基于生物标志物的策略对肿瘤药物研发的影响：对导致美国食品药品监督管理局（FDA）批准的临床试验的荟萃分析。
Impact of a Biomarker-Based Strategy on Oncology Drug Development: A Meta-analysis of Clinical Trials Leading to FDA Approval.
作者信息
Jardim Denis L, Schwaederle Maria, Wei Caimiao, Lee J Jack, Hong David S, Eggermont Alexander M, Schilsky Richard L, Mendelsohn John, Lazar Vladimir, Kurzrock Razelle
机构信息
Department of Clinical Medicine, Hemocentro da Unicamp, University of Campinas, Sao Paulo, Brazil (DLFJ); Department of Clinical Oncology, Hospital Sirio Libanes, Sao Paulo, Brazil (DLFJ); Center for Personalized Cancer Therapy and Division of Hematology and Oncology, University of California, San Diego, CA (MS, RK); Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX (CW, JJL); Department of Investigational Cancer Therapeutics (Phase I Clinical Trials Program), The University of Texas MD Anderson Cancer Center, Houston, TX (DSH); Department of Functional Genomics, Institut Gustave Roussy, University Paris-Sud, Villejuif, France (AME, VL); Worldwide Innovative Network in Personalized Cancer Medicine, Villejuif, France (AME, RLS, JM, VL, RK); American Society of Clinical Oncology, Alexandria, VA (RLS); The University of Texas MD Anderson Cancer Center, Houston, TX (JM).
出版信息
J Natl Cancer Inst. 2015 Sep 15;107(11). doi: 10.1093/jnci/djv253. Print 2015 Nov.
BACKGROUND
In order to ascertain the impact of a biomarker-based (personalized) strategy, we compared outcomes between US Food and Drug Administration (FDA)-approved cancer treatments that were studied with and without such a selection rationale.
METHODS
Anticancer agents newly approved (September 1998 to June 2013) were identified at the Drugs@FDA website. Efficacy, treatment-related mortality, and hazard ratios (HRs) for time-to-event endpoints were analyzed and compared in registration trials for these agents. All statistical tests were two-sided.
RESULTS
Fifty-eight drugs were included (leading to 57 randomized [32% personalized] and 55 nonrandomized trials [47% personalized], n = 38 104 patients). Trials adopting a personalized strategy more often included targeted (100% vs 65%, P < .001), oral (68% vs 35%, P = .001), and single agents (89% vs 71%, P = .04) and more frequently permitted crossover to experimental treatment (67% vs 28%, P = .009). In randomized registration trials (using a random-effects meta-analysis), personalized therapy arms were associated with higher relative response rate ratios (RRRs, compared with their corresponding control arms) (RRRs = 3.82, 95% confidence interval [CI] = 2.51 to 5.82, vs RRRs = 2.08, 95% CI = 1.76 to 2.47, adjusted P = .03), longer PFS (hazard ratio [HR] = 0.41, 95% CI = 0.33 to 0.51, vs HR = 0.59, 95% CI = 0.53 to 0.65, adjusted P < .001) and a non-statistically significantly longer OS (HR = 0.71, 95% CI = 0.61 to 0.83, vs HR = 0.81, 95% CI = 0.77 to 0.85, adjusted P = .07) compared with nonpersonalized trials. Analysis of experimental arms in all 112 registration trials (randomized and nonrandomized) demonstrated that personalized therapy was associated with higher response rate (48%, 95% CI = 42% to 55%, vs 23%, 95% CI = 20% to 27%, P < .001) and longer PFS (median = 8.3, interquartile range [IQR] = 5 vs 5.5 months, IQR = 5, adjusted P = .002) and OS (median = 19.3, IQR = 17 vs 13.5 months, IQR = 8, Adjusted P = .04). A personalized strategy was an independent predictor of better RR, PFS, and OS, as demonstrated by multilinear regression analysis. Treatment-related mortality rate was similar for personalized and nonpersonalized trials.
CONCLUSIONS
A biomarker-based approach was safe and associated with improved efficacy outcomes in FDA-approved anticancer agents.
背景
为了确定基于生物标志物（个性化）策略的影响，我们比较了美国食品药品监督管理局（FDA）批准的癌症治疗药物在有或没有这种选择依据的情况下的研究结果。
方法
在Drugs@FDA网站上识别1998年9月至2013年6月新批准的抗癌药物。对这些药物的注册试验中的疗效、治疗相关死亡率以及事件发生时间终点的风险比（HRs）进行分析和比较。所有统计检验均为双侧检验。
结果
纳入了58种药物（产生57项随机试验[32%为个性化试验]和55项非随机试验[47%为个性化试验]，n = 38104例患者）。采用个性化策略的试验更常纳入靶向药物（100%对65%，P <.001）、口服药物（68%对35%，P =.001）和单一药物（89%对71%，P =.04），并且更频繁地允许交叉接受实验性治疗（67%对28%，P =.009）。在随机注册试验（使用随机效应荟萃分析）中，与非个性化试验相比，个性化治疗组的相对缓解率比值（RRRs，与其相应对照组相比）更高（RRRs = 3.82，95%置信区间[CI] = 2.51至5.82，而非RRRs = 2.08，95% CI = 1.76至2.47，校正P =.03），无进展生存期更长（风险比[HR] = 0.41，95% CI = 0.33至0.51，而非HR = 0.59，95% CI = 0.53至0.65，校正P <.001），总生存期虽无统计学显著差异但也更长（HR = 0.71，95% CI = 0.61至0.83，而非HR = 0.81，95% CI = 0.77至0.85，校正P =.07）。对所有112项注册试验（随机和非随机）的实验组分析表明，个性化治疗与更高的缓解率（48%，95% CI = 42%至55%，而非23%，95% CI = 20%至27%，P <.
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