| Literature DB >> 30854085 |
Lian Liu1, Yue Zhang1, Jia Wei1, Zhaoxin Chen1, Jing Yu1.
Abstract
Introduction: To estimate the efficacy and safety of vascular endothelial growth factor receptor tyrosine kinase inhibitors (VEGFR-TKIs) in combination with chemotherapy for patients with advanced non-small cell lung cancer (NSCLC).Entities:
Keywords: VEGFR-TKIs; chemotherapy; efficacy; meta-analysis; non-small cell lung cancer; safety
Year: 2019 PMID: 30854085 PMCID: PMC6400799 DOI: 10.7150/jca.29643
Source DB: PubMed Journal: J Cancer ISSN: 1837-9664 Impact factor: 4.207
Eligible clinical studies for clinical meta-analysis and their characteristics
| Author | Agents | Year | Country | Line of treatment | Phase | Regimens | Number of patients | Median OS (months) | Median PFS (months) | ORR | DCR |
|---|---|---|---|---|---|---|---|---|---|---|---|
| (percentage) | (percentage) | ||||||||||
| Luis Paz-Ares | Sorafenib | 2012 | Spain | First | III | Sorafenib + gemcitabine + cisplatin vs. | 385 | 12.4 | 6 | 27.8 | 62.1 |
| placebo | 387 | 12.5 | 5.5 | 25.8 | 63.1 | ||||||
| (HR 0.98, | (HR 0.83, | ( | ( | ||||||||
| Giorgio Scagliotti | Sorafenib | 2010 | Italy | First | III | Sorafenib + paclitaxel + carboplatin vs. | 464 | 10.7 | 4.6 | ||
| placebo + paclitaxel + carboplatin | 462 | 10.6 | 5.4 | ||||||||
| (HR 1.15, 95% CI 0.94-1.41, | (HR 0.99, 95% CI 0.84-1.16, | ||||||||||
| Yan Wang | Sorafenib | 2011 | China | First | NR | Sorafenib + gemcitabine + cisplatin vs. | 18 | 18 | 5 | 55.6 | 88.9 |
| placebo + gemcitabine + cisplatin | 12 | 18 | 4 | 41.7 | 100 | ||||||
| ( | ( | ( | |||||||||
| Lihong Zhang | Sorafenib | 2014 | China | First | NR | Sorafenib + gemcitabine + cisplatin vs. | 12 | 12.8 | 7.4 | 33.3 | 75 |
| placebo + gemcitabine + cisplatin | 17 | 12.7 | 4.3 | 11.8 | 88.2 | ||||||
| ( | ( | ( | ( | ||||||||
| John V. Heymach | Vandetanib | 2008 | Spain | First | II | Vandetanib + paclitaxel + carboplatin vs. | 56 | 6 | |||
| placebo + paclitaxel + carboplatin | 52 | 5.75 | |||||||||
| (HR 1.15, 95% CI, 0.75-1.77) | (HR 0.76, 95% CI, 0.51-1.14) | ||||||||||
| John V. Heymach | Vandetanib | 2007 | Spain | Second | II | Vandetanib + docetaxel vs. | 42 | 13.1 | 4.7 | ||
| placebo + docetaxel | 41 | 13.4 | 3 | ||||||||
| (HR 0.91, 95% CI, 0.55-1.52, P = 0.0361) | (HR 0.64, 95% CI, 0.38-1.05, P = 0.037) | ||||||||||
| Prof Roy Herbst | Vandetanib | 2011 | USA | Second | III | Vandetanib + docetaxel vs. | 694 | 10.3 | 4 | 17 | |
| docetaxel | 697 | 9.9 | 3.2 | 10 | |||||||
| (HR 0.91, 97.52% CI 0.78-1.07, | (HR 0.79, 97.58% CI 0.70-0.90, | ( | |||||||||
| Richard H. de Boer | Vandetanib | 2011 | Australia | Second | III | Vandetanib + pemetrexed vs. | 256 | 10.5 | 4.1 | 19 | 57 |
| placebo + pemetrexed | 278 | 9.2 | 2.8 | 8 | 46 | ||||||
| (HR 0.86, 97.54% CI 0.65-1.13, | (HR 0.86, 97.58% CI 0.69-1.06, | ( | ( | ||||||||
| Gridelli | Vandetanib | 2014 | Italy | First | II | Vandetanib + gemcitabine vs. | 61 | 8.7 | 6.1 | 15 | 72 |
| placebo + gemcitabine | 63 | 10.2 | 5.6 | 13 | 67 | ||||||
| Martin Reck | Nintedanib | 2014 | Germany | Second | III | Nintedanib + docetaxel vs. | 655 | 10.1 | 3.4 | 35.1 | 73.6 |
| placebo + docetaxel | 659 | 9.1 | 2.7 | 30.1 | 68.3 | ||||||
| (HR 0.94, 95% CI 0.83-1.05, | (HR 0.79, 95% CI 0.68-0.92, | ||||||||||
| Hanna | Nintedanib | 2013 | Germany | Second | III | Nintedanib + pemetrexed vs. | 353 | 4.4 | 9 | 61 | |
| placebo + pemetrexed | 360 | 3.6 | 9 | 53 | |||||||
| (HR 0.83, 95% CI 0.70-0.99) | |||||||||||
| Chandra P Belani | Axitinib | 2014 | USA | First | II | Axitinib + PEM + DDP vs. | 55 | 17 | 8 | 45.5 | |
| PEM + DDP | 57 | 15.9 | 7.1 | 26.3 | |||||||
| (HR 1.05, 95% CI, 0.65-1.69, P = 0.58) | (HR 0.89, 95% CI, 0.56-1.42, P = 0.036) | ||||||||||
