Treating individuals 2. Subgroup analysis in randomised controlled trials: importance, indications, and interpretation

Effects of icosapent ethyl according to baseline residual risk in patients with atherosclerotic cardiovascular disease: results from REDUCE-IT

AIMS

Icosapent ethyl lowers triglycerides and significantly reduces major adverse cardiovascular events (MACE), though treatment effects may vary between individuals. This study aimed to determine the relative and absolute effects of icosapent ethyl on MACE according to baseline cardiovascular disease (CVD) risk in patients with atherosclerotic cardiovascular disease (ASCVD).

METHODS AND RESULTS

Participants from the Reduction of Cardiovascular Events with Icosapent Ethyl-Intervention Trial (REDUCE-IT) with ASCVD were included (n = 5785). The primary outcome was 3-point MACE, i.e. non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death. Baseline 5-year risk of MACE was estimated using the European Society of Cardiology (ESC) guideline-recommended SMART2 risk score. Modification of the relative treatment effects of icosapent ethyl by baseline risk was assessed using Cox proportional hazards models, including a treatment-by-risk interaction. Next, treatment effects were assessed stratified by quartiles of baseline risk. During a median follow-up of 4.8 years (interquartile range 3.2-5.3), MACE occurred in 361 vs. 489 patients in the icosapent ethyl vs. placebo group [95% confidence interval (CI)]; hazard ratio (HR) 0.72 (0.63-0.82), absolute risk reduction (ARR) 4.4% (2.6-6.2%), number needed to treat (NNT) 23 (16-38), and 5-year Kaplan-Meier estimated cumulative incidence reduction (CIR) 5.7% (3.5-7.9%). Icosapent ethyl significantly reduced MACE in all risk quartiles, with an HR (95% CI) of 0.62 (0.43-0.88), 0.66 (0.48-0.92), 0.69 (0.53-0.90), and 0.78 (0.63-0.96), respectively (P for treatment-by-risk interaction = 0.106). The ARR (95% CI) increased across risk quartiles, i.e. was 3.9% (1.0-6.8%), 4.3% (1.2-7.3%), 5.1% (1.4-8.7%), and 5.6% (1.3-10.0%), respectively. This translates to NNTs (95% CI) of 26 (15-98), 24 (14-84), 20 (11-70), and 18 (10-77). The 5-year CIR (95% CI) was 4.8% (1.3-8.2%), 5.0% (1.3-8.7%), 6.1% (1.7-10.5%), and 7.7% (2.3-13.2%), respectively. Consistent results were obtained for 5-point MACE, additionally including coronary revascularization and unstable angina.

CONCLUSION

Among patients with ASCVD and elevated triglyceride levels, icosapent ethyl significantly reduces the risk of MACE irrespective of baseline CVD risk, though absolute benefits are largest for patients at the highest risk.

The impact of mold exposure on anxiety symptoms in the older adults: A moderated mediation model based on CLHLS

BACKGROUND

Mold exposure is a common environmental issue that can adversely affect health, particularly among older adults. The impact of mold exposure on anxiety symptoms in this population has not been extensively studied.

OBJECTIVE

This study aims to examine the relationship between mold exposure and anxiety symptoms in older adults, considering the mediating role of cognitive function and the moderating effects of open window ventilation and multivitamin supplementation.

METHODS

Data from the eighth wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) was utilized, including 11,021 participants aged 65 and older. Logistic regression models and moderated mediation analysis were employed to explore these relationships.

RESULTS

Mold exposure was significantly associated with increased anxiety symptoms (OR=1.831, 95 % CI=1.588-2.110). Cognitive impairment partially mediated this relationship. Open window ventilation (B=-0.040, P<0.001) and multivitamin supplementation (B=-0.197, P<0.001) served as protective factors. Subgroup analysis indicated higher vulnerability among females (OR=1.72, P<0.001), those aged 65-79 (OR=1.86, P<0.001), urban residents (OR=2.50, P<0.001), individuals not living with family members (OR=1.89, P<0.001), those with higher education (OR=2.01, P<0.001), married individuals (OR=1.80, P<0.001), and those in very good health (OR=2.11, P=0.026).

CONCLUSION

Mold exposure contributes to anxiety symptoms in older adults, with cognitive decline playing a mediating role. Effective interventions, including improved ventilation and multivitamin supplementation, can mitigate these effects. These findings highlight the need for targeted public health strategies to enhance the well-being of older adults.

