School of Pharmacy, BRAC University, Dhaka, Bangladesh.
Cancer Med. 2024 Oct;13(19):e70289. doi: 10.1002/cam4.70289.
We evaluated the validity of surrogacy of progression-free survival (PFS) or time-to-progression (TTP) and overall response rate (ORR) in phase II trials of pancreatic ductal adenocarcinoma (PDAC). In addition, we explored the impact of predictive variables on overall survival (OS) and developed an optimal OS model.
We analyzed 1867 clinical endpoint from 619 phase II PDAC trials with a systematic search from PubMed. Endpoint correlations were determined by Spearman's rank correlation. The assessed predictive factors included PFS/TTP, treatment size, therapy type, stage, and previous treatment. The relationship between predictors and OS was explored by a gamma generalized linear model (GLM) with a log-link function and compared with linear models.
The Spearman rank correlation coefficient between PFS/TTP and OS was 0.88 (95% confidence interval [CI] 0.85-0.89; p < 0.0001; n = 610) and between ORR and OS was 0.58 (0.52-0.64; p < 0.0001; n = 514). Model comparison favored the GLM model over the linear model, offering more accurate predictions for higher OS values. Consequently, PFS/TTP was the strongest predictor (pseudo-R = 0.75), with 1 added median PFS/TTP month associated with 13% (95% CI 13%-14%) increase in median OS. Subgroup analysis revealed that chemotherapy conferred significantly longer OS compared to targeted therapy in 1-Agent and 2-Agent trials, exhibiting a "very large" and "medium" effect size, respectively (rank biserial, r = 0.40 [95% CI 0.22-0.56] and r = 0.29 [0.16-0.41], both p < 0.0001), although inconsistent efficacy in 3-Agent trials (r = 0.12 [-0.07-0.30], p = 0.21).
PFS/TTP is a more reliable surrogate than ORR and a strong predictor of OS in phase II trials of pancreatic cancer. Moreover, gamma GLM (log-link function) is a robust tool for modeling positively skewed survival data with non-constant variance, thus can be applied to other cancers' OS data of such nature.
我们评估了在胰腺导管腺癌（PDAC）的 II 期试验中，无进展生存期（PFS）或进展时间（TTP）和总缓解率（ORR）替代的有效性。此外，我们还探讨了预测变量对总生存期（OS）的影响，并建立了一个最佳 OS 模型。
我们从 PubMed 进行系统搜索，分析了 619 项 PDAC II 期试验中的 1867 项临床终点。通过 Spearman 秩相关系数确定终点相关性。评估的预测因素包括 PFS/TTP、治疗规模、治疗类型、分期和既往治疗。通过对数链接函数的伽马广义线性模型（GLM）探讨了预测因素与 OS 之间的关系，并与线性模型进行了比较。
PFS/TTP 与 OS 之间的 Spearman 秩相关系数为 0.88（95%置信区间 0.85-0.89；p<0.0001；n=610），ORR 与 OS 之间的 Spearman 秩相关系数为 0.58（0.52-0.64；p<0.0001；n=514）。模型比较表明，GLM 模型优于线性模型，可更准确地预测更高的 OS 值。因此，PFS/TTP 是最强的预测因子（伪 R=0.75），1 个中位数 PFS/TTP 月增加与中位数 OS 增加 13%（95%CI 13%-14%）相关。亚组分析显示，与靶向治疗相比，1 药和 2 药化疗在 1 药和 2 药试验中均能显著延长 OS，表现出“非常大”和“中等”的效应大小（秩二项，r=0.40[95%CI 0.22-0.56]和 r=0.29[0.16-0.41]，均 p<0.0001），而 3 药试验中的疗效不一致（r=0.12[-0.07-0.30]，p=0.21）。
在胰腺导管腺癌的 II 期试验中，PFS/TTP 是一种比 ORR 更可靠的替代指标，也是 OS 的有力预测因子。此外，伽马 GLM（对数链接函数）是一种用于建模具有非恒定方差的正偏生存数据的强大工具，因此可应用于其他具有此类性质的癌症 OS 数据。
