Detecting Heterogeneity of Intervention Effects Using Analysis and Meta-analysis of Differences in Variance Between Trial Arms

Lifting the veil off treatment effect heterogeneity

Clinicians often suspect that a treatment effect can vary across individuals. However, they usually lack "evidence-based" guidance regarding potential heterogeneity of treatment effects (HTE). Potentially actionable HTE is rarely discovered in clinical trials and is widely believed (or rationalized) by researchers to be rare. Conventional statistical methods to test for possible HTE are extremely conservative and tend to reinforce this belief. In truth, though, there is no realistic way to know whether a common, or average, effect estimated from a clinical trial is relevant for all, or even most, patients. This absence of evidence, misinterpreted as evidence of absence, may be resulting in sub-optimal treatment for many individuals. We first summarize the historical context in which current statistical methods for randomized controlled trials (RCTs) were developed, focusing on the conceptual and technical limitations that shaped, and restricted, these methods. In particular, we explain how the common-effect assumption came to be virtually unchallenged. Second, we propose a simple graphical method for exploratory data analysis that can provide useful visual evidence of possible HTE. The basic approach is to display the complete distribution of outcome data rather than relying uncritically on simple summary statistics. Modern graphical methods, unavailable when statistical methods were initially formulated a century ago, now render fine-grained interrogation of the data feasible. We propose comparing observed treatment-group data to "pseudo data" engineered to mimic that which would be expected under a particular HTE model, such as the common-effect model. A clear discrepancy between the distributions of the common-effect pseudo data and the actual treatment-effect data provides prima facie evidence of HTE to motivate additional confirmatory investigation. Artificial data are used to illustrate implications of ignoring heterogeneity in practice and how the graphical method can be useful.

The importance of context (placebo effects) in conservative interventions for musculoskeletal pain: A systematic review and meta-analysis of randomized controlled trials

BACKGROUND AND OBJECTIVE

Contextual effects (e.g. patient expectations) may play a role in treatment effectiveness. This study aimed to estimate the magnitude of contextual effects for conservative, non-pharmacological interventions for musculoskeletal pain conditions. A systematic review and meta-analysis of randomized controlled trials (RCTs) that compared placebo conservative non-pharmacological interventions to no treatment for musculoskeletal pain. The outcomes assessed included pain intensity, physical functioning, health-related quality of life, global rating of change, depression, anxiety and sleep at immediate, short-, medium- and/or long-term follow-up.

DATABASES AND DATA TREATMENT

MEDLINE, EMBASE, CINAHL, Web of Science Core Collection, CENTRAL and SPORTDiscus were searched from inception to September 2021. Trial registry searches, backward and forward citation tracking and searches for prior systematic reviews were completed. The Cochrane risk of bias 2 tool was implemented.

RESULTS

The study included 64 RCTs (N = 4314) out of 8898 records. For pain intensity, a mean difference of (MD: -5.32, 95% confidence interval (CI): -7.20, -3.44, N = 57 studies with 74 outcomes, GRADE: very low) was estimated for placebo interventions. A small effect in favour of the placebo interventions for physical function was estimated (SMD: -0.22, 95% CI: -0.35, -0.09; N = 37 with 48 outcomes, GRADE: very low). Similar results were found for a broad range of patient-reported outcomes. Meta-regression analyses did not explain heterogeneity among analyses.

CONCLUSION

The study found that the contextual effect of non-pharmacological conservative interventions for musculoskeletal conditions is likely to be small. However, given the known effect sizes of recommended evidence-based treatments for musculoskeletal conditions, it may still contribute an important component.

SIGNIFICANCE

Contextual effects of non-pharmacological conservative interventions for musculoskeletal conditions are likely to be small for a broad range of patient-reported outcomes (pain intensity, physical function, quality of life, global rating of change and depression). Contextual effects are unlikely, in isolation, to offer much clinical care. But these factors do have relevance in an overall treatment context as they provide almost 30% of the minimally clinically important difference.