Heterogeneous Treatment Effects in the Incredible Years Teacher Classroom Management Programme - A Latent Profile Approach

Heterogeneous effects from interventions often remain hidden in between-group analyses, risking overgeneralized conclusions of treatment effects. In this exploratory study, we performed latent profile analysis to unveil differential treatment effects among children in The Incredible Years Teacher Classroom Management Programme (IY TCMP). This program has previously been shown to reduce behavioral problems in preschools and schools in total samples and subgroups. A total of 726 children (48.7% girls; Mage = 4.21 years; SDage = 0.86) from 92 childcare centers in Norway participated in either the intervention (n = 338) or the matched control condition (n = 388). First, by conducting latent profile analysis on baseline levels of child-teacher relationship (closeness, conflict), behavioral problems, and social competence, three distinct profiles were identified: High Risk (26.4%), Moderate Risk (42.8%), and Low Risk (30.7%) - each profile with unique characteristics. Second, we tested for within-profile, condition-by-time interactions following the intervention, showing distinct treatment responses for each profile. High-risk profiles profited most from the IY TCMP, with a substantial decrease in externalizing problems, more teacher closeness, and less teacher conflict. Moderate-risk profiles also gained better teacher-child relationships and improved social competence. The Low-Risk profiles showed no effects from the intervention. It is argued that latent profile analysis presents a feasible approach for examining within-sample heterogeneity in intervention research. It also reveals crucial information on treatment variability, as demonstrated in the Incredible Years Programme.

A Causal Mediation Approach to Account for Interaction of Treatment and Intercurrent Events: Using Hypothetical Strategy

Hypothetical strategy is a common strategy for handling intercurrent events (IEs). No current guideline or study considers treatment-IE interaction to target the estimand in any one IE-handling strategy. Based on the hypothetical strategy, we aimed to (1) assess the performance of three estimators with different considerations for the treatment-IE interaction in a simulation and (2) compare the estimation of these estimators in a real trial. Simulation data were generalized based on realistic clinical trials of Alzheimer's disease. The estimand of interest was the effect of treatment with no IE occurring under the hypothetical strategy. Three estimators, namely, G-estimation with and without interaction and IE-ignored estimation, were compared in scenarios where the treatment-IE interaction effect was set as -50% to 50% of the main effect. Bias was the key performance measure. The real case was derived from a randomized trial of methadone maintenance treatment. Only G-estimation with interaction exhibited unbiased estimations regardless of the existence, direction or magnitude of the treatment-IE interaction in those scenarios. Neglecting the interaction and ignoring the IE would introduce a bias as large as 0.093 and 0.241 (true value, -1.561) if the interaction effect existed. In the real case, compared with G-estimation with interaction, G-estimation without interaction and IE-ignored estimation increased the estimand of interest by 33.55% and 34.36%, respectively. This study highlights the importance of considering treatment-IE interaction in the estimand framework. In practice, it would be better to include the interaction in the estimator by default.

Estimating optimal decision trees for treatment assignment: The case of K > 2 treatment alternatives

For many problems in clinical practice, multiple treatment alternatives are available. Given data from a randomized controlled trial or an observational study, an important challenge is to estimate an optimal decision rule that specifies for each client the most effective treatment alternative, given his or her pattern of pretreatment characteristics. In the present paper we will look for such a rule within the insightful family of classification trees. Unfortunately, however, there is dearth of readily accessible software tools for optimal decision tree estimation in the case of more than two treatment alternatives. Moreover, this primary tree estimation problem is also cursed with two secondary problems: a structural missingness in typical studies on treatment evaluation (because every individual is assigned to a single treatment alternative only), and a major issue of replicability. In this paper we propose solutions for both the primary and the secondary problems at stake. We evaluate the proposed solution in a simulation study, and illustrate with an application on the search for an optimal tree-based treatment regime in a randomized controlled trial on K = 3 different types of aftercare for younger women with early-stage breast cancer. We conclude by arguing that the proposed solutions may have relevance for several other classification problems inside and outside the domain of optimal treatment assignment.

