Knee cartilage change on magnetic resonance imaging: Should we lump or split topographical regions? A 2-year study of data from the osteoarthritis initiative.

OBJECTIVE: We challenge the paradigm that a simplistic approach evaluating anatomic regions (e.g., medial femur or tibia) is ideal for assessing articular cartilage loss on magnetic resonance (MR) imaging. We used a data-driven approach to explore whether specific topographical locations of knee cartilage loss may identify novel patterns of cartilage loss over time that current assessment strategies miss. DESIGN: We assessed 60 location-specific measures of articular cartilage on a sample of 99 knees with baseline and 24-month MR images from the Osteoarthritis Initiative, selected as a group with a high likelihood to change. We performed factor analyses of the change in these measures in two ways: (1) summing the measures to create one measure for each of the six anatomically regional-based summary (anatomic regions; e.g., medial tibia) and (2) treating each location separately for a total of 60 measures (location-specific measures). RESULTS: The first analysis produced three factors accounting for 66% of the variation in the articular cartilage changes that occur over 24 months of follow-up: (1) medial tibiofemoral, (2) medial and lateral patellar, and (3) lateral tibiofemoral. The second produced 20 factors accounting for 75% of the variance in cartilage changes. Twelve factors only involved one anatomic region. Five factors included locations from adjoining regions (defined by the first analysis; e.g., medial tibiofemoral). Three factors included articular cartilage loss from disparate locations. CONCLUSIONS: Novel patterns of cartilage loss occur within each anatomic region and across these regions, including in disparate regions. The traditional anatomic regional approach is simpler to implement and interpret but may obscure meaningful patterns of change.

Hemodynamic Response to Oral Vasodilator Therapy in Systemic Sclerosis-Related Pulmonary Hypertension.

PURPOSE: Although classified as group 1 pulmonary arterial hypertension (PAH), patients with systemic sclerosis-related pulmonary hypertension (SSc-PH) experience poorer clinical response to PAH therapy and increased mortality compared to those with idiopathic PAH. Due to heterogeneity in phenotypes, identifying patients likely to respond to therapy is challenging. The goal of this study was to determine clinical factors associated with hemodynamic response, defined by a > 20% reduction in pulmonary vascular resistance on repeat right heart catheterization. METHODS: We applied a time-to-event model using a retrospective cohort of 39 patients with precapillary SSc-PH, defined by a mean pulmonary artery pressure of ≥ 25 mmHg and pulmonary arterial wedge pressure (PAWP) ≤ 15 mmHg on right heart catheterization. RESULTS: Patients with PAWP ≤ 8 mmHg were nearly fourfold more likely to achieve a hemodynamic response compared to those with PAWP > 8 mmHg (HR 3.88; 95% CI: 1.20, 12.57); each 1 mmHg increase in PAWP was associated with a decreased hazard for hemodynamic response (HR 0.84; 95% CI: 0.70, 1.00). CONCLUSION: In patients with precapillary SSc-PH, PAWP was associated with time to hemodynamic response, suggesting the importance of subclinical cardiac disease in determining hemodynamic response to oral vasodilator therapy.

Natural Walking Intensity in Persons With Parkinson Disease.

BACKGROUND AND PURPOSE: Few persons with Parkinson disease (PD) appear to engage in moderate-intensity walking associated with disease-modifying health benefits. How much time is spent walking at lower, yet still potentially beneficial, intensities is poorly understood. The purpose of this exploratory, observational study was to describe natural walking intensity in ambulatory persons with PD. METHODS: Accelerometer-derived real-world walking data were collected for more than 7 days at baseline from 82 participants enrolled in a PD clinical trial. Walking intensity was defined according to the number of steps in each active minute (1-19, 20-39, 40-59, 60-79, 80-99, or ≥100 steps). Daily minutes of walking and duration of the longest sustained walking bout were calculated at each intensity. Number of sustained 10 to 19, 20 to 29, and 30-minute bouts and greater at any intensity also were calculated. Values were analyzed in the context of physical activity guidelines. RESULTS: Most daily walking occurred at lower intensities (157.3 ± 58.1 min of 1-19 steps; 81.3 ± 32.6 min of 20-39 steps; 38.2 ± 21.3 min of 40-59 steps; 15.1 ± 11.5 min of 60-79 steps; 7.4 ± 7.0 min of 80-99 steps; 7.3 ± 9.6 min of ≥100 steps). The longest daily sustained walking bout occurred at the lowest intensity level (15.9 ± 5.2 min of 1-19 steps). Few bouts lasting 20 minutes and greater occurred at any intensity. DISCUSSION AND CONCLUSIONS: Despite relatively high daily step counts, participants tended to walk at remarkably low intensity, in bouts of generally short duration, with relatively few instances of sustained walking. The findings reinforced the need for health promotion interventions designed specifically to increase walking intensity.Video Abstract available for more insight from authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A426 ).