Current evidence on the efficacy of mental health smartphone apps for symptoms of depression and anxiety. A meta-analysis of 176 randomized controlled trials

The mental health care available for depression and anxiety has recently undergone a major technological revolution, with growing interest towards the potential of smartphone apps as a scalable tool to treat these conditions. Since the last comprehensive meta-analysis in 2019 established positive yet variable effects of apps on depressive and anxiety symptoms, more than 100 new randomized controlled trials (RCTs) have been carried out. We conducted an updated meta-analysis with the objectives of providing more precise estimates of effects, quantifying generalizability from this evidence base, and understanding whether major app and trial characteristics moderate effect sizes. We included 176 RCTs that aimed to treat depressive or anxiety symptoms. Apps had overall significant although small effects on symptoms of depression (N=33,567, g=0.28, p<0.001; number needed to treat, NNT=11.5) and generalized anxiety (N=22,394, g=0.26, p<0.001, NNT=12.4) as compared to control groups. These effects were robust at different follow-ups and after removing small sample and higher risk of bias trials. There was less variability in outcome scores at post-test in app compared to control conditions (ratio of variance, RoV=-0.14, 95% CI: -0.24 to -0.05 for depressive symptoms; RoV=-0.21, 95% CI: -0.31 to -0.12 for generalized anxiety symptoms). Effect sizes for depression were significantly larger when apps incorporated cognitive behavioral therapy (CBT) features or included chatbot technology. Effect sizes for anxiety were significantly larger when trials had generalized anxiety as a primary target and administered a CBT app or an app with mood monitoring features. We found evidence of moderate effects of apps on social anxiety (g=0.52) and obsessive-compulsive (g=0.51) symptoms, a small effect on post-traumatic stress symptoms (g=0.12), a large effect on acrophobia symptoms (g=0.90), and a non-significant negative effect on panic symptoms (g=-0.12), although these results should be considered with caution, because most trials had high risk of bias and were based on small sample sizes. We conclude that apps have overall small but significant effects on symptoms of depression and generalized anxiety, and that specific features of apps - such as CBT or mood monitoring features and chatbot technology - are associated with larger effect sizes.

Heterogeneity of treatment response to beta-blockers in the treatment of portal hypertension: A systematic review

BACKGROUND

It has been suggested that a relevant proportion of patients do not respond to nonselective beta-blockers (NSBB)s, which raises questions regarding the need for individualized therapy. The existence of potential heterogeneity in the treatment response can be assessed using the variability ratio (VR) of the outcome measurement (in this case, HVPG) between the treated and placebo groups. We conducted a systematic review and meta-analysis of randomized controlled trials to assess the potential heterogeneity in the portal pressure response to NSBBs.

METHODS

After a systematic search, we quantified the heterogeneity of treatment response with the VR between the treatment and control groups, with VR > 1 indicating potential heterogeneity. We used a similar approach to compare carvedilol with propranolol and statins with placebo.

RESULTS

We identified 18 studies that included 965 patients. A comparison between beta-blockers and placebo showed a pooled VR of 0.99 (95% CI:0.87-1.14), which suggests a homogeneous HVPG response to NSBB at the individual patient level (ie, no evidence to support that some patients responded to beta-blockers and others did not). For the comparison between carvedilol and propranolol, pooled VR was 0.97 (95% CI 0.82-1.14), suggesting that carvedilol achieves a greater average response (rather than an increase in the proportion of responders). There was no evidence of a heterogeneous response to statins.

CONCLUSION

Our analysis did not support the existence of a heterogeneous patient-by-patient response to NSBBs in cirrhosis. These findings challenge the concept of personalized therapy based on portal pressure response and indicate that routine portal pressure measurement may not be necessary to guide NSBB therapy.

Resistance training and inter-interindividual response differences on cardiorespiratory fitness in older adults: An ancillary meta-analysis of randomized controlled trials

Examine true inter-individual response differences (IIRD) as a result of resistance training on cardiorespiratory fitness in older adults. Data from a recent meta-analysis of 22 randomized controlled trials representing 552 men and women (292 resistance training, 260 control) ≥ 60 years of age were included. The primary outcome was cardiorespiratory fitness (VO2max) in ml.kg-1.min-1. Using the inverse variance heterogeneity (IVhet) model, statistically significant treatment effect (resistance training minus control) increases in VO2max in ml.kg-1.min-1 were found (mean, 1.8, 95% CI, 0.4 to 3.3 ml.kg-1.min-1, p = 0.01; Q = 82.8, p < 0.001; I2 = 74.6%, 95% CI, 61.6 to 83.3%; τ 2 =1.1). The 95% prediction interval (PI) was -0.8 to 4.5 ml.kg-1.min-1. However, no statistically significant IIRD was observed (mean, 0.6, 95% CI, -1.1 to 1.4 ml.kg-1.min-1; τ 2 =1.5). The 95% PI was -1.8 to 2.0 ml.kg-1.min-1. In conclusion, while progressive resistance training may increase VO2max in ml.kg-1.min-1, a lack of true resistance-training-associated IIRD exist.

