Can pathoanatomical pathways of degeneration in lumbar motion segments be identified by clustering MRI findings

Background: Magnetic Resonance Imaging (MRI) is the gold standard for detailed visualisation of spinal pathological and degenerative processes, but the prevailing view is that such imaging findings have little or no clinical relevance for low back pain. This is because these findings appear to have little association with treatment effects in clinical populations, and mostly a weak association with the presence of pain in the general population.However, almost all research into these associations is based on the examination of individual MRI findings, despite its being very common for multiple MRI findings to coexist. Therefore, this proof-of-concept study investigated the capacity of a multivariable statistical method to identify clusters of MRI findings and for those clusters to be grouped into pathways of vertebral degeneration. Methods. This study is a secondary analysis of data from 631 patients, from an outpatient spine clinic, who had been screened for inclusion in a randomised controlled trial. The available data created a total sample pool of 3,155 vertebral motion segments. The mean age of the cohort was 42 years (SD 10.8, range 18-73) and 54% were women.MRI images were quantitatively coded by an experienced musculoskeletal research radiologist using a detailed and standardised research MRI evaluation protocol that has demonstrated high reproducibility. Comprehensive MRI findings descriptive of the disco-vertebral component of lumbar vertebrae were clustered using Latent Class Analysis. Two pairs of researchers, each containing an experienced MRI researcher, then independently categorised the clusters into hypothetical pathoanatomic pathways based on the known histological changes of discovertebral degeneration. Results: Twelve clusters of MRI findings were identified, described and grouped into five different hypothetical pathways of degeneration that appear to have face validity. Conclusions: This study has shown that Latent Class Analysis can be used to identify clusters of MRI findings from people with LBP and that those clusters can be grouped into degenerative pathways that are biologically plausible. If these clusters of MRI findings are reproducible in other datasets of similar patients, they may form a stable platform to investigate the relationship between degenerative pathways and clinically important characteristics such as pain and activity limitation

Degenerative Pathways of Lumbar Motion Segments--A Comparison in Two Samples of Patients with Persistent Low Back Pain

Background: Magnetic resonance imaging (MRI) is used to identify spinal pathoanatomy in people with persistent low back pain. However, the clinical relevance of spinal degenerative MRI findings remains uncertain. Although multiple MRI findings are almost always present at the same time, research into the association with clinical outcomes (such as pain) has predominantly focused on individual MRI findings. This study aimed to: (i) investigate how multiple MRI lumbar spine findings cluster together within two different samples of patients with low back pain, (ii) classify these clusters into hypothetical pathways of degeneration based on scientific knowledge of disco-vertebral degeneration, and (iii) compare these clusters and degenerative pathways between samples. Methods: We performed a secondary cross-sectional analysis on two dissimilar MRI samples collected in a hospital department: (1) data from the spinal MRI reports of 4,162 low back pain patients and (2) data from an MRI research protocol of 631 low back pain patients. Latent Class Analysis was used in both samples to cluster MRI findings from lumbar motion segments. Using content analysis, each cluster was then categorised into hypothetical pathways of degeneration. Results: Six clusters of MRI findings were identified in each of the two samples. The content of the clusters in the two samples displayed some differences but had the same overall pattern of MRI findings. Although the hypothetical degenerative pathways identified in the two samples were not identical, the overall pattern of increasing degeneration within the pathways was the same. Conclusions: It was expected that different clusters could emerge from different samples, however, when organised into hypothetical pathways of degeneration, the overall pattern of increasing degeneration was similar and biologically plausible. This evidence of reproducibility suggests that Latent Class Analysis may provide a new approach to investigating the relationship between MRI findings and clinically important characteristics such as pain and activity limitation

Do MRI findings identify patients with chronic low back pain and Modic changes who respond best to rest or exercise: A subgroup analysis of a randomised controlled trial

Background: No previous clinical trials have investigated MRI findings as effect modifiers for conservative treatment of low back pain. This hypothesis-setting study investigated if MRI findings modified response to rest compared with exercise in patients with chronic low back pain and Modic changes. Methods: This study is a secondary analysis of a randomised controlled trial comparing rest with exercise. Patients were recruited from a specialised outpatient spine clinic and included in a clinical trial if they had chronic low back pain and an MRI showing Modic changes. All patients received conservative treatment while participating in the trial. Five baseline MRI findings were investigated as effect modifiers: Modic changes Type 1 (any size), large Modic changes (any type), large Modic changes Type 1, severe disc degeneration and large disc herniation. The outcome measure was change in low back pain intensity measured on a 0-10 point numerical rating scale at 14-month follow-up (n = 96). An interaction = 1.0 point (0-10 scale) between treatment group and MRI findings in linear regression was considered clinically important. Results: The interactions for Modic Type 1, with large Modic changes or with large Modic changes Type 1 were all potentially important in size (-0.99 (95% CI -3.28 to 1.29), -1.49 (-3.73 to 0.75), -1.49 (-3.57 to 0.58), respectively) but the direction of the effect was the opposite to what we had hypothesized-that people with these findings would benefit more from rest than from exercise. The interactions for severe disc degeneration (0.74 (-1.40 to 2.88)) and large disc herniation (-0.92 (3.15 to 1.31)) were less than the 1.0-point threshold for clinical importance. As expected, because of the lack of statistical power, no interaction term for any of the MRI findings was statistically significant. Conclusions: Three of the five MRI predictors showed potentially important effect modification, although the direction of the effect was surprising and confidence intervals were wide so very cautious interpretation is required. Further studies with adequate power are warranted to study these and additional MRI findings as potential effect modifiers for common interventions

