Raveendhara R. Bannuru

OARSI guidelines for the non-surgical management of knee osteoarthritis

OBJECTIVE To develop concise, up-to-date, patient-focused, evidence-based, expert consensus guidelines for the management of knee osteoarthritis (OA), intended to inform patients, physicians, and allied healthcare professionals worldwide. METHOD Thirteen experts from relevant medical disciplines (primary care, rheumatology, orthopedics, physical therapy, physical medicine and rehabilitation, and evidence-based medicine), three continents and ten countries (USA, UK, France, Netherlands, Belgium, Sweden, Denmark, Australia, Japan, and Canada) and a patient representative comprised the Osteoarthritis Guidelines Development Group (OAGDG). Based on previous OA guidelines and a systematic review of the OA literature, 29 treatment modalities were considered for recommendation. Evidence published subsequent to the 2010 OARSI guidelines was based on a systematic review conducted by the OA Research Society International (OARSI) evidence team at Tufts Medical Center, Boston, USA. Medline, EMBASE, Google Scholar, Web of Science, and the Cochrane Central Register of Controlled Trials were initially searched in first quarter 2012 and last searched in March 2013. Included evidence was assessed for quality using Assessment of Multiple Systematic Reviews (AMSTAR) criteria, and published criticism of included evidence was also considered. To provide recommendations for individuals with a range of health profiles and OA burden, treatment recommendations were stratified into four clinical sub-phenotypes. Consensus recommendations were produced using the RAND/UCLA Appropriateness Method and Delphi voting process. Treatments were recommended as Appropriate, Uncertain, or Not Appropriate, for each of four clinical sub-phenotypes and accompanied by 1-10 risk and benefit scores. RESULTS Appropriate treatment modalities for all individuals with knee OA included biomechanical interventions, intra-articular corticosteroids, exercise (land-based and water-based), self-management and education, strength training, and weight management. Treatments appropriate for specific clinical sub-phenotypes included acetaminophen (paracetamol), balneotherapy, capsaicin, cane (walking stick), duloxetine, oral non-steroidal anti-inflammatory drugs (NSAIDs; COX-2 selective and non-selective), and topical NSAIDs. Treatments of uncertain appropriateness for specific clinical sub-phenotypes included acupuncture, avocado soybean unsaponfiables, chondroitin, crutches, diacerein, glucosamine, intra-articular hyaluronic acid, opioids (oral and transdermal), rosehip, transcutaneous electrical nerve stimulation, and ultrasound. Treatments voted not appropriate included risedronate and electrotherapy (neuromuscular electrical stimulation). CONCLUSION These evidence-based consensus recommendations provide guidance to patients and practitioners on treatments applicable to all individuals with knee OA, as well as therapies that can be considered according to individualized patient needs and preferences.

2015 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis.

To develop a new evidence‐based, pharmacologic treatment guideline for rheumatoid arthritis (RA).

Therapeutic trajectory of hyaluronic acid versus corticosteroids in the treatment of knee osteoarthritis: a systematic review and meta-analysis.

OBJECTIVE To compare the efficacy of intraarticular hyaluronic acid with corticosteroids for knee osteoarthritis (OA). METHODS Our data sources were Medline, EMBASE, CINAHL, BIOSIS, and the Cochrane database, as well as hand- searched reviews, manuscripts, and supplements. For unpublished data we used author contacts. Randomized trials that reported effects of intraarticular hyaluronic acid versus corticosteroids on knee OA were selected based on inclusion criteria. Two reviewers extracted data independently. Using a random-effects model, we computed effect sizes for pain change from baseline at 2, 4, 8, 12, and 26 weeks. We also performed multivariate analyses accounting for within and between-study covariance. We performed sensitivity analyses for trials that reported intent-to-treat (ITT) analysis and blinding, and directly compared Hyalgan with methylprednisolone. RESULTS The 7 eligible trials included 606 participants. Five reported ITT analyses. At week 2 the effect size was -0.39 (95% confidence interval [95% CI], -0.65, -0.12) favoring corticosteroids; at week 4 it was -0.01 (95% CI -0.23, 0.21) suggesting equal efficacy. At week 8 the effect size was 0.22 (95% CI -0.05, 0.49) favoring hyaluronic acid, and at week 12 it was 0.35 (95% CI 0.03, 0.66) favoring hyaluronic acid. At week 26 the effect size was 0.39 (95% CI 0.18, 0.59), favoring hyaluronic acid. The multivariate analyses and sensitivity analyses generated consistent results. CONCLUSION From baseline to week 4, intraarticular corticosteroids appear to be relatively more effective for pain than intraarticular hyaluronic acid. By week 4, the 2 approaches have equal efficacy, but beyond week 8, hyaluronic acid has greater efficacy. Understanding this trend is useful to clinicians when treating knee OA.

