Clinical assessment and management of lumbar spinal stenosis: clinical dilemmas and considerations for surgical referral.

Lumbar spinal stenosis is the leading indication for spine surgery in older adults. Surgery is recommended in clinical guidelines if non-surgical treatments have been provided with insufficient benefit. The difficulty for clinicians is that the current number of randomised controlled trials is low, which creates uncertainty about which treatments to provide. For non-surgical clinicians this paucity of data leads to a clinical dilemma of whether to continue managing the patient or refer to a spine surgeon. This Viewpoint aims to provide an update on the assessment of lumbar spinal stenosis, treatment recommendations, indications for referral to a spine surgeon, and current clinical dilemmas facing non-surgical clinicians and spinal surgeons.

Mortality with concurrent treatment with gabapentin and opioids among people with spine diagnoses in the U.S. Medicare population: a propensity-matched cohort study.

IMPORTANCE: Given the negative impact of opioid use on population health, prescriptions for alternative pain-relieving medications, including gabapentin, have increased. Concurrent gabapentin and opioid prescriptions are commonly reported in retrospective studies of opioid-related overdose deaths. OBJECTIVE: To determine whether people who filled gabapentin and opioid prescriptions concurrently ('gabapentin + opioids') had greater mortality than those who filled an active control medication (tricyclic antidepressants [TCAs] or duloxetine) and opioids concurrently ('TCAs/duloxetine + opioids'). We hypothesized that people treated with gabapentin + opioids would have higher mortality rates compared to people treated with TCAs/duloxetine + opioids. DESIGN: Propensity score-matched cohort study with an incident user, active control design. The median (maximum) follow-up was 45 (1093) days. SETTING: Population-based. PARTICIPANTS: Medicare beneficiaries with spine-related diagnoses 2017-2019. The primary analysis included those who concurrently (within 30 days) filled at least 1 incident gabapentin + at least 1 opioid or at least 1 incident TCA/duloxetine + at least 1 opioid. EXPOSURES: People treated with gabapentin + opioids (n=67,133) were matched on demographic and clinical factors in a 1:1 ratio to people treated with TCAs/duloxetine + opioids (n=67,133). MAIN OUTCOMES AND MEASURES: The primary outcome was mortality at any time. A secondary outcome was occurrence of a major medical complication at any time. RESULTS: Among 134,266 participants (median age 73.4 years; 66.7% female), 2360 died before the end of follow-up. No difference in mortality was observed between groups (adjusted hazard ratio (HR) and 95% confidence interval (CI) for gabapentin + opioids was 0.98 (0.90, 1.06); p=0.63). However, people treated with gabapentin + opioids were at slightly increased risk of a major medical complication (1.02 (1.00, 1.04); p=0.03) compared to those treated with TCAs/duloxetine + opioids. Results were similar in analyses (a) restricted to less than or = 30-day follow-up and (b) that required at least 2 fills of each prescription. CONCLUSIONS AND RELEVANCE: When treating pain in older adults taking opioids, the addition of gabapentin did not increase mortality risk relative to addition of TCAs or duloxetine. However, providers should be cognizant of a small increased risk of major medical complications among opioid users initiating gabapentin compared to those initiating TCAs or duloxetine.

Description and initial validation of a novel measure of pain intensity: the Numeric Rating Scale of Underlying Pain without concurrent Analgesic use.

ABSTRACT: Although many individuals with chronic pain use analgesics, the methods used in many randomized controlled trials (RCTs) do not sufficiently account for confounding by differential post-randomization analgesic use. This may lead to underestimation of average treatment effects and diminished power. We introduce (1) a new measure-the Numeric Rating Scale of Underlying Pain without concurrent Analgesic use (NRS-UP(A))-which can shift the estimand of interest in an RCT to target effects of a treatment on pain intensity in the hypothetical situation where analgesic use was not occurring at the time of outcome assessment; and (2) a new pain construct-an individuals' perceived effect of analgesic use on pain intensity (EA). The NRS-UP(A) may be used as a secondary outcome in RCTs of point treatments or nonpharmacologic treatments. Among 662 adults with back pain in primary care, participants' mean value of the NRS-UP(A) among those using analgesics was 1.2 NRS points higher than their value on the conventional pain intensity NRS, reflecting a mean EA value of -1.2 NRS points and a perceived beneficial effect of analgesics. More negative values of EA (ie, greater perceived benefit) were associated with a greater number of analgesics used but not with pain intensity, analgesic type, or opioid dose. The NRS-UP(A) and EA were significantly associated with future analgesic use 6 months later, but the conventional pain NRS was not. Future research is needed to determine whether the NRS-UP(A), used as a secondary outcome may allow pain RCTs to target alternative estimands with clinical relevance.

