scholarly journals Nocebo effect in multiple system atrophy: systematic review and meta-analysis of placebo-controlled clinical trials

2022 ◽  
Author(s):  
Zi-Xuan Wang ◽  
Nan-Nan Zhang ◽  
Hai-Xia Zhao ◽  
Jie Song
Keyword(s):  
Drug Treatment ◽  
Multiple System Atrophy ◽  
Active Drug ◽  
Neurological Diseases ◽  
Meta Analysis ◽  
Dropout Rate ◽  
Dropping Out ◽  
Nocebo Effect ◽  
Symptomatic Disease ◽  
Disease Modifying

Abstract Background Nocebo effect is prevalent among neurological diseases, resulting in low adherence and treatment outcome. We sought to examine the nocebo effect in randomized controlled trials (RCTs) in multiple system atrophy (MSA). Methods We searched RCTs in MSA from Medline since September, 2021. RCTs for drug treatment conducted in adult MSA patients with more than 5 cases in each treatment arm were included. We assessed the number of dropout due to placebo intolerance. We also did a symptomatic/disease-modifying subgroup analysis based on two different treatment purposes. The STATA software was used for statistical analysis. Overall heterogeneity was assessed using the Cochran Q and I2. Results Data were extracted from 11 RCTs fulfilling our search criteria. Of 540 placebo-treated patients, 64.2% reported at least one adverse event (AE) and 7.5% reported dropout because of AEs. The chance of dropping out because of an AE and experiencing at least one AE did not differ between placebo and active drug treatment arms. Besides, the pooled nocebo dropout rate in the symptomatic subgroup was similar to that of the disease-modifying subgroup. Conclusion In MSA RCTs, nocebo dropout rate was not at a low level among neurological disorders. Nocebo effect was an important reason of dropout because of AE in placebo and active drug treatment arms. Different treatment purposes may not influence nocebo effect.

scholarly journals Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis (Preprint)

2020 ◽  
Author(s):  
Gideon Meyerowitz-Katz ◽  
Sumathy Ravi ◽  
Leonard Arnolda ◽  
Xiaoqi Feng ◽  
Glen Maberly ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Meta Analysis ◽  
Dropout Rate ◽  
Dropout Rates ◽  
Dropping Out ◽  
Future Research ◽  
Controlled Trials ◽  
Qualitative Synthesis ◽  
Attrition Rates ◽  
Central Register

BACKGROUND Chronic disease represents a large and growing burden to the health care system worldwide. One method of managing this burden is the use of app-based interventions; however attrition, defined as lack of patient use of the intervention, is an issue for these interventions. While many apps have been developed, there is some evidence that they have significant issues with sustained use, with up to 98% of people only using the app for a short time before dropping out and/or dropping use down to the point where the app is no longer effective at helping to manage disease. OBJECTIVE Our objectives are to systematically appraise and perform a meta-analysis on dropout rates in apps for chronic disease and to qualitatively synthesize possible reasons for these dropout rates that could be addressed in future interventions. METHODS MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, Cochrane CENTRAL (Central Register of Controlled Trials), and Embase were searched from 2003 to the present to look at mobile health (mHealth) and attrition or dropout. Studies, either randomized controlled trials (RCTs) or observational trials, looking at chronic disease with measures of dropout were included. Meta-analysis of attrition rates was conducted in Stata, version 15.1 (StataCorp LLC). Included studies were also qualitatively synthesized to examine reasons for dropout and avenues for future research. RESULTS Of 833 studies identified in the literature search, 17 were included in the review and meta-analysis. Out of 17 studies, 9 (53%) were RCTs and 8 (47%) were observational trials, with both types covering a range of chronic diseases. The pooled dropout rate was 43% (95% CI 29-57), with observational studies having a higher dropout rate (49%, 95% CI 27-70) than RCTs in more controlled scenarios, which only had a 40% dropout rate (95% CI 16-63). The studies were extremely varied, which is represented statistically in the high degree of heterogeneity (I<sup>2</sup>&gt;99%). Qualitative synthesis revealed a range of reasons relating to attrition from app-based interventions, including social, demographic, and behavioral factors that could be addressed. CONCLUSIONS Dropout rates in mHealth interventions are high, but possible areas to minimize attrition exist. Reducing dropout rates will make these apps more effective for disease management in the long term. CLINICALTRIAL International Prospective Register of Systematic Reviews (PROSPERO) CRD42019128737; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019128737