A Clinical Decision Tool for Risk Stratifying Patients with Systemic Sclerosis-Related Pulmonary Hypertension.

We devised a scoring system to identify patients with systemic sclerosis (SSc) at risk for pulmonary hypertension (PH) and predict all-cause mortality. Using 7 variables obtained via pulmonary function testing, echocardiography, and computed tomographic chest imaging, we applied the score to a retrospective cohort of 117 patients with SSc. There were 60 (51.3%) who were diagnosed with PH by right heart catheterization. Using a scoring threshold ≥ 0, our decision tool predicted PH with a sensitivity, specificity, and accuracy of 0.87 (95% CI 0.75, 0.94), 0.74 (95% CI 0.60, 0.84), and 0.80 (95% CI 0.72, 0.87), respectively. When adjusted for age at PH diagnosis, sex, and receipt of pulmonary arterial vasodilators, each one-point score increase was associated with an adjusted HR of 1.19 (95% CI 1.05, 1.34) for all-cause mortality. With further validation in external cohorts, our simplified clinical decision tool may better streamline earlier detection of PH in SSc.

One Pill, Once a Day: Simplified Treatment Regimens and Retention in HIV Care.

Simplified drug regimens may improve retention in care for persons with chronic diseases. In April 2013, South Africa adopted a once-daily single-pill human immunodeficiency virus (HIV) treatment regimen as the standard of care, replacing a multiple-pill regimen. Because the regimens had similar biological efficacy, the shift to single-pill therapy offered a real-world test of the impact of simplified drug-delivery mechanisms on patient behavior. Using a quasi-experimental regression discontinuity design, we assessed retention in care among patients starting HIV treatment just before and just after the guideline change. The study included 4,484 patients starting treatment at a large public sector clinic in Johannesburg, South Africa. The share of patients prescribed a single-pill regimen increased by over 40 percentage points between March and April 2013. Initiating treatment after the policy change was associated with 11.7-percentage-points' higher retention at 12 months (95% confidence interval: -2.2, 29.4). Findings were robust to different measures of retention, different bandwidths, and different statistical models. Patients starting treatment early in HIV infection-a key population in the test-and-treat era-experienced the greatest improvements in retention from single-pill regimens.

Calculating power for the Finkelstein and Schoenfeld test statistic for a composite endpoint with two components.

The Finkelstein and Schoenfeld (FS) test is a popular generalized pairwise comparison approach to analyze prioritized composite endpoints (eg, components are assessed in order of clinical importance). Power and sample size estimation for the FS test, however, are generally done via simulation studies. This simulation approach can be extremely computationally burdensome, compounded by increasing number of composite endpoints and with increasing sample size. Here we propose an analytical solution to calculate power and sample size for commonly encountered two-component hierarchical composite endpoints. The power formulas are derived assuming underlying distributions in each of the component outcomes on the population level, which provide a computationally efficient and practical alternative to the standard simulation approach. Monte Carlo simulation results demonstrate that performance of the proposed power formulas are consistent with that of the simulation approach, and have generally desirable objective properties including robustness to mis-specified distributional assumptions. We demonstrate the application of the proposed formulas by calculating power and sample size for the Transthyretin Amyloidosis Cardiomyopathy Clinical Trial.