Multi-Trait Exome-Wide Association Study of Back Pain-Related Phenotypes.

Back pain (BP) is a major contributor to disability worldwide, with heritability estimated at 40-60%. However, less than half of the heritability is explained by common genetic variants identified by genome-wide association studies. More powerful methods and rare and ultra-rare variant analysis may offer additional insight. This study utilized exome sequencing data from the UK Biobank to perform a multi-trait gene-based association analysis of three BP-related phenotypes: chronic back pain, dorsalgia, and intervertebral disc disorder. We identified the SLC13A1 gene as a contributor to chronic back pain via loss-of-function (LoF) and missense variants. This gene has been previously detected in two studies. A multi-trait approach uncovered the novel FSCN3 gene and its impact on back pain through LoF variants. This gene deserves attention because it is only the second gene shown to have an effect on back pain due to LoF variants and represents a promising drug target for back pain therapy.

Repurposing Antihypertensive and Statin Medications for Spinal Pain: A Mendelian Randomization Study.

STUDY DESIGN: Mendelian randomization (MR) study. OBJECTIVE: To examine whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal pain (back or neck pain). SUMMARY OF BACKGROUND DATA: Observational studies and a recent MR study have found associations between elevated blood pressure and a greater risk of back pain. Observational studies have found associations between hyperlipidemia and statin use and greater risk of back pain. No prior MR studies have examined the effects of antihypertensives or statins on spinal pain. MATERIALS AND METHODS: This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies (GWAS). Sample sizes in exposure GWASs were n=757,601 (systolic blood pressure) and n=173,082 (low-density lipoprotein cholesterol), and n=1,028,947 for the outcome GWAS of spinal pain defined as health care seeking for any spinal pain-related diagnosis. Genes and cis-acting variants were identified as proxies for the drug targets of interest. MR analyses used inverse-variance weighted meta-analysis. The threshold for statistical significance after correction for multiple testing was P <0.0125. RESULTS: No statistically significant associations of these medications with spinal pain were found. However, findings were suggestive of a protective effect of beta-blockers on spinal pain risk (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72-0.98; P =0.03), and calcium channel blockers on greater spinal pain risk (OR 1.12, 95% CI 1.02-1.24; P =0.02). CONCLUSIONS: A protective effect of beta-blockers on spinal pain was suggested in the current study, consistent with findings from observational studies of various other pain phenotypes. The detrimental effect of calcium channel blockers on spinal pain suggested in the current study must be interpreted in the context of conflicting directions of effect on nonspinal pain phenotypes in other observational studies.This Mendelian randomization study examined whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal.This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies ranging size from 173,082 to 1,028,947 adults.While no statistically significant associations were found, a protective effect of beta-blockers on spinal pain was suggested (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72 to 0.98; p= 0.03), as was a detrimental effect of calcium channel blockers on spinal pain (OR 1.12, 95% CI 1.02 to 1.24; p= 0.02).

Bidirectional Mendelian Randomization Study of Personality Traits Reveals a Positive Feedback Loop Between Neuroticism and Back Pain.