scholarly journals Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis

10.2196/20283 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e20283
Author(s):  
Gideon Meyerowitz-Katz ◽  
Sumathy Ravi ◽  
Leonard Arnolda ◽  
Xiaoqi Feng ◽  
Glen Maberly ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Meta Analysis ◽  
Dropout Rate ◽  
Dropout Rates ◽  
Dropping Out ◽  
Future Research ◽  
Controlled Trials ◽  
Qualitative Synthesis ◽  
Attrition Rates ◽  
Central Register

Background Chronic disease represents a large and growing burden to the health care system worldwide. One method of managing this burden is the use of app-based interventions; however attrition, defined as lack of patient use of the intervention, is an issue for these interventions. While many apps have been developed, there is some evidence that they have significant issues with sustained use, with up to 98% of people only using the app for a short time before dropping out and/or dropping use down to the point where the app is no longer effective at helping to manage disease. Objective Our objectives are to systematically appraise and perform a meta-analysis on dropout rates in apps for chronic disease and to qualitatively synthesize possible reasons for these dropout rates that could be addressed in future interventions. Methods MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, Cochrane CENTRAL (Central Register of Controlled Trials), and Embase were searched from 2003 to the present to look at mobile health (mHealth) and attrition or dropout. Studies, either randomized controlled trials (RCTs) or observational trials, looking at chronic disease with measures of dropout were included. Meta-analysis of attrition rates was conducted in Stata, version 15.1 (StataCorp LLC). Included studies were also qualitatively synthesized to examine reasons for dropout and avenues for future research. Results Of 833 studies identified in the literature search, 17 were included in the review and meta-analysis. Out of 17 studies, 9 (53%) were RCTs and 8 (47%) were observational trials, with both types covering a range of chronic diseases. The pooled dropout rate was 43% (95% CI 29-57), with observational studies having a higher dropout rate (49%, 95% CI 27-70) than RCTs in more controlled scenarios, which only had a 40% dropout rate (95% CI 16-63). The studies were extremely varied, which is represented statistically in the high degree of heterogeneity (I2>99%). Qualitative synthesis revealed a range of reasons relating to attrition from app-based interventions, including social, demographic, and behavioral factors that could be addressed. Conclusions Dropout rates in mHealth interventions are high, but possible areas to minimize attrition exist. Reducing dropout rates will make these apps more effective for disease management in the long term. Trial Registration International Prospective Register of Systematic Reviews (PROSPERO) CRD42019128737; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019128737

scholarly journals Conditional power of antidepressant network meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lisa Holper
Keyword(s):  
Meta Analysis ◽  
Indirect Evidence ◽  
Dropout Rate ◽  
Conclusive Evidence ◽  
Effect Sizes ◽  
Current Evidence ◽  
Hamilton Depression Scale ◽  
Conditional Power ◽  
Sample Sizes ◽  
Antidepressant Treatments

