Pedro Saramago

Bio: Pedro Saramago is an academic researcher from University of York. The author has contributed to research in topics: Cost effectiveness & Medicine. The author has an hindex of 12, co-authored 31 publications receiving 530 citations.

Acupuncture for chronic pain: an individual patient data meta-analysis

Abstract: BACKGROUND Although acupuncture is widely used for chronic pain, there remains considerable controversy as to its value. We aimed to determine the effect size of acupuncture for 4 chronic pain conditions: back and neck pain, osteoarthritis, chronic headache, and shoulder pain. METHODS We conducted a systematic review to identify randomized controlled trials (RCTs) of acupuncture for chronic pain in which allocation concealment was determined unambiguously to be adequate. Individual patient data meta-analyses were conducted using data from 29 of 31 eligible RCTs, with a total of 17 922 patients analyzed. RESULTS In the primary analysis, including all eligible RCTs, acupuncture was superior to both sham and no-acupuncture control for each pain condition (P < .001 for all comparisons). After exclusion of an outlying set of RCTs that strongly favored acupuncture, the effect sizes were similar across pain conditions. Patients receiving acupuncture had less pain, with scores that were 0.23 (95% CI, 0.13-0.33), 0.16 (95% CI, 0.07-0.25), and 0.15 (95% CI, 0.07-0.24) SDs lower than sham controls for back and neck pain, osteoarthritis, and chronic headache, respectively; the effect sizes in comparison to no-acupuncture controls were 0.55 (95% CI, 0.51-0.58), 0.57 (95% CI, 0.50-0.64), and 0.42 (95% CI, 0.37-0.46) SDs. These results were robust to a variety of sensitivity analyses, including those related to publication bias. CONCLUSIONS Acupuncture is effective for the treatment of chronic pain and is therefore a reasonable referral option. Significant differences between true and sham acupuncture indicate that acupuncture is more than a placebo. However, these differences are relatively modest, suggesting that factors in addition to the specific effects of needling are important contributors to the therapeutic effects of acupuncture.

Mixed treatment comparisons using aggregate and individual participant level data.

Abstract: Mixed treatment comparisons (MTC) extend the traditional pair-wise meta-analytic framework to synthesize information on more than two interventions. Although most MTCs use aggregate data (AD), a proportion of the evidence base might be available at the individual level (IPD). We develop a series of novel Bayesian statistical MTC models to allow for the simultaneous synthesis of IPD and AD, potentially incorporating study and individual level covariates. The effectiveness of different interventions to increase the provision of functioning smoke alarms in households with children was used as a motivating dataset. This included 20 studies (11 AD and 9 IPD), including 11 500 participants. Incorporating the IPD into the network allowed the inclusion of information on subject level covariates, which produced markedly more accurate treatment-covariate interaction estimates than an analysis solely on the AD from all studies. Including evidence at the IPD level in the MTC is desirable when exploring participant level covariates; even when IPD is available only for a fraction of the studies. Such modelling may not only reduce inconsistencies within networks of trials but also assist the estimation of intervention subgroup effects to guide more individualised treatment decisions.

VenUS IV (Venous leg Ulcer Study IV) - compression hosiery compared with compression bandaging in the treatment of venous leg ulcers: a randomised controlled trial, mixed-treatment comparison and decision-analytic model.

Abstract: Compression is an effective and recommended treatment for venous leg ulcers. Although the four-layer bandage (4LB) is regarded as the gold standard compression system, it is recognised that the amount of compression delivered might be compromised by poor application technique. Also the bulky nature of the bandages might reduce ankle or leg mobility and make the wearing of shoes difficult. Two-layer compression hosiery systems are now available for the treatment of venous leg ulcers. Two-layer hosiery (HH) may be advantageous, as it has reduced bulk, which might enhance ankle or leg mobility and patient adherence. Some patients can also remove and reapply two-layer hosiery, which may encourage self-management and could reduce costs. However, little robust evidence exists about the effectiveness of two-layer hosiery for ulcer healing and no previous trials have compared two-layer hosiery delivering ‘high’ compression with the 4LB.

Point prevalence of complex wounds in a defined United Kingdom population.

Abstract: Complex wounds (superficial-, partial-, or full-thickness skin loss wounds healing by secondary intention) are common; however, there is a lack of high-quality, contemporary epidemiological data. This paper presents point prevalence estimates for complex wounds overall as well as for individual types. A multiservice, cross-sectional survey was undertaken across a United Kingdom city (Leeds, population 751,485) during 2 weeks in spring of 2011. The mean age of people with complex wounds was approximately 70 years, standard deviation 19.41. The point prevalence of complex wounds was 1.47 per 1,000 of the population, 95% confidence interval 1.38 to 1.56. While pressure ulcers and leg ulcers were the most frequent, one in five people in the sample population had a less common wound type. Surveys confined to people with specific types of wound would underestimate the overall impact of complex wounds on the population and health care resources.