Moderate to Vigorous Intensity Locomotor Training After Stroke: A Systematic Review and Meta-analysis of Mean Effects and Response Variability

BACKGROUND AND PURPOSE

This meta-analysis quantified mean effects of moderate to vigorous intensity locomotor training (LT mv ) on walking outcomes in subacute and chronic stroke, and the magnitude of variability in LT mv response.

METHODS

Databases were searched for randomized trials comparing LT mv with no intervention, nongait intervention, or low-intensity gait training. Comfortable gait speed (CGS), fastest gait speed (FGS), 6-minute walk test (6MWT), walking activity (steps per day), and adverse effect/event (AE) data were extracted. Pooled estimates were calculated for mean changes, AE relative risks, and the standard deviation of response (SD response ) to LT mv versus control groups, stratified by study chronicity where possible.

RESULTS

There were 19 eligible studies (total N = 1096): 14 in chronic stroke (N = 839) and 5 in subacute stroke (N = 257). Compared with control interventions, LT mv yielded significantly greater increases in CGS (chronic, +0.06 m/s [95% confidence interval (CI), 0.01-0.10]; subacute, +0.16 [0.12-0.19]; subacute vs chronic, P = 0.03), FGS (chronic, +0.07 m/s [0.02-0.13]; subacute, +0.21 [0.01, 0.41]; P = 0.04), and 6MWT (chronic, +33 m [24-42]; subacute, +51 [26-77]; P = 0.054) but not steps/day (+260 [-1159 to 1679]). There were no treatment-related serious AEs among 398 LT mv participants in 14 AE-reporting studies. SD response estimates indicated substantial response variability: CGS, 0.11 m/s [0.00-0.15]; FGS, 0.14 m/s [-0.00 to 0.20]; and 6MWT, 41 m [27-51].

DISCUSSION AND CONCLUSIONS

LT mv improves mean walking capacity outcomes in subacute and chronic stroke and does not appear to have high risk of serious harm. Response magnitude varies within and between chronicity subgroups, and few studies have tested effects on daily walking activity or non-serious AEs.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A452 ).

Trial arm outcome variance difference after dropout as an indicator of missing-not-at-random bias in randomized controlled trials

Randomized controlled trials (RCTs) are vulnerable to bias from missing data. When outcomes are missing not at random (MNAR), estimates from complete case analysis (CCA) and multiple imputation (MI) may be biased. There is no statistical test for distinguishing between outcomes missing at random (MAR) and MNAR. Current strategies rely on comparing dropout proportions and covariate distributions, and using auxiliary information to assess the likelihood of dropout being associated with the outcome. We propose using the observed variance difference across trial arms as a tool for assessing the risk of dropout being MNAR in RCTs with continuous outcomes. In an RCT, at randomization, the distributions of all covariates should be equal in the populations randomized to the intervention and control arms. Under the assumption of homogeneous treatment effects and homoskedastic outcome errors, the variance of the outcome will also be equal in the two populations over the course of follow-up. We show that under MAR dropout, the observed outcome variances, conditional on the variables included in the model, are equal across trial arms, whereas MNAR dropout may result in unequal variances. Consequently, unequal observed conditional trial arm variances are an indicator of MNAR dropout and possible bias of the estimated treatment effect. Heterogeneous treatment effects or heteroskedastic outcome errors are another potential cause of observing different outcome variances. We show that for longitudinal data, we can isolate the effect of MNAR outcome-dependent dropout by considering the variance difference at baseline in the same set of patients who are observed at final follow-up. We illustrate our method in simulation for CCA and MI, and in applications using individual-level data and summary data.

