ability of SoD growth rate and the growth rate of the fastest growing target lesion to predict OS.
Methods: CT scans from 84 adult (18+) stage III/IV NSCLC patients with varying baseline mutation status (N=19 non-Exon-20 EGFR mutation, 15 ALK rearrangements, 5 other mutations, 44 No driver mutation), treated in Finland in secondary care setting were analyzed by a radiologist to identify and track the diameters of up to 5 target lesions in each patient. Lesion diameters from the last two CT scans of each treatment line (representing 224 distinct patient-lines of treatment: 78 1 st Line, 63 2 nd Line, 99 3 rd -6 th Line, 4 unknown) were analyzed in two ways: EGRmax = max of the (signed) exponential growth rates (EGR) of target lesions; EGRSoD = EGR of SoD of target lesions. EGRmax and EGRSoD values were then clustered into three categories: low (L), medium (M) and high (H). Kaplan-Meier (KM) and Cox Proportional Hazards (CPH) analyses were then performed to determine the correlation of EGRmax or EGRSoD categories to OS.
Results: Clustering analysis (independent of OS) resulted in EGRmax cutoffs of 0.06/month between L and M and 0.25/month between M and H (resulting in N=137/75/12 patient-lines in L/M/H categories), and EGRSoD cutoffs of -0.015/month between L and M and 0.095/month between M and H (resulting in N=46/151/27 patient-lines in L/M/H). Directionally, the KM analysis was as expected, with higher EGRs correlating with lower OS. However, KM analysis revealed consistent separation between L, M, and H categories for EGRmax (median OS of 33, 17.8 and 15.4 months respectively), while the KM curves for EGRSoD were overlapping for L and M and only separated for H (median OS of 19.5, 27.7, and 17 months respectively). Accordingly, CPH analysis indicated a spread of statistically significant hazard ratios (HRs) for EGRmax (HR = 1.97 for M/L and 3.28 for H/L), while only significant differences between H and L for EGRSoD (HR = 0.98 for M/L and 1.99 for H/L).
Conclusions: In this population of NSCLC patients across several treatment lines, EGRmax appears to be a better predictor of OS than RECIST-based EGRSoD.
利益披露 Disclosure
D. C. Bottino,
Takeda Development Centers America Employment, Stock, Stock Option.
J. Narang,
Takeda Development Center Americas Employment, Stock, Stock Option.
M. Hanley,
Takeda Development Center Americas Employment, Stock, Stock Option.
M. Guzman Castillo,
MedEngine Oy Employment.
H. Loponen,
MedEngine Oy Employment.
R. Kesavuori,
MedEngine Oy Independent Contractor.
Mehilainen Employment.
J. Mehtala,
MedEngine Oy Employment.
M. Lin,
Takeda Development Center Americas Employment, Stock, Stock Option.