A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB

Background: There are various methodological approaches to identifying clinically important subgroups and one method is to identify clusters of characteristics that differentiate people in cross-sectional and/or longitudinal data using Cluster Analysis (CA) or Latent Class Analysis (LCA). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold LCA and SNOB LCA). Methods. The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program's ease of use and interpretability of the presentation of results.We analysed five real datasets of varying complexity in a secondary analysis of data from other research projects. Three datasets contained only MRI findings (n = 2,060 to 20,810 vertebral disc levels), one dataset contained only pain intensity data collected for 52 weeks by text (SMS) messaging (n = 1,121 people), and the last dataset contained a range of clinical variables measured in low back pain patients (n = 543 people). Four artificial datasets (n = 1,000 each) containing subgroups of varying complexity were also analysed testing the ability of these clustering methods to detect subgroups and correctly classify individuals when subgroup membership was known. Results: The results from the real clinical datasets indicated that the number of subgroups detected varied, the certainty of classifying individuals into those subgroups varied, the findings had perfect reproducibility, some programs were easier to use and the interpretability of the presentation of their findings also varied. The results from the artificial datasets indicated that all three clustering methods showed a near-perfect ability to detect known subgroups and correctly classify individuals into those subgroups. Conclusions: Our subjective judgement was that Latent Gold offered the best balance of sensitivity to subgroups, ease of use and presentation of results with these datasets but we recognise that different clustering methods may suit other types of data and clinical research questions

Immunity to self co-generates regulatory T cells

Immune responses to self are kept in check by tolerance mechanisms, including suppression by regulatory T cells (Tregs). The defective generation of Tregs specific for self-antigens may lead to autoimmune disease. We identified a novel population of human CD4^+^ Tregs, characterized by high surface expression of CD52, which is co-generated in response to autoantigen. Blood CD4^+^CD52^hi^ T cells were generated preferentially in response to low-dose autoantigen and suppressed proliferation and interferon-[gamma] production by other T cells. Depletion of resting CD4^+^CD52^hi^ T cells enhanced the T-cell response to autoantigen. CD4^+^CD52^hi^ Tregs were neither derived from nor distinguished by markers of conventional resting CD4^+^CD25^+^ Tregs. In response to the pancreatic islet autoantigens glutamic acid decarboxylase, the generation of CD4^+^CD52^hi^ Tregs was impaired in individuals with and at-risk for type 1 diabetes, compared to healthy controls and individuals with type 2 diabetes. CD4^+^CD52^hi^ Tregs co-generated to self-antigen may therefore contribute to immune homeostasis and protect against autoimmune disease

Directed Percolation with a Wall or Edge

We examine the effects of introducing a wall or edge into a directed percolation process. Scaling ansatzes are presented for the density and survival probability of a cluster in these geometries, and we make the connection to surface critical phenomena and field theory. The results of previous numerical work for a wall can thus be interpreted in terms of surface exponents satisfying scaling relations generalising those for ordinary directed percolation. New exponents for edge directed percolation are also introduced. They are calculated in mean-field theory and measured numerically in 2+1 dimensions.Comment: 14 pages, submitted to J. Phys.

Surface Critical Behavior in Systems with Non-Equilibrium Phase Transitions

We study the surface critical behavior of branching-annihilating random walks with an even number of offspring (BARW) and directed percolation (DP) using a variety of theoretical techniques. Above the upper critical dimensions d_c, with d_c=4 (DP) and d_c=2 (BARW), we use mean field theory to analyze the surface phase diagrams using the standard classification into ordinary, special, surface, and extraordinary transitions. For the case of BARW, at or below the upper critical dimension, we use field theoretic methods to study the effects of fluctuations. As in the bulk, the field theory suffers from technical difficulties associated with the presence of a second critical dimension. However, we are still able to analyze the phase diagrams for BARW in d=1,2, which turn out to be very different from their mean field analog. Furthermore, for the case of BARW only (and not for DP), we find two independent surface beta_1 exponents in d=1, arising from two distinct definitions of the order parameter. Using an exact duality transformation on a lattice BARW model in d=1, we uncover a relationship between these two surface beta_1 exponents at the ordinary and special transitions. Many of our predictions are supported using Monte-Carlo simulations of two different models belonging to the BARW universality class.Comment: 19 pages, 12 figures, minor additions, 1 reference adde

The association between subgroups of MRI findings identified with latent class analysis and low back pain in 40-year old Danes