We conducted a bidirectional Mendelian randomization study to examine the causal effects of six personality traits (anxiety, neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) on back pain associated with health care use and the causal effect of back pain on the same risk factors. Genetic instruments for the personality traits and back pain were obtained from the largest published genome-wide association studies conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis and Causal Analysis Using Summary Effect for primary analyses and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results of at least one primary analysis were statistically significant after accounting for multiple statistical testing (P-value < .0042), and the direction and magnitude of effect estimates were concordant between primary and sensitivity analyses. We found evidence for statistically significant bidirectional causal associations between neuroticism and back pain, with odds ratio 1.51 (95% confidence interval 1.37; 1.67) of back pain per neuroticism sum score standard deviation, P-value = 7.80e-16; and beta = .12, se = .04 of neuroticism sum score standard deviation per log odds of back pain, P-value = 2.48e-03. Other relationships did not meet our predefined criteria for causal association. PERSPECTIVE: The significant positive feedback loop between neuroticism and back pain highlights the importance of considering neuroticism in the management of patients with back pain.

Combining Procedural and Behavioral Treatments for Chronic Low Back Pain: A Pilot Feasibility Randomized Controlled Trial.

Individual treatments for chronic low back pain (CLBP) have small magnitude effects. Combining different types of treatments may produce larger effects. This study used a 2×2 factorial randomized controlled trial (RCT) design to combine procedural and behavioral treatments for CLBP. The study aims were to: (1) assess feasibility of conducting a factorial RCT of these treatments; and (2) estimate individual and combined treatment effects of (a) lumbar radiofrequency ablation (LRFA) of the dorsal ramus medial branch nerves (vs. a simulated LRFA control procedure) and (b) Activity Tracker-Informed Video-Enabled Cognitive Behavioral Therapy program for CLBP (AcTIVE-CBT) (vs. an educational control treatment) on back-related disability at 3 months post-randomization. Participants (n=13) were randomized in a 1:1:1:1 ratio. Feasibility goals included an enrollment proportion ≥30%, a randomization proportion ≥80%, and a ≥80% proportion of randomized participants completing the 3-month Roland-Morris Disability Questionnaire (RMDQ) primary outcome endpoint. An intent-to-treat analysis was used. The enrollment proportion was 62%, the randomization proportion was 81%, and all randomized participants completed the primary outcome. Though not statistically significant, there was a beneficial, moderate-magnitude effect of LRFA vs. control on 3-month RMDQ (-3.25 RMDQ points; 95% CI: -10.18, 3.67). There was a significant, beneficial, large-magnitude effect of AcTIVECBT vs. control (-6.29, 95% CI: -10.97, -1.60). Though not statistically significant, there was a beneficial, large effect of LRFA+AcTIVE-CBT vs. control (-8.37; 95% CI: -21.47, 4.74). We conclude that it is feasible to conduct an RCT combining procedural and behavioral treatments for CLBP.

Development and Replication of a Genome-Wide Polygenic Risk Score for Chronic Back Pain.

Chronic back pain (CBP) is a complex heritable trait and a major cause of disability worldwide. We developed and validated a genome-wide polygenic risk score (PRS) for CBP using a large-scale GWAS based on UK Biobank participants of European ancestry (N = 265,000). The PRS showed poor overall predictive ability (AUC = 0.56 and OR = 1.24 per SD, 95% CI: 1.22-1.26), but individuals from the 99th percentile of PRS distribution had a nearly two-fold increased risk of CBP (OR = 1.82, 95% CI: 1.60-2.06). We validated the PRS on an independent TwinsUK sample, obtaining a similar magnitude of effect. The PRS was significantly associated with various ICD-10 and OPCS-4 diagnostic codes, including chronic ischemic heart disease (OR = 1.1, p-value = 4.8 × 10-15), obesity, metabolism-related traits, spine disorders, disc degeneration, and arthritis-related disorders. PRS and environment interaction analysis with twelve known CBP risk factors revealed no significant results, suggesting that the magnitude of G × E interactions with studied factors is small. The limited predictive ability of the PRS that we developed is likely explained by the complexity, heterogeneity, and polygenicity of CBP, for which sample sizes of a few hundred thousand are insufficient to estimate small genetic effects robustly.

Mortality among older adults with osteoporotic vertebral fracture.

