Comparison with other studies
59.5% of the sickness absentees achieved s-WPS within two-year follow up, which is indicative of a population with a high level of work disability. In a large study of neck and back pain [
31], only 8% reported sick leave the previous year when asked at 3-year follow up. The study [
31] was conducted in a workplace setting, hence, study participants were presumably less disabled than those referred to secondary care settings as in the current study. From secondary care settings however, previous studies [
7,
32] have also found what seemed to be better work outcomes than in the current study. In a study of low back pain, 72% achieved RTW within 1 year; however RTW was defined as 4 consecutive weeks of work [
7]. In another study of primarily musculoskeletal pain, 60 % achieved had a more sustainable RTW outcome at 1 year follow up, namely 3 consecutive months with increased working time compared to baseline [
32]. The study population of this study [
32] was comprised of sickness absentees referred to a secondary care setting like ours. Hence, we consider the similarity of work outcomes to be indicative of work disability that hampers work participation.
A comprehensive literature search strategy adapted from a 2017 review [
2] was performed using Medline and yet, no studies were identified which categorized prognostic variables and used an analytical approach resembling the order of information obtained in a clinical setting. For this reason, direct comparison with previous studies was not possible, but some studies reported measures that can be compared with the current study [
33,
34]. In a Norwegian study [
33], the sickness absentees’ own prediction of sick leave duration ≥26 weeks yielded a slightly better PPV (0.78) than any of the models in the current study. However, the sensitivity based on self-prediction was 0.28 and the sensitivity based on dedicated medical consultants was 0.07. Both measures are notably lower than the sensitivity estimates of the current study suggesting that 1) perhaps the sickness absentees in Fleten et al.’s study were over-optimistic, leading to a low sensitivity of self-prediction, and 2) the information that was available to the medical consultants [
33] was inadequate to result in a sensitivity as high as in the current study.
Rehabilitation professionals in another study [
34] predicted the chance of RTW based on sick leave duration, reason for sick leave, unemployment, age > 45 years, female sex and ‘gut feeling’. Their prediction was concordant with actual RTW in 73% and thus lower than the specificity estimates of all four models in the current study. Of interest is that the rehabilitation professionals in that study [
34] had access to some similar information as was available in the current study, namely sex and sick leave duration. But in spite of their access to further information about reason for sick leave, unemployment, age > 45 and “gut feeling”, specificity estimates similar to the current study were not achieved.
Regarding the association between sex and work outcomes, results in previous studies have been conflicting. In a population-based study [
35] and in studies from secondary care on spinal pain [
36] and shoulder pain [
37], sex was not associated with work outcomes, while a primary care study [
28] did find predictive value of sex. In summary, reviews have found conflicting evidence on the impact of sex on work outcomes [
1,
3,
28,
35‐
37] and with this in mind, the current study’s estimates in Model 1 based on sex alone are not surprising.
The impact of sick leave duration corroborates the findings in numerous reviews [
1,
3,
8,
38,
39] and cohort studies of both shoulder pain, spinal pain and whiplash trauma [
28,
40,
41]. Due to the non-modifiable nature of sick leave duration, our findings highlight the need for action that prevents and/or addresses sick leave early enough to minimize the duration.
The ÖMPSQ score covers psychosocial risk factors of work disability (e.g. feelings of anxiety or depression and self-perceived chances of returning to work in 6 months). The negative association between the ÖMPSQ score and s-WPS is in line with previous findings [
21,
42]. While studies from primary care settings and workplaces [
43,
44] have suggested ÖMPSQ cut-off values of 90 and 105, the current study suggests that in a secondary care setting, ÖMPSQ has important properties regarding prognosis of work participation also as a discrete variable.
Interestingly, a study of primarily chronic spinal pain suggested cut-offs of 90 and 105 [
44] but did not yield sensitivity and specificity measures that were concurrently as high as any of the models including ÖMPSQ in the current study. In contrast, a primary care study of patients with acute or sub-acute spinal pain [
43], a cut-off of 90 yielded better sensitivity and slightly lower specificity [
43], thereby demonstrating the properties of ÖMPSQ in early detection of poor work prognosis.
The negative association between ongoing workers’ compensation claim and s-WPS is in line with the findings of a previous Danish study of patients with neck/arm pain or back/leg pain [
4].
In the context of clinical variables, a cohort study on low back pain [
45] found a crude association between tender points count (discrete variable) and unsuccessful RTW. However, this was not maintained in the multivariable model. Moreover, no association was found between radiculopathy and work outcomes [
45], which was supported by a review presenting moderate evidence for no association between radiating pain and RTW [
2]. Therefore, our finding of the limited improvement of predictive values in Model 3 is in line with these previous findings [
2,
45].
