Literature search

We searched in Medline, Embase, Cinahl, Web of Science, Cochrane, SportDiscus, OT Seeker and PsychInfo from their inception until February 2019 without limitation on date. An experienced research librarian collaborated in the production of individual search strategies for each of the eight databases (see online supplementary appendix 1).

Eligibility criteria

Risk of bias

Risk of bias was assessed using the Quality in Prognostic Studies (QUIPS) tool.15 On the study level, NP and AR independently rated the 26 included studies and reached consensus on all risk of bias assessments (table 2). Prognostic factors from studies with a high risk of bias, were excluded from figure 1.

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Table 2

Risk of bias in included studies. With the Quality in Prognostic Studies tool studies were assessed on the overall risk of bias within each of the six domains and rated as low, moderate or high risk of bias

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Figure 1

Prognostic factors for persistent musculoskeletal pain, according to pain type, population size, sex, follow-up and the biopsychosocial model.

Reporting of results

We were not able to conduct our a priori planned meta-analysis because of heterogeneity in terms of patient population, setting and time points for follow-up. The evidence on included prognostic factors was reported with ORs, RR and/or p values. As OR and RR may differ in interpretation, we reported them separately. A statistically significant association between a patient characteristic and an outcome was defined as an RR or OR above or below 1 that did not include 1 in the 95% CI. As for p value, a statistically significant association was defined as p<0.05. Average on pain at follow-up was calculated as average of individual studies reporting same musculoskeletal pain type at same follow-up duration (figure 2).

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Figure 2

Persistent musculoskeletal pain, stratified in pain type and follow-up. The included studies investigated pain at follow-up time points ranging from 3 months to 11 years. General musculoskeletal pain (black) persisted in >50% of participants after 1, 2, 3, 4 and 9 years of follow-up.

We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist when writing our report18 (see online supplementary appendix 2).

Supplemental material

[bmjopen-2018-024921supp002.pdf]

Included studies

Figure 3 reports the results of the search strategy. Of the 48 538 titles identified, 41 735 studies were screened, and 26 studies9 11 17 19–41 were included. All included studies were prospective studies. The included studies used a mix of different measures to capture pain at follow-up. Musculoskeletal pain types included in our search were general musculoskeletal pain, neck, back, lower back, lower limb, knee and growing pain. No treatment effect modifiers were identified.

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Figure 3

PRISMA flowchart presenting the flow of citations reviewed in the course of the systematic review. Forty-eight thousand five hundred and thirty-eight articles were identified through search in eight databases, resulting in 223 articles for full-text eligibility screen and a final number of 26 studies for inclusion yielding 111 prognostic factors on musculoskeletal pain.

Extracted data from the included studies: MSK pain type, baseline age, recruitment setting, size of study population, follow-up and percentage of study participants who represented persistent pain at follow-up, both stratified by gender and combined.

Risk of bias

The most common reasons for a moderate or high risk of bias were inadequately described study participation and statistical analyses (n=6, 23%), attrition rates (n=5, 20%) and poor adjustment for confounders (n=11, 42%). Three studies were rated with high risk of bias. With the purpose of filtering the results of prognostic factors, we excluded these studies from the final results depicted in figure 1.

Risk of bias in included studies. With the QUIPS tool studies were assessed on the overall risk of bias within each of the six domains and rated as low, moderate or high risk of bias. Three studies were rated with high risk of bias, and hence excluded from the final results.

Prognosis

Figure 2 highlights the persistence of musculoskeletal pain in all included studies at different follow-up time points and is calculated based on persistent pain at follow-up in table 1. At 1 year follow-up, an average of 54.4% with general musculoskeletal pain, an average of 41.8% with neck pain and 48.8% with knee pain reported pain. At 4-year follow-up, 63.5% with general musculoskeletal pain, 33.5% with neck pain and 26% with low back pain reported pain. At 9-year follow-up, 59% with general musculoskeletal pain reported pain. A complete report of all the identified prognostic factors is listed in online supplementary table 1. Figure 1 depicts the majority of these prognostic factors, stratified by pain type, sex, study population size and follow-up (please see online supplemental table 1 for explanatory notes).

Very few prognostic factors were reported on back pain, growing pain, lower limb pain and widespread musculoskeletal pain (see online supplementary table 1); consequently, they were excluded from figure 1. Table 3 condenses the results from online supplementary table 1 and highlights four prognostic factors on four different musculoskeletal pain types. Below each factor are suggestive questions to provide the general practitioner with insight into the patient’s prognosis. Table 3 and figure 1 can be printed and used by a general practitioner at time of initial consultation with a 0-year-old to 19 year-old patient with musculoskeletal pain.

Please see the online supplementary file-video for an animation showing how our findings can be used in a clinical setting.

Prognostic factors associated with pain at follow-up

A total of 111 prognostic factors were associated with musculoskeletal pain at follow-up, of which most were on general musculoskeletal pain and low back pain (table 3). Online supplementary table 1 includes these results and further detailed depiction of prognostic factors.

Female sex was the most frequently identified prognostic factor associated with musculoskeletal pain at follow-up. Eleven studies identified psychological factors (eg, depression, anxiety and low self-esteem) to be associated with pain at follow-up in seven out of nine musculoskeletal pain types.9 17 19 21 22 25 26 30 35 36 40

Longer pain duration was associated with pain at follow-up across four musculoskeletal pain types: musculoskeletal, low back, knee and back pain.21 23 25 36

Five studies identified sleep-related problems associated with outcome.22 26 30 35 40

Other indicators for musculoskeletal pain at follow-up were increasing age,9 22 27 30 smoking,32 35 parental pain17 23 41 and multisite pain.22 23 40

Figure 1 summarises all identified prognostic factors for musculoskeletal pain at follow-up, stratified by pain type, study population size, sex and follow-up.

Non-significant prognostic factors

We identified a total of 134 patient characteristics across nine musculoskeletal pain types and different follow-up time points with a non-significant association with musculoskeletal pain at follow-up (see online supplementary table 1).

Increasing age11 21 23 28 29 31 36 41 was the most frequently identified baseline factor with a non-significant association to musculoskeletal pain at follow-up. Multiple studies reported non-significant evidence on higher body mass index23 26 28 and hypermobility.11 30 40

Principal findings

Female sex was consistently associated with an increased risk (OR and RR between 1.24 and 3.66) of pain at follow-up across six different musculoskeletal pain types. Depressive symptoms,9 17 19 22 24 26 30 35 36 40 factors related to sleep/daytime tiredness22 26 30 35 40 and parental pain condition17 23 41 were all associated with a higher risk of pain at follow-up. Collectively, the identified studies included prognostic factors across all aspects of the biopsychosocial model, despite a main focus on biological factors. Increasing age was identified as both a significant and a non-significant prognostic factor in the included studies. This conflicting finding reflects the uncertainty surrounding the importance of age as a prognostic factor. A complete overview of strength of associations can be found in online supplementary table 1.

Strengths and limitations in comparison with existing literature

The latest systematic review on prognostic factors for children and adolescents with musculoskeletal pain ended their search in July 2015 which makes for a timely update.12 In addition to adding newer studies, our review differs from the previous with search in more databases, no restriction on publication language and no restriction on pain duration.41 Furthermore, this review is highly updated with a search up to February 2019 and the protocol for this review was developed using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2015 statement (see online supplementary appendix 3). Despite methodology differences, we did not identify additional studies from inception to 2015, but identified three new studies from January 2016 to 2017. These studies added important knowledge of female sex, pain frequency and the prognosis of knee pain and general musculoskeletal pain. Thereby, supporting the previous research. Despite the commonality of children and adolescents with musculoskeletal pain in general practice,6 we did not identify a single study with a population of children or adolescents recruited from general practice.

A previous review on prognostic factors for adults with musculoskeletal pain in primary care was published in 201742 with findings similar to ours, that is, female gender, older age, depression/anxiety and long pain duration were found associated with an increased risk of musculoskeletal pain at follow-up. This suggest that some of the prognostic factors function well across the age range and their use is not isolated to specific age groups.

Explanation of findings and implications for clinical practice

Our findings suggest that females are at higher risk of persistent pain. Previous research highlights potential sex differences in pain responses by assessing pain intensity and threshold and conclude that females display greater sensitivity to multiple pain modalities compared with males.43 Importantly, pain-coping strategies have been found to differ between the sexes.44 45 Females make use of social support, cognitive reinterpretation and positive self-statements, while males use behavioural distraction and problem-focused tactics to manage pain. This could partly explain the sex-difference in prognosis and may open new opportunities for targeted treatment to improve long-term outcomes of young females with musculoskeletal pain.

The current results point towards both modifiable (psychological factors, smoking and peer problems) and non-modifiable (sex, age and pain duration) factors associated with prognosis. Despite time constraints in general practice, most of these factors can be extracted from electronic stored patient data, psychometric tests and examination in a clinical general practice setting.

By asking your patient a few questions at the first consultation of musculoskeletal pain, the general practitioner may improve their understanding of their patients’ risk of pain in the future. In the case of a present, baseline factor with a poor prognosis, for example, smoking among low back pain patients, the general practitioner now both has a scientific reason for and the clinical tool to modulate this factor. By prescribing cessation of smoking, thus, making an effort to improve the outcome for this patient.

Treatment of musculoskeletal pain requires the general practitioner to apply a multifactorial rather than a single-factor approach, hence, including the entire person and their life circumstances when treating patients with pain.16 46 47 Clinicians must be aware of the multifactorial aetiology and consider biological, psychological and social factors of musculoskeletal pain when addressing patient’s coping behaviour and cognitive appraisal.48

Implications for future research

Most of our included studies investigated biological prognostic factors (54 factors). Fewer investigated social (35 factors) and even fewer psychological prognostic factors (22 factors). Future research should include the entire patient, in terms of biological, psychological and social-related components and aim to study these prognostic factors in a general practice setting. There is a dearth of knowledge of how psychosocial factors are associated with prognosis and how general practitioners can harness this information to tailor treatment and information to their patients. Despite the potential importance of pain, ‘who’ the patient is should not be discounted. Geographical location of home, parental pain, profession and income, and social identity in terms of cultural differences, religious beliefs and relations could be important because we know from the biopsychosocial model that social background is important in relation to pain coping.

Only one study did follow-up after 4, 6.5, 9 and 11 years, respectively, which highlights the lack of long-term cohort studies on prognosis and impact of musculoskeletal pain in youth.

Almost one in every two children and adolescents still reported pain even years later.10 11 49 This highlights the importance of prognosis of pain in children and adolescents. Healthcare practitioners should be cognisant not to assume that musculoskeletal pain during childhood or adolescence is transient or self-limiting.