A comparison of statistical methods to predict the residual lifetime risk.

Lifetime risk measures the cumulative risk for developing a disease over one's lifespan. Modeling the lifetime risk must account for left truncation, the competing risk of death, and inference at a fixed age. In addition, statistical methods to predict the lifetime risk should account for covariate-outcome associations that change with age. In this paper, we review and compare statistical methods to predict the lifetime risk. We first consider a generalized linear model for the lifetime risk using pseudo-observations of the Aalen-Johansen estimator at a fixed age, allowing for left truncation. We also consider modeling the subdistribution hazard with Fine-Gray and Royston-Parmar flexible parametric models in left truncated data with time-covariate interactions, and using these models to predict lifetime risk. In simulation studies, we found the pseudo-observation approach had the least bias, particularly in settings with crossing or converging cumulative incidence curves. We illustrate our method by modeling the lifetime risk of atrial fibrillation in the Framingham Heart Study. We provide technical guidance to replicate all analyses in R.

End-stage renal disease and metalworking fluid exposure.

OBJECTIVE: Despite increasing prevalence of end-stage renal disease (ESRD), little attention has been directed to how occupational exposures may contribute to risk. Our objective was to investigate the relationship between metalworking fluids (MWF) and ESRD in a cohort of 36 703 male autoworkers. METHODS: We accounted for competing risk of death, using the subdistribution hazard approach to estimate subhazard ratios (sHRs) and 95% CIs in models with cubic splines for cumulative exposure to MWF (straight, soluble or synthetic). RESULTS: Based on 501 ESRD cases and 13 434 deaths, we did not observe an association between MWF and ESRD overall. We observed modest associations between MWF and ESRD classification of glomerulonephritis and diabetic nephropathy. For glomerulonephritis, the 60th percentile of straight MWF was associated with an 18% increased subhazard (sHR=1.18, 95% CI: 0.99 to 1.41). For diabetic nephropathy, the subhazard increased 28% at the 60th percentile of soluble MWF (sHR=1.28, 95% CI: 1.00 to 1.64). Differences by race suggest that black males may have higher disease rates following MWF exposure. CONCLUSIONS: Exposure to straight and soluble MWF may be related to ESRD classification, though this relationship should be further examined.

Association of Back Pain with Mortality: a Systematic Review and Meta-analysis of Cohort Studies.

BACKGROUND: Back pain is the most common cause of disability worldwide. While disability generally is associated with greater mortality, the association between back pain and mortality is unclear. Our objective was to examine whether back pain is associated with increased mortality risk and whether this association varies by age, sex, and back pain severity. METHODS: A systematic search of published literature was conducted using PubMed, Web of Science, and Embase databases from inception through March 2019. We included English-language prospective cohort studies evaluating the association of back pain with all-cause mortality with follow-up periods >5 years. Three reviewers independently screened studies, abstracted data, and appraised risk of bias using the Quality in Prognosis Studies (QUIPS) tool. A random-effects meta-analysis estimated combined odds ratios (OR) and 95% confidence intervals (CI), using the most adjusted model from each study. Potential effect modification by a priori hypothesized factors (age, sex, and back pain severity) was evaluated with meta-regression and stratified estimates. RESULTS: We identified eleven studies with 81,337 participants. Follow-up periods ranged from 5 to 23 years. The presence of any back pain, compared to none, was not associated with an increase in mortality (OR, 1.06; 95% CI, 0.97 to 1.16). However, back pain was associated with mortality in studies of women (OR, 1.22; 95% CI, 1.02 to 1.46) and among adults with more severe back pain (OR, 1.26; 95% CI, 1.14 to 1.40). CONCLUSION: Back pain was associated with a modest increase in all-cause mortality among women and those with more severe back pain.

Use of the likelihood reduction factor in a path analysis framework to quantify surrogacy in clinical trials.