Personalized redox biology: Designs and concepts

Personalized interventions are regarded as a next-generation approach in almost all fields of biomedicine, such as clinical medicine, exercise, nutrition and pharmacology. At the same time, an increasing body of evidence indicates that redox processes regulate, at least in part, multiple aspects of human physiology and pathology. As a result, the idea of applying personalized redox treatments to improve their efficacy has gained popularity among researchers in recent years. The aim of the present primer-style review was to highlight some crucial yet underappreciated methodological, statistical, and interpretative concepts within the redox biology literature, while also providing a physiology-oriented perspective on personalized redox biology. The topics addressed are: (i) the critical issue of investigating the potential existence of inter-individual variability; (ii) the importance of distinguishing a genuine and consistent response of a subject from a chance finding; (iii) the challenge of accurately quantifying the effect of a redox treatment when dealing with 'extreme' groups due to mathematical coupling and regression to the mean; and (iv) research designs and analyses that have been implemented in other fields, and can be reframed and exploited in a redox biology context.

Heterogeneous Treatment Effects after Inspiratory Muscle Training during Recovery from Postacute COVID-19 Syndrome

PURPOSE

The objective of this study is to investigate whether heterogeneous treatment effects occur for changes in inspiratory muscle strength, perceived dyspnea, and health-related quality of life after 8 wk of unsupervised home-based inspiratory muscle training (IMT) in adults with postacute coronavirus disease 2019 (COVID-19) syndrome.

METHODS

In total, 147 adults with self-reported prior COVID-19 either completed an 8-wk home-based IMT intervention ( n = 111, 92 females, 48 ± 11 yr, 9.3 ± 3.6 months postacute COVID-19 infection) or acted as "usual care" wait list controls ( n = 36, 34 females, 49 ± 12 yr, 9.4 ± 3.2 months postacute COVID-19 infection).

RESULTS

Applying a Bayesian framework, we found clear evidence of heterogeneity of treatment response for inspiratory muscle strength: the estimated difference between standard deviations (SD) of the IMT and control groups was 22.8 cm H 2 O (75% credible interval (CrI), 4.7-37.7) for changes in maximal inspiratory pressure (MIP) and 86.8 pressure time units (75% CrI, 55.7-116.7) for sustained MIP (SMIP). Conversely, there were minimal differences in the SD between the IMT and the control group for changes in perceived dyspnea and health-related quality of life, providing no evidence of heterogeneous treatment effects. Higher cumulative power during the IMT intervention was related to changes in MIP ( β = 10.9 cm H 2 O (95% CrI, 5.3-16.8) per 1 SD) and SMIP ( β = 63.7 (32.2-95.3) pressure time units per 1 SD), clearly indicating an IMT dose response for changes in inspiratory muscle strength. Older age (>50 yr), a longer time postacute COVID-19 (>3 months), and greater severity of dyspnea at baseline were also associated with smaller improvements in inspiratory muscle strength.

CONCLUSIONS

Heterogeneous individual responses occurred after an 8-wk home-based IMT program in people with postacute COVID-19 syndrome. Consistent with standard exercise theory, larger improvements in inspiratory muscle strength are strongly related to a greater cumulative dose of IMT.

Meta-analysis of variation in sport and exercise science: Examples of application within resistance training research

Meta-analysis has become commonplace within sport and exercise science for synthesising and summarising empirical studies. However, most research in the field focuses upon mean effects, particularly the effects of interventions to improve outcomes such as fitness or performance. It is thought that individual responses to interventions vary considerably. Hence, interest has increased in exploring precision or personalised exercise approaches. Not only is the mean often affected by interventions, but variation may also be impacted. Exploration of variation in studies such as randomised controlled trials (RCTs) can yield insight into interindividual heterogeneity in response to interventions and help determine generalisability of effects. Yet, larger samples sizes than those used for typical mean effects are required when probing variation. Thus, in a field with small samples such as sport and exercise science, exploration of variation through a meta-analytic framework is appealing. Despite the value of embracing and exploring variation alongside mean effects in sport and exercise science, it is rarely applied to research synthesis through meta-analysis. We introduce and evaluate different effect size calculations along with models for meta-analysis of variation using relatable examples from resistance training RCTs.

Inter-individual variability in redox and performance responses after antioxidant supplementation: A randomized double blind crossover study

AIM

We aimed to investigate the inter-individual variability in redox and physiological responses of antioxidant-deficient subjects after antioxidant supplementation.

METHODS

Two hundred individuals were sorted by plasma vitamin C levels. A low vitamin C group (n = 22) and a control group (n = 22) were compared in terms of oxidative stress and performance. Subsequently, the low vitamin C group received for 30 days vitamin C (1 g) or placebo, in randomized, double-blind, crossover fashion, and the effects were examined through a mixed-effects model, while individual responses were calculated.