| Giorgio Scagliotti | pazopanib | 2013 | Italy | First | II | pazopanib+ PEM + DDP vs. | 62 | 14 | 27 | ||
| PEM + DDP | 35 | 12 | 26 | ||||||||
| (HR 1.22, 95% CI, 0.64-2.33, P = 0.5519) | (HR 0.75, 95% CI, 0.43-1.28, P = 0.2647) | ||||||||||
| S.A. Laurie | cediranib | 2014 | Canada | First | III | cediranib + carboplatin + paclitaxel vs. | 151 | 12.2 | 5.5 | ||
| carboplatin + paclitaxel | 153 | 12.1 | 5.5 | ||||||||
| (HR 0.94, 95% CI, 0.69-1.30, P = 0.72) | (HR 0.91, 95% CI, 0.71-1.18, P = 0.49) | ||||||||||
| Glenwood D. Goss | cediranib | 2010 | Canada | First | II/III | Cediranib + carboplatin + paclitaxel vs. | 126 | 10.5 | 5.6 | ||
| carboplatin + paclitaxel | 125 | 10.1 | 5 | ||||||||
| (HR 0.78, 95% CI, 0.57-1.06, | (HR 0.77, 95% CI, 0.56-1.08, | ||||||||||
| Grace K. Dy | cediranib | 2013 | USA | First | II | Cediranib + carboplatin + gemcitabine vs. | 58 | 12 | 6.3 | 19 | |
| carboplatin + gemcitabine | 29 | 9.9 | 4.5 | 20 | |||||||
| (HR 0.66, 95% CI, 0.41-1.08) | (HR 0.69, 95% CI, 0.43-1.09) | ||||||||||
| Ramalingam | Linifanib | 2015 | USA | First | II | Linifanib + carboplatin + paclitaxel vs. | 44 | 11.4 | 8.3 | 43 | |
| placebo + carboplatin + paclitaxel | 47 | 11.3 | 5.4 | 26 | |||||||
| (HR 1.08) | (HR 0.51) | ||||||||||
| Heist | Sunitinib | 2014 | USA | Second | II | Sunitinib + pemetrexed vs. | 41 | 6.7 | 3.7 | ||
| pemetrexed | 42 | 10.5 | 4.9 | ||||||||
| (HR 2.0, 95% CI, 1.2-3.2) | (HR 1.3, 95% CI, 0.9-2.1) | ||||||||||
| Scagliotti | Motesanib | 2012 | Italy | First | III | Motesanib + carboplatin + paclitaxel vs. | 541 | 13.5 | 5.6 | 39 | |
| placebo + carboplatin + paclitaxel | 549 | 11 | 5.4 | 25 | |||||||
| (HR 0.88, 95% CI, 0.75-1.03) | (HR 0.78, 95% CI, 0.67-0.91) | ||||||||||
| Kubota | Motesanib | 2014 | Japan | First | III | Motesanib + carboplatin + paclitaxel vs. | 110 | 20.9 | 7 | 62 | 91 |
| placebo + carboplatin + paclitaxel | 117 | 14.5 | 5.3 | 27 | 77 | ||||||
| (HR 0.669, 95% CI, 0.473-0.946) | (HR 0.58, 95% CI, 0.42-0.79) |
Abbrevations: OS, overall survival; PFS, progression-free survival; ORR, objective response rate; DCR, disease control rate.
Fig 1Assessment of risk of bias based on the evaluation domains listed in the Cochrane Collaboration Risk of Bias Tool: risk of bias graph (A), risk of bias summary (B).
Fig 2Flowchart of computerized search and the eligible studies included in this systematic review and meta-analysis.
Fig 3Meta-analysis of PFS, OS, ORR and DCR. (A) Change in PFS between VEGFR-TKIs and chemotherapy: fixed-effects model. (B) Change in OS between VEGFR-TKIs and chemotherapy: fixed-effects model. (C) Change in ORR between VEGFR-TKIs and chemotherapy: random-effects model. (D) Change in DCR between VEGFR-TKIs and chemotherapy: fixed-effects model.
Fig 4Meta-analysis of subgroup. (A) Subgroup of first line of treatment on PFS between VEGFR-TKIs and chemotherapy: fixed-effects model. (B) Subgroup of second line of treatment on PFS between VEGFR-TKIs and chemotherapy: fixed-effects model. (C) Subgroup of first line of treatment on OS between VEGFR-TKIs and chemotherapy: fixed-effects model. (D) Subgroup of second line of treatment on OS between VEGFR-TKIs and chemotherapy: fixed-effects model. (E) Subgroup of first line of treatment on ORR between VEGFR-TKIs and chemotherapy: fixed-effects model. (F) Subgroup of second line of treatment on ORR between VEGFR-TKIs and chemotherapy: fixed-effects model. (G) Subgroup of first line of treatment on DCR between VEGFR-TKIs and chemotherapy: random-effects model. (H) Subgroup of second line of treatment on DCR between VEGFR-TKIs and chemotherapy: random-effects model.
Fig 5RR of high grade adverse events in patients with advanced NSCLC treated with VEGFR-TKIs.