Clinical Sciences/Health Conditions
Jordana Barbosa-Silva, PhD
PhD
Hochschule Osnabrück - University of Applied Sciences
Osnabrück, Niedersachsen, Germany
Ana Izabela Oliveira Souza, PhD
PhD
Hochschule Osnabruck - University of Applied Sciences
Osnabrueck, Niedersachsen, Germany
Tiago Pereira, n/a
PhD
University of Oxford
University of Oxford, England, United Kingdom
Javier Muñoz Laguna, n/a
PhD
Epidemiology, Biostatistics and Prevention Institute, University of Zurich
Zürich, Zurich, Switzerland
Nathalie M. Schweyckart, n/a
Master
Epidemiology, Biostatistics and Prevention Institute, University of Zurich
Zürich, Zurich, Switzerland
Dorothea Charlotte Zimmerman, n/a
Master candidate
ZHAW- Zürcher Hochschule für Angewandte Wissenschaften
Winterthur, Zurich, Switzerland
Haliton de Oliveira Junior, n/a
Dr
Health Technology Assessment unit. A Beneficência Portuguesa de São Paulo.
São Paulo, Sao Paulo, Brazil
Henry Dan Kiyomoto, n/a
PhD
Instituto de Pesquisa e Ensino em Avaliação de Tecnologia em Saúde
Porto Alegre, Rio Grande do Sul, Brazil
Clara Gieseke Lopes, n/a
Master candidate
Epidemiology, Biostatistics and Prevention Institute, University of Zurich
Zürich, Zurich, Switzerland
Cesar A Hincapié, n/a
Prof. Dr.
Epidemiology, Biostatistics and Prevention Institute, University of Zurich
Zürich, Zurich, Switzerland
Matthias Schürmann, n/a
PT
University of Zurich
Zurich, Zurich, Switzerland
Nikolaus Ballenberger, n/a
Prof. Dr.
University of Applied Sciences Osnabrück
Osnabrück, Niedersachsen, Germany
Bruno R. Da Costa, n/a
Prof. Dr.
University of Oxford
Oxford, England, United Kingdom
Douglas P Gross, n/a
Prof. Dr.
University of Alberta / Department of Physical Therapy
Edmonton, Alberta, Canada
Susan Armijo-Olivo, PhD
Prof. Dr.
Hochschule Osnabrück - University of Applied Sciences/University of Alberta
Osnabrück, Niedersachsen, Germany
To determine which type or combination of manual therapy (MT) techniques is most likely to be effective in reducing neck pain intensity in patients with chronic neck pain (CNP).
Design:
Network meta-analysis (NMA) of randomized controlled trials (RCTs). Studies included adults with CNP who received MT compared to any other type of treatment/no treatment. Searches were conducted in five different databases, without language or publication date restrictions. Risk of bias was assessed by the revised RoB-2 . The Bayesian random-effects NMA models were used, and treatment effects were summarized as standardized mean differences (SMDs) with 95% credible intervals (95%-CrI). The reference node was "no intervention" with an SMD< 0, favoring MT over "no intervention”. We ranked interventions according to the surface under the cumulative ranking curve (SUCRA, 0-100%, higher values indicating a better overall ranking).
Results: Twenty-nine RCTs (n=2187 participants) were included, mostly high RoB (93%). Twenty nodes were identified and the highest-ranked interventions by SUCRA (90.6%, 88.3%, and 86.7%, respectively) were combination of more than three types of MT (SMD:-0.67; 95%-CrI:-1.93,0.59, based on two trials with 60 participants), self-administered MT (SMD:-0.91;95%-CrI:-2.79, 0.96, based on one trial with 30 participants), and other types of treatment not involving MT (SMD:-0.71; 95%-CrI:-2.08,0.65, based on two trials with 51 participants), each with >85.7% probability of being superior to no treatment. The fourth highest-ranked intervention by SUCRA was the control group (no treatment). A high between-trial heterogeneity (τ²=0.35 (95%-CrI:0.11,0.87)) was found, but no evidence of incoherence was present.
Conclusion: There is a high-uncertainty on the effects. Interventions combining MT techniques, as well as self-administered MT and other non-MT treatments, consistently ranked among the most favorable options. Several MT approaches were not more effective than control. Findings suggest potential benefits of multifaceted MT, but the limited precision and small samples highlight the need for robust trials.