Tai Chi on psychological well-being: systematic review and meta-analysis

BackgroundPhysical activity and exercise appear to improve psychological health. However, the quantitative effects of Tai Chi on psychological well-being have rarely been examined. We systematically reviewed the effects of Tai Chi on stress, anxiety, depression and mood disturbance in eastern and western populations.MethodsEight English and 3 Chinese databases were searched through March 2009. Randomized controlled trials, non-randomized controlled studies and observational studies reporting at least 1 psychological health outcome were examined. Data were extracted and verified by 2 reviewers. The randomized trials in each subcategory of health outcomes were meta-analyzed using a random-effects model. The quality of each study was assessed.ResultsForty studies totaling 3817 subjects were identified. Approximately 29 psychological measurements were assessed. Twenty-one of 33 randomized and nonrandomized trials reported that 1 hour to 1 year of regular Tai Chi significantly increased psychological well-being including reduction of stress (effect size [ES], 0.66; 95% confidence interval [CI], 0.23 to 1.09), anxiety (ES, 0.66; 95% CI, 0.29 to 1.03), and depression (ES, 0.56; 95% CI, 0.31 to 0.80), and enhanced mood (ES, 0.45; 95% CI, 0.20 to 0.69) in community-dwelling healthy participants and in patients with chronic conditions. Seven observational studies with relatively large sample sizes reinforced the beneficial association between Tai Chi practice and psychological health.ConclusionsTai Chi appears to be associated with improvements in psychological well-being including reduced stress, anxiety, depression and mood disturbance, and increased self-esteem. Definitive conclusions were limited due to variation in designs, comparisons, heterogeneous outcomes and inadequate controls. High-quality, well-controlled, longer randomized trials are needed to better inform clinical decisions.

Comparative Effectiveness of Pharmacologic Interventions for Knee Osteoarthritis: A Systematic Review and Network Meta-analysis

Knee osteoarthritis (OA) is a common and progressive joint disease affecting more than 250 million people worldwide (1). It has significant effects on function (2) and considerable societal costs in terms of work loss (3), early retirement, and joint replacement (4). Osteoarthritis is a leading indication for use of prescription drugs, which costs about

Therapeutic trajectory following intra-articular hyaluronic acid injection in knee osteoarthritis – meta-analysis