In clinical trials, surrogate endpoints are useful when the endpoint of interest is difficult to measure or requires a long follow-up time. Current methodology for validating surrogate endpoints encounters challenges in the presence of collinearity between the treatment and surrogate endpoint, which is often present in clinical trials. The proposed methods adapt current methodology in the structural framework of path analysis to quantify the validity of a surrogate endpoint. The path analysis framework provides an improved interpretation of treatment effect. Through derivation and simulation we show the proposed path likelihood reduction factor (LRF P ), is less biased and more robust than current methodology in cases of collinearity between the treatment and surrogate endpoint, with notable improvement when surrogacy is weak or moderate. LRF P can be expanded to evaluate multiple correlated surrogate endpoints, which as shown through simulation, is also less biased and more robust than current methodology in the case of collinearity between the treatment and surrogate endpoint.

Revisiting methods for modeling longitudinal and survival data: Framingham Heart Study.

BACKGROUND: Statistical methods for modeling longitudinal and time-to-event data has received much attention in medical research and is becoming increasingly useful. In clinical studies, such as cancer and AIDS, longitudinal biomarkers are used to monitor disease progression and to predict survival. These longitudinal measures are often missing at failure times and may be prone to measurement errors. More importantly, time-dependent survival models that include the raw longitudinal measurements may lead to biased results. In previous studies these two types of data are frequently analyzed separately where a mixed effects model is used for the longitudinal data and a survival model is applied to the event outcome. METHODS: In this paper we compare joint maximum likelihood methods, a two-step approach and a time dependent covariate method that link longitudinal data to survival data with emphasis on using longitudinal measures to predict survival. We apply a Bayesian semi-parametric joint method and maximum likelihood joint method that maximizes the joint likelihood of the time-to-event and longitudinal measures. We also implement the Two-Step approach, which estimates random effects separately, and a classic Time Dependent Covariate Model. We use simulation studies to assess bias, accuracy, and coverage probabilities for the estimates of the link parameter that connects the longitudinal measures to survival times. RESULTS: Simulation results demonstrate that the Two-Step approach performed best at estimating the link parameter when variability in the longitudinal measure is low but is somewhat biased downwards when the variability is high. Bayesian semi-parametric and maximum likelihood joint methods yield higher link parameter estimates with low and high variability in the longitudinal measure. The Time Dependent Covariate method resulted in consistent underestimation of the link parameter. We illustrate these methods using data from the Framingham Heart Study in which lipid measurements and Myocardial Infarction data were collected over a period of 26 years. CONCLUSIONS: Traditional methods for modeling longitudinal and survival data, such as the time dependent covariate method, that use the observed longitudinal data, tend to provide downwardly biased estimates. The two-step approach and joint models provide better estimates, although a comparison of these methods may depend on the underlying residual variance.

Are Mobile Persons With Parkinson Disease Necessarily More Active?

BACKGROUND AND PURPOSE: Walking activity in persons with Parkinson disease (PD) is important for preventing functional decline. The contribution of walking activity to home and community mobility in PD is poorly understood. METHODS: Cross-sectional baseline data (N = 69) were analyzed from a randomized controlled PD trial. The Life-Space Assessment (LSA) quantified the extent, frequency, and independence across 5 expanding levels of home and community mobility, producing individual subscores and a total score. Two additional summed scores were used to represent mobility within (Levels 1-3) and beyond (Levels 4-5) neighborhood limits. An accelerometer measured walking activity for 7 days. Regression and correlation analyses evaluated relationships between daily steps and mobility scores. Mann-Whitney U tests secondarily compared differences in mobility scores between the active and sedentary groups. RESULTS: Walking activity contributed significantly to the summed Level 1-3 score (ß = 0.001, P = 0.004) but not to the summed Level 4-5 (ß = 0.001, P = 0.33) or total (ß = 0.002, P = 0.07) scores. Walking activity was significantly related to Level 1 (ρ = 0.336, P = 0.005), Level 2 (ρ = 0.307, P = 0.010), and Level 3 (ρ = 0.314, P = 0.009) subscores. Only the summed Level 1-3 score (P = 0.030) was significantly different between the active and sedentary groups. DISCUSSION AND CONCLUSIONS: Persons with PD who demonstrated greater mobility beyond the neighborhood were not necessarily more active; walking activity contributed more so to home and neighborhood mobility. Compared with LSA total score, the Level 1-3 summed score may be a more useful participation-level measure for assessing the impact of changes in walking activity.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A349).