We evaluated whether older adults who received kyphoplasty had reduced risk of mortality compared to those who did not. In unmatched analyses, those receiving kyphoplasty were at reduced risk of death but after matching on age and medical complications, patients who received kyphoplasty were at increased risk of death. PURPOSE: In previous observational studies, kyphoplasty for treatment of osteoporotic vertebral fractures has been associated with decreased mortality compared to conservative management. The purpose of this research was to determine whether older adults who received kyphoplasty had reduced risk of mortality compared to matched patients who did not. METHODS: Retrospective cohort study of US Medicare enrollees with osteoporotic vertebral fractures between 2017-2019 comparing patients who underwent kyphoplasty to those who did not. We identified 2 control groups a priori: 1) non-augmented patients who met inclusion criteria (group 1); 2) propensity-matched patients on demographic and clinical variables (group 2). We then identified additional control groups using matching for medical complications (group 3) and age + comorbidities (group 4). We calculated hazard ratios (HRs) and 95% confidence intervals (95% CIs) associated with mortality. RESULTS: A total of 235,317 patients (mean (± standard deviation) age 81.1 ± 8.3 years; 85.8% female) were analyzed. In the primary analyses, those who received kyphoplasty were at reduced risk of death compared to those who did not: adjusted HR (95% CI) in group 1 = 0.84 (0.82, 0.87); and in group 2 = 0.88 (0.85, 0.91). However, in post hoc analyses, patients who received kyphoplasty were at increased risk of death: adjusted HR (95% CI) in group 3 = 1.32 (1.25, 1.41) and 1.81 (1.58, 2.09) in group 4. CONCLUSION: An apparent benefit of kyphoplasty on mortality among patients with vertebral fractures was not present after rigorous propensity matching, illustrating the importance of comparing similar individuals when evaluating observational data.

Risk Factors for Chronic Prescription Opioid Use in Multiple Sclerosis.

OBJECTIVE: To characterize patterns of prescription opioid use among individuals with multiple sclerosis (MS) and identify risk factors associated with chronic use. DESIGN: Retrospective longitudinal cohort study examining US Department of Veterans Affairs electronic medical record data of Veterans with MS. The annual prevalence of prescription opioid use by type (any, acute, chronic, incident chronic) was calculated for each study year (2015-2017). Multivariable logistic regression was used to identify demographics and medical, mental health, and substance use comorbidities in 2015-2016 associated with chronic prescription opioid use in 2017. SETTING: US Department of Veterans Affairs, Veteran's Health Administration. PARTICIPANTS: National sample of Veterans with MS (N=14,974). MAIN OUTCOME MEASURE: Chronic prescription opioid use (≥90 days). RESULTS: All types of prescription opioid use declined across the 3 study years (chronic opioid use prevalence=14.6%, 14.0%, and 12.2%, respectively). In multivariable logistic regression, prior chronic opioid use, history of pain condition, paraplegia or hemiplegia, post-traumatic stress disorder, and rural residence were associated with greater risk of chronic prescription opioid use. History of dementia and psychotic disorder were both associated with lower risk of chronic prescription opioid use. CONCLUSION: Despite reductions over time, chronic prescription opioid use remains common among a substantial minority of Veterans with MS and is associated with multiple biopsychosocial factors that are important for understanding risk for long-term use.

Evidence of causal effects of blood pressure on back pain and back pain on type II diabetes provided by a bidirectional Mendelian randomization study.

BACKGROUND CONTEXT: Cardiovascular risk factors (hypertension, dyslipidemia, and type II diabetes) have been proposed as risk factors for back pain. However, few longitudinal studies have found significant associations between cardiovascular risk factors and back pain, and these may be explained by confounding or reverse causation. PURPOSE: To examine potential causal effects of cardiovascular risk factors on back pain, and vice versa. STUDY DESIGN: Bidirectional Mendelian randomization (MR) study. PATIENT SAMPLES: Genome-wide association studies (GWAS) with sample sizes between 173,082 and 1,028,947 participants. OUTCOME MEASURES: Outcomes included (1) back pain associated with health care use (BP-HC) in the forward MR; and (2) seven cardiovascular phenotypes in the reverse MR, including 2 measurements used for the evaluation of hypertension (diastolic blood pressure and systolic blood pressure), 4 phenotypes related to dyslipidemia (LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides), and type II diabetes. METHODS: We used summary statistics from large, publicly available GWAS for BP-HC and the 7 cardiovascular phenotypes to obtain genetic instrumental variables. We examined MR evidence for causal associations using inverse-variance weighted (IVW) analysis, Causal Analysis Using Summary Effect (CAUSE), and sensitivity analyses. RESULTS: In forward MR analyses of seven cardiovascular phenotypes, diastolic blood pressure was associated with BP-HC across all analyses (IVW estimate: OR = 1.10 per 10.5 mm Hg increase [1.04-1.17], p-value = .001), and significant associations of systolic blood pressure with BP-HC were also found (IVW estimate: OR = 1.09 per 19.3 mm Hg increase [1.04-1.15], p-value = .0006). In reverse MR analyses, only type II diabetes was associated with BP-HC across all analyses (IVW estimate: OR = 1.40 [1.13-1.73], p-value = .002). CONCLUSIONS: These findings from analyses of large, population-based samples indicate that higher blood pressure increases the risk of BP-HC, and BP-HC itself increases the risk of type II diabetes.