Abstract Background Conditional power of network meta-analysis (NMA) can support the planning of randomized controlled trials (RCTs) assessing medical interventions. Conditional power is the probability that updating existing inconclusive evidence in NMA with additional trial(s) will result in conclusive evidence, given assumptions regarding trial design, anticipated effect sizes, or event probabilities. Methods The present work aimed to estimate conditional power for potential future trials on antidepressant treatments. Existing evidence was based on a published network of 502 RCTs conducted between 1979-2018 assessing acute antidepressant treatment in major depressive disorder (MDD). Primary outcomes were efficacy in terms of the symptom change on the Hamilton Depression Scale (HAMD) and tolerability in terms of the dropout rate due to adverse events. The network compares 21 antidepressants consisting of 231 relative treatment comparisons, 164 (efficacy) and 127 (tolerability) of which are currently assumed to have inconclusive evidence. Results Required sample sizes to achieve new conclusive evidence with at least 80% conditional power were estimated to range between N = 894 - 4190 (efficacy) and N = 521 - 1246 (tolerability). Otherwise, sample sizes ranging between N = 49 - 485 (efficacy) and N = 40 - 320 (tolerability) may require stopping for futility based on a boundary at 20% conditional power. Optimizing trial designs by considering multiple trials that contribute both direct and indirect evidence, anticipating alternative effect sizes or alternative event probabilities, may increase conditional power but required sample sizes remain high. Antidepressants having the greatest conditional power associated with smallest required sample sizes were identified as those on which current evidence is low, i.e., clomipramine, levomilnacipran, milnacipran, nefazodone, and vilazodone, with respect to both outcomes. Conclusions The present results suggest that conditional power to achieve new conclusive evidence in ongoing or future trials on antidepressant treatments is low. Limiting the use of the presented conditional power analysis are primarily due to the estimated large sample sizes which would be required in future trials as well as due to the well-known small effect sizes in antidepressant treatments. These findings may inform researchers and decision-makers regarding the clinical relevance and justification of research in ongoing or future antidepressant RCTs in MDD.

scholarly journals Disease-modifying anti-rheumatic drugs for the management of Takayasu arteritis—a systematic review and meta-analysis

2021 ◽  
Author(s):  
Durga Prasanna Misra ◽  
Upendra Rathore ◽  
Pallavi Patro ◽  
Vikas Agarwal ◽  
Aman Sharma
Keyword(s):  
Systematic Review ◽  
Takayasu Arteritis ◽  
Meta Analysis ◽  
Disease Modifying

scholarly journals AB0116 THE EFFECTS OF DISEASE MODIFYING ANTI-RHEUMATIC DRUGS ON PATIENT REPORTED OUTCOMES; PRELIMINARY RESULTS OF A SYSTEMATIC REVIEW AND NETWORK META-ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1087.1-1087
Author(s):  
M. Van den Dikkenberg, Msc ◽  
N. Luurssen-Masurel ◽  
M. Kuijper ◽  
M. R. Kok ◽  
P. De Jong ◽  
...  
Keyword(s):  
Systematic Review ◽  
Patient Reported Outcomes ◽  
Treatment Effects ◽  
Meta Analysis ◽  
Activity Limitations ◽  
Definitive Answer ◽  
Preliminary Results ◽  
Patient Reported ◽  
Standard Set ◽  
Disease Modifying

Background:The need to involve patient reported outcomes (PROs) in the management of rheumatoid arthritis (RA) increases, since PROs quantify patient relevant outcomes. Although PROs have been incorporated in the core-outcome sets in clinical trials, knowledge about the treatment effects on these PROs is scarce. Therefore, we performed a systematic review on the effects of disease modifying anti-rheumatic drugs (DMARDs), of any type, on relevant PRO domains mentioned in the ICHOM standard set. This might support rheumatologists and RA patients during treatment decisions.Objectives:To get insight in the treatment effects of DMARDs of any type on three PRO domains that matter to patients (pain, activity limitations and fatigue).Methods:A systematic review was performed in Embase, Medline, Web of Science, Cochrane and Google Scholar. Included were all studies that were published before August 2019 and showed DMARD treatment effects in RA on PROs that are part of the ICHOM standard set. Three Bayesian network meta-analyses were performed for the PRO domains pain, activity limitations and fatigue. Preliminary results of DMARDs (in)directly compared to placebo were visualized by forest plots using R.Results:The search strategy yielded n=5974 articles. After selection was performed by 2 independent researchers, n=70 individual articles representing n=53 studies were extracted, over the three PRO domains; pain (n=31), activity limitations (n=41) and fatigue (n=21). In all RCTs, PROs were only reported as secondary or tertiary endpoints. In figure 1, we show the effects on PROs for any type of DMARD investigated compared to placebo. Overall, DMARDs show a greater reduction in pain (standardized mean difference (SMD); -0.97 – -0.22) and most of them in activity limitations (SMD; -0.81 – 0.56). In fatigue, this clear direction is lacking (SMD; -0.86 – 3.5). csDMARDs and anti-TNF seem to perform slightly, but nog significantly, worse than other bDMARDs and tsDMARDs in the first two domains.Conclusion:Within in this systematic review we report a reduction for DMARDs of any type on the domains of pain and activity limitations compared to placebo. However, results are still preliminary and should be interpreted with care. A more comprehensive network analysis might give a more definitive answer which DMARD performs best.Figure 1.Disclosure of Interests:None declared

scholarly journals Outcomes associated with modern treatment paradigms in connective tissue disease (CTD)-associated pulmonary arterial hypertension (PAH): a meta-analysis of randomized controlled trials (RCTs)

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
V McLaughlin ◽  
C Zhao ◽  
J.G Coghlan ◽  
L.S Chung ◽  
S.C Mathai ◽  
...  
Keyword(s):  
Drug Treatment ◽  
Treatment Effect ◽  
Meta Analysis ◽  
Response To Treatment ◽  
Funding Source ◽  
Class Iii ◽  
Inclusion Criteria ◽  
Private Company ◽  
Mortality Event

Abstract Background CTD-PAH has historically represented a PAH subtype with poor prognosis. New therapies, as well as combination therapy approaches targeting multiple pathways have been approved for PAH based on RCTs. CTD-PAH patients comprise a subgroup of the RCT populations and efficacy analyses are based on subgroup analyses which can be less reliable than the overall analysis. We conducted a meta-analysis of RCTs of approved PAH therapies to evaluate outcomes of patients with CTD-PAH. Purpose To use meta-analysis to determine response to treatment in patients with CTD-PAH. Methods The PubMed and EMBASE databases were searched for English-only articles published between January 1, 2000 and November 25, 2019. Inclusion criteria were multicenter RCTs that enrolled adults with WHO group 1 pulmonary hypertension (PAH); enrollment in 2000 or later; long-term clinical morbidity and/or mortality event or 6-minute walk distance (6MWD) as an efficacy endpoint reported for ≥30 patients with CTD-PAH; and evaluation of a US Food and Drug Administration-approved PAH therapy. The primary outcomes were treatment effect as measured by the study time to first morbidity or morality event and change in 6MWD from baseline to between 3–6 months, per the data provided in each article. Results from individual studies were combined using a random-effects model for overall study population (PAH patients) and the subgroup of CTD-PAH patients. Results Ten RCTs (N=4329 PAH patients; n=1263 (29%) with CTD-PAH) met inclusion criteria and were included in the meta-analysis. At baseline, PAH patients had a mean age of 50 years, approximately 78% were female, and approximately 58% had functional class III or IV disease. These characteristics were balanced between treatment and control groups. Baseline 6MWD was 356 m for the overall population and 337 m for patients with CTD-PAH. Five RCTs (N=3172; n=941 with CTD-PAH [30%]) reported hazard ratios (HRs) for time to a morbidity or mortality event by drug treatment and PAH etiology: overall population HR=0.63 (95% confidence interval [CI], 0.56–0.72; P&lt;0.001); CTD-PAH population HR=0.64 (95% CI, 0.51–0.80; P&lt;0.001) (Figure). Nine RCTs reported mean change with drug treatment from baseline to 3 to 6 months in 6MWD for PAH and CTD patients: 33.9 m (95% CI, 21.9–45.9; P&lt;0.001) in the overall population; 20.2 m (95% CI, 10.8–29.7; P&lt;0.001) in CTD-PAH patients. Conclusions The improvement in 6MWD in patients with CTD-PAH is smaller than in those with other types of PAH, perhaps reflecting comorbidities and CTD-induced mobility constraints, independent of their cardiopulmonary capacity. Data from long term clinical morbidity/mortality endpoint studies in this large group of patients with CTD-PAH demonstrate that these patients derive significant benefit from currently available PAH therapies which, in many patients, comprised the addition of a drug targeting a second or third pathway involved in the pathophysiology of PAH. Treatment effect on morbidity/mortality Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Actelion Pharmaceuticals US, Inc.

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