Daily Walking and the Risk of Knee Replacement Over 5 Years Among Adults With Advanced Knee Osteoarthritis in the United States.

OBJECTIVE: To examine the association of the volume and intensity of daily walking at baseline with the risk of knee replacement (KR) over 5 years in adults with advanced structural knee osteoarthritis. DESIGN: Prospective, longitudinal, and multicenter observational study. SETTING: Osteoarthritis Initiative study with follow-up from 2008-2015. PARTICIPANTS: Community-dwelling adults with or at risk of knee osteoarthritis were recruited from 4 sites in the United States (N=516; mean age, 67.7±8.6y; body mass index, 29.3±4.7 kg/m2; 52% female). We included participants with advanced structural disease, without KR and had valid daily walking data (quantified using Actigraph GT1M), at baseline. INTERVENTIONS: Not applicable. MAIN OUTCOMES: KR. Walking volume was measured as steps/day and intensity as minutes/day spent not walking (0 steps/min) and walking at very light (1-49 steps/min), light (50-100 steps/min), or moderate (>100 steps/min) intensities. To examine the relationship of walking volume and intensity with the risk of KR, we calculated hazard ratios (HRs) and 95% confidence intervals (CIs) adjusting for covariates. RESULTS: Of 516 adults with advanced structural disease, 88 received a KR over 5 years (17%). Walking an additional 1000 steps/d was not associated with the risk of KR (adjusted HR=0.95; 95% CI, 0.84-1.04). Statistically, replacing 10 min/d of very light and light walking with 10 min/d of moderate walking reduced the risk of KR incidence by 35% and 37%, respectively (adjusted HR=0.65, 95% CI, 0.45-0.94, for very light and adjusted HR=0.63; 95% CI, 0.40-1.00, for light). CONCLUSIONS: Daily walking volume and intensity did not increase KR risk over 5 years and may be protective in some cases in adults with advanced structural knee osteoarthritis.

Does cartilage loss cause pain in osteoarthritis and if so, how much?

OBJECTIVES: Although treatment development in osteoarthritis (OA) focuses on chondroprotection, it is unclear how much preventing cartilage loss reduces joint pain. It is also unclear how nociceptive tissues may be involved. METHODS: Using data from the Osteoarthritis Initiative, we quantified the relation between cartilage loss and worsening knee pain after adjusting for bone marrow lesions (BMLs) and synovitis, and examined how much these factors mediated this association. 600 knee MRIs were scored at baseline, 12 months and 24 months for quantitative and semiquantitative measures of OA structural features. We focused on change in medial cartilage thickness using an amount similar to that seen in recent trials. Linear models calculated mean change in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score with cartilage loss, adjusted for baseline BMLs, synovitis and covariates. Mediation analysis tested whether change in synovitis or BMLs mediated the cartilage loss-pain association. We carried out a subanalysis for knees with non-zero baseline WOMAC pain scores and another for non-valgus knees. RESULTS: Cartilage thickness loss was significantly associated with a small degree of worsening in pain over 24 months. For example, a loss of 0.1 mm of cartilage thickness over 2 years was associated with a 0.32 increase in WOMAC pain (scale 0-20). The association of cartilage thickness loss with pain was mediated by synovitis change but not by BML change. Subanalysis results were similar. CONCLUSIONS: Cartilage thickness loss is associated with only a small amount of worsening knee pain, an association mediated in part by worsening synovitis. Demonstrating that chondroprotection reduces knee pain will be extremely challenging and is perhaps unachievable.

Design of the WHIP-PD study: a phase II, twelve-month, dual-site, randomized controlled trial evaluating the effects of a cognitive-behavioral approach for promoting enhanced walking activity using mobile health technology in people with Parkinson-disease.