Virtual reality exposure therapy for social anxiety disorders: a meta-analysis and meta-regression of randomized controlled trials

BACKGROUND AND OBJECTIVES

Virtual reality exposure therapy offers a unique opportunity to treat social anxiety disorder. This meta-analysis aims to evaluate the effectiveness of virtual reality exposure therapy compared to waitlist comparators or other interventions for individuals with social anxiety disorder in alleviating anxiety symptoms.

METHODS

A three-step comprehensive search for the randomized controlled trials of virtual reality exposure therapy was conducted from inception to 7 December 2023. The overall effect was measured using Hedges' g and determined using t-statistics at a significance level of p < 0.05. Sensitivity, subgroup, and meta-regression analyses were carried out.

RESULTS

A total of 17 randomized control trials were retrieved from nine electronic databases. Virtual reality exposure therapy has greater efficacy than waitlist comparators in reducing anxiety symptoms at post-intervention and follow-up assessment. Virtual reality exposure therapy demonstrates a similar effect to other interventions at post-intervention and follow-up assessment. We observed a greater effect for participants with symptomatic social anxiety when we combined the intervention with cognitive behavioral therapy compared to its counterpart. Meta-regression analyses found no significant covariate.

CONCLUSIONS

Overall, virtual reality exposure therapy can provide supplementary therapy for improving anxiety symptoms. Additional high-quality and large-scale trials with long-term follow-up are needed.

Prognostic Factors and Treatment Effect Modifiers for Physical Health, Opioid Prescription, and Health Care Utilization in Patients With Musculoskeletal Disorders in Primary Care: Exploratory Secondary Analysis of the STEMS Randomized Trial of Direct Access to Physical Therapist-Led Care

OBJECTIVE

The aims of the study were to identify prognostic factors associated with health care outcomes in patients with musculoskeletal (MSK) conditions in primary care and to determine whether characteristics associated with choice of care modify treatment effects of a direct-access physical therapist-led pathway in addition to general practitioner (GP)-led care compared to GP-led care alone.

METHODS

A secondary analysis of a 2-parallel-arm, cluster randomized controlled trial involving general practices in the United Kingdom was conducted. Practices were randomized to continue offering GP-led care or to also offer a direct-access physical therapist-led pathway. Data from adults with MSK conditions who completed the 6-month follow-up questionnaire were analyzed. Outcomes included physical health, opioid prescription, and self-reported health care utilization over 6 months. Treatment effect modifiers were selected a priori from associations in observational studies. Multivariable regression models identified potential prognostic factors, and interaction analysis tested for potential treatment effect modifiers.

RESULTS

Analysis of 767 participants indicated that baseline pain self-efficacy, pain severity, and having low back pain statistically predicted outcomes at 6 months. Higher pain self-efficacy scores at baseline were associated with improved physical health scores, reduced opioid prescription, and less health care utilization. Higher bodily pain at baseline and having low back pain were associated with worse physical health scores and increased opioid prescription. Main interaction analyses did not reveal that patients' age, level of education, duration of symptoms, or MSK presentation influenced response to treatment, but visual trends suggested those in the older age group proceeded to fewer opioid prescriptions and utilized less health care when offered direct access to physical therapy.

CONCLUSIONS

Patients with MSK conditions with lower levels of pain self-efficacy, higher pain severity, and presenting with low back pain have less favorable clinical and health care outcomes in primary care. Prespecified characteristics did not modify the treatment effect of the offer of a direct-access physical therapist-led pathway compared to GP-led care.

IMPACT

Patients with MSK conditions receiving primary care in the form of direct-access physical therapist-led or GP-led care who have lower levels of self-efficacy, higher pain severity, and low back pain are likely to have a less favorable prognosis. Age and duration of symptoms should be explored as potential patient characteristics that modify the treatment response to a direct-access physical therapist-led model of care.

Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data

In this paper, we review recent advances in statistical methods for the evaluation of the heterogeneity of treatment effects (HTE), including subgroup identification and estimation of individualized treatment regimens, from randomized clinical trials and observational studies. We identify several types of approaches using the features introduced in Lipkovich et al (Stat Med 2017;36: 136-196) that distinguish the recommended principled methods from basic methods for HTE evaluation that typically rely on rules of thumb and general guidelines (the methods are often referred to as common practices). We discuss the advantages and disadvantages of various principled methods as well as common measures for evaluating their performance. We use simulated data and a case study based on a historical clinical trial to illustrate several new approaches to HTE evaluation.