RESULTS

The low vitamin C group exhibited lower vitamin C (-25 μmol/L; 95%CI[-31.7, -18.3]; p < 0.001), higher F2 -isoprostanes (+17.1 pg/mL; 95%CI[6.5, 27.7]; p = 0.002), impaired VO2max (-8.2 mL/kg/min; 95%CI[-12.8, -3.6]; p < 0.001) and lower isometric peak torque (-41.5 Nm; 95%CI[-61.8, -21.2]; p < 0.001) compared to the control group. Regarding antioxidant supplementation, a significant treatment effect was found in vitamin C (+11.6 μmol/L; 95%CI[6.8, 17.1], p < 0.001), F2 -isoprostanes (-13.7 pg/mL; 95%CI[-18.9, -8.4], p < 0.001), VO2max (+5.4 mL/kg/min; 95%CI[2.7, 8.2], p = 0.001) and isometric peak torque (+18.7; 95%CI[11.8, 25.7 Nm], p < 0.001). The standard deviation for individual responses (SDir) was greater than the smallest worthwhile change (SWC) for all variables indicating meaningful inter-individual variability. When a minimal clinically important difference (MCID) was set, inter-individual variability remained for VO2max , but not for isometric peak torque.

CONCLUSION

The proportion of response was generally high after supplementation (82.9%-95.3%); however, a few participants did not benefit from the treatment. This underlines the potential need for personalized nutritional interventions in an exercise physiology context.

Average Causal Effect Estimation Via Instrumental Variables: the No Simultaneous Heterogeneity Assumption

BACKGROUND

Instrumental variables (IVs) can be used to provide evidence as to whether a treatment has a causal effect on an outcome . Even if the instrument satisfies the three core IV assumptions of relevance, independence, and exclusion restriction, further assumptions are required to identify the average causal effect (ACE) of on . Sufficient assumptions for this include homogeneity in the causal effect of on ; homogeneity in the association of with ; and no effect modification.

METHODS

We describe the no simultaneous heterogeneity assumption, which requires the heterogeneity in the - causal effect to be mean independent of (i.e., uncorrelated with) both and heterogeneity in the - association. This happens, for example, if there are no common modifiers of the - effect and the - association, and the - effect is additive linear. We illustrate the assumption of no simultaneous heterogeneity using simulations and by re-examining selected published studies.

RESULTS

Under no simultaneous heterogeneity, the Wald estimand equals the ACE even if both homogeneity assumptions and no effect modification (which we demonstrate to be special cases of-and therefore stronger than-no simultaneous heterogeneity) are violated.

CONCLUSIONS

The assumption of no simultaneous heterogeneity is sufficient for identifying the ACE using IVs. Since this assumption is weaker than existing assumptions for ACE identification, doing so may be more plausible than previously anticipated.

Effects of resistance training on body weight and body composition in older adults: An inter-individual response difference meta-analysis of randomized controlled trials

Whether true inter-individual response differences (IIRD) occur as a result of resistance training on body weight and body composition in older adults with overweight and obesity is not known. To address this gap, data from a previous meta-analysis representing 587 men and women (333 resistance training, 254 control) ≥ 60 years of age nested in 15 randomized controlled trials of resistance training ≥ 8 weeks were included. Resistance training and control group change outcome standard deviations treated as point estimates for body weight and body composition (percent body fat, fat mass, body mass index in kg.m2, and lean body mass) were used to calculate true IIRD from each study. True IIRD as well as traditional pairwise comparisons were pooled using the inverse-variance (IVhet) model. Both 95% confidence intervals (CI) and prediction intervals (PI) were calculated. While statistically significant improvements were found for body weight and all body composition outcomes (p < 0.05 for all), no statistically significant IIRD was observed for any of the outcomes (p > 0.05 for all) and all 95% PIs overlapped. Conclusions: While resistance training is associated with improvements in body weight and body composition in older adults, the lack of true IIRD suggests that factors other than training response variation (random variation, physiological responses associated with behavioral changes that are not the result of resistance training) are responsible for the observed variation in body weight and body composition.