Genotype-by-environment interactions in chronic back pain.

BACKGROUND CONTEXT: Chronic back pain (CBP) is a common debilitating condition with substantial societal impact. While understanding genotype-by-environment (GxE) interactions may be crucial to achieving the goals of personalized medicine, there are few large-scale studies investigating this topic for CBP. None of them systematically explore multiple CBP risk factors. PURPOSE: To estimate the extent to which genetic effects on CBP are modified by known demographic and clinical risk factors. RESEARCH DESIGN: Case-control study, genome-wide GxE interaction study. PATIENT SAMPLE: Data on up to 331,610 unrelated participants (57,881 CBP cases and 273,729 controls) from the UK Biobank cohort were used. UK Biobank is a prospective cohort with collected deep genetic and phenotypic data on approximately 500,000 individuals across the UK. OUTCOME MEASURES: Self-reported chronic back pain. METHODS: We applied a whole-genome approach to estimate the proportion of phenotypic variance explained by interactions between genotype and 12 known risk factors. We also analyzed if effects of common single-nucleotide polymorphisms on CBP are changed in presence of known risk factors. RESULTS: The results indicate a modest, if any, modification of genetic effects by examined risk factors in CBP. Our estimates suggest that detecting such weak effects would require a sample size of millions of individuals. CONCLUSIONS: The GxE interactions with examined common risk factors for CBP are either weak or absent. Interactions of such magnitude are unlikely to have the potential to inform and influence treatment strategies. Risk estimation models may use common genetic variation and the considered risk factors as independent predictors, without accounting for GxE.

Treatment With Opioids Is Not Associated With Poor Outcomes Among Older Adults With Lumbar Spinal Stenosis Receiving Epidural Injections.

STUDY DESIGN: Secondary analysis of a randomized controlled trial. OBJECTIVE: To assess how baseline treatment with opioids is associated with pain and function in older adults with lumbar spinal stenosis who receive epidural injections. SUMMARY OF BACKGROUND DATA: Data were obtained from the Lumbar Epidural Steroid injections for Spinal Stenosis trial, a double-blind, multisite, randomized controlled trial. METHODS: Baseline treatment with opioids was assessed from electronic medical record prescription pharmacy data or from health utilization records collected from patients. We calculated adjusted changes in back pain numerical rating scale, leg pain numerical rating scale, and back-related disability (Roland Morris Disability Questionnaire scores) from baseline to three weeks and to six weeks among patients treated and not treated with opioids at baseline using generalized linear regression. RESULTS: Baseline treatment with opioids was not significantly associated with back pain intensity (adjusted difference in means at three weeks of follow-up between patients treated with opioids at baseline versus not [±95% CI, 0.1 (-0.7, 0.7)], leg pain intensity [-0.2 (-0.9, 0.4)], or back-related function [-0.8 (-2.1, 0.4)]. We found similar results at six weeks of follow-up. CONCLUSIONS: Among older adults with lumbar spinal stenosis who are receiving epidural injections, those treated with opioids at baseline had similar outcomes to those who were not.

Predicting decompression surgery by applying multimodal deep learning to patients' structured and unstructured health data.

BACKGROUND: Low back pain (LBP) is a common condition made up of a variety of anatomic and clinical subtypes. Lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS) are two subtypes highly associated with LBP. Patients with LDH/LSS are often started with non-surgical treatments and if those are not effective then go on to have decompression surgery. However, recommendation of surgery is complicated as the outcome may depend on the patient's health characteristics. We developed a deep learning (DL) model to predict decompression surgery for patients with LDH/LSS. MATERIALS AND METHOD: We used datasets of 8387 and 8620 patients from a prospective study that collected data from four healthcare systems to predict early (within 2 months) and late surgery (within 12 months after a 2 month gap), respectively. We developed a DL model to use patients' demographics, diagnosis and procedure codes, drug names, and diagnostic imaging reports to predict surgery. For each prediction task, we evaluated the model's performance using classical and generalizability evaluation. For classical evaluation, we split the data into training (80%) and testing (20%). For generalizability evaluation, we split the data based on the healthcare system. We used the area under the curve (AUC) to assess performance for each evaluation. We compared results to a benchmark model (i.e. LASSO logistic regression). RESULTS: For classical performance, the DL model outperformed the benchmark model for early surgery with an AUC of 0.725 compared to 0.597. For late surgery, the DL model outperformed the benchmark model with an AUC of 0.655 compared to 0.635. For generalizability performance, the DL model outperformed the benchmark model for early surgery. For late surgery, the benchmark model outperformed the DL model. CONCLUSIONS: For early surgery, the DL model was preferred for classical and generalizability evaluation. However, for late surgery, the benchmark and DL model had comparable performance. Depending on the prediction task, the balance of performance may shift between DL and a conventional ML method. As a result, thorough assessment is needed to quantify the value of DL, a relatively computationally expensive, time-consuming and less interpretable method.

Noncoding rare variants in PANX3 are associated with chronic back pain.

ABSTRACT: Back pain is the leading cause of years lived with disability worldwide, yet surprisingly, little is known regarding the biology underlying this condition. The impact of genetics is known for chronic back pain: its heritability is estimated to be at least 40%. Large genome-wide association studies have shown that common variation may account for up to 35% of chronic back pain heritability; rare variants may explain a portion of the heritability not explained by common variants. In this study, we performed the first gene-based association analysis of chronic back pain using UK Biobank imputed data including rare variants with moderate imputation quality. We discovered 2 genes, SOX5 and PANX3 , influencing chronic back pain. The SOX5 gene is a well-known back pain gene. The PANX3 gene has not previously been described as having a role in chronic back pain. We showed that the association of PANX3 with chronic back pain is driven by rare noncoding intronic polymorphisms. This result was replicated in an independent sample from UK Biobank and validated using a similar phenotype, dorsalgia, from FinnGen Biobank. We also found that the PANX3 gene is associated with intervertebral disk disorders. We can speculate that a possible mechanism of action of PANX3 on back pain is due to its effect on the intervertebral disks.

Estimating individualized treatment effects using a risk-modeling approach: an application to epidural steroid injections for lumbar spinal stenosis.

ABSTRACT: Conventional "1-variable-at-a-time" analyses to identify treatment effect modifiers are often underpowered and prone to false-positive results. This study used a "risk-modeling" approach guided by the Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement framework: (1) developing and validating a multivariable model to estimate predicted future back-related functional limitations as measured by the Roland-Morris Disability Questionnaire (RMDQ) and (2) stratifying patients from a randomized controlled trial (RCT) of lumbar epidural steroid injections (LESIs) for the treatment of lumbar spinal stenosis into subgroups with different individualized treatment effects on RMDQ scores at the 3-week follow-up. Model development and validation were conducted in a cohort (n = 3259) randomly split into training and testing sets in a 4:1 ratio. The model was developed in the testing set using linear regression with least absolute shrinkage and selection regularization and 5-fold cross-validation. The model was then applied in the testing set and subsequently in patients receiving the control treatment in the RCT of LESI. R2 values in the training set, testing set, and RCT were 0.38, 0.32, and 0.34, respectively. There was statistically significant modification ( P = 0.03) of the LESI treatment effect according to predicted risk quartile, with clinically relevant LESI treatment effect point estimates in the 2 quartiles with greatest predicted risk (-3.7 and -3.3 RMDQ points) and no effect in the lowest 2 quartiles. A multivariable risk-modeling approach identified subgroups of patients with lumbar spinal stenosis with a clinically relevant treatment effect of LESI on back-related functional limitations.

Improving Power and Accuracy in Randomized Controlled Trials of Pain Treatments by Accounting for Concurrent Analgesic Use.

The 0 to 10 numeric rating scale of pain intensity is a standard outcome in randomized controlled trials (RCTs) of pain treatments. For individuals taking analgesics, there may be a disparity between "observed" pain intensity (pain intensity with concurrent analgesic use) and pain intensity without concurrent analgesic use (what the numeric rating scale would be had analgesics not been taken). Using a contemporary causal inference framework, we compare analytic methods that can potentially account for concurrent analgesic use, first in statistical simulations, and second in analyses of real (non-simulated) data from an RCT of lumbar epidural steroid injections. The default analytic method was ignoring analgesic use, which is the most common approach in pain RCTs. Compared to ignoring analgesic use and other analytic methods, simulations showed that a quantitative pain and analgesia composite outcome based on adding 1.5 points to pain intensity for those who were taking an analgesic (the QPAC1.5) optimized power and minimized bias. Analyses of real RCT data supported the results of the simulations, showing greater power with analysis of the QPAC1.5 as compared to ignoring analgesic use and most other methods examined. We propose alternative methods that should be considered in the analysis of pain RCTs. PERSPECTIVE: This article presents the conceptual framework behind a new quantitative pain and analgesia composite outcome, the QPAC1.5, and the results of statistical simulations and analyses of trial data supporting improvements in power and bias using the QPAC1.5. Methods of this type should be considered in the analysis of pain RCTs.

Consensus for Statements Regarding a Definition for Spinal Osteoarthritis for Use in Research and Clinical Practice: A Delphi Study.

OBJECTIVE: To determine consensus among an international, multidisciplinary group of experts regarding definitions of spinal osteoarthritis for research and for clinical practice. METHODS: A 15-member, multidisciplinary steering committee generated 117 statements for a 3-round Delphi study. Experts in back pain and/or osteoarthritis were identified and invited to participate. In round 1, participants could propose additional statements for voting. All statements were rated on a 1-9 Likert scale, and consensus was set at ≥70% of respondents agreeing or disagreeing with the statement and <15% of respondents providing the opposite response. RESULTS: In total, 255 experts from 11 different professional backgrounds were invited. From 173 available experts, 116 consented to participate. In round 1, 103 participants completed the survey, followed by 85 of 111 participants in round 2 (77%) and 87 of 101 participants in round 3 (86%). One-third of participants were from Europe (30%), most were male (58%), one-fifth were physical therapists (21%), and over one-third had been in their profession for 11-20 years (35%). Of 131 statements, consensus was achieved for 71 statements (54%): 53 in agreement (75%) and 18 in disagreement (25%). CONCLUSION: Although there was consensus for statements for definitions of spinal osteoarthritis that were analogous to definitions of osteoarthritis in appendicular joints, a future definition still needs refinement. Importantly, this Delphi highlighted that a future definition should be considered across a spectrum of structural changes and patient symptoms and expressed on a progressive scale.

Modelling time-varying volatility using GARCH models: evidence from the Indian stock market.

Background: In this study, we examined the volatility of the Indian stock market from 2008 to 2021. Owing to the financial crisis, volatility forecasting of the Indian stock market has become crucial for economic and financial analysts. An empirical study of the returns of the NSE indices revealed an autoregressive conditional heteroskedastic trend in the Indian stock market. Methods: Using GARCH 1, 1 (generalized autoregressive conditional heteroskedasticity) and FIGARCH (fractionally integrated GARCH), we examine investor behaviour and the persistence of long-term volatility. Results: The empirical findings of the estimated models suggest that shocks persist for a long time in NSE returns. Furthermore, bad news has a greater impact on stock volatility than good news. The return on assets is stable but highly volatile, even though the Indian economy has experienced the global crash to some extent. Conclusions: Models of volatility derived from the GARCH equation provide accurate forecasts and are useful for portfolio allocation, performance measurement, and option valuation.