Per protocol analyses produced larger treatment effect sizes than intention to treat: a meta-epidemiological study

Effects of exercise, metformin and their combination on glucose metabolism in individuals with abnormal glycaemic control: a systematic review and network meta-analysis

OBJECTIVE

To compare the efficacy of exercise, metformin and their combination on glucose metabolism in individuals with abnormal glycaemic control.

DESIGN

Systematic review and network meta-analysis.

DATA SOURCES

Embase, Web of Science, PubMed/MEDLINE and SPORTDiscus.

ELIGIBILITY CRITERIA

Randomised controlled trials involving exercise, metformin or their combined treatments in individuals with prediabetes or type 2 diabetes mellitus (T2DM) were included. Outcomes included haemoglobin A1c (HbA1c), 2-hour glucose during oral glucose tolerance test, fasting glucose, fasting insulin and homeostasis model assessment of insulin resistance (HOMA-IR).

RESULTS

407 articles with 410 randomised controlled trials (n=33 802) were included. In prediabetes, the exercise showed greater efficacy than metformin on HbA1c levels (mean difference -0.16%, 95% CI (-0.23 to -0.09) vs -0.10%, 95% CI (-0.21 to 0.02)), 2-hour glucose (-0.68 mmol/L, 95% CI (-0.97 to -0.39) vs 0.01 mmol/L, 95% CI (-0.38 to 0.41)) and HOMA-IR (-0.54, 95% CI (-0.71 to -0.36) vs -0.23, 95% CI (-0.55 to 0.10)), while the efficacy on fasting glucose was comparable (-0.26 mmol/L, 95% CI (-0.32 to -0.19) vs -0.33 mmol/L, 95% CI (-0.45 to -0.21)). In T2DM, metformin was more efficacious than exercise on HbA1c (-0.88%, 95% CI (-1.07 to -0.69) vs -0.48%, 95% CI (-0.58 to -0.38)), 2-hour glucose (-2.55 mmol/L, 95% CI (-3.24 to -1.86) vs -0.97 mmol/L, 95% CI (-1.52 to -0.42)) and fasting glucose (-1.52 mmol/L, 95% CI (-1.73 to -1.31) vs -0.85 mmol/L, 95% CI (-0.96 to -0.74)); exercise+metformin also showed greater efficacy in improving HbA1c (-1.23%, 95% CI (-2.41 to -0.05)) and fasting glucose (-2.02 mmol/L, 95% CI (-3.31 to -0.74)) than each treatment alone. However, the efficacies were modified by exercise modality and metformin dosage.

CONCLUSION

Exercise, metformin and their combination are efficacious in improving glucose metabolism in both prediabetes and T2DM. The efficacy of exercise appears to be superior to metformin in prediabetes, but metformin appears to be superior to exercise in patients with T2DM.

PROSPERO REGISTRATION NUMBER

CRD42023400622.

A Randomized Clinical Trial of Online Social Intelligence Training With Custodial Grandmothers

BACKGROUND AND OBJECTIVES

In this study, we investigated the efficacy of a self-administered, online Social Intelligence Training (SIT) program aimed at enhancing psychological and relational well-being among a nationwide U.S. sample of custodial grandmothers.

RESEARCH DESIGN AND METHODS

A two-arm randomized clinical trial (RCT) was conducted, where 349 grandmothers raising grandchildren aged 11-18 years were assigned to either SIT or an attention control condition (ACC). Participants self-completed online surveys at baseline and immediately postintervention, in addition to follow-ups at 3-, 6-, and 9-month postintervention. First-order latent difference score models were used to compare SIT to ACC, across all times of measurement, along key indicators of psychological and relational well-being on an intent-to-treat basis.

RESULTS

Although SIT was largely superior to ACC at yielding positive results, it appears that it attenuated longitudinal declines that occurred among ACC participants. SIT also exerted stronger effects on relational than psychological outcomes, with perceived relations with grandchildren being the most positively affected.