Using Bayesian hierarchical models for controlled post hoc subgroup analysis of clinical trials: application to smoking cessation treatment in American Indians and Alaska Natives

Clinical trials powered to detect subgroup effects provide the most reliable data on heterogeneity of treatment effect among different subpopulations. However, pre-specified subgroup analysis is not always practical and post hoc analysis results should be examined cautiously. Bayesian hierarchical modelling provides grounds for defining a controlled post hoc analysis plan that is developed after seeing outcome data for the population but before unblinding the outcome by subgroup. Using simulation based on the results from a tobacco cessation clinical trial conducted among the general population, we defined an analysis plan to assess treatment effect among American Indians and Alaska Natives (AI/AN) enrolled in the study. Patients were randomized into two arms using Bayesian adaptive design. For the opt-in arm, clinicians offered a cessation treatment plan after verifying that a patient was ready to quit. For the opt-out arm, clinicians provided all participants with free cessation medications and referred them to a Quitline. The study was powered to test a hypothesis of significantly higher quit rates for the opt-out arm at one-month post randomization. Overall, one-month abstinence rates were 15.9% and 21.5% (opt-in and opt-out arm, respectively). For AI/AN, one-month abstinence rates were 10.2% and 22.0% (opt-in and opt-out arm, respectively). The posterior probability that the abstinence rate in the treatment arm is higher is 0.96, indicating that AI/AN demonstrate response to treatment at almost the same probability as the whole population.

Tailoring the treatment of inflammatory rheumatic diseases by a better stratification and characterization of the clinical patient heterogeneity. Findings from a systematic literature review and experts' consensus

Inflammatory rheumatic diseases are different pathologic conditions associated with a deregulated immune response, codified along a spectrum of disorders, with autoinflammatory and autoimmune diseases as two-end phenotypes of this continuum. Despite pathogenic differences, inflammatory rheumatic diseases are commonly managed with a limited number of immunosuppressive drugs, sometimes with partial evidence or transferring physicians' knowledge in different patients. In addition, several randomized clinical trials, enrolling these patients, did not meet the primary pre-established outcomes and these findings could be linked to the underlying molecular diversities along the spectrum of inflammatory rheumatic disorders. In fact, the resulting patient heterogeneity may be driven by differences in underlying molecular pathology also resulting in variable responses to immunosuppressive drugs. Thus, the identification of different clinical subsets may possibly overcome the major obstacles that limit the development more effective therapeutic strategies for these patients with inflammatory rheumatic diseases. This clinical heterogeneity could require a diverse therapeutic management to improve patient outcomes and increase the frequency of clinical remission. Therefore, the importance of better patient stratification and characterization is increasingly pointed out according to the precision medicine principles, also suggesting a new approach for disease treatment. In fact, based on a better proposed patient profiling, clinicians could more appropriately balance the therapeutic management. On these bases, we synthetized and discussed the available literature about the patient profiling in regard to therapy in the context of inflammatory rheumatic diseases, mainly focusing on randomized clinical trials. We provided an overview of the importance of a better stratification and characterization of the clinical heterogeneity of patients with inflammatory rheumatic diseases identifying this point as crucial in improving the management of these patients.

Are there patients with an intracapsular fracture of the hip who may benefit from an uncemented hemiarthroplasty?

Aims

Cemented hemiarthroplasty is an effective form of treatment for most patients with an intracapsular fracture of the hip. However, it remains unclear whether there are subgroups of patients who may benefit from the alternative operation of a modern uncemented hemiarthroplasty - the aim of this study was to investigate this issue. Knowledge about the heterogeneity of treatment effects is important for surgeons in order to target operations towards specific subgroups who would benefit the most.

Methods

We used causal forest analysis to compare subgroup- and individual-level treatment effects between cemented and modern uncemented hemiarthroplasty in patients aged > 60 years with an intracapsular fracture of the hip, using data from the World Hip Trauma Evaluation 5 (WHiTE 5) multicentre randomized clinical trial. EuroQol five-dimension index scores were used to measure health-related quality of life at one, four, and 12 months postoperatively.

Results

Our analysis revealed a complex landscape of responses to the use of a cemented hemiarthroplasty in the 12 months after surgery. There was heterogeneity of effects with regard to baseline characteristics, including age, pre-injury health status, and lifestyle factors such as alcohol consumption. This heterogeneity was greater at the one-month mark than at subsequent follow-up timepoints, with particular regard to subgroups based on age. However, for all subgroups, the effect estimates for quality of life lay within the confidence intervals derived from the analysis of all patients.