3000 per year per patient (5). In the absence of effective disease-modifying medical treatments, a range of symptomatic treatments is available. Nonsteroidal anti-inflammatory drugs (NSAIDs) are the most frequently prescribed medicines for OA yet have significant toxicity, especially among the demographic groups in which the disorder is most prevalent (6). Intra-articular (IA) treatments are widely used, although their efficacy and safety remain in question. More knowledge about the comparative efficacy and toxicity of these compounds, which would be helpful for patients, physicians, payers, and policymakers, is needed to formulate rational treatment algorithms for OA. The relative effectiveness of OA treatments is difficult to discern from the literature, in part because few head-to-head comparison studies are available and traditional pairwise meta-analysis cannot integrate all of the evidence from several comparators. Therefore, our goal was to comprehensively review the literature and determine the relative efficacy of the primary knee OA treatments using a network meta-analysis design. Methods Data Sources and Searches We searched MEDLINE, EMBASE, Web of Science, Google Scholar, and the Cochrane Central Register of Controlled Trials from inception to 15 August 2014 (Supplement Table 1). All searches were limited to randomized, controlled trials in humans. No limits were applied for language, publication date, or publication status, and foreign-language papers were translated. We also hand-searched the reference lists of all retrieved studies and conference proceedings of the American Association of Orthopedic Surgeons, American College of Rheumatology, British Society for Rheumatology, European League Against Rheumatism, International League of Associations of Rheumatology, and Osteoarthritis Research Society International. The conference proceedings were searched from January 1990 to August 2014. We attempted to identify unpublished data by searching the Food and Drug Administration registry, ClinicalTrials.gov, product inserts, and pharmaceutical company Web sites, and by contacting experts, study authors, manufacturers, and primary authors of abstracts with incomplete data. Supplement. Data Supplement Study Selection We included all randomized, controlled trials involving adult human participants with clinical or radiologic diagnosis of symptomatic primary knee OA that compared at least 2 interventions of interest and reported extractable data for at least 1 measure of pain, function, or stiffness. On the basis of the treatment recommendations from the latest clinical practice guidelines for knee OA (7, 8) and the current prescription patterns worldwide (6), we included the following interventions and comparators: acetaminophen, diclofenac, ibuprofen, naproxen, celecoxib, IA corticosteroids, IA hyaluronic acid, oral placebo, and IA placebo. We did not include nonrandomized studies because they generally lacked the high quality of the randomized evidence; without individual-participant data, we could not properly adjust effect estimates for potential confounders. Two reviewers independently screened all titles and abstracts identified by the searches. Full manuscripts of studies screened as potentially relevant by either reviewer were obtained and assessed by 2 independent reviewers according to the aforementioned criteria. Any discrepancies were resolved by consensus. Data Extraction and Quality Assessment After developing a data extraction form, we tested it on 10 randomly selected, included studies and refined accordingly. After completing an a priori training exercise, 2 reviewers independently extracted data from each study. The data were reviewed for consistency between the 2 extractors, and any disagreements were resolved by consensus. For each study, data extraction details included design, selection criteria, population characteristics, treatments, outcome measures, length of follow-up, and results. The outcome measures of interest were change from baseline in pain, function, and stiffness scores reported at 3-month follow-up. If 3-month data were not available, we used data from 2 to 6 months (the data point closest to 3 months was given preference). Intention-to-treat analysis data were used whenever available. When an article provided data on more than 1 outcome scale or a different outcome from the same construct, we extracted data from the scale that was highest on the hierarchy of suggested outcomes for meta-analysis of knee OA trials (9). Two independent reviewers assessed individual study quality using the Cochrane risk-of-bias tool, with any discrepancies resolved by consensus (10). We investigated the effect of study quality on results in the sensitivity analysis. Data Synthesis and Analysis Because the studies used different outcome measures, the change from baseline Western Ontario and McMaster Universities OA Index (WOMAC), visual analogue scale (VAS), and Likert scale scores in each study was translated into Hedges g effect sizes (11). Hedges g is defined as the difference in change from baseline between 2 interventions divided by the pooled SD of the differences, with corrections for small sample sizes. To assess potential heterogeneity among the studies, we calculated the between-study variance and examined baseline characteristics of participants, interventions, outcomes, and study quality. Network Meta-analysis A network meta-analysis synthesizes all available evidence within a consistent framework, thereby fully preserving the randomization within each trial (12). It accounts for multiple comparisons within a trial when there are more than 2 treatment groups (1315). This method considers all trials simultaneously and enables integration of direct evidence from head-to-head trials (when they exist) with indirect evidence (obtained from comparisons of treatments through their common reference) (16). To account for the expected clinical and methodological heterogeneity, we used Bayesian hierarchical random-effects models for mixed multiple-treatment comparisons with noninformative prior distributions (Supplement [Data Synthesis and Analysis]) (17, 18). The model contained parameters that described the relative treatment effect of each intervention compared with a common comparator (oral placebo). Other treatment comparisons were derived as differences between model parameters. We assumed a normal likelihood distribution for the effect size. The main assumption behind the validity of network meta-analysis is transitivity (13). This assumption requires that a valid synthesis of studies indirectly comparing 2 treatments (for example, A with C) by way of 2 direct comparisons (for example, A with B and B with C) must include studies that are sufficiently similar in important clinical and methodological characteristics (potential effect modifiers) (19). The populations within the included studies were similar and could be eligible for any of the treatments considered here based on the distributions of effect modifiers (mean age, percentage of women, baseline disease severity, baseline pain scores, duration of disease, and study quality) and inclusion and exclusion criteria of the studies. Another key assumption in a network meta-analysis is consistencythe notion that the direct and indirect estimates of the treatment effects are the same (20). Consistency was assessed using the node-splitting method (Supplement [Data Synthesis and Analysis]) (21). The results were presented graphically to visually assess the agreement between direct and indirect estimates. A value near 0 indicated that the comparisons in the network were consistent. Results were presented as median effect sizes for pain, function, and stiffness along with 95% central credible intervals (CrIs). For improving the clinical interpretability, they were converted back to the natural units of the most commonly used scale (WOMAC VAS, 0 to 100) (22). On the basis of the Osteoarthritis Research Society InternationalOutcome Measures in Rheumatology responder criteria, we prespecified an absolute change of 20 points on a scale of 0 to 100 as clinically significant improvement (23). We performed several sensitivity analyses on the primary outcome of pain to explore potential causes for heterogeneity. Multiple-treatment meta-regression analysis and subgroup analyses were done to assess the effect of study quality, sample size, and type of outcome scale used (WOMAC vs. other) (24). To examine the potential effect of reporting bias, we analyzed pain outcomes in trials reporting only pain; those reporting both pain and function; and those reporting pain, function, and stiffness. We also compared the baseline characteristics and study quality measures of these subsets of trials. The Supplement (Data Synthesis and Analysis) provides additional details of the statistical methods used. Role of the Funding Source The Agency for Healthcare Research and Quality had no role in study design, data collection, analysis or interpretation, preparation, review, or approval of the manuscript. The funding agency had no access to the data and did not perform any of the study analyses. Results Of the 4122 citations identified through our literature search, 3625 were excluded through title and abstract screening. Among the 497 full-text reports, 137 studies met inclusion criteria for the network meta-analysis (Appendix Figure). Figure 1 shows the network of all treatment comparisons analyzed for pain; the networks for function and stiffness are shown in the Supplement. Thirteen trials had 3 study group

