A practical approach to predict expansion of evidence networks: a case study in treatment-naive advanced melanoma
A practical approach to predict expansion of evidence networks: a case study in treatment-naive advanced melanoma
Network meta-analysis (NMA) is a statistical method used to produce comparable estimates of efficacy across a range of treatments that may not be compared directly within any single trial. NMA feasibility is determined by the comparability of the data and presence of a connected network. In rapidly evolving treatment landscapes, evidence networks can change substantially in a short period of time. We investigate methods to determine the optimum time to conduct or update a NMA based on anticipated available evidence. We report the results of a systematic review conducted in treatment-naive advanced melanoma and compare networks of evidence available at retrospective, current, and prospective time points. For included publications, we compared the primary completion date of trials from clinical trials registries (CTRs) with the date of their first available publication to provide an estimate of publication lag. Using CTRs we were able to produce anticipated networks for future time points based on projected study completion dates and average publication lags which illustrated expansion and strengthening of the initial network. We found that over a snapshot of periods between 2015 and 2018, evidence networks in melanoma changed substantively, adding new comparators and increasing network connectedness. Searching CTRs for ongoing trials demonstrates it is possible to anticipate future networks at a certain time point. Armed with this information, sensible decisions can be made over when best to conduct or update a NMA. Incorporating new and upcoming interventions in a NMA enables presentation of a complete, up-to-date and evolving picture of the evidence.
Antineoplastic Agents/therapeutic use, Clinical Trials as Topic, Decision Support Techniques, Drug Therapy, Combination, Humans, Melanoma/drug therapy, Network Meta-Analysis, Prognosis, Research Design, Survival Rate
13-18
Halfpenny, Nicholas J A
b22ef50d-d9ae-4c2a-9b1a-973a5e98ab26
Scott, David A
19b5fd34-9974-4ae4-8be0-27a693639e20
Thompson, Juliette C
28a24d4b-8b21-436c-85db-0b6608c46a09
Gurung, Binu
580a65b4-2a5b-4918-9e77-bb18bec325bb
Quigley, Joan M
473a7cea-23e7-4d40-ac5c-e6c3060b5f0f
February 2019
Halfpenny, Nicholas J A
b22ef50d-d9ae-4c2a-9b1a-973a5e98ab26
Scott, David A
19b5fd34-9974-4ae4-8be0-27a693639e20
Thompson, Juliette C
28a24d4b-8b21-436c-85db-0b6608c46a09
Gurung, Binu
580a65b4-2a5b-4918-9e77-bb18bec325bb
Quigley, Joan M
473a7cea-23e7-4d40-ac5c-e6c3060b5f0f
Halfpenny, Nicholas J A, Scott, David A, Thompson, Juliette C, Gurung, Binu and Quigley, Joan M
(2019)
A practical approach to predict expansion of evidence networks: a case study in treatment-naive advanced melanoma.
Melanoma Research, 29 (1), .
(doi:10.1097/CMR.0000000000000513).
Abstract
Network meta-analysis (NMA) is a statistical method used to produce comparable estimates of efficacy across a range of treatments that may not be compared directly within any single trial. NMA feasibility is determined by the comparability of the data and presence of a connected network. In rapidly evolving treatment landscapes, evidence networks can change substantially in a short period of time. We investigate methods to determine the optimum time to conduct or update a NMA based on anticipated available evidence. We report the results of a systematic review conducted in treatment-naive advanced melanoma and compare networks of evidence available at retrospective, current, and prospective time points. For included publications, we compared the primary completion date of trials from clinical trials registries (CTRs) with the date of their first available publication to provide an estimate of publication lag. Using CTRs we were able to produce anticipated networks for future time points based on projected study completion dates and average publication lags which illustrated expansion and strengthening of the initial network. We found that over a snapshot of periods between 2015 and 2018, evidence networks in melanoma changed substantively, adding new comparators and increasing network connectedness. Searching CTRs for ongoing trials demonstrates it is possible to anticipate future networks at a certain time point. Armed with this information, sensible decisions can be made over when best to conduct or update a NMA. Incorporating new and upcoming interventions in a NMA enables presentation of a complete, up-to-date and evolving picture of the evidence.
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Published date: February 2019
Keywords:
Antineoplastic Agents/therapeutic use, Clinical Trials as Topic, Decision Support Techniques, Drug Therapy, Combination, Humans, Melanoma/drug therapy, Network Meta-Analysis, Prognosis, Research Design, Survival Rate
Identifiers
Local EPrints ID: 440866
URI: http://eprints.soton.ac.uk/id/eprint/440866
ISSN: 0960-8931
PURE UUID: 29c82e03-4387-4fd1-86f5-627124b02c0c
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Date deposited: 21 May 2020 16:30
Last modified: 17 Mar 2024 04:02
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Contributors
Author:
Nicholas J A Halfpenny
Author:
David A Scott
Author:
Juliette C Thompson
Author:
Binu Gurung
Author:
Joan M Quigley
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