BACKGROUND: Parkinson disease (PD) is a debilitating and chronic neurodegenerative disease resulting in ambulation difficulties. Natural walking activity often declines early in disease progression despite the relative stability of motor impairments. In this study, we propose a paradigm shift with a "connected behavioral approach" that targets real-world walking using cognitive-behavioral training and mobile health (mHealth) technology. METHODS/DESIGN: The Walking and mHealth to Increase Participation in Parkinson Disease (WHIP-PD) study is a twelve-month, dual site, two-arm, randomized controlled trial recruiting 148 participants with early to mid-stage PD. Participants will be randomly assigned to connected behavioral or active control conditions. Both conditions will include a customized program of goal-oriented walking, walking-enhancing strengthening exercises, and eight in-person visits with a physical therapist. Participants in the connected behavioral condition also will (1) receive cognitive-behavioral training to promote self-efficacy for routine walking behavior and (2) use a mHealth software application to manage their program and communicate remotely with their physical therapist. Active control participants will receive no cognitive-behavioral training and manage their program on paper. Evaluations will occur at baseline, three-, six-, and twelve-months and include walking assessments, self-efficacy questionnaires, and seven days of activity monitoring. Primary outcomes will include the change between baseline and twelve months in overall amount of walking activity (mean number of steps per day) and amount of moderate intensity walking activity (mean number of minutes per day in which > 100 steps were accumulated). Secondary outcomes will include change in walking capacity as measured by the six-minute walk test and ten-meter walk test. We also will examine if self-efficacy mediates change in amount of walking activity and if change in amount of walking activity mediates change in walking capacity. DISCUSSION: We expect this study to show the connected behavioral approach will be more effective than the active control condition in increasing the amount and intensity of real-world walking activity and improving walking capacity. Determining effective physical activity interventions for persons with PD is important for preserving mobility and essential for maintaining quality of life. Clinical trials registration NCT03517371, May 7, 2018. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03517371. Date of registration: May 7, 2018. Protocol version: Original.

Association of Back Pain with All-Cause and Cause-Specific Mortality Among Older Women: a Cohort Study.

BACKGROUND: The impact of back pain on disability in older women is well-understood, but the influence of back pain on mortality is unclear. OBJECTIVE: To examine whether back pain was associated with all-cause and cause-specific mortality in older women and mediation of this association by disability. DESIGN: Prospective cohort study. SETTING: The Study of Osteoporotic Fractures. PARTICIPANTS: Women aged 65 or older. MEASUREMENT: Our primary outcome, time to death, was assessed using all-cause and cause-specific adjusted Cox models. We used a four-category back pain exposure (no back pain, non-persistent, infrequent persistent, or frequent persistent back pain) that combined back pain frequency and persistence across baseline (1986-1988) and first follow-up (1989-1990) interviews. Disability measures (limitations of instrumental activities of daily living [IADL], slow chair stand time, and slow walking speed) from 1991 were considered a priori potential mediators. RESULTS: Of 8321 women (mean age 71.5, SD = 5.1), 4975 (56%) died over a median follow-up of 14.1 years. A higher proportion of women with frequent persistent back pain died (65.8%) than those with no back pain (53.5%). In the fully adjusted model, women with frequent persistent back pain had higher hazard of all-cause (hazard ratio [HR] = 1.24 [95% CI, 1.11-1.39]), cardiovascular (HR = 1.34 [CI, 1.12-1.62]), and cancer (HR = 1.33, [CI 1.03-1.71]) mortality. No association with mortality was observed for other back pain categories. In mediation analyses, IADL limitations explained 47% of the effect of persistent frequent back pain on all-cause mortality, slow chair stand time, and walking speed, explained 27% and 24% (all significant, p < 0.001), respectively. LIMITATIONS: Only white women were included. CONCLUSION: Frequent persistent back pain was associated with increased mortality in older women. Much of this association was mediated by disability.

Adjusted restricted mean survival times in observational studies.