2015 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis: ACR RA Treatment Recommendations

OBJECTIVE To evaluate the therapeutic trajectory of intra-articular hyaluronic acid (IAHA) vs placebo for knee osteoarthritis (OA). DESIGN Our data sources include Medline, EMBASE, CINAHL, BIOSIS, Web of Science, Google Scholar, Cochrane database; hand searched reviews, manuscripts, and, supplements; author contacts for unpublished data. Randomized trials that reported effects of IAHA vs placebo on knee OA were selected based on inclusion criteria. We computed effect sizes for change from baseline at 4, 8, 12, 16, 20 and 24 weeks, using Bayesian random effects model. We performed multivariate analyses adjusting for correlation between time points. Meta-regressions were performed adjusting for potential confounders. RESULTS The 54 eligible trials included 7545 participants. The conduct and quality of these trials varied in number of aspects. The effect size (ES) favored IAHA by week 4 (0.31; 95% CI 0.17, 0.45), reaching peak at week 8 (0.46; 0.28, 0.65), and then trending downwards, with a residual detectable effect at week 24 (0.21; 0.10, 0.31). This therapeutic trajectory was consistent among the subset of high quality trials and on multivariate analysis adjusting for correlation between time points. CONCLUSIONS Our meta-analysis highlights a therapeutic trajectory of IAHA for knee OA pain over 6 months post-intervention. With this additional perspective, we are able to infer that IAHA is efficacious by 4 weeks, reaches its peak effectiveness at 8 weeks and exerts a residual detectable at 24 weeks. On the other hand, the peak effect size (0.46; 0.28, 0.65), is greater than published effects from other OA analgesics [acetaminophen (ES=0.13; 0.04, 0.22); NSAIDs (ES=0.29; 0.22, 0.35); COX-2 inhibitors (ES=0.44; 0.33, 0.55)]. An effect size above 0.20 is considered to be clinically relevant on an individual patient basis in chronic pain conditions such as knee OA. Thus, its properties could have utility for certain clinical situations, or in combination with other therapies.

Relative efficacy of hyaluronic acid in comparison with NSAIDs for knee osteoarthritis: A systematic review and meta-analysis

To develop a new evidence‐based, pharmacologic treatment guideline for rheumatoid arthritis (RA).

Effectiveness and Implications of Alternative Placebo Treatments: A Systematic Review and Network Meta-analysis of Osteoarthritis Trials

