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Figure.
Pooled Estimates for All Possible Treatment Effects for Each Outcome
Pooled Estimates for All Possible Treatment Effects for Each Outcome

Effect estimates reflect comparison of the treatment in the row heading being compared to the column heading. Overall survival and progression-free survival are presented with hazard ratios. Objective response rate (C) are presented with odds ratios. Numbers in parentheses are 95% credible intervals. Chemo indicates chemotherapy; CTLA-4, cytotoxic T-lymphocyte–associated antigen 4; GM-CSF, granulocyte macrophage colony–stimulating factor; PD-1, programmed cell death protein 1.

1.
Lens  MB, Dawes  M.  Global perspectives of contemporary epidemiological trends of cutaneous malignant melanoma.  Br J Dermatol. 2004;150(2):179-185.PubMedGoogle ScholarCrossref
2.
Little  EG, Eide  MJ.  Update on the current state of melanoma incidence.  Dermatol Clin. 2012;30(3):355-361.PubMedGoogle ScholarCrossref
3.
Survival statistics for melanoma. Toronto, ON: Canadian Cancer Society; 2015 [July 14, 2014]. Available from: http://www.cancer.ca/en/cancer-information/cancer-type/skin-melanoma/prognosis-and-survival/survival-statistics/?region=on.
4.
Grob  JJ, Amonkar  MM, Martin-Algarra  S,  et al.  Patient perception of the benefit of a BRAF inhibitor in metastatic melanoma: quality-of-life analyses of the BREAK-3 study comparing dabrafenib with dacarbazine.  Ann Oncol. 2014;25(7):1428-1436.Google ScholarCrossref
5.
Tsao  H, Goel  V, Wu  H, Yang  G, Haluska  FG.  Genetic interaction between NRAS and BRAF mutations and PTEN/MMAC1 inactivation in melanoma.  J Invest Dermatol. 2004;122(2):337-341.PubMedGoogle ScholarCrossref
6.
Curtin  JA, Fridlyand  J, Kageshita  T,  et al.  Distinct sets of genetic alterations in melanoma.  N Engl J Med. 2005;353(20):2135-2147.PubMedGoogle ScholarCrossref
7.
Davies  H, Bignell  GR, Cox  C,  et al.  Mutations of the BRAF gene in human cancer.  Nature. 2002;417(6892):949-954.PubMedGoogle ScholarCrossref
8.
O’Day  SJ, Hamid  O, Urba  WJ.  Targeting cytotoxic T-lymphocyte antigen-4 (CTLA-4): a novel strategy for the treatment of melanoma and other malignancies.  Cancer. 2007;110(12):2614-2627.PubMedGoogle ScholarCrossref
9.
Topalian  SL, Hodi  FS, Brahmer  JR,  et al.  Safety, activity, and immune correlates of anti-PD-1 antibody in cancer.  N Engl J Med. 2012;366(26):2443-2454.PubMedGoogle ScholarCrossref
10.
Wang  C, Thudium  KB, Han  M,  et al.  In vitro characterization of the anti-PD-1 antibody nivolumab, BMS-936558, and in vivo toxicology in non-human primates.  Cancer Immunol Res. 2014;2(9):846-856.PubMedGoogle ScholarCrossref
11.
Chapman  PBH, Hauschild  A, Robert  C,  et al; BRIM-3 Study Group.  Improved survival with vemurafenib in melanoma with BRAF V600E mutation.  N Engl J Med. 2011;364(26):2507-2516.PubMedGoogle ScholarCrossref
12.
Hauschild  A, Grob  JJ, Demidov  LV,  et al.  Dabrafenib in BRAF-mutated metastatic melanoma: a multicentre, open-label, phase 3 randomised controlled trial.  Lancet. 2012;380(9839):358-365.PubMedGoogle ScholarCrossref
13.
Larkin  J, Ascierto  PA, Dréno  B,  et al.  Combined vemurafenib and cobimetinib in BRAF-mutated melanoma.  N Engl J Med. 2014;371(20):1867-1876.PubMedGoogle ScholarCrossref
14.
Long  GV, Stroyakovskiy  D, Gogas  H,  et al.  Dabrafenib and trametinib vs dabrafenib and placebo for Val600 BRAF-mutant melanoma: a multicentre, double-blind, phase 3 randomised controlled trial.  Lancet. 2015;386(9992):444-451.Google ScholarCrossref
15.
Robert  C, Karaszewska  B, Schachter  J,  et al.  Improved overall survival in melanoma with combined dabrafenib and trametinib.  N Engl J Med. 2015;372(1):30-39.PubMedGoogle ScholarCrossref
16.
Hodi  FSOD, O’Day  SJ, McDermott  DF,  et al.  Improved survival with ipilimumab in patients with metastatic melanoma.  [Erratum appears in N Engl J Med. 2010 Sep 23;363(13):1290].  N Engl J Med. 2010;363(8):711-723.PubMedGoogle ScholarCrossref
17.
Larkin  J, Chiarion-Sileni  V, Gonzalez  R,  et al.  Combined nivolumab and ipilimumab or monotherapy in untreated melanoma.  N Engl J Med. 2015;373(1):23-34.PubMedGoogle ScholarCrossref
18.
Postow  MA, Chesney  J, Pavlick  AC,  et al.  Nivolumab and ipilimumab vs ipilimumab in untreated melanoma.  N Engl J Med. 2015;372(21):2006-2017.Google ScholarCrossref
19.
Ribas  A, Puzanov  I, Dummer  R,  et al.  Pembrolizumab vs investigator-choice chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): a randomised, controlled, phase 2 trial.  Lancet Oncol. 2015;16(8):908-918.Google ScholarCrossref
20.
Robert  C, Thomas  L, Bondarenko  I,  et al.  Ipilimumab plus dacarbazine for previously untreated metastatic melanoma.  N Engl J Med. 2011;364(26):2517-2526.PubMedGoogle ScholarCrossref
21.
Weber  JS, D’Angelo  SP, Minor  D,  et al.  Nivolumab vs chemotherapy in patients with advanced melanoma who progressed after anti-CTLA-4 treatment (CheckMate 037): a randomised, controlled, open-label, phase 3 trial.  Lancet Oncol. 2015;16(4):375-384.Google ScholarCrossref
22.
Larkin  J, Lao  CD, Urba  WJ,  et al.  Efficacy and safety of nivolumab in patients with BRAF V600 mutant and BRAF wild-type advanced melanoma: a pooled analysis of 4 clinical trials.  JAMA Oncol. 2015;1(4):433-440.PubMedGoogle ScholarCrossref
23.
Shahabi  V, Whitney  G, Hamid  O,  et al.  Assessment of association between BRAF-V600E mutation status in melanomas and clinical response to ipilimumab.  Cancer Immunol Immunother. 2012;61(5):733-737.PubMedGoogle ScholarCrossref
24.
Jansen  JP, Crawford  B, Bergman  G, Stam  W.  Bayesian meta-analysis of multiple treatment comparisons: an introduction to mixed treatment comparisons.  Value Health. 2008;11(5):956-964.Google ScholarCrossref
25.
Mills  EJ, Ioannidis  JP, Thorlund  K, Schünemann  HJ, Puhan  MA, Guyatt  GH.  How to use an article reporting a multiple treatment comparison meta-analysis.  JAMA. 2012;308(12):1246-1253.PubMedGoogle ScholarCrossref
26.
Higgins  JPT, Green  S.  Cochrane handbook for systematic reviews of interventions version 5.1. 0. [updated March 2011] The Cochrane Collaboration; 2011.
27.
Wilczynski  NL, McKibbon  KA, Haynes  RB.  Enhancing retrieval of best evidence for health care from bibliographic databases: calibration of the hand search of the literature.  Stud Health Technol Inform. 2001;84(Pt 1):390-393.PubMedGoogle Scholar
28.
NCI Common Terminology Criteria for Adverse Events (CTCAE) v.4 2010 [April 16, 2016]. http://evsnci.nih.gov/ftp1/CTCAE/CTCAE_4.03_2010-06-14_QuickReference_8.5x11.pdf. Accessed September 21, 2016.
29.
Guyot  P, Ades  AE, Ouwens  MJ, Welton  NJ.  Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves.  BMC Med Res Methodol. 2012;12:9.PubMedGoogle ScholarCrossref
30.
Landis  JR, Koch  GG.  The measurement of observer agreement for categorical data.  Biometrics. 1977;33(1):159-174.PubMedGoogle ScholarCrossref
31.
Orwin  RG. Evaluating coding decisions. In: Cooper  H, Hedges  LV, eds.  The Handbook of Research Synthesis. New York, NY: Russell Sage Foundation; 1994:177-200.
32.
Higgins  J. Identifying and addressing inconsistency in network meta-analysis: Cochrane comparing multiple interventions methods group Oxford training event. 2013. http://methods.cochrane.org/cmi/sites/methods.cochrane.org.cmi/files/uploads/S9-L%20Identifying%20and%20addressing%20inconsistency%20in%20network%20meta-analysis.pdf. Accessed September 21, 2016.
33.
Higgins  JP, Thompson  SG.  Quantifying heterogeneity in a meta-analysis.  Stat Med. 2002;21(11):1539-1558.PubMedGoogle ScholarCrossref
34.
Dias  S, Welton  NJ, Caldwell  DM, Ades  AE.  Checking consistency in mixed treatment comparison meta-analysis.  Stat Med. 2010;29(7-8):932-944.PubMedGoogle ScholarCrossref
35.
Salanti  G, Ades  AE, Ioannidis  JP.  Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial.  J Clin Epidemiol. 2011;64(2):163-171.PubMedGoogle ScholarCrossref
36.
Ribas  A, Kefford  R, Marshall  MA,  et al.  Phase III randomized clinical trial comparing tremelimumab with standard-of-care chemotherapy in patients with advanced melanoma.  J Clin Oncol. 2013;31(5):616-622.PubMedGoogle ScholarCrossref
37.
Wolchok  JDH, Hoos  A, O’Day  S,  et al.  Guidelines for the evaluation of immune therapy activity in solid tumors: immune-related response criteria.  Clin Cancer Res. 2009;15(23):7412-7420.PubMedGoogle ScholarCrossref
38.
Ascierto  PA.  Is there still a role for tremelimumab in the treatment of cancer?  Transl Cancer Res. 2013;2(1):48-50.Google Scholar
39.
Gupta  A, Love  S, Schuh  A,  et al.  DOC-MEK: a double-blind randomized phase II trial of docetaxel with or without selumetinib in wild-type BRAF advanced melanoma.  Ann Oncol. 2014;25(5):968-974.PubMedGoogle ScholarCrossref
40.
Hodi  FSL, Lee  S, McDermott  DF,  et al.  Ipilimumab plus sargramostim vs ipilimumab alone for treatment of metastatic melanoma: a randomized clinical trial.  JAMA. 2014;312(17):1744-1753.PubMedGoogle ScholarCrossref
41.
Kirkwood  JM, Bastholt  L, Robert  C,  et al.  Phase II, open-label, randomized trial of the MEK1/2 inhibitor selumetinib as monotherapy versus temozolomide in patients with advanced melanoma.  Clin Cancer Res. 2012;18(2):555-567.PubMedGoogle ScholarCrossref
42.
McArthur  GAC, Chapman  PB, Robert  C,  et al.  Safety and efficacy of vemurafenib in BRAF(V600E) and BRAF(V600K) mutation-positive melanoma (BRIM-3): extended follow-up of a phase 3, randomised, open-label study.  Lancet Oncol. 2014;15(3):323-332.PubMedGoogle ScholarCrossref
43.
Robert  C, Dummer  R, Gutzmer  R,  et al.  Selumetinib plus dacarbazine versus placebo plus dacarbazine as first-line treatment for BRAF-mutant metastatic melanoma: a phase 2 double-blind randomised study.  Lancet Oncol. 2013;14(8):733-740.PubMedGoogle ScholarCrossref
44.
Robert  C, Long  GV, Brady  B,  et al.  Nivolumab in previously untreated melanoma without BRAF mutation.  N Engl J Med. 2015;372(4):320-330.PubMedGoogle ScholarCrossref
45.
Robert  C, Schachter  J, Long  GV,  et al; KEYNOTE-006 investigators.  Pembrolizumab vs Ipilimumab in Advanced Melanoma.  N Engl J Med. 2015;372(26):2521-2532.Google ScholarCrossref
46.
Maio  M, Grob  JJ, Aamdal  S,  et al.  Five-year survival rates for treatment-naive patients with advanced melanoma who received ipilimumab plus dacarbazine in a phase III trial.  J Clin Oncol. 2015;33(10):1191-1196.PubMedGoogle ScholarCrossref
47.
Hatzivassiliou  G, Song  K, Yen  I,  et al.  RAF inhibitors prime wild-type RAF to activate the MAPK pathway and enhance growth.  Nature. 2010;464(7287):431-435.PubMedGoogle ScholarCrossref
48.
Long  GV, Stroyakovskiy  D, Gogas  H,  et al.  Dabrafenib and trametinib versus dabrafenib and placebo for Val600 BRAF-mutant melanoma: a multicentre, double-blind, phase 3 randomised controlled trial.  Lancet. 2015;386(9992):444-451.PubMedGoogle ScholarCrossref
49.
Long  GV, Menzies  AM, Nagrial  AM,  et al.  Prognostic and clinicopathologic associations of oncogenic BRAF in metastatic melanoma.  J Clin Oncol. 2011;29(10):1239-1246.Google ScholarCrossref
50.
von Moos  R, Seifert  B, Simcock  M,  et al.  First-line temozolomide combined with bevacizumab in metastatic melanoma: a multicentre phase II trial (SAKK 50/07).  Ann Oncol. 2012;23(2):531-536.Google ScholarCrossref
51.
Bhatia  P, Friedlander  P, Zakaria  EA, Kandil  E.  Impact of BRAF mutation status in the prognosis of cutaneous melanoma: an area of ongoing research.  Ann Transl Med. 2015;3(2):24.PubMedGoogle Scholar
52.
Atkins  MB, Kunkel  L, Sznol  M, Rosenberg  SA.  High-dose recombinant interleukin-2 therapy in patients with metastatic melanoma: long-term survival update.  Cancer J Sci Am. 2000;6(suppl 1):S11-S14.PubMedGoogle Scholar
53.
Agarwala  SS.  Current systemic therapy for metastatic melanoma.  Expert Rev Anticancer Ther. 2009;9(5):587-595.PubMedGoogle ScholarCrossref
54.
Middleton  MR, Grob  JJ, Aaronson  N,  et al.  Randomized phase III study of temozolomide versus dacarbazine in the treatment of patients with advanced metastatic malignant melanoma.  [Erratum appears in J Clin Oncol 2000 Jun;18(11):2351].  J Clin Oncol. 2000;18(1):158-166.PubMedGoogle ScholarCrossref
55.
National Cancer Institute. Dabrafenib and Trametinib Followed by Ipilimumab and Nivolumab or Ipilimumab and Nivolumab Followed by Dabrafenib and Trametinib in Treating Patients With Stage III-IV BRAFV600 Melanoma. NLM Identifier: NCT02224781. https://clinicaltrials.gov/ct2/show/NCT02224781 Accessed September 21, 2016.
Original Investigation
March 2017

Systemic Therapy for Previously Untreated Advanced BRAF-Mutated MelanomaA Systematic Review and Network Meta-Analysis of Randomized Clinical Trials

Author Affiliations
  • 1Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton , Ontario, Canada
  • 2Department of Oncology, McMaster University, Hamilton, Ontario, Canada
  • 3Father Sean O’Sullivan Research Centre, St Joseph’s Healthcare-Hamilton, Hamilton, Ontario, Canada
 

Copyright 2016 American Medical Association. All Rights Reserved.

JAMA Oncol. 2017;3(3):366-373. doi:10.1001/jamaoncol.2016.4877
Key Points

Question  What is the relative efficacy and safety of systemic therapies for advanced, treatment-naive, BRAF-mutated melanoma?

Findings  In this systematic review and network meta-analysis, BRAF/MEK and programmed cell death protein 1 (PD-1) inhibition were associated with improved overall survival benefit compared with all treatments except cytotoxic T-lymphocyte–associated antigen 4/granulocyte macrophage colony–stimulating factor. There was no significant difference in overall survival between BRAF/MEK and PD-1; BRAF/MEK conferred a significant advantage over all other treatments for progression-free survival; chemotherapy and PD-1 were associated with lowest risk of serious adverse events, with no significant difference in risk between treatments.

Meaning  The favorable efficacy and safety profile of PD-1 inhibitors supports using this option as first-line therapy.

Abstract

Importance  Multiple effective first-line systemic treatment options are available for patients with advanced BRAF-mutated melanoma. A lack of head-to-head randomized clinical trials (RCTs) comparing targeted and immunotherapies leaves uncertainty regarding optimal first-line treatment.

Objective  To estimate the relative efficacy and safety of systemic therapies for advanced, treatment-naive, BRAF-mutated melanoma.

Data Sources  We searched MEDLINE, Embase, and the Cochrane Central Registry of Controlled Trials for phase 2 or 3 RCTs published up until April 29, 2016.

Study Selection  We included RCTs in which at least 1 intervention was a targeted (BRAF or MEK) or an immune checkpoint (cytotoxic T-lymphocyte–associated antigen 4 [CTLA-4] or programmed cell death 1 [PD-1]) inhibitor.

Data Extraction and Synthesis  Two reviewers performed study selection, data abstraction, and risk of bias assessment. We performed a Bayesian network meta-analysis using a fixed-effect model to combine direct comparisons with indirect evidence. We estimated hazard ratios (HRs) for overall survival (OS) and progression-free survival (PFS), and odds ratios (OR) for objective response rate (ORR) and serious adverse events.

Results  Sixteen eligible articles reporting 15 RCTs involving 6662 patients assigned to 1 of 10 treatment strategies were included. Both BRAF/MEK and PD-1 were associated with improved OS benefit compared with all other treatments except CTLA-4/granulocyte macrophage colony-stimulating factor. There was no significant difference in OS between BRAF/MEK and PD-1 (HR, 1.02; 95% credible interval [CrI], 0.72-1.45). The network meta-analysis showed a significant advantage of BRAF/MEK compared with all other treatment strategies for PFS. BRAF/MEK was associated with higher ORR (OR, 2.00; 95% CrI, 1.64-2.45) compared with BRAF alone, with both being superior in achieving ORR compared with other treatments. Chemotherapy and PD-1 were associated with lowest risk of serious adverse events. There was no significant difference in the risk of serious adverse events between chemotherapy and PD-1 (OR, 1.00; 95% CrI, 0.74-1.34).

Conclusions and Relevance  Compared with other treatments, BRAF/MEK and PD-1 inhibition significantly improved OS. The favorable safety profile of PD-1 inhibitors supports using this option as first-line therapy in circumstances where rapid response is not a priority.

Introduction

Cutaneous melanoma is an aggressive and deadly form of skin cancer. Incidence rates of melanoma have rapidly risen over the last 30 years with an annual increase of 3% to 7% worldwide.1,2 Early stage melanoma is often cured with surgery alone; however, most patients presenting with advanced-stage disease are not candidates for surgical resection and thus systemic therapy is the main treatment modality. Prognosis for patients with unresectable or metastatic melanoma is poor, with a 5-year survival rate of 24% to 29% and 10% to 19% for patients with stage IIIC and IV disease, respectively.3 Until recently, treatment options were limited for advanced disease. Multiple developments in understanding the molecular mechanisms of melanoma oncogenesis and immune evasion have revolutionized the standard of care for patients with advanced melanoma.

The mitogen-activated protein (MAP) kinase signaling pathway is an important mediator of cell proliferation and differentiation in melanoma.4,5 Approximately 40% to 60% of cutaneous melanomas harbor a mutation in the BRAF gene that leads to constitutive activation of downstream signaling through the MAP kinase pathway.6,7 In addition, immune checkpoint inhibitors including cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) have been identified as key coregulatory molecules responsible for down-regulation of T-cell activation.8-10

Targeted therapies, including selective BRAF and MEK inhibitors, have drastically improved rates of progression-free survival (PFS) and overall survival (OS) in patients with metastatic melanoma harboring a BRAF V600 mutation.11-15 Immune checkpoint inhibitors have also shown significant benefit over conventional chemotherapies in randomized trials,16-21 regardless of BRAF mutation status.18,22,23 Thus, in the case of advanced BRAF-mutated melanoma, multiple effective first-line treatment options are available. No head-to-head randomized trials of targeted agents and immunotherapies have been conducted, and thus the optimal treatment is unknown. Our aim was to systematically review the literature and determine the relative efficacy and safety of systemic treatment options for advanced BRAF-mutated melanoma in the first-line setting. To obtain the estimates of relative treatment effects for all possible comparisons, we employed a network meta-analysis (NMA) technique, which simultaneously integrates direct evidence from head-to-head trials and indirect evidence (relative treatment effects between 2 treatments derived from a common comparator).24,25

Methods
Literature Search

We conducted this study according to the methods outlined in the Cochrane Handbook for Systematic Reviews of Interventions.26 MEDLINE, EMBASE, and Cochrane Central Registry of Controlled Trials (CENTRAL) were systematically searched from inception up to and including April 29, 2016. Search terms included extensive controlled vocabulary (MeSH and EMTREE) in various combinations, supplemented with keywords including melanoma, targeted therapy, and immunotherapy (eTable 1 in the Supplement). We limited our search to randomized clinical trials (RCTs) by applying a filter developed by the Health Information Research Unit at McMaster University.27 There were no language or date restrictions made. We manually searched the reference lists of included studies and consulted with experts to search for additional studies.

Study Selection

We included phase 2 or 3 RCTs that met the following criteria: (1) the study enrolled treatment-naive adult patients with unresectable lymph node metastasis (American Joint Committee on Cancer [AJCC] TNM Stage IIIC) or distant metastatic (AJCC TNM stage IV) melanoma; (2) at least 1 of the interventions compared in the trial was either a targeted (BRAF or MEK) or an immune checkpoint (CTLA-4 or PD-1) inhibitor; and (3) the study reported on at least 1 of the following outcomes: OS, PFS, objective response rate (ORR), and/or serious adverse events (SAEs) defined as greater than or equal to grade 3 according to the National Cancer Institute Common Terminology Criteria for Adverse Events.28

Although our population of interest is BRAF-mutated melanoma, we did not restrict study eligibility by BRAF mutation status. Targeted therapies (BRAF or MEK inhibitors) have generally been studied in a selected population of patients with tumors harboring the mutation of interest. Immunotherapies (CTLA-4 or PD-1 inhibitors) have been studied either in a mixed population or in a BRAF wild-type population. Based on proven efficacy of immunotherapy in melanoma regardless of BRAF mutation status,18,22,23 these treatments have become important options even for the BRAF-mutated cancers. To generate a comprehensive network of trials comparing all treatment options of current clinical relevance, it was necessary to capture immunotherapy trials. Hence, we were inclusive of trials irrespective of the BRAF mutation status.

Two reviewers (T.D. and O.L.) independently screened titles and abstracts in duplicate, obtained full texts of articles that either reviewer considered potentially eligible, and determined eligibility from the full texts independently and in duplicate. All discrepancies were resolved by consensus or with a third adjudicator (F.X.). Interobserver agreement for the reviewers’ assessments of study eligibility was calculated with the Cohen κ coefficient of agreement.

Data Extraction and Risk of Bias Assessment

The same 2 reviewers used a pilot-tested, standardized form to independently extract information from each eligible study. Data regarding study and population characteristics, as well as treatments and outcomes (PFS, OS, ORR, and SAEs) were abstracted. For PFS and OS, we extracted the hazard ratio (HR) and confidence interval (CI) when available. When HRs and corresponding CIs were not reported, we estimated them by reconstructing individual patient data from published Kaplan-Meier curves with methods described by Guyot and colleagues.29 Authors of included studies were contacted if important data were unclear or not reported. For multiple reports of the same trial, we used longest follow-up data for analysis. Risk of bias of individual studies was assessed independently by the reviewers (T.D. and O.L.) using the Cochrane Collaboration risk-of-bias tool,26 and interrater agreement was calculated by weighted κ.30,31 Any disagreements were resolved by consensus.

Data Synthesis and Analysis

Given the limited number of RCTs for any individual treatment, we categorized therapies by drug class: targeted therapy (BRAF, MEK, combined BRAF and MEK [BRAF/MEK]), immunotherapy (CTLA-4, PD-1, CTLA-4/PD-1), chemotherapy, and combinations of these treatment groups (MEK/CHEMO, CTLA-4/CHEMO, CTLA-4/granulocyte macrophage colony–stimulating factor [GM-CSF]). We synthesized evidence for 4 outcomes: PFS, OS, ORR, and any SAEs. For each outcome, we performed a Bayesian NMA using a Markov Chain Monte Carlo (MCMC) simulation technique with 100 000 iterations in each of the 4 chains. Noninformative priors (ie, N[0, 10000]) were chosen for the effect parameters. The analysis was performed under the fixed-effect model, as only 1 trial provided direct evidence for most of the treatment comparisons. However, a random-effects (RE) model was also performed as sensitivity analysis and model fits were compared using deviance information criteria (DIC).32 In the comparison of any 2 models, we deemed a better fit model if its DIC was less than the DIC of the other model by at least 5. Heterogeneity in the network was assessed with the Cochrane Q (χ2) test and quantified using the I2 statistic within each pairwise comparison when 2 or more trials were available for the comparison.33 Because it was uncommon to have both direct and indirect evidence for most comparisons in our networks, we assumed coherence for our analysis (ie, direct and indirect evidence, when both available for a given comparison, were statistically similar). To test the robustness of this assumption we used the node-splitting method to assess whether there was incoherence in any closed loops.32,34

Relative effects of treatments are reported as HR for survival outcomes (PFS and OS) and odds ratio (OR) for binary outcomes (ORR and SAEs) along with corresponding 95% credible intervals (CrIs), the Bayesian equivalent of 95% CIs. We estimated the overall ranks of treatments by calculating the surface under the cumulative ranking curve (SUCRA) for each.35 The SUCRA index ranges between 0 (or 0%) and 1 (or 100%), where the treatments with highest and lowest SUCRA are considered to be the best and worst treatments, respectively.

We combined different drugs of the same class within a single treatment category, which may have introduced heterogeneity in our NMA. In the trial by Ribas et al,36 tremelimumab, a fully human monoclonal antibody against CTLA-4, did not show significant benefit for OS over chemotherapy. This trial is discordant with results of ipilimumab, a similar CTLA-4-directed molecule. Tremelimumab was administered every 90 days, and based on early progression most patients received only 1 dose.36 At the time, risk of pseudo-progression and immune-related response criteria had not been well established.37 The dosing schedule and early discontinuation of treatment may have limited the benefit of tremelimumab.38 We performed a sensitivity analysis excluding this trial from the network to determine the impact of combining results for both CTLA-4 agents.

Network meta-analysis was performed in WinBUGS software (version 1.4.3, MRC Biostatistics Unit) interfacing through R software.

Results
Study Characteristics

Of the 2546 citations identified through our literature search (1848 after duplicates were removed), 1750 were deemed ineligible after title and abstract screening, leaving 98 studies plus 1 identified from the relevant article search for full-text review (eFigure 1 in the Supplement). Sixteen eligible publications reporting 15 RCTs12-15,17,18,20,36,39-45 were included in the review and NMA (eTable 2 in the Supplement). Overall agreement between the 2 reviewers for final eligibility was excellent (κ = 0.87;, 95% CI, 0.79-0.94).

eTable 2 in the Supplement summarizes the characteristics of the 15 RCTs involving 6662 patients. All studies were multicenter (13 conducted internationally) and published between 2011 and 2015. Five RCTs17,18,20,41,44 focused on both patients with BRAF mutations and wild-type tumors, 2 RCTs39,44 on patients with wild-type tumors only, 6 RCTs12-15,42,43 on patients with BRAF mutations, and 2 trials36,40 did not specify the BRAF status. Ten treatment strategies were compared. No RCTs directly compared immunotherapies with targeted therapies; eFigure 2 in the Supplement provides the network geometries for all 4 outcomes.

Quality of Evidence

The overall risk of bias was low and agreement between reviewers in this assessment was excellent (κ = 0.90; 95% CI, 0.80-0.96). The detailed risk of bias assessment can be found in eFigure 3 in the Supplement. For all outcomes, most of the direct treatment comparisons had only 1 trial providing evidence; hence heterogeneity was not estimable for such comparisons. We found minimal heterogeneity (I2 = 0%) in all direct comparisons with 2 or more trials in the OS and PFS networks. However, heterogeneity was detected for the PD-1/CTLA-4 vs CTLA-4 comparison (I2 = 51%, 2 trials) in the ORR network, and for the BRAF/MEK vs BRAF comparison (I2 = 88%, 2 trials) in the SAEs network. The fit of the fixed-effect model was similar or better than that of RE model in the OS, PFS and ORR networks. Although the RE model was a better fit for the SAEs network, 8 of 9 direct comparisons each had just 1 trial, hence heterogeneity was driven entirely by the comparison of BRAF/MEK vs BRAF from just 2 trials. Therefore, the fixed-effect model was a practical choice for analysis of all outcomes including SAEs.

Overall Survival

Thirteen trials (5361 patients) comparing 9 treatments were included in the OS analysis (eFigure 2A in the Supplement). We obtained extended follow-up (5-year) data of 1 trial20 from a second publication.46 Both BRAF/MEK and PD-1 were associated with improved OS benefit compared with all other treatments except CTLA-4/GM-CSF (key comparisons include BRAF/MEK vs BRAF: HR, 0.69; 95% CrI, 0.59-0.82 and PD-1 vs CTLA-4: HR, 0.58; 95% CrI, 0.47-0.71) (Figure, A). There was no significant difference in OS between BRAF/MEK and PD-1 (HR, 1.02; 95% CrI, 0.72-1.45). The SUCRA values of 92% and 90% for BRAF/MEK and PD-1, respectively, suggested that these were the 2 treatments with the highest chance of improving OS in advanced melanoma (eTable 3 in the Supplement). The sensitivity analysis by removing the Ribas et al36 trial resulted in a ranking order with PD-1 higher than BRAF/MEK, SUCRA of 93% and 84%, respectively. The analysis of this outcome does not include CTLA-4/PD-1 because OS data are awaited from landmark trials.

Progression-Free Survival

Fourteen trials (6738 patients) comparing 10 treatments were included in the PFS analysis (eFigure 2B in the Supplement). The results of NMA showed a significant advantage of BRAF/MEK compared with all other treatment strategies for PFS (Figure, B). Overall, PD-1/CTLA-4 showed a significant improvement in PFS compared with PD-1 alone (HR, 0.75; 95% CrI, 0.62-0.91) and all other treatments except BRAF/MEK (HR, 1.49; 95% CrI, 1.03-2.18). For PFS, BRAF/MEK was most likely the best treatment (SUCRA: 100%), followed by PD-1/CTLA-4 (SUCRA: 87%) and BRAF (SUCRA: 78%), whereas MEK was least likely to be the best treatment strategy (SUCRA: 7%) (eTable 3 in the Supplement).

Objective Response Rate

Thirteen trials (5580 patients) comparing 9 treatment strategies were included in the ORR analysis (eFigure 2C in the Supplement). As shown in Figure, C, BRAF/MEK was associated with a higher ORR compared with BRAF alone (OR, 2.00; 95% CrI, 1.64-2.45); both treatments, however, conferred a significant improvement in ORR compared with all other interventions included in the network (BRAF/MEK vs PD-1/CTLA-4 OR, 0.26; 95% CrI 0.14-0.48). Among the immunotherapies, PD-1/CTLA-4 was associated with higher ORR when compared with PD-1 alone (OR, 1.82; 95% CrI, 1.34-2.47), which in turn was better than CTLA-4 (with or without chemotherapy). The SUCRA analysis suggested that BRAF/MEK is likely the best treatment in achieving an objective response (SUCRA: 100%) followed by BRAF (SUCRA: 87%) and PD-1/CTLA-4 (SUCRA: 75%) (eTable 3 in the Supplement). Sensitivity analysis with the removal of the Ribas et al36 trial did not affect the results of our primary analysis.

Serious Adverse Events

Only 8 trials (4395 patients) comparing 8 treatment strategies reported adverse events of grade 3 or higher (eFigure 2D in the Supplement). Rates of SAEs ranged from 38.4% for chemotherapy to 68.7% for CTLA-4/PD-1 (eTable 4 in the Supplement). As shown in eTable 5 in the Supplement, chemotherapy and PD-1 were associated with lowest risk of SAEs compared with all other treatments. There was no significant difference in the risk of SAEs between chemotherapy and PD-1 (OR, 1.00; 95% CrI, 0.74-1.34). Among the immunotherapies, CTLA-4/PD-1 was associated with higher risk of SAEs compared with CTLA-4 (OR, 1.63; 95% CrI, 1.19-2.26) and PD-1 (OR, 2.99; 95% CrI, 2.18-4.12). Among the targeted therapies, BRAF/MEK was associated with lower risk of SAEs compared with BRAF (OR, 0.84; 95% CrI, 0.66-1.06). The SUCRA analysis suggested that chemotherapy and PD-1 had the lowest risk of SAEs with SUCRA values of 93% (eTable 3 in the Supplement).

Discussion

Until recently, therapeutic options for patients with advanced melanoma were limited, and the prognosis was guarded at best. With the advent of targeted therapies and immune checkpoint inhibitors, the treatment landscape has changed dramatically, complicating decision making for patients and clinicians. In this systematic review and NMA focusing on targeted and immunotherapies for treatment-naive patients with advanced BRAF-mutated melanoma, we found that BRAF/MEK and PD-1 inhibitors showed significant survival benefit over all other treatments with the only exception of CTLA-4/GM-CSF therapy where there was no difference in OS. In our primary and sensitivity analyses of OS, there was no statistically significant difference between BRAF/MEK and PD-1 inhibitors. We therefore conclude that these treatment strategies should be considered equivalent with respect to survival benefit based on current evidence. A caveat in interpreting our analysis is the lack of OS data for CTLA-4/PD-1. The combination immunotherapy shows promise in early outcomes and could change the treatment landscape once longer-term results are published.

Only 1 randomized phase 2 trial addressed CTLA-4/GM-CSF treatment showing an OS benefit with the addition of sargramostim to ipilimumab. There is potential synergy between GM-CSF (which augments antigen presentation) and CTLA4 inhibition (which promotes T-cell proliferation) in immune response. Additionally, reduced toxic effects with the combination compared to CTLA-4 monotherapy likely contributes to improved survival. Further phase 3 evidence will be required to confirm the efficacy of this therapy.40

BRAF/MEK inhibition was most effective with respect to PFS followed by CTLA-4/PD-1 inhibition. Unlike OS, PFS is not influenced by crossover or postprogression therapies. Yet, given the variability in response patterns using immunotherapies,37 PFS may be less robust as an outcome measure in this setting.

Survival benefit must be balanced against risk of toxic effects. In the setting of advanced disease, systemic treatment is noncurative for most, and thus quality of life is a priority. Rates of SAEs were high for all treatment strategies with the exception of PD-1 inhibitors, which showed no increased risk compared with chemotherapy. Among immunotherapies, CTLA-4/PD-1 was associated with a significantly increased risk of toxic effects compared with either monotherapy. Each immune checkpoint inhibitor activates T cells by a unique mechanism, and to see higher rates of immune-related toxic effects is expected with the combination. With respect to targeted therapy, BRAF/MEK was less toxic than BRAF monotherapy. This is consistent with results of primary trials and reflects the BRAF-inhibitor–induced paradoxical activation of the MAP kinase pathway, which causes skin-related toxic effects, including secondary cutaneous malignancy.47,48

Our analysis of ORR showed best results with BRAF/MEK inhibition. This supports first-line use of combination targeted therapy for patients with bulky or highly symptomatic disease, when rapid reduction in tumor volume is necessary to improve health status. This may also influence choice of treatment in the setting of nondisseminated but unresectable disease. Our analysis does not address resection rates following use of systemic treatment, thus clinical significance for locally advanced disease is tentative.

There are several strengths of our study. Our safety analysis helps provide a uniform assessment of risks of toxic effects across treatment categories. An inadequate number of trials (n = 4) reported treatment–related adverse events to provide a meaningful comparison across treatment categories. For a more comprehensive comparison, we analyzed rates of any SAE. Treatment-related adverse event rate is a clinically relevant safety outcome, but the rate of any adverse event is a more conservative and pragmatic metric.

Our analysis is also strengthened by high quality and low risk of bias in the primary trials. Although the included randomized phase 2 trials offer less precise estimates due to smaller sample sizes, these studies allow for a comprehensive overview of the current treatment landscape for patients with advanced melanoma. We considered only treatment-naive patients in an attempt to standardize baseline prognosis. Moreover, inclusion criteria for primary trials were very similar, producing a homogeneous population for the meta-analysis with the exception of the BRAF status of eligible patients. The inclusion of patients with BRAF wild-type tumors receiving immunotherapy is justified by the efficacy of immune checkpoint inhibitors regardless of mutation status.17,18,23 For trials that included a mixed BRAF population, subgroups based on mutation status were often not reported. Had we limited our analysis to patients who were BRAF mutation positive there would be no common reference trial linking targeted and immunotherapies in our network, making comparison impossible. Some reports suggest BRAF mutation may be a negative prognostic indicator.49,50 In our NMA, studies that included BRAF wild-type tumors were predominantly immunotherapy trials. The indirect comparisons could therefore be biased by prognostic differences in study populations. However, evidence regarding the prognostic importance of BRAF status in advanced melanoma is mixed,51 and the influence on our analysis is uncertain.

We classified treatments by mechanism of action. This resulted in a concise network often with multiple trials contributing to a comparison between 2 treatment categories. We feel this is more informative compared with an alternate design in which each drug is considered separately yielding a very sparse network. The inclusion of various drugs within a single network node is a potential source of heterogeneity, although significant heterogeneity was not detected or not assessable for most direct comparisons.

Limitations

Our analysis is limited by sparse networks for all outcomes. Imprecise estimates of treatment effects are likely even when the magnitude of the estimates are important since direct evidence for each network was limited. Most direct comparisons were based on evidence from a single trial, and around three-fourths of all treatment comparisons were derived from indirect evidence alone, which must be considered when making inferences from our study findings. We did not suspect indirectness (related to the question or due to transitivity) because trial populations and study characteristics were very comparable to the target population of our NMA. Indirect evidence for most comparisons was derived from the common comparator of chemotherapy. Chemotherapy dose and frequency was similar in all trials, so it is reasonable to assume transitivity. All networks had an almost star-shaped geometry, and there were no more than 2 closed loops of evidence formed by different independent trials in these networks. The node splitting analysis did not detect incoherence in any closed loop. Publication bias could not be formally assessed due to the small number of trials available for direct comparisons.

Conclusions

Our systematic review and NMA provides the first comparison between targeted therapies and immune checkpoint inhibitors for treatment-naive, BRAF-mutated advanced melanomas. In the absence of a compelling clinical circumstance to guide choice of treatment, it has been unclear which treatment strategy is optimal for patient-important outcomes. Though limited by a sparse network and a lack of OS data for CTLA-4/PD-1, this analysis provides an evidence-based framework to inform clinical decision making. Our results show that OS is best with either PD-1 or combined BRAF/MEK inhibition. The favorable safety profile of PD-1 inhibitors supports using this treatment option as first-line therapy in circumstances where rapid response is not a priority.

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Article Information

Corresponding Author: Feng Xie, PhD, Department of Clinical Epidemiology & Biostatistics, McMaster University, 50 Charlton Ave E, Rm H306 Martha Wing, Hamilton, ON L8N 4A6, Canada (fengxie@mcmaster.ca).

Accepted for Publication: August 30, 2016.

Published Online: October 27, 2016. doi:10.1001/jamaoncol.2016.4877

Author Contributions: Dr Xie and Ms Devji had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Devji, Levine, Xie.

Acquisition, analysis, or interpretation of data: All Authors.

Drafting of the manuscript: Devji, Levine, Neupane.

Critical revision of the manuscript for important intellectual content: All Authors.

Statistical analysis: Devji, Neupane, Beyene, Xie.

Administrative, technical, or material support: Xie.

Study supervision: Devji, Xie.

Conflict of Interest Disclosures: None reported.

References
1.
Lens  MB, Dawes  M.  Global perspectives of contemporary epidemiological trends of cutaneous malignant melanoma.  Br J Dermatol. 2004;150(2):179-185.PubMedGoogle ScholarCrossref
2.
Little  EG, Eide  MJ.  Update on the current state of melanoma incidence.  Dermatol Clin. 2012;30(3):355-361.PubMedGoogle ScholarCrossref
3.
Survival statistics for melanoma. Toronto, ON: Canadian Cancer Society; 2015 [July 14, 2014]. Available from: http://www.cancer.ca/en/cancer-information/cancer-type/skin-melanoma/prognosis-and-survival/survival-statistics/?region=on.
4.
Grob  JJ, Amonkar  MM, Martin-Algarra  S,  et al.  Patient perception of the benefit of a BRAF inhibitor in metastatic melanoma: quality-of-life analyses of the BREAK-3 study comparing dabrafenib with dacarbazine.  Ann Oncol. 2014;25(7):1428-1436.Google ScholarCrossref
5.
Tsao  H, Goel  V, Wu  H, Yang  G, Haluska  FG.  Genetic interaction between NRAS and BRAF mutations and PTEN/MMAC1 inactivation in melanoma.  J Invest Dermatol. 2004;122(2):337-341.PubMedGoogle ScholarCrossref
6.
Curtin  JA, Fridlyand  J, Kageshita  T,  et al.  Distinct sets of genetic alterations in melanoma.  N Engl J Med. 2005;353(20):2135-2147.PubMedGoogle ScholarCrossref
7.
Davies  H, Bignell  GR, Cox  C,  et al.  Mutations of the BRAF gene in human cancer.  Nature. 2002;417(6892):949-954.PubMedGoogle ScholarCrossref
8.
O’Day  SJ, Hamid  O, Urba  WJ.  Targeting cytotoxic T-lymphocyte antigen-4 (CTLA-4): a novel strategy for the treatment of melanoma and other malignancies.  Cancer. 2007;110(12):2614-2627.PubMedGoogle ScholarCrossref
9.
Topalian  SL, Hodi  FS, Brahmer  JR,  et al.  Safety, activity, and immune correlates of anti-PD-1 antibody in cancer.  N Engl J Med. 2012;366(26):2443-2454.PubMedGoogle ScholarCrossref
10.
Wang  C, Thudium  KB, Han  M,  et al.  In vitro characterization of the anti-PD-1 antibody nivolumab, BMS-936558, and in vivo toxicology in non-human primates.  Cancer Immunol Res. 2014;2(9):846-856.PubMedGoogle ScholarCrossref
11.
Chapman  PBH, Hauschild  A, Robert  C,  et al; BRIM-3 Study Group.  Improved survival with vemurafenib in melanoma with BRAF V600E mutation.  N Engl J Med. 2011;364(26):2507-2516.PubMedGoogle ScholarCrossref
12.
Hauschild  A, Grob  JJ, Demidov  LV,  et al.  Dabrafenib in BRAF-mutated metastatic melanoma: a multicentre, open-label, phase 3 randomised controlled trial.  Lancet. 2012;380(9839):358-365.PubMedGoogle ScholarCrossref
13.
Larkin  J, Ascierto  PA, Dréno  B,  et al.  Combined vemurafenib and cobimetinib in BRAF-mutated melanoma.  N Engl J Med. 2014;371(20):1867-1876.PubMedGoogle ScholarCrossref
14.
Long  GV, Stroyakovskiy  D, Gogas  H,  et al.  Dabrafenib and trametinib vs dabrafenib and placebo for Val600 BRAF-mutant melanoma: a multicentre, double-blind, phase 3 randomised controlled trial.  Lancet. 2015;386(9992):444-451.Google ScholarCrossref
15.
Robert  C, Karaszewska  B, Schachter  J,  et al.  Improved overall survival in melanoma with combined dabrafenib and trametinib.  N Engl J Med. 2015;372(1):30-39.PubMedGoogle ScholarCrossref
16.
Hodi  FSOD, O’Day  SJ, McDermott  DF,  et al.  Improved survival with ipilimumab in patients with metastatic melanoma.  [Erratum appears in N Engl J Med. 2010 Sep 23;363(13):1290].  N Engl J Med. 2010;363(8):711-723.PubMedGoogle ScholarCrossref
17.
Larkin  J, Chiarion-Sileni  V, Gonzalez  R,  et al.  Combined nivolumab and ipilimumab or monotherapy in untreated melanoma.  N Engl J Med. 2015;373(1):23-34.PubMedGoogle ScholarCrossref
18.
Postow  MA, Chesney  J, Pavlick  AC,  et al.  Nivolumab and ipilimumab vs ipilimumab in untreated melanoma.  N Engl J Med. 2015;372(21):2006-2017.Google ScholarCrossref
19.
Ribas  A, Puzanov  I, Dummer  R,  et al.  Pembrolizumab vs investigator-choice chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): a randomised, controlled, phase 2 trial.  Lancet Oncol. 2015;16(8):908-918.Google ScholarCrossref
20.
Robert  C, Thomas  L, Bondarenko  I,  et al.  Ipilimumab plus dacarbazine for previously untreated metastatic melanoma.  N Engl J Med. 2011;364(26):2517-2526.PubMedGoogle ScholarCrossref
21.
Weber  JS, D’Angelo  SP, Minor  D,  et al.  Nivolumab vs chemotherapy in patients with advanced melanoma who progressed after anti-CTLA-4 treatment (CheckMate 037): a randomised, controlled, open-label, phase 3 trial.  Lancet Oncol. 2015;16(4):375-384.Google ScholarCrossref
22.
Larkin  J, Lao  CD, Urba  WJ,  et al.  Efficacy and safety of nivolumab in patients with BRAF V600 mutant and BRAF wild-type advanced melanoma: a pooled analysis of 4 clinical trials.  JAMA Oncol. 2015;1(4):433-440.PubMedGoogle ScholarCrossref
23.
Shahabi  V, Whitney  G, Hamid  O,  et al.  Assessment of association between BRAF-V600E mutation status in melanomas and clinical response to ipilimumab.  Cancer Immunol Immunother. 2012;61(5):733-737.PubMedGoogle ScholarCrossref
24.
Jansen  JP, Crawford  B, Bergman  G, Stam  W.  Bayesian meta-analysis of multiple treatment comparisons: an introduction to mixed treatment comparisons.  Value Health. 2008;11(5):956-964.Google ScholarCrossref
25.
Mills  EJ, Ioannidis  JP, Thorlund  K, Schünemann  HJ, Puhan  MA, Guyatt  GH.  How to use an article reporting a multiple treatment comparison meta-analysis.  JAMA. 2012;308(12):1246-1253.PubMedGoogle ScholarCrossref
26.
Higgins  JPT, Green  S.  Cochrane handbook for systematic reviews of interventions version 5.1. 0. [updated March 2011] The Cochrane Collaboration; 2011.
27.
Wilczynski  NL, McKibbon  KA, Haynes  RB.  Enhancing retrieval of best evidence for health care from bibliographic databases: calibration of the hand search of the literature.  Stud Health Technol Inform. 2001;84(Pt 1):390-393.PubMedGoogle Scholar
28.
NCI Common Terminology Criteria for Adverse Events (CTCAE) v.4 2010 [April 16, 2016]. http://evsnci.nih.gov/ftp1/CTCAE/CTCAE_4.03_2010-06-14_QuickReference_8.5x11.pdf. Accessed September 21, 2016.
29.
Guyot  P, Ades  AE, Ouwens  MJ, Welton  NJ.  Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves.  BMC Med Res Methodol. 2012;12:9.PubMedGoogle ScholarCrossref
30.
Landis  JR, Koch  GG.  The measurement of observer agreement for categorical data.  Biometrics. 1977;33(1):159-174.PubMedGoogle ScholarCrossref
31.
Orwin  RG. Evaluating coding decisions. In: Cooper  H, Hedges  LV, eds.  The Handbook of Research Synthesis. New York, NY: Russell Sage Foundation; 1994:177-200.
32.
Higgins  J. Identifying and addressing inconsistency in network meta-analysis: Cochrane comparing multiple interventions methods group Oxford training event. 2013. http://methods.cochrane.org/cmi/sites/methods.cochrane.org.cmi/files/uploads/S9-L%20Identifying%20and%20addressing%20inconsistency%20in%20network%20meta-analysis.pdf. Accessed September 21, 2016.
33.
Higgins  JP, Thompson  SG.  Quantifying heterogeneity in a meta-analysis.  Stat Med. 2002;21(11):1539-1558.PubMedGoogle ScholarCrossref
34.
Dias  S, Welton  NJ, Caldwell  DM, Ades  AE.  Checking consistency in mixed treatment comparison meta-analysis.  Stat Med. 2010;29(7-8):932-944.PubMedGoogle ScholarCrossref
35.
Salanti  G, Ades  AE, Ioannidis  JP.  Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial.  J Clin Epidemiol. 2011;64(2):163-171.PubMedGoogle ScholarCrossref
36.
Ribas  A, Kefford  R, Marshall  MA,  et al.  Phase III randomized clinical trial comparing tremelimumab with standard-of-care chemotherapy in patients with advanced melanoma.  J Clin Oncol. 2013;31(5):616-622.PubMedGoogle ScholarCrossref
37.
Wolchok  JDH, Hoos  A, O’Day  S,  et al.  Guidelines for the evaluation of immune therapy activity in solid tumors: immune-related response criteria.  Clin Cancer Res. 2009;15(23):7412-7420.PubMedGoogle ScholarCrossref
38.
Ascierto  PA.  Is there still a role for tremelimumab in the treatment of cancer?  Transl Cancer Res. 2013;2(1):48-50.Google Scholar
39.
Gupta  A, Love  S, Schuh  A,  et al.  DOC-MEK: a double-blind randomized phase II trial of docetaxel with or without selumetinib in wild-type BRAF advanced melanoma.  Ann Oncol. 2014;25(5):968-974.PubMedGoogle ScholarCrossref
40.
Hodi  FSL, Lee  S, McDermott  DF,  et al.  Ipilimumab plus sargramostim vs ipilimumab alone for treatment of metastatic melanoma: a randomized clinical trial.  JAMA. 2014;312(17):1744-1753.PubMedGoogle ScholarCrossref
41.
Kirkwood  JM, Bastholt  L, Robert  C,  et al.  Phase II, open-label, randomized trial of the MEK1/2 inhibitor selumetinib as monotherapy versus temozolomide in patients with advanced melanoma.  Clin Cancer Res. 2012;18(2):555-567.PubMedGoogle ScholarCrossref
42.
McArthur  GAC, Chapman  PB, Robert  C,  et al.  Safety and efficacy of vemurafenib in BRAF(V600E) and BRAF(V600K) mutation-positive melanoma (BRIM-3): extended follow-up of a phase 3, randomised, open-label study.  Lancet Oncol. 2014;15(3):323-332.PubMedGoogle ScholarCrossref
43.
Robert  C, Dummer  R, Gutzmer  R,  et al.  Selumetinib plus dacarbazine versus placebo plus dacarbazine as first-line treatment for BRAF-mutant metastatic melanoma: a phase 2 double-blind randomised study.  Lancet Oncol. 2013;14(8):733-740.PubMedGoogle ScholarCrossref
44.
Robert  C, Long  GV, Brady  B,  et al.  Nivolumab in previously untreated melanoma without BRAF mutation.  N Engl J Med. 2015;372(4):320-330.PubMedGoogle ScholarCrossref
45.
Robert  C, Schachter  J, Long  GV,  et al; KEYNOTE-006 investigators.  Pembrolizumab vs Ipilimumab in Advanced Melanoma.  N Engl J Med. 2015;372(26):2521-2532.Google ScholarCrossref
46.
Maio  M, Grob  JJ, Aamdal  S,  et al.  Five-year survival rates for treatment-naive patients with advanced melanoma who received ipilimumab plus dacarbazine in a phase III trial.  J Clin Oncol. 2015;33(10):1191-1196.PubMedGoogle ScholarCrossref
47.
Hatzivassiliou  G, Song  K, Yen  I,  et al.  RAF inhibitors prime wild-type RAF to activate the MAPK pathway and enhance growth.  Nature. 2010;464(7287):431-435.PubMedGoogle ScholarCrossref
48.
Long  GV, Stroyakovskiy  D, Gogas  H,  et al.  Dabrafenib and trametinib versus dabrafenib and placebo for Val600 BRAF-mutant melanoma: a multicentre, double-blind, phase 3 randomised controlled trial.  Lancet. 2015;386(9992):444-451.PubMedGoogle ScholarCrossref
49.
Long  GV, Menzies  AM, Nagrial  AM,  et al.  Prognostic and clinicopathologic associations of oncogenic BRAF in metastatic melanoma.  J Clin Oncol. 2011;29(10):1239-1246.Google ScholarCrossref
50.
von Moos  R, Seifert  B, Simcock  M,  et al.  First-line temozolomide combined with bevacizumab in metastatic melanoma: a multicentre phase II trial (SAKK 50/07).  Ann Oncol. 2012;23(2):531-536.Google ScholarCrossref
51.
Bhatia  P, Friedlander  P, Zakaria  EA, Kandil  E.  Impact of BRAF mutation status in the prognosis of cutaneous melanoma: an area of ongoing research.  Ann Transl Med. 2015;3(2):24.PubMedGoogle Scholar
52.
Atkins  MB, Kunkel  L, Sznol  M, Rosenberg  SA.  High-dose recombinant interleukin-2 therapy in patients with metastatic melanoma: long-term survival update.  Cancer J Sci Am. 2000;6(suppl 1):S11-S14.PubMedGoogle Scholar
53.
Agarwala  SS.  Current systemic therapy for metastatic melanoma.  Expert Rev Anticancer Ther. 2009;9(5):587-595.PubMedGoogle ScholarCrossref
54.
Middleton  MR, Grob  JJ, Aaronson  N,  et al.  Randomized phase III study of temozolomide versus dacarbazine in the treatment of patients with advanced metastatic malignant melanoma.  [Erratum appears in J Clin Oncol 2000 Jun;18(11):2351].  J Clin Oncol. 2000;18(1):158-166.PubMedGoogle ScholarCrossref
55.
National Cancer Institute. Dabrafenib and Trametinib Followed by Ipilimumab and Nivolumab or Ipilimumab and Nivolumab Followed by Dabrafenib and Trametinib in Treating Patients With Stage III-IV BRAFV600 Melanoma. NLM Identifier: NCT02224781. https://clinicaltrials.gov/ct2/show/NCT02224781 Accessed September 21, 2016.
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