Advanced methods and implementations for the meta-analyses of animal models: Current practices and future recommendations

Meta-analytic techniques have been widely used to synthesize data from animal models of human diseases and conditions, but these analyses often face two statistical challenges due to complex nature of animal data (e.g., multiple effect sizes and multiple species): statistical dependency and confounding heterogeneity. These challenges can lead to unreliable and less informative evidence, which hinders the translation of findings from animal to human studies. We present a literature survey of meta-analysis using animal models (animal meta-analysis), showing that these issues are not adequately addressed in current practice. To address these challenges, we propose a meta-analytic framework based on multilevel (linear mixed-effects) models. Through conceptualization, formulations, and worked examples, we illustrate how this framework can appropriately address these issues while allowing for testing new questions. Additionally, we introduce other advanced techniques such as multivariate models, robust variance estimation, and meta-analysis of emergent effect sizes, which can deliver robust inferences and novel biological insights. We also provide a tutorial with annotated R code to demonstrate the implementation of these techniques.

Homogeneity in the Instrument-exposure Association and Point Estimation Using Binary Instrumental Variables

BACKGROUND

Interpreting instrumental variable results often requires further assumptions in addition to the core assumptions of relevance, independence, and the exclusion restriction.

METHODS

We assess whether instrument-exposure additive homogeneity renders the Wald estimand equal to the average derivative effect (ADE) in the case of a binary instrument and a continuous exposure.

RESULTS

Instrument-exposure additive homogeneity is insufficient for ADE identification when the instrument is binary, the exposure is continuous, and the effect of the exposure on the outcome is nonlinear on the additive scale. For a binary exposure, the exposure-outcome effect is necessarily additive linear, so the homogeneity condition is sufficient.

CONCLUSIONS

For binary instruments, instrument-exposure additive homogeneity identifies the ADE if the exposure is also binary. Otherwise, additional assumptions (such as additive linearity of the exposure-outcome effect) are required.

Animal pollination increases stability of crop yield across spatial scales

The benefits of animal pollination to crop yield are well known. In contrast, the effects of animal pollination on the spatial or temporal stability (the opposite of variability) of crop yield remain poorly understood. We use meta-analysis to combine variability information from 215 experimental comparisons between animal-pollinated and wind- or self-pollinated control plants in apple, oilseed rape and faba bean. Animal pollination increased yield stability (by an average of 32% per unit of yield) at between-flower, -plant, -plot and -field scales. Evidence suggests this occurs because yield benefits of animal pollination become progressively constrained closer to the maximum potential yield in a given context, causing clustering. The increase in yield stability with animal pollination is greatest when yield benefits of animal pollination are greatest, indicating that managing crop pollination to increase yield also increases yield stability. These additional pollination benefits have not yet been included in economic assessments but provide further justification for policies to protect pollinators.

Are There Interindividual Differences in Anxiety as a Result of Aerobic Exercise Training in Adults With Fibromyalgia? An Ancillary Meta-analysis of Randomized Controlled Trials

OBJECTIVE

To determine whether true interindividual response differences (IIRD) exist with respect to changes in anxiety because of aerobic exercise training in adults with fibromyalgia (FM).

DATA SOURCES

Data from a previous meta-analytical database of randomized controlled trials of exercise in adults with arthritis and other rheumatic diseases.

STUDY SELECTION

Randomized controlled trials limited to aerobic exercise training on anxiety in adults 18 years or older with FM were included.

DATA EXTRACTION

Change outcome SDs treated as point estimates for anxiety were used to calculate true IIRD from each study. In addition, treatment effect data were extracted.

DATA SYNTHESIS

The inverse variance heterogeneity model was used to pool all results. For the 5 studies and 321 participants in which results were pooled, statistically significant treatment effect reductions in anxiety were observed (mean, -0.77 points, 95% CI, -1.25 to -0.77). However, no significant IIRD were found (mean, 0.6 points, 95% CI, -1.2 to 1.5). The 95% prediction interval for true IIRD in a future study was -1.7 to 0.8. The percent chance, ie, probability, of a clinically meaningful difference in variability, was 61.5% (only possibly clinically important).

CONCLUSIONS

The results of the current study suggest that aerobic exercise is associated with reductions in anxiety among adults with fibromyalgia. However, there is currently a lack of convincing evidence to support the notion that true IIRD exist. Therefore, a search for potential mediators and moderators associated with aerobic exercise and changes in anxiety among adults with FM may not be warranted. However, additional research is needed before any true level of certainty can be established. This includes (1) the assessment of IIRD in future randomized controlled trials, (2) randomized controlled trials of longer duration, and (3) an increase in the proportion of men included in randomized controlled trials.