DISCUSSION AND IMPLICATIONS

Given that the historical time of this RCT unpredictably corresponded with the coronavirus disease 2019 pandemic, we suspect that SIT helped offset declines in psychological and relational well-being that are widely documented to have resulted from the pandemic. Our overall positive findings support future use of the inexpensive and easily delivered SIT program under normal environmental conditions, with the vulnerable and geographically disperse population of custodial grandmothers.

CLINICAL TRIALS REGISTRATION NUMBER

NCT03239977.

Validation and impact of algorithms for identifying variables in observational studies of routinely collected data

BACKGROUND AND OBJECTIVES

Among observational studies of routinely collected health data (RCD) for exploring treatment effects, algorithms are used to identify study variables. However, the extent to which algorithms are reliable and impact the credibility of effect estimates is far from clear. This study aimed to investigate the validation of algorithms for identifying study variables from RCD, and examine the impact of alternative algorithms on treatment effects.

METHODS

We searched PubMed for observational studies published in 2018 that used RCD to explore drug treatment effects. Information regarding the reporting, validation, and interpretation of algorithms was extracted. We summarized the reporting and methodological characteristics of algorithms and validation. We also assessed the divergence in effect estimates given alternative algorithms by calculating the ratio of estimates of the primary vs. alternative analyses.

RESULTS

A total of 222 studies were included, of which 93 (41.9%) provided a complete list of algorithms for identifying participants, 36 (16.2%) for exposure, and 132 (59.5%) for outcomes, and 15 (6.8%) for all study variables including population, exposure, and outcomes. Fifty-nine (26.6%) studies stated that the algorithms were validated, and 54 (24.3%) studies reported methodological characteristics of 66 validations, among which 61 validations in 49 studies were from the cross-referenced validation studies. Of those 66 validations, 22 (33.3%) reported sensitivity and 16 (24.2%) reported specificity. A total of 63.6% of studies reporting sensitivity and 56.3% reporting specificity used test-result-based sampling, an approach that potentially biases effect estimates. Twenty-eight (12.6%) studies used alternative algorithms to identify study variables, and 24 reported the effects estimated by primary analyses and sensitivity analyses. Of these, 20% had differential effect estimates when using alternative algorithms for identifying population, 18.2% for identifying exposure, and 45.5% for classifying outcomes. Only 32 (14.4%) studies discussed how the algorithms may affect treatment estimates.

CONCLUSION

In observational studies of RCD, the algorithms for variable identification were not regularly validated, and-even if validated-the methodological approach and performance of the validation were often poor. More seriously, different algorithms may yield differential treatment effects, but their impact is often ignored by researchers. Strong efforts, including recommendations, are warranted to improve good practice.

Compelling evidence from meta-epidemiological studies demonstrates overestimation of effects in randomized trials that fail to optimize randomization and blind patients and outcome assessors

OBJECTIVES

To investigate the impact of potential risk of bias elements on effect estimates in randomized trials.

STUDY DESIGN AND SETTING

We conducted a systematic survey of meta-epidemiological studies examining the influence of potential risk of bias elements on effect estimates in randomized trials. We included only meta-epidemiological studies that either preserved the clustering of trials within meta-analyses (compared effect estimates between trials with and without the potential risk of bias element within each meta-analysis, then combined across meta-analyses; between-trial comparisons), or preserved the clustering of substudies within trials (compared effect estimates between substudies with and without the element, then combined across trials; within-trial comparisons). Separately for studies based on between- and within-trial comparisons, we extracted ratios of odds ratios (RORs) from each study and combined them using a random-effects model. We made overall inferences and assessed certainty of evidence based on Grading of Recommendations, Assessment, development, and Evaluation and Instrument to assess the Credibility of Effect Modification Analyses.