Percutaneous Revascularization for Ischemic Left Ventricular Dysfunction.

Abstract: BACKGROUND Whether revascularization by percutaneous coronary intervention (PCI) can improve event-free survival and left ventricular function in patients with severe ischemic left ventricular systolic dysfunction, as compared with optimal medical therapy (i.e., individually adjusted pharmacologic and device therapy for heart failure) alone, is unknown. METHODS We randomly assigned patients with a left ventricular ejection fraction of 35% or less, extensive coronary artery disease amenable to PCI, and demonstrable myocardial viability to a strategy of either PCI plus optimal medical therapy (PCI group) or optimal medical therapy alone (optimal-medical-therapy group). The primary composite outcome was death from any cause or hospitalization for heart failure. Major secondary outcomes were left ventricular ejection fraction at 6 and 12 months and quality-of-life scores. RESULTS A total of 700 patients underwent randomization - 347 were assigned to the PCI group and 353 to the optimal-medical-therapy group. Over a median of 41 months, a primary-outcome event occurred in 129 patients (37.2%) in the PCI group and in 134 patients (38.0%) in the optimal-medical-therapy group (hazard ratio, 0.99; 95% confidence interval [CI], 0.78 to 1.27; P = 0.96). The left ventricular ejection fraction was similar in the two groups at 6 months (mean difference, -1.6 percentage points; 95% CI, -3.7 to 0.5) and at 12 months (mean difference, 0.9 percentage points; 95% CI, -1.7 to 3.4). Quality-of-life scores at 6 and 12 months appeared to favor the PCI group, but the difference had diminished at 24 months. CONCLUSIONS Among patients with severe ischemic left ventricular systolic dysfunction who received optimal medical therapy, revascularization by PCI did not result in a lower incidence of death from any cause or hospitalization for heart failure. (Funded by the National Institute for Health and Care Research Health Technology Assessment Program; REVIVED-BCIS2 ClinicalTrials.gov number, NCT01920048.).

Is network meta-analysis as valid as standard pairwise meta-analysis? It all depends on the distribution of effect modifiers.

Abstract: In the last decade, network meta-analysis of randomized controlled trials has been introduced as an extension of pairwise meta-analysis. The advantage of network meta-analysis over standard pairwise meta-analysis is that it facilitates indirect comparisons of multiple interventions that have not been studied in a head-to-head fashion. Although assumptions underlying pairwise meta-analyses are well understood, those concerning network meta-analyses are perceived to be more complex and prone to misinterpretation. In this paper, we aim to provide a basic explanation when network meta-analysis is as valid as pairwise meta-analysis. We focus on the primary role of effect modifiers, which are study and patient characteristics associated with treatment effects. Because network meta-analysis includes different trials comparing different interventions, the distribution of effect modifiers cannot only vary across studies for a particular comparison (as with standard pairwise meta-analysis, causing heterogeneity), but also between comparisons (causing inconsistency). If there is an imbalance in the distribution of effect modifiers between different types of direct comparisons, the related indirect comparisons will be biased. If it can be assumed that this is not the case, network meta-analysis is as valid as pairwise meta-analysis. The validity of network meta-analysis is based on the underlying assumption that there is no imbalance in the distribution of effect modifiers across the different types of direct treatment comparisons, regardless of the structure of the evidence network.

Evidence Synthesis for Decision Making 3 Heterogeneity—Subgroups, Meta-Regression, Bias, and Bias-Adjustment

Abstract: In meta-analysis, between-study heterogeneity indicates the presence of effect-modifiers and has implications for the interpretation of results in cost-effectiveness analysis and decision making A distinction is usually made between true variability in treatment effects due to variation in patient populations or settings and biases related to the way in which trials were conducted Variability in relative treatment effects threatens the external validity of trial evidence and limits the ability to generalize from the results; imperfections in trial conduct represent threats to internal validity We provide guidance on methods for meta-regression and bias-adjustment, in pairwise and network metaanalysis (including indirect comparisons), using illustrative examples We argue that the predictive distribution of a treatment effect in a ‘‘new’’ trial may, in many cases, be more relevant to decision making than the distribution of the mean effect Investigators should consider the relative contribution of true variability and random variation due to biases when considering their response to heterogeneity In network meta-analyses, various types of meta-regression models are possible when trial-level effect-modifying covariates are present or suspected We argue that a model with a single interaction term is the one most likely to be useful in a decision-making context Illustrative examples of Bayesian meta-regression against a continuous covariate and meta-regression against ‘‘baseline’’ risk are provided