Conclusion

The use of a cemented hemiarthroplasty is expected to increase health-related quality of life compared with modern uncemented hemiarthroplasty for all subgroups of patients aged > 60 years with a displaced intracapsular fracture of the hip.

Considerations for Subgroup Analyses in Cluster-Randomized Trials Based on Aggregated Individual-Level Predictors

In research assessing the effect of an intervention or exposure, a key secondary objective often involves assessing differential effects of this intervention or exposure in subgroups of interest; this is often referred to as assessing effect modification or heterogeneity of treatment effects (HTE). Observed HTE can have important implications for policy, including intervention strategies (e.g., will some patients benefit more from intervention than others?) and prioritizing resources (e.g., to reduce observed health disparities). Analysis of HTE is well understood in studies where the independent unit is an individual. In contrast, in studies where the independent unit is a cluster (e.g., a hospital or school) and a cluster-level outcome is used in the analysis, it is less well understood how to proceed if the HTE analysis of interest involves an individual-level characteristic (e.g., self-reported race) that must be aggregated at the cluster level. Through simulations, we show that only individual-level models have power to detect HTE by individual-level variables; if outcomes must be defined at the cluster level, then there is often low power to detect HTE by the corresponding aggregated variables. We illustrate the challenges inherent to this type of analysis in a study assessing the effect of an intervention on increasing COVID-19 booster vaccination rates at long-term care centers.

Predicting subgroup treatment effects for a new study: Motivations, results and learnings from running a data challenge in a pharmaceutical corporation

We present the motivation, experience, and learnings from a data challenge conducted at a large pharmaceutical corporation on the topic of subgroup identification. The data challenge aimed at exploring approaches to subgroup identification for future clinical trials. To mimic a realistic setting, participants had access to 4 Phase III clinical trials to derive a subgroup and predict its treatment effect on a future study not accessible to challenge participants. A total of 30 teams registered for the challenge with around 100 participants, primarily from Biostatistics organization. We outline the motivation for running the challenge, the challenge rules, and logistics. Finally, we present the results of the challenge, the participant feedback as well as the learnings. We also present our view on the implications of the results on exploratory analyses related to treatment effect heterogeneity.

The potential benefit of statin prescription based on prediction of treatment responsiveness in older individuals: an application to the PROSPER randomized controlled trial

AIMS

Clinical guidelines often recommend treating individuals based on their cardiovascular risk. We revisit this paradigm and quantify the efficacy of three treatment strategies: (i) overall prescription, i.e. treatment to all individuals sharing the eligibility criteria of a trial; (ii) risk-stratified prescription, i.e. treatment only to those at an elevated outcome risk; and (iii) prescription based on predicted treatment responsiveness.

METHODS AND RESULTS

We reanalysed the PROSPER randomized controlled trial, which included individuals aged 70-82 years with a history of, or risk factors for, vascular diseases. We conducted the derivation and internal-external validation of a model predicting treatment responsiveness. We compared with placebo (n = 2913): (i) pravastatin (n = 2891); (ii) pravastatin in the presence of previous vascular diseases and placebo in the absence thereof (n = 2925); and (iii) pravastatin in the presence of a favourable prediction of treatment response and placebo in the absence thereof (n = 2890). We found an absolute difference in primary outcome events composed of coronary death, non-fatal myocardial infarction, and fatal or non-fatal stroke, per 10 000 person-years equal to: -78 events (95% CI, -144 to -12) when prescribing pravastatin to all participants; -66 events (95% CI, -114 to -18) when treating only individuals with an elevated vascular risk; and -103 events (95% CI, -162 to -44) when restricting pravastatin to individuals with a favourable prediction of treatment response.

CONCLUSION

Pravastatin prescription based on predicted responsiveness may have an encouraging potential for cardiovascular prevention. Further external validation of our results and clinical experiments are needed.

TRIAL REGISTRATION

ISRCTN40976937.