Background: Research into the clinical importance of spinal MRI findings in patients with low back pain (LBP) has primarily focused on single imaging findings, such as Modic changes or disc degeneration, and found only weak associations with the presence of pain. However, numerous MRI findings almost always co-exist in the lumbar spine and are often present at more than one lumbar level. It is possible that multiple MRI findings are more strongly associated with LBP than single MRI findings. Latent Class Analysis is a statistical method that has recently been tested and found useful for identifying latent classes (subgroups) of MRI findings within multivariable datasets. The purpose of this study was to investigate the association between subgroups of MRI findings and the presence of LBP in people from the general population. Methods: To identify subgroups of lumbar MRI findings with potential clinical relevance, Latent Class Analysis was initially performed on a clinical dataset of 631 patients seeking care for LBP. Subsequently, 412 participants in a general population cohort (the ‘Backs on Funen’ project) were statistically allocated to those existing subgroups by Latent Class Analysis, matching their MRI findings at a segmental level. The subgroups containing MRI findings from the general population were then organised into hypothetical pathways of degeneration and the association between subgroups in the pathways and the presence of LBP was tested using exact logistic regression. Results: Six subgroups were identified in the clinical dataset and the data from the general population cohort fitted the subgroups well, with a median posterior probability of 93%–100%. These six subgroups described two pathways of increasing degeneration on upper (L1-L3) and lower (L4-L5) lumbar levels. An association with LBP was found for the subgroups describing severe and multiple degenerative MRI findings at the lower lumbar levels but none of the other subgroups were associated with LBP

Prognostic implications of the Quebec Task Force classification of back-related leg pain: An analysis of longitudinal routine clinical data

Background: Low back pain (LBP) patients with related leg pain have a more severe profile than those with local LBP and a worse prognosis. Pain location above or below the knee and the presence of neurological signs differentiate patients with different profiles, but knowledge about the prognostic value of these subgroups is sparse. The objectives of this study were (1) to investigate whether subgroups consisting of patients with Local LBP only, LBP + leg pain above the knee, LBP + leg pain below the knee, and LBP + leg pain and neurological signs had different prognoses, and (2) to determine if this was explained by measured baseline factors. Methods. Routine clinical data were collected during the first visit to an outpatient department and follow-ups were performed after 3 and 12 months. Patients were divided into the four subgroups and associations between subgroups and the outcomes of activity limitation, global perceived effect (GPE) after 3 months, and sick leave after 3 months were tested by means of generalised estimating equations. Models were univariate (I), adjusted for duration (II), and adjusted for all baseline differences (III). Results: A total of 1,752 patients were included, with a 76% 3-month and 70% 12-month follow-up. Subgroups were associated with activity limitation in all models (p < 0.001). Local LBP had the least and LBP + neurological signs the most severe limitations at all time-points, although patients with neurological signs improved the most. Associations with GPE after 3 months were only significant in Model I. Subgroups were associated with sick leave after 3 months in model I and II, with sick leave being most frequent in the subgroup with neurological signs. No significant differences were found in any pairwise comparisons of patients with leg pain above or below the knee. Conclusions: Subgrouping LBP patients, based on pain location and neurological signs, was associated with activity limitation and sick leave, but not with GPE. The presence of neurological signs and pain in the leg both have prognostic implications but whether that leg pain without neurological signs is above or below the knee does not

Patients with low back pain differ from those who also have leg pain or signs of nerve root involvement - A cross-sectional study

Background: Leg pain associated with low back pain (LBP) is recognized as a risk factor for a poor prognosis, and is included as a component in most LBP classification systems. The location of leg pain relative to the knee and the presence of a positive straight leg raise test have been suggested to have clinical implications. To understand differences between such leg pain subgroups, and whether differences include potentially modifiable characteristics, the purpose of this paper was to describe characteristics of patients classified into the Quebec Task Force (QTF) subgroups of: 1) LBP only, 2) LBP and pain above the knee, 3) LBP and pain below the knee, and 4) LBP and signs of nerve root involvement. Methods. Analysis of routine clinical data from an outpatient department. Based on patient reported data and clinical findings, patients were allocated to the QTF subgroups and described according to the domains of pain, activity limitation, work participation, psychology, general health and clinical examination findings. Results: A total of 2,673 patients aged 18-95 years (median 47) who were referred for assessment of LBP were included. Increasing severity was consistently observed across the subgroups from LBP only to LBP with signs of nerve root involvement although subgroup differences were small. LBP patients with leg pain differed from those with LBP only on a wide variety of parameters, and patients with signs of nerve root involvement had a more severe profile on almost all measures compared with other patients with back-related leg pain. Conclusion: LBP patients with pain referral to the legs were more severely affected than those with local LBP, and patients with signs of nerve root involvement were the ones most severily affected. These findings underpin the concurrent validity of the Quebec Task Force Classification. However, the small size of many between-subgroup differences amid the large variability in this sample of cross-sectional data also underlines that the heterogeneity of patients with LBP is more complex than that which can be explained by leg pain patterns alone. The implications of the observed differences also require investigation in longitudinal studies