Development and internal validation of prognostic models for recovery in patients with non-specific neck pain presenting in primary care

Wingbermühle, Roel W.; Chiarotto, Alessandro; Trijffel, Emiel van; Koes, Bart W.; Verhagen, Arianne P.; Heymans, Martijn W.

doi:10.1016/j.physio.2021.05.011

Cited by 3 publications

(8 citation statements)

References 56 publications

(79 reference statements)

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“…Our results show that with the chosen set of predictors, disability is more accurately predicted than pain intensity and EQ-5D. The difference in explained variance between pain intensity and NDI is in keeping with previous studies using pain intensity and disability as outcomes [ 19 , 21 , 22 , 45 ]. One study included a large number of psychological candidate prognostic factors [ 21 ], while another more recent study included a wide selection of biopsychosocial candidate predictors [ 22 ].…”

Section: Discussionsupporting

confidence: 88%

“…The difference in explained variance between pain intensity and NDI is in keeping with previous studies using pain intensity and disability as outcomes [ 19 , 21 , 22 , 45 ]. One study included a large number of psychological candidate prognostic factors [ 21 ], while another more recent study included a wide selection of biopsychosocial candidate predictors [ 22 ]. Hence, it is reasonable to suggest that the consistent differences in performance with different outcomes, is due to measurement properties of the various outcomes.…”

Section: Discussionsupporting

confidence: 88%

“…Although it can be argued that there is an implicit perception that pain intensity is included in the pain patterns (Block 1), we found that pain intensity as a single predictor or when added to the final model only contributes little to prediction, regardless of outcome measure. The association with outcome for the remaining predictors (radiating pain to shoulder and/or elbow, physical leisure activity, MSK pain-sites and education level) were less consistent, in line with previous research on prognostic factors and models for neck pain [ 18 , 20 , 22 ]. Consultation-type has previous proven to be associated with outcome [ 20 ], but not to interact with other predictors [ 20 , 30 ].…”

Section: Discussionsupporting

confidence: 72%

“…Independent of outcome measure, the pain patterns and baseline values of outcomes were the predictors that contributed the most to prediction. Previously, neck pain history (including previous episodes and duration) and future expectations assessed by traditional measures (i.e., numeric scales) have been found to be predictors of GPE, pain and disability [ 17 , 19 , 22 , 30 , 45 ]. These findings support our results on pain history and expectations as consistent prognostic factors.…”

Section: Discussionmentioning

confidence: 99%

“…Few studies have investigated if the predictive performance of prognostic factors or models varies across outcomes representing different health domains [ 19 ]. In existing prognostic model studies, a pre-set of candidate prognostic factors are defined and subsequently for each outcome different prognostic models are developed, and the predictive performance of each model reported [ 21 , 22 ]. Studies rarely explore if predictors included in a model equally predict outcomes that represent different health domains (predictive strength), and how well a model predicts different outcome measures (predictive ability).…”

Section: Introductionmentioning

confidence: 99%

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The association between different outcome measures and prognostic factors in patients with neck pain: a cohort study

Myhrvold

Kongsted

Irgens

et al. 2022

BMC Musculoskelet Disord

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Background Health domains like pain, disability, and health-related quality of life are commonly used outcomes for musculoskeletal disorders. Most prognostic studies include only one outcome, and it is unknown if prognostic factors and models may be generic across different outcomes. The objectives of this study were to examine the correlation among commonly used outcomes for neck pain (pain intensity, disability, and health-related quality of life) and to explore how the predictive performance of a prognostic model differs across commonly used outcomes. Methods We conducted an observational prospective cohort study with data from patients with neck pain aged 18–84 years consulting Norwegian chiropractors. We used three different outcomes: pain intensity (Numeric Pain Rating Scale), the Neck Disability Index (NDI), and health-related quality of Life (EQ-5D). We assessed associations between change in outcome scores at 12-weeks follow-up with Pearson’s correlation coefficient. We used multivariable linear regression models to explore differences in explained variance and relationship between predictors and outcomes. Results The study sample included 1313 patients and 941 (72%) completed follow-up at 12 weeks. The strongest correlation was between NDI and EQ-5D (r = 0.57) while the weakest correlation was between EQ-5D and pain intensity (r = 0.39). The correlation between NDI and pain intensity was moderate (r = 0.53) In the final regression models, the explained variance ranged from adjusted R2 of 0.26 to 0.60, highest with NDI and lowest with pain intensity as outcome. The predictive contributions of the included predictors were similar across outcomes. Among the investigated predictors, pain patterns and the baseline measure of the corresponding outcome measure contributed the most to explained variance across all outcomes. Conclusions The highest correlation was found between NDI and EQ-5D and the lowest with pain intensity. The same prognostic model showed highest predictive performance with NDI as outcome and poorest with pain intensity as outcome. These results suggest that we need more knowledge on the reasons for the differences in predictive performance variation across outcomes.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 72%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The association between different outcome measures and prognostic factors in patients with neck pain: a cohort study

Myhrvold

Kongsted

Irgens

et al. 2022

BMC Musculoskelet Disord

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External validation and updating of prognostic models for predicting recovery of disability in people with (sub)acute neck pain was successful: broad external validation in a new prospective cohort

Wingbermühle¹,

Chiarotto²,

Trijffel³

et al. 2023

Journal of Physiotherapy

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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

et al. 2023

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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.

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Development and internal validation of prognostic models for recovery in patients with non-specific neck pain presenting in primary care

Cited by 3 publications

References 56 publications

The association between different outcome measures and prognostic factors in patients with neck pain: a cohort study

The association between different outcome measures and prognostic factors in patients with neck pain: a cohort study

External validation and updating of prognostic models for predicting recovery of disability in people with (sub)acute neck pain was successful: broad external validation in a new prospective cohort

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

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