Background Many studies have been performed to identify important prognostic factors for outcomes after rehabilitation of patients with chronic pain, and there is a need to synthesize them through systematic review. In this process, it is important to assess the study quality and risk of bias. The “Quality In Prognosis Studies” (QUIPS) tool has been developed for this purpose and consists of several prompting items categorized into six domains, and each domain is judged on a three-grade scale (low, moderate or high risk of bias). The aim of the present study was to determine the interrater agreement of the risk of bias assessment in prognostic studies of patients with chronic pain using QUIPS and to elaborate on the use of this instrument. Methods We performed a systematic review and a meta-analysis of prognostic factors for long-term outcomes after multidisciplinary rehabilitation in patients with chronic pain. Two researchers rated the risk of bias in 43 published papers in two rounds (15 and 28 papers, respectively). The interrater agreement and Cohen’s quadratic weighted kappa coefficient ( κ ) and 95% confidence interval (95%CI) were calculated in all domains and separately for the first and second rounds. Results The raters agreed in 61% of the domains (157 out of 258), with similar interrater agreement in the first (59%, 53/90) and second rounds (62%, 104/168). The overall weighted kappa coefficient (kappa for all domains and all papers) was weak: κ = 0.475 (95%CI = 0.358–0.601). A “minimal agreement” between the raters was found in the first round, κ = 0.323 (95%CI = 0.129–0.517), but increased to “weak agreement” in the second round, κ = 0.536 (95%CI = 0.390–0.682). Conclusion Despite a relatively low interrater agreement, QUIPS proved to be a useful tool in assessing the risk of bias when performing a meta-analysis of prognostic studies in pain rehabilitation, since it demands of raters to discuss and investigate important aspects of study quality. Some items were particularly hard to differentiate in-between, and a learning phase was required to increase the interrater agreement. This paper highlights several aspects of the tool that should be kept in mind when rating the risk of bias in prognostic studies, and provides some suggestions on common pitfalls to avoid during this process. Trial registration PROSPERO CRD42016025339 ; registered 05 February 2016. Electronic supplementary material The online version of this article (10.1186/s41512-019-0050-0) contains supplementary material, which is available to authorized users.

BackgroundChronic pain patients frequently suffer from psychological symptoms. There is no consensus concerning the prevalence of severe anxiety and depressive symptoms and the strength of the associations between pain intensity and psychological distress. Although an important aspect of the clinical picture is understanding how the pain condition impacts life, little is known about the relative importance of pain and psychological symptoms for individual’s life impact. The aims of this study were to identify subgroups of pain patients; to analyze if pain, psychological distress, and life impact variables influence subgrouping; and to investigate how patients in the subgroups benefit from treatments.MethodsBackground variables, pain aspects (intensity/severity and spreading), psychological distress (depressive and anxiety symptoms), and two life impact variables (pain interference and perceived life control) were obtained from the Swedish Quality Registry for Pain Rehabilitation for chronic pain patients and analyzed mainly using advanced multivariate methods.ResultsBased on >35,000 patients, 35%–40% had severe anxiety or depressive symptoms. Severe psychological distress was associated with being born outside Europe (21%–24% vs 6%–8% in the category without psychological distress) and low education level (20.7%–20.8% vs 26%–27% in the category without psychological distress). Dose relationships existed between the two psychological distress variables and pain aspects, but the explained variances were generally low. Pain intensity/severity and the two psychological distress variables were significantly associated (R2=0.40–0.48; P>0.001) with the two life impact variables (pain interference and life control). Two subgroups of patients were identified at baseline (subgroup 1: n=15,901–16,119; subgroup 2: n=20,690–20,981) and the subgroup with the worst situation regarding all variables participated less in an MMRP (51% vs 58%, P<0.001) but showed the largest improvements in outcomes.ConclusionThe results emphasize the need to assess both pain and psychological distress and not take for granted that pain involves high psychological stress in the individual case. Not all patients benefit from MMRP. A better matching between common clinical pictures and the content of MMRPs may help improve results. We only partly found support for treatment resistance in patients with psychological distress burden.