RESULTS

Forty-one meta-epidemiological studies (34 of between-, 7 of within-trial comparisons) proved eligible. Inadequate random sequence generation (ROR 0.94, 95% confidence interval [CI] 0.90-0.97) and allocation concealment (ROR 0.92, 95% CI 0.88-0.97) probably lead to effect overestimation (moderate certainty). Lack of patients blinding probably overestimates effects for patient-reported outcomes (ROR 0.36, 95% CI 0.28-0.48; moderate certainty). Lack of blinding of outcome assessors results in effect overestimation for subjective outcomes (ROR 0.69, 95% CI 0.51-0.93; high certainty). The impact of patients or outcome assessors blinding on other outcomes, and the impact of blinding of health-care providers, data collectors, or data analysts, remain uncertain. Trials stopped early for benefit probably overestimate effects (moderate certainty). Trials with imbalanced cointerventions may overestimate effects, while trials with missing outcome data may underestimate effects (low certainty). Influence of baseline imbalance, compliance, selective reporting, and intention-to-treat analysis remain uncertain.

CONCLUSION

Failure to ensure random sequence generation or adequate allocation concealment probably results in modest overestimates of effects. Lack of patients blinding probably leads to substantial overestimates of effects for patient-reported outcomes. Lack of blinding of outcome assessors results in substantial effect overestimation for subjective outcomes. For other elements, though evidence for consistent systematic overestimate of effect remains limited, failure to implement these safeguards may still introduce important bias.

Intention-to-treat versus as-treated versus per-protocol approaches to analysis

Randomized controlled trials (RCTs) are considered the most rigorous study design for testing hypotheses and the gold standard for evaluating intervention effectiveness. However, RCTs are often conducted under the assumption of ideal conditions that may differ from real-world scenarios in which various issues, such as loss to follow-up, mistakes in participant enrollment or intervention, and low subject compliance or adherence, may occur. There are various group-defining strategies for analyzing RCT data, including the intention-to-treat (ITT), as-treated, and per-protocol (PP) approaches. The ITT principle involves analyzing all participants according to their initial group assignments, regardless of study completion and compliance or adherence to treatment protocols. This approach aims to replicate real-world clinical settings in which several anticipated or unexpected conditions may occur with regard to the study protocol. For the PP approach, only participants who meet the inclusion criteria, complete the interventions according to the study protocols, and have primary outcome data available are included. This approach aims to confirm treatment effects under optimal conditions. In general, the ITT principle is preferred for superiority and inequality trials, whereas the PP approach is preferred for equivalence and non-inferiority trials. However, both analytical approaches should be conducted and their results compared to determine whether significant differences exist. Overall, using both the ITT and PP approaches can provide a more complete picture of the treatment effects and ensure the reliability of the trial results.

Reporting, handling, and interpretation of time-varying drug treatments in observational studies using routinely collected healthcare data

BACKGROUND

Time-varying drug treatments are common in studies using routinely collected health data (RCD) for assessing treatment effects. This study aimed to examine how these studies reported, handled, and interpreted time-varying drug treatments.

METHODS

A systematic search was conducted on PubMed from 2018 to 2020. Eligible studies were those used RCD to explore drug treatment effects. We summarized the reporting characteristics and methods employed for handling time-varying treatments. Logistic regressions were performed to investigate the association between study characteristics and the reporting of time-varying treatments.

RESULTS

Two hundred and fifty-six studies were included, and 225 (87.9%) studies involved time-varying treatments. Of these, 24 (10.7%) reported the proportion of time-varying treatments and 105 (46.7%) reported methods used to handle time-varying treatments. Multivariable logistic regression showed that medical studies, prespecified protocol, and involvement of methodologists were associated with a higher likelihood of reporting the methods applied to handle time-varying treatments. Among the 105 studies that reported methods, as-treated analyses were the most commonly used analysis sets, which were employed in 73.9%, 75.3% and 88.2% of studies that reported approaches for treatment discontinuation, treatment switching and treatment add-on. Among the 225 studies involved time-varying treatments, 27 (12.0%) acknowledged the potential bias introduced by treatment change, of which 14 (51.9%) suggested that potential biases may impact acceptance or rejection of the null hypothesis.

CONCLUSIONS

Among observational studies using RCD, the underreporting about the presence and methods for handling time-varying treatments was largely common. The potential biases due to time-varying treatments have frequently been disregarded. Collaborative endeavors are strongly needed to enhance the prevailing practices.

The Efficacy and Safety of Oral Irrigator on the Control of Dental Plaque and Gingivitis: A Randomized, Single-Blind, Parallel-Group Clinical Trial

BACKGROUND

To evaluate the efficacy and safety of oral irrigator (OI) in controlling dental plaque and gingivitis.

METHODS

Ninety participants diagnosed with gingivitis were randomly assigned to two groups, given a toothbrush combined with OI (WaterPik®) (test) or a toothbrush alone (control). The Turesky-Modified Quigley-Hein Plaque Index (T-QH), Modified Gingival Index (MGI), Bleeding Index (BI), and percentage of sites with bleeding on probing (BOP%) were evaluated at baseline, 4 weeks, 8 weeks, and 12 weeks. The full analysis set (FAS) and per-protocol set (PPS) were analyzed. Adverse events were recorded through electronic diaries and examinations.

RESULTS

Of the 90 participants, the efficacy was assessed in the following numbers (FAS/PPS): test (45/33) and control (43/38). Compared with the control, MGI, BI, and BOP% were significantly lower in the test group after 4 weeks (4 weeks: p = 0.017, p = 0.001, and p = 0.001, respectively; 8 weeks and 12 weeks: p < 0.001 for all, FAS); T-QH was significantly lower after 8 weeks (8 weeks: p = 0.033; 12 weeks: p = 0.006, FAS). Transient gingival bleeding may be associated with OI. Self-reported pain and dentin hypersensitivity symptoms were similar between groups.

CONCLUSIONS

As adjuncts to toothbrushing, OI demonstrated significantly better efficacy in controlling dental plaque and gingival inflammation with no substantial safety hazards.

Different dosing regimens of Tenecteplase in acute ischemic stroke: A network meta-analysis of the clinical evidence

Introduction:

Acute ischemic stroke remains the major cause of death and disability and conclusive evidence of Tenecteplase in treating stroke is lacking.

Objective:

To conduct a meta-analysis to determine whether Tenecteplase produces better outcomes than Alteplase and a network meta-analysis comparing the different dosing regimens of Tenecteplase.

Methods:

Searches were made in MEDLINE, CENTRAL, and ClinicalTrials.gov. The outcome measures are recanalization, early neurological improvement, functional outcomes at 90 days (modified Rankin Scale 0–1 and 0–2), intracranial hemorrhage, symptomatic intracranial hemorrhage, and mortality within 90 days from treatment.

Results:

Fourteen studies are included in the meta-analyses and 18 studies in the network meta-analyses. In the meta-analysis, Tenecteplase 0.25 mg/kg has significant results in early neurological improvement (OR = 2.35, and 95% CI = 1.16–4.72) and excellent functional outcome (OR = 1.20, and 95% CI = 1.02–1.42). In the network meta-analysis, Tenecteplase 0.25 mg/kg produces significant results in early neurological improvement (OR = 1.52 [95% CI = 1.13–2.05], p-value = 0.01), functional outcomes (mRS 0–1 and 0–2) (OR = 1.19 [95% CI = 1.03–1.37], p-value = 0.02; OR = 1.21 [95% CI = 1.05–1.39], p-value = 0.01; respectively) and mortality (OR = 0.78 [95% CI = 0.64–0.96], p-value = 0.02) whereas Tenecteplase 0.40 mg/kg increases the chances of symptomatic intracranial hemorrhage (OR = 2.35 [95% CI = 1.19–4.64], p-value = 0.01).

Conclusion:

While not conclusive, our study lends evidence to 0.25 mg/kg Tenecteplase dose for ischemic stroke treatment. Further randomized trials need to be done to validate this finding.

Registration:

International prospective register of systematic reviews (PROSPERO) – CRD42022339774 URL: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=339774