Response variation as a result of tai chi on resting blood pressure in hypertensive adults: An aggregate data meta-analysis

PURPOSE

Determine if inter-individual response differences (IIRD) are present with respect to tai chi as a treatment for high blood pressure in adults with hypertension.

METHODS

Using the aggregate data meta-analytic approach, seven randomized controlled trials (RCTs) representing 503 hypertensive participants from a recent meta-analysis of tai chi on resting systolic blood pressure (SBP) and diastolic blood pressure (DBP) were included. Tai chi and control group change outcome standard deviations treated as point estimates for both resting SBP and DBP were used to calculate true IIRD from each study. The inverse variance heterogeneity (IVhet) model was used to pool results.

RESULTS

Among adults with hypertension, statistically and clinically significant reductions in resting SBP (X‾, -8.68 mmHg, 95% CI, -9.55 to -7.81) and DBP (X‾, -4.42 mmHg, 95% CI, -5.71 to -3.13) were observed as an effect of practicing tai chi. In the same population, neither statistically nor clinically significant true IIRD was observed for resting SBP (X‾, -0.47 mmHg, 95% CI -5.13 to 5.08) while statistically, but not clinically significant differences were observed for resting DBP (X‾, 1.97 mmHg, 95% CI, 1.02 to 2.60).

CONCLUSIONS

The current findings suggest that while reductions in resting SBP and DBP were observed, a search for potential moderators and mediators for tai-chi-associated changes in resting DBP but not SBP may be warranted. However, a need exists for additional well-designed RCTs, including those from other countries, before a greater level of certainty can be established.

Walking and resting blood pressure: An inter-individual response difference meta-analysis of randomized controlled trials

While walking is associated with reductions in resting SBP and DBP, a lack of true IIRD exists, suggesting that factors other than training response variation (random variation, physiological responses associated with behavioral changes that are not the result of walking) are responsible for the observed variation in resting SBP and DBP.

Mendelian randomization

Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and give methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The difference between the assumptions required for MR analysis and other forms of non-interventional epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference.

A Systematic Review Examining the Approaches Used to Estimate Interindividual Differences in Trainability and Classify Individual Responses to Exercise Training

Background: Many reports describe statistical approaches for estimating interindividual differences in trainability and classifying individuals as "responders" or "non-responders." The extent to which studies in the exercise training literature have adopted these statistical approaches remains unclear. Objectives: This systematic review primarily sought to determine the extent to which studies in the exercise training literature have adopted sound statistical approaches for examining individual responses to exercise training. We also (1) investigated the existence of interindividual differences in trainability, and (2) tested the hypothesis that less conservative thresholds inflate response rates compared with thresholds that consider error and a smallest worthwhile change (SWC)/minimum clinically important difference (MCID). Methods: We searched six databases: AMED, CINAHL, EMBASE, Medline, PubMed, and SportDiscus. Our search spanned the aerobic, resistance, and clinical or rehabilitation training literature. Studies were included if they used human participants, employed standardized and supervised exercise training, and either: (1) stated that their exercise training intervention resulted in heterogenous responses, (2) statistically estimated interindividual differences in trainability, and/or (3) classified individual responses. We calculated effect sizes (ES_IR) to examine the presence of interindividual differences in trainability. We also compared response rates (n = 614) across classification approaches that considered neither, one of, or both errors and an SWC or MCID. We then sorted response rates from studies that also reported mean changes and response thresholds (n = 435 response rates) into four quartiles to confirm our ancillary hypothesis that larger mean changes produce larger response rates. Results: Our search revealed 3,404 studies, and 149 were included in our systematic review. Few studies (n = 9) statistically estimated interindividual differences in trainability. The results from these few studies present a mixture of evidence for the presence of interindividual differences in trainability because several ES_IR values lay above, below, or crossed zero. Zero-based thresholds and larger mean changes significantly (both p < 0.01) inflated response rates. Conclusion: Our findings provide evidence demonstrating why future studies should statistically estimate interindividual differences in trainability and consider error and an SWC or MCID when classifying individual responses to exercise training. Systematic Review Registration: [website], identifier [registration number].