Finally, regarding MRI, only one study was identified which explored the association between MRI findings and work outcomes [
7]. In this study of sickness absentees with low back pain, the presence of Modic type 1 changes was associated with unsuccessful RTW. Unfortunately, we were unable to assess the impact of Modic changes in the current study since the inter- and intra-rater reliability for this pathology was not established owing to too low prevalences [
27].
Strengths
First, the use of registry data for the outcome assessment ensured 100% follow up thereby reducing the risk of attrition bias. Second, the use of registry data reduced the risk of measurement bias since the outcome assessment was unaffected by knowledge of the prognostic variables. Likewise, the assessment of prognostic factors was unaffected by knowledge of the outcome. Third, the risk of attrition bias was minimized by the low number of missing values for the majority of variables (demographic, patient-reported and clinical variables). Only for MRI was the number of missing values substantial. However, the distribution between exposure and outcome was assessed for all the variables in Table
1, which revealed that attrition was not skewed for any of the variables, hence attrition bias was not suspected (data not shown). Fourth, the duration of follow up reaching 2 years constitutes a realistic long-term outcome. A fifth strength is the a priori decision to take an analytical approach resembling the working conditions of the clinicians who are responsible for appraisal of work prognosis. This reduced the risk of purely data-driven results. Sixth, the risk of bias owing to potential misclassification of MRI findings was minimal owing to high levels of observed agreement for kyphosis and spinal canal stenosis [
27]. Finally, when bearing in mind the well-established impact of external societal factors on the process of sick leave [
47,
48], it is a further strength of the current study that the Danish legislation on sickness benefits did not undergo major changes from 2009 to 2014. A change in legislation in 2014 reduced the right for sickness benefits from 52 to 22 weeks. It affected only six sickness absentees (four achieved s-WPS and two did not) and is thus not suspected to bias the estimates.
Limitations
First, since the study population was originally included in an RCT, the results may not be generalizable to all sickness absentees with neck or shoulder pain. The possibility of sampling bias due to referral patterns of the general practitioners cannot be refuted nor elucidated. Hence, the results are expected to be representative of sickness absentees with neck or shoulder pain who are seen in a secondary care setting. Generalizability to primary care settings should be made with caution and confirmatory studies including all sickness absentees with neck or shoulder pain would be needed to improve generalizability.
Second, the representativeness of the results should be considered in the light of the above-mentioned change in legislation, implying that the right to sickness benefits is now limited to 22 weeks compared with 52 weeks during most of the study. Confirmatory studies would be desirable to assess the impact of this change in legislation. But given that the literature over the past decades is corroborated (i.e. major impact of sick leave duration and psychosocial factors [
49]), we expect that similar results would be found.
Third, the limited MRI sample affects precision of the estimates; an issue that was further attenuated for certain MRI variables (disc bulge/protrusion/extrusion, neural foraminal stenosis, zygapophyseal osteoarthritis and uncovertebral osteoarthritis). For these variables, the available sequences did not allow for evaluation on all 97 MRIs (Table
1 and [
27]). Had MRI been available for the entire cohort, confidence intervals for MRI variables would have been narrowed down.
Fourth, the use of registry data is usually an advantage, but the data source also warrants consideration since registration procedures imply a risk of unequal registration of short-term sick leave. Sick leave registration in DREAM begins at the end of the employer paid period and backward adjustments are made, so that the number of sickness benefit weeks in DREAM equal the total number of sick leave weeks. Since registration is initiated at the end of the employer paid period, multiple absences due to sick leave lasting only days or a few weeks are usually not registered (because they are within the employer-paid period). In the current study, some participants may have been misclassified as having achieved s-WPS although they had multiple short-term absences due to sick leave. A related problem applies to employees with a §56-agreement, i.e. their employers are entitled to reimbursement of sickness benefits from day one; such employees may be misclassified as u-WPS in the current study due to sick leave registrations exceeding actual duration. These possible misclassifications are considered non-differentiated since they are not suspected to be associated with the exposure (i.e. the prognostic variables). Unfortunately, the data do not offer any insight as to the possible distribution of §56-agreements in the current study. However, explorative post-hoc analyses were performed in which single weeks of sickness benefit reimbursement were considered as §56-agreements, i.e. regarded as working weeks. This resulted in the distribution of s-WPS/u-WPS changing from 100/68 to 102/66 (data not shown). It did not change the results of the study.
Sixth, the limited sample size implies a risk of type II errors. That is, important prognostic factors may not be discovered as statistically significant owing to the limited sample size. Other factors that could affect the prognosis for work outcomes include fear avoidance beliefs [
2,
3,
49] and physical workload [
1,
2,
39]. These factors were not isolated for analysis in the current study since they were covered by the ÖMPSQ score and we wished for all variables to be as mutually exclusive as possible. Furthermore, the aim was not to investigate a complete list of all possible factors affecting WPS prognosis but rather to explore the contributions of demographic, patient-reported, clinical and MRI variables for which purpose we believe the current sample size was adequate.