Interaction analysis of subgroup effects in randomized trials: the essential methodological points

Subgroup analysis aims to identify subgroups (usually defined by baseline/demographic characteristics), who would (or not) benefit from an intervention under specific conditions. Often performed post hoc (not pre-specified in the protocol), subgroup analyses are prone to elevated type I error due to multiple testing, inadequate power, and inappropriate statistical interpretation. Aside from the well-known Bonferroni correction, subgroup treatment interaction tests can provide useful information to support the hypothesis. Using data from a previously published randomized trial where a p value of 0.015 was found for the comparison between standard and Hemopatch® groups in (the subgroup of) 135 patients who had hand-sewn pancreatic stump closure we first sought to determine whether there was interaction between the number and proportion of the dependent event of interest (POPF) among the subgroup population (patients with hand-sewn stump closure and use of Hemopatch®), Next, we calculated the relative excess risk due to interaction (RERI) and the "attributable proportion" (AP). The p value of the interaction was p = 0.034, the RERI was - 0.77 (p = 0.0204) (the probability of POPF was 0.77 because of the interaction), the RERI was 13% (patients are 13% less likely to sustain POPF because of the interaction), and the AP was - 0.616 (61.6% of patients who did not develop POPF did so because of the interaction). Although no causality can be implied, Hemopatch® may potentially decrease the POPF after distal pancreatectomy when the stump is closed hand-sewn. The hypothesis generated by our subgroup analysis requires confirmation by a specific, randomized trial, including only patients undergoing hand-sewn closure of the pancreatic stump after distal pancreatectomy.Trial registration: INS-621000-0760.

Which antiseptic to use for a caesarean section? A systematic review and network meta-analysis of randomized controlled trials

Guidelines for pre-operative skin antisepsis recommend using chlorhexidine in an alcohol-based solution. However, other antiseptics such as aqueous povidone-iodine or alcohol-based solutions continue to be used. Randomized controlled trials (RCTs) in caesarean section are rare and do not include all possible comparisons of antiseptics. The aim of this study was to assess the efficacy (reduction of surgical site infections) of chlorhexidine at two different concentrations (0.3% and 2%) and povidone-iodine in aqueous or alcohol-based solutions using a network meta-analysis, including only RCTs of caesarean sections. Fragility indices and prediction intervals were also estimated. A systematic literature review and network meta-analysis were performed. RCTs published up to February 2024 were collected from PubMed, ScienceDirect and the Cochrane Library. Interventions included alcohol-based povidone-iodine, aqueous povidone-iodine, and alcohol-based chlorhexidine 2% and 0.3%. The primary outcome measure was surgical site infection. Nine RCTs with 4915 patients and four interventions were included in the network meta-analysis. All credible intervals of the compared interventions overlapped. Alcohol-based 2% chlorhexidine had the highest probability of being effective in preventing surgical site infections, followed by alcohol-based povidone-iodine. The fragility index ranged from 4 to 18. The prediction intervals were wide. On the basis of rank probabilities, chlorhexidine 2% in an alcohol-based solution was most likely to be effective in preventing surgical site infections after caesarean section, followed by alcohol-based povidone-iodine. Given the paucity of literature and the relatively small difference between povidone-iodine and chlorhexidine found in our meta-analysis, we suggest that either can be used in an alcohol-based solution as antisepsis for planned or emergency caesarean section.

Impact of the PATH Statement on Analysis and Reporting of Heterogeneity of Treatment Effect in Clinical Trials: A Scoping Review

Background

The Predictive Approaches to Treatment Effect Heterogeneity (PATH) Statement provides guidance for using predictive modeling to identify differences (i.e., heterogeneity) in treatment effects (benefits and harms) among participants in randomized clinical trials (RCTs). It distinguished risk modeling, which uses a multivariable model to predict risk of trial outcome(s) and then examines treatment effects within strata of predicted risk, from effect modeling, which predicts trial outcomes using models that include treatment, individual participant characteristics and interactions of treatment with selected characteristics.

Purpose

To describe studies of heterogeneous treatment effects (HTE) that use predictive modeling in RCT data and cite the PATH Statement.

Data Sources

The Cited By functions in PubMed, Google Scholar, Web of Science and SCOPUS databases (Jan 7, 2020 - June 5, 2023).

Study Selection

42 reports presenting 45 predictive models.

Data Extraction

Double review with adjudication to identify risk and effect modeling and examine consistency with Statement consensus statements. Credibility of HTE findings was assessed using criteria adapted from the Instrument to assess Credibility of Effect Modification Analyses (ICEMAN). Clinