TY - JOUR
T1 - Mixed treatment comparison meta-analysis of altered fractionated radiotherapy and chemotherapy in head and neck cancer
AU - Blanchard, Pierre
AU - Hill, Catherine
AU - Guihenneuc-Jouyaux, Chantal
AU - Baey, Charlotte
AU - Bourhis, Jean
AU - Pignon, Jean Pierre
N1 - Funding Information:
The authors thank the Meta-Analysis of Chemotherapy on Head and Neck Cancer and Meta-Analysis of Radiotherapy in Carcinomas of the Head and neck Collaborative Groups for the data set. List of investigators are given in Refs. [13] and [14] . They also thank the following institutions for funding the investigators meeting or the meta-analysis projects: Association pour la Recherche sur le Cancer , Ligue Nationale Contre le Cancer , Programme Hospitalier de Recherche Clinique (no. IDF 95009 and 98083 ), and Sanofi-Aventis (unrestricted grants). They thank the Assistance Publique Hôpitaux de Paris for Pierre Blanchard’s Masters Scholarship. They thank Lorna Saint Ange for editing.
PY - 2011/9/1
Y1 - 2011/9/1
N2 - Objective: Different treatments have been investigated in head and neck cancers (HNCs) but not all of them have been appraised using pairwise comparison. This has resulted in failure to directly identify the best treatment with standard methods. Mixed treatment comparison (MTC) meta-analysis allows one to perform simultaneous inference regarding all treatments and select the best among them. Study Design and Setting: We applied MTC models to the Meta-Analyses of Chemotherapy and Radiotherapy in HNC, which pooled individual patient data concerning more than 24,000 patients involved in 102 trials. Fixed- and random-effects models, models with or without consistency factors, possibly adapted to multiarm trials are discussed. Results: Altered fractionated concomitant chemoradiotherapy (AF-CRT) leads to the highest probability of survival in nonmetastatic HNC. The probability that AF-CRT is the best treatment is 94% with random-effects models. There was no relevant inconsistency. When only the most recent trials were selected, AF-CRT and concomitant chemoradiotherapy (CRT) were the two best treatments. AF-CRT remains better than CRT but with a lower posterior probability. Conclusion: MTC is a powerful method for investigating networks of randomized trials. Homogeneity, similarity of trial designs, populations, and the consistency of the network should be thoroughly checked.
AB - Objective: Different treatments have been investigated in head and neck cancers (HNCs) but not all of them have been appraised using pairwise comparison. This has resulted in failure to directly identify the best treatment with standard methods. Mixed treatment comparison (MTC) meta-analysis allows one to perform simultaneous inference regarding all treatments and select the best among them. Study Design and Setting: We applied MTC models to the Meta-Analyses of Chemotherapy and Radiotherapy in HNC, which pooled individual patient data concerning more than 24,000 patients involved in 102 trials. Fixed- and random-effects models, models with or without consistency factors, possibly adapted to multiarm trials are discussed. Results: Altered fractionated concomitant chemoradiotherapy (AF-CRT) leads to the highest probability of survival in nonmetastatic HNC. The probability that AF-CRT is the best treatment is 94% with random-effects models. There was no relevant inconsistency. When only the most recent trials were selected, AF-CRT and concomitant chemoradiotherapy (CRT) were the two best treatments. AF-CRT remains better than CRT but with a lower posterior probability. Conclusion: MTC is a powerful method for investigating networks of randomized trials. Homogeneity, similarity of trial designs, populations, and the consistency of the network should be thoroughly checked.
KW - Chemotherapy
KW - Head and neck cancers
KW - Individual patient data
KW - Meta-analysis
KW - Mixed treatment comparisons
KW - Radiotherapy
UR - http://www.scopus.com/inward/record.url?scp=79960838351&partnerID=8YFLogxK
U2 - 10.1016/j.jclinepi.2010.10.016
DO - 10.1016/j.jclinepi.2010.10.016
M3 - Article
C2 - 21330105
AN - SCOPUS:79960838351
SN - 0895-4356
VL - 64
SP - 985
EP - 992
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
IS - 9
ER -