OBJECTIVE To assess the relative efficacy of intra-articular hyaluronic acid (IAHA) in comparison with non-steroidal anti-inflammatory drugs (NSAIDs) for knee osteoarthritis (OA). METHODS We searched Medline, EMBASE, Google Scholar, ISI Web of Science, and Cochrane Database from inception until February 2013. Randomized controlled trials comparing HA with NSAIDs for knee OA were included if they reported at least one pain outcome. Two reviewers abstracted data and determined quality. Outcomes included pain, function, and stiffness. Random-effects meta-analyses were performed. RESULTS Five trials (712 participants) contributed to the pain analysis. Both groups showed improvement from baseline. The analysis found an effect size (ES) of -0.07 (95% CI: -0.24 to 0.10) at trial end, favoring neither treatment. There were no statistically significant differences between the groups at 4 and 12 weeks in function [ES = -0.08 (95% CI: -0.39 to 0.23)] or stiffness [ES = 0.03 (95% CI: -0.27 to 0.34)] analyses based on two trials. Injection site pain was the most common adverse event reported in the HA group, and gastrointestinal adverse events were more common in the NSAIDs group. CONCLUSION This meta-analysis suggests that IAHA is not significantly different from continuous oral NSAIDs at 4 and 12 weeks. Our study detected no safety concerns; however, the included trials had only a short follow-up duration. Given the favorable safety profile of IAHA over NSAIDs, this result suggests that IAHA might be a viable alternative to NSAIDs for knee OA, especially for older patients at greater risk for systemic adverse events.

The Impact of COPD on Management and Outcomes of Patients Hospitalized With Acute Myocardial Infarction: A 10-Year Retrospective Observational Study