In observational studies with censored data, exposure-outcome associations are commonly measured with adjusted hazard ratios from multivariable Cox proportional hazards models. The difference in restricted mean survival times (RMSTs) up to a pre-specified time point is an alternative measure that offers a clinically meaningful interpretation. Several regression-based methods exist to estimate an adjusted difference in RMSTs, but they digress from the model-free method of taking the area under the survival function. We derive the adjusted RMST by integrating an adjusted Kaplan-Meier estimator with inverse probability weighting (IPW). The adjusted difference in RMSTs is the area between the two IPW-adjusted survival functions. In a Monte Carlo-type simulation study, we demonstrate that the proposed estimator performs as well as two regression-based approaches: the ANCOVA-type method of Tian et al and the pseudo-observation method of Andersen et al. We illustrate the methods by reexamining the association between total cholesterol and the 10-year risk of coronary heart disease in the Framingham Heart Study.

Smoking paradox in the development of psoriatic arthritis among patients with psoriasis: a population-based study.

OBJECTIVES: Smoking is associated with an increased risk of psoriatic arthritis (PsA) in the general population, but not among patients with psoriasis. We sought to clarify the possible methodological mechanisms behind this paradox. METHODS: Using 1995-2015 data from The Health Improvement Network, we performed survival analysis to examine the association between smoking and incident PsA in the general population and among patients with psoriasis. We clarified the paradox using mediation analysis and conducted bias sensitivity analyses to evaluate the potential impact of index event bias and quantify its magnitude from uncontrolled/unmeasured confounders. RESULTS: Of 6.65 million subjects without PsA at baseline, 225 213 participants had psoriasis and 7057 developed incident PsA. Smoking was associated with an increased risk of PsA in the general population (HR 1.27; 95% CI 1.19 to 1.36), but with a decreased risk among patients with psoriasis (HR 0.91; 95% CI 0.84 to 0.99). Mediation analysis showed that the effect of smoking on the risk of PsA was mediated almost entirely through its effect on psoriasis. Bias-sensitivity analyses indicated that even when the relation of uncontrolled confounders to either smoking or PsA was modest (both HRs=~1.5), it could reverse the biased effect of smoking among patients with psoriasis (HR=0.9). CONCLUSIONS: In this large cohort representative of the UK general population, smoking was positively associated with PsA risk in the general population, but negatively associated among patients with psoriasis. Conditioning on a causal intermediate variable (psoriasis) may even reverse the association between smoking and PsA, potentially explaining the smoking paradox for the risk of PsA among patients with psoriasis.

Exploring the variability in Behçet's disease prevalence: a meta-analytical approach.

Background: Surveys of Behçet's disease (BD) have shown substantial geographic variations in prevalence, but some of these differences may result from methodological inconsistencies. This meta-analysis explored the effect of geographic location and study methodology on the prevalence of BD. Methods: We systematically searched the literature in electronic databases and by handsearching to identify population-based prevalence surveys of BD. Studies were eligible if they provided an original population-based prevalence estimate for BD with the number of prevalent cases identified in the study area. Pooled prevalence proportions across all studies were computed by using random effects models based on a Poisson normal distribution. Pre-defined subgroup analyses and meta-regression were used to investigate the effect of covariates on the prevalence proportions. Results: We included 45 reports published from 1974 to 2015 and covering worldwide areas. The pooled estimates of prevalence proportions (expressed as cases/100 000 inhabitants) were 10.3 (95% CI 6.1, 17.7) for all studies and 119.8 (59.8, 239.9) for Turkey, 31.8 (12.9, 78.4) for the Middle East, 4.5 (2.2, 9.4) for Asia and 3.3 (2.1, 5.2) for Europe. Subgroup analyses showed a strikingly greater prevalence for studies with a sample survey design than a census design [82.5 (95% CI 47.3, 143.9) vs 3.6 (2.6, 5.1)]. Metaregression identified study design as an independent covariate significantly affecting BD prevalence proportions. Conclusions: Differences in BD prevalence proportions likely reflect a combination of true geographic variation and methodological artefacts. In particular, use of a sample or census study design may strongly affect the estimated prevalence.