Maria Schwaederle1, Melissa Zhao1, J Jack Lee2, Vladimir Lazar3, Brian Leyland-Jones4, Richard L Schilsky5, John Mendelsohn6, Razelle Kurzrock7. 1. Center for Personalized Cancer Therapy, Division of Hematology and Oncology, University of California, San Diego. 2. Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston. 3. Worldwide Innovative Network for Personalized Cancer Therapy, Villejuif, France. 4. Avera Cancer Institute, Sioux Falls, South Dakota. 5. Worldwide Innovative Network for Personalized Cancer Therapy, Villejuif, France5American Society of Clinical Oncology, Alexandria, Virginia. 6. Worldwide Innovative Network for Personalized Cancer Therapy, Villejuif, France6Khalifa Institute for Personalized Cancer Therapy, University of Texas MD Anderson Cancer Center, Houston. 7. Center for Personalized Cancer Therapy, Division of Hematology and Oncology, University of California, San Diego3Worldwide Innovative Network for Personalized Cancer Therapy, Villejuif, France.
Abstract
IMPORTANCE: The impact of a biomarker-based (personalized) cancer treatment strategy in the setting of phase 1 clinical trials was analyzed. OBJECTIVE: To compare patient outcomes in phase 1 studies that used a biomarker selection strategy with those that did not. DATA SOURCES: PubMed search of phase 1 cancer drug trials (January 1, 2011, through December 31, 2013). STUDY SELECTION: Studies included trials that evaluated single agents, and reported efficacy end points (at least response rate [RR]). DATA EXTRACTION AND SYNTHESIS: Data were extracted independently by 2 investigators. MAIN OUTCOMES AND MEASURES: Response rate and progression-free survival (PFS) were compared for arms that used a personalized strategy (biomarker selection) vs those that did not. Overall survival was not analyzed owing to insufficient data. RESULTS: A total of 346 studies published in the designated 3-year time period were included in the analysis. Multivariable analysis (meta-regression and weighted multiple regression models) demonstrated that the personalized approach independently correlated with a significantly higher median RR (30.6% [95% CI, 25.0%-36.9%] vs 4.9% [95% CI, 4.2%-5.7%]; P < .001) and a longer median PFS (5.7 [95% CI, 2.6-13.8] vs 2.95 [95% CI, 2.3-3.7] months; P < .001). Targeted therapy arms that used a biomarker-based selection strategy (n = 57 trials) were associated with statistically improved RR compared with targeted therapy arms (n = 177 arms) that did not (31.1% [95% CI, 25.4%-37.4%] vs 5.1% [95% CI, 4.3%-6.0%]; P < .001). Nonpersonalized targeted arms had outcomes comparable with those that tested a cytotoxic agent (median RR, 5.1% [95% CI, 4.3%-6.0%] vs 4.7% [95% CI, 3.6%-6.2%]; P = .63; respectively; median PFS, 3.3 [95% CI, 2.6-4.0] months vs 2.5 [95% CI, 2.0-3.7] months; P = .22). Personalized arms using a "genomic (DNA) biomarker" had higher median RR than those using a "protein biomarker" (42.0% [95% CI, 33.7%-50.9%] vs 22.4% [95% CI, 15.6%-30.9%]; P = .001). The median treatment-related mortality was not statistically different for arms that used a personalized strategy vs not (1.89% [95% CI, 1.36%-2.61%] vs 2.27% [95% CI, 1.97%-2.62%]; P = .31). CONCLUSIONS AND RELEVANCE: In this meta-analysis, most phase 1 trials of targeted agents did not use a biomarker-based selection strategy. However, use of a biomarker-based approach was associated with significantly improved outcomes (RR and PFS). Response rates were significantly higher with genomic vs protein biomarkers. Studies that used targeted agents without a biomarker had negligible response rates.
IMPORTANCE: The impact of a biomarker-based (personalized) cancer treatment strategy in the setting of phase 1 clinical trials was analyzed. OBJECTIVE: To compare patient outcomes in phase 1 studies that used a biomarker selection strategy with those that did not. DATA SOURCES: PubMed search of phase 1 cancer drug trials (January 1, 2011, through December 31, 2013). STUDY SELECTION: Studies included trials that evaluated single agents, and reported efficacy end points (at least response rate [RR]). DATA EXTRACTION AND SYNTHESIS: Data were extracted independently by 2 investigators. MAIN OUTCOMES AND MEASURES: Response rate and progression-free survival (PFS) were compared for arms that used a personalized strategy (biomarker selection) vs those that did not. Overall survival was not analyzed owing to insufficient data. RESULTS: A total of 346 studies published in the designated 3-year time period were included in the analysis. Multivariable analysis (meta-regression and weighted multiple regression models) demonstrated that the personalized approach independently correlated with a significantly higher median RR (30.6% [95% CI, 25.0%-36.9%] vs 4.9% [95% CI, 4.2%-5.7%]; P < .001) and a longer median PFS (5.7 [95% CI, 2.6-13.8] vs 2.95 [95% CI, 2.3-3.7] months; P < .001). Targeted therapy arms that used a biomarker-based selection strategy (n = 57 trials) were associated with statistically improved RR compared with targeted therapy arms (n = 177 arms) that did not (31.1% [95% CI, 25.4%-37.4%] vs 5.1% [95% CI, 4.3%-6.0%]; P < .001). Nonpersonalized targeted arms had outcomes comparable with those that tested a cytotoxic agent (median RR, 5.1% [95% CI, 4.3%-6.0%] vs 4.7% [95% CI, 3.6%-6.2%]; P = .63; respectively; median PFS, 3.3 [95% CI, 2.6-4.0] months vs 2.5 [95% CI, 2.0-3.7] months; P = .22). Personalized arms using a "genomic (DNA) biomarker" had higher median RR than those using a "protein biomarker" (42.0% [95% CI, 33.7%-50.9%] vs 22.4% [95% CI, 15.6%-30.9%]; P = .001). The median treatment-related mortality was not statistically different for arms that used a personalized strategy vs not (1.89% [95% CI, 1.36%-2.61%] vs 2.27% [95% CI, 1.97%-2.62%]; P = .31). CONCLUSIONS AND RELEVANCE: In this meta-analysis, most phase 1 trials of targeted agents did not use a biomarker-based selection strategy. However, use of a biomarker-based approach was associated with significantly improved outcomes (RR and PFS). Response rates were significantly higher with genomic vs protein biomarkers. Studies that used targeted agents without a biomarker had negligible response rates.
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