Placebo controls are supposedly ineffectual medical therapies that serve as common comparators with which to establish a null baseline and maintain blinding in evaluations of the effectiveness of medical treatments in clinical trials (1, 2). The extent to which alternative modes of administration of placebo treatments can result in real and clinically significant changes has been subject to both hype and controversy (3, 4). One meta-analysis comparing the placebo groups of randomized, controlled trials with control groups in which patients received no treatment found placebo-related benefits to be small to nonexistent across various clinical conditions and outcomes (3). On the other hand, a reanalysis of these studies concluded that in methodologically adequate trials and clinical conditions amenable to placebos, the placebo effect was robust and neared the efficacy of active treatment (4). Finally, the possibility of nocebo effects can create an experimental design that compares active treatment to something worse than nothing (5). Thus, beyond providing a no treatment group, the placebo response itself may be important because trial results and interpretation depend not only on the response to the active drug but also on the magnitude and direction of the response to the placebo. A systematic variation in the magnitude of response according to the type of placebo delivered would have important implications for the interpretation of results of placebo-controlled trials. However, it is not clear whether differential placebo effects actually exist. The ability and need to distinguish between placebo effects have increased with the advent of network meta-analysis; this type of analysis entails a quantitative synthesis of studies on a set of multiple treatments, not all of which are compared with each other in every study. Network meta-analyses estimate treatment effects between all possible pairs of treatments and can then rank them in order of the sizes of their effects. Network meta-analyses that involve different types of placebo control groups often assume that the different placebo groups have similar (null) effects and combine them into a single network node (treatment group) (6). Combination into a single node can lead to misleading results if the placebo components differ in efficacy (7, 8). Comparing network analyses that separate and combine different placebos within a network provides a mechanism to investigate the existence of differential placebo effects. Our recent paper comparing different pharmacologic treatments for knee osteoarthritis suggested that conclusions might be sensitive to the treatment of alternative placebos within a network model (9). In this report, using knee osteoarthritis as an example, we expanded the previous network model to include more placebo interventions and corresponding active treatments and explored the potential importance and influence of differential effects with alternative types of placebos. The current investigation sought to determine whether the different placebo interventions used in knee osteoarthritis trials differ in efficacy and to quantify the effect of differential placebo effects on active-treatment effect estimates. Methods Data Sources We searched MEDLINE, the Cochrane Central Register of Controlled Trials, Web of Science, EMBASE, and Google Scholar from inception to 1 June 2015 (Appendix Table 1). We did not restrict the search according to publication status, date, or language (all relevant nonEnglish-language reports were translated). We translated articles from Chinese, French, German, Japanese, Russian, Spanish, and Turkish. We also manually searched reference lists for all retrieved studies, as well as conference proceedings of the Osteoarthritis Research Society International, the British Society for Rheumatology, the European League Against Rheumatism, the American College of Rheumatology, the American Association of Orthopaedic Surgeons, and the International League of Associations for Rheumatology. We searched conference proceedings from January 1990 to June 2015. Unpublished data were identified by searching ClinicalTrials.gov, the U.S. Food and Drug Administration registry, pharmaceutical company Web sites, and product inserts and by contacting manufacturers, study authors, experts, and primary authors of abstracts reporting incomplete data. Appendix Table 1. Literature Search Strategy (MEDLINE) Study Selection All randomized, controlled trials of adults diagnosed with clinical or radiologic knee osteoarthritis were included if they compared at least 2 interventions of interest and reported extractable data for at least 1 pain measure. On the basis of consultation with research and clinical experts, we included 4 alternative placebo interventions and corresponding active comparators, as follows: oral placebo, topical placebo, intra-articular placebo, oral plus topical placebo, acetaminophen, oral nonselective nonsteroidal anti-inflammatory drugs (NSAIDs) (diclofenac, ibuprofen, naproxen), oral cyclooxygenase-2 (COX-2)selective NSAIDs (celecoxib), topical NSAIDs, intra-articular corticosteroids, and intra-articular hyaluronic acid. Studies investigating complementary and alternative interventions, such as tai chi, acupuncture, sham acupuncture, and surgical therapies, were excluded to reduce substantial anticipated heterogeneity, inconsistency, and documented low methodological quality (10). Two reviewers independently screened titles and abstracts identified by the searches. For studies that either reviewer considered potentially relevant, both reviewers obtained full reports and independently assessed them according to the preceding criteria. Any disagreements were resolved by consensus. Data Extraction and Quality Assessment After developing a data extraction form, we tested it on 10 randomly selected included studies and refined it as necessary. After completion of an a priori training exercise, the same 2 reviewers independently extracted such data as study design, selection criteria, population characteristics, treatments, outcome measures, length of follow-up, Cochrane risk of bias items (11), and results from each study. The reviewers then evaluated the extractions for consistency and resolved any disagreements by consensus. The outcome measure of interest was change in pain scores from baseline to 3-month follow-up. If 3-month data were not available, we selected the pain score from whichever time point was closest to 3 months within the period from 2 to 6 months from baseline. Intention-to-treat data were used whenever available. When a trial provided data on more than 1 scale, we referred to a hierarchy of osteoarthritis-related outcomes and extracted the outcome that was highest on the list (12, 13). Data Synthesis and Analysis Because the studies used different outcome scales (Western Ontario and McMaster Universities Arthritis Index [WOMAC], visual analogue scale, and Likert), the change from baseline in each study was translated into Hedges g effect sizes (14), defined as the difference in change from baseline between 2 interventions divided by the pooled SD of the differences, with a correction for small sample size. To assess potential heterogeneity among the studies, we calculated the between-study variance and also examined baseline characteristics of participants, interventions, outcomes, and study quality. We quantified the differences between the placebo interventions by using a network meta-analysis, which synthesizes the direct and indirect evidence from a network of studies involving 2 or more of the interventions (15). Figure 1 (panel A) depicts the differential placebo network model with 4 placebo nodes. We used multivariable Bayesian hierarchical random-effects models for mixed multiple-treatment comparisons with noninformative prior distributions (16) to account for the expected clinical and methodological heterogeneity. Consistency between the direct and indirect estimates within the network was assessed by using the node-splitting method (17). Results are presented as median effect size along with 95% central credibility intervals (CrIs). To present the results in a more clinically relevant format, we converted them back to the natural units of the most commonly used scale (WOMAC: 0 to 100) (18). An absolute change of 20 points on a 0-to-100 scale was prespecified as clinically significant improvement according to Osteoarthritis Research Society International/Outcome Measures in Rheumatology responder criteria (19). We performed several sensitivity analyses to explore potential factors influencing the placebo effect. Meta-regression analysis was used to assess the effect of presence or absence of blinding, sample size, and randomization ratio of placebo to active treatment (1 to 1 vs. 1 to >1) (20). Because baseline pain scores were reported on a variety of scales, we normalized all these pain scales onto a 0-to-100 scale. We ran the meta-regression analysis on the normalized baseline pain scores. Figure 1. Network of different placebo comparisons. A. Differential placebo effects model. B. Nondifferential combined placebo effects model. Combined placebo = all 4 placebo groups (oral, topical, IA, and oral plus topical) are combined into a single group. Circle size reflects number of participants, and the line width reflects number of direct comparisons. No connecting line between 2 circles indicates that there was no direct comparison between the 2 treatments. COX = cyclooxygenase; IA = intra-articular; NSAID = nonsteroidal anti-inflammatory drug. To assess the implications of ignoring differential placebo effects on apparent treatment effects, we evaluated 1 other network meta-analysis model (nondifferential combined placebo network model) (Figure 1, panel B). This model assumed that all 4 placebos had the same effect, so we combined them into a single group (combined placebo). We compared these results wit