A study protocol for the validation of a prognostic model with an emphasis on modifiable factors to predict chronic pain after a new episode of acute- or subacute nonspecific idiopathic, non-traumatic neck pain presenting in primary care
A study protocol for the validation of a prognostic model with an emphasis on modifiable factors to predict chronic pain after a new episode of acute- or subacute nonspecific idiopathic, non-traumatic neck pain presenting in primary care
Samenvatting
Background
The primary objective of this study is to identify which modifiable and non-modifiable factors
are independent predictors of the development of chronic pain in patients with acute- or subacute
nonspecific idiopathic, non-traumatic neck pain, and secondly, to combine these to
develop and internally validate a prognostic prediction model.
Methods
A prospective cohort study will be conducted by physiotherapists in 30 primary physiotherapy
practices between January 26, 2020, and August 31, 2022, with a 6-month follow-up
until March 17, 2023. Patients who consult a physiotherapist with a new episode of acute- (0
to 3 weeks) or subacute neck pain (4 to 12 weeks) will complete a baseline questionnaire.
After their first appointment, candidate prognostic variables will be collected from participants
regarding their neck pain symptoms, prior conditions, work-related factors, general
factors, psychological and behavioral factors. Follow-up assessments will be conducted at
six weeks, three months, and six months after the initial assessment. The primary outcome
measure is the Numeric Pain Rating Scale (NPRS) to examine the presence of chronic
pain. If the pain is present at six weeks, three months, and six months with a score of NPRS
�3, it is classified as chronic pain. An initial exploratory analysis will use univariate logistic
regression to assess the relationship between candidate prognostic factors at baseline and
outcome. Multiple logistic regression analyses will be conducted. The discriminative ability
of the prognostic model will be determined based on the Area Under the receiver operating
characteristic Curve (AUC), calibration will be assessed using a calibration plot and formally
tested using the Hosmer and Lemeshow goodness-of-fit test, and model fit will be quantified
as Nagelkerke’s R2. Internal validation will be performed using bootstrapping-resampling to
yield a measure of overfitting and the optimism-corrected AUC.
Discussion
The results of this study will improve the understanding of prognostic and potential protective
factors, which will help clinicians guide their clinical decision making, develop an individualized
treatment approach, and predict chronic neck pain more accurately.
Organisatie | Hogeschool Utrecht |
Afdeling | Kenniscentrum Gezond en Duurzaam Leven |
Lectoraat | Leefstijl en Gezondheid |
Gepubliceerd in | PLoS ONE Vol. 18, Uitgave: 1, Pagina: e0280278 |
Jaar | 2023 |
Type | Artikel |
DOI | 10.1371/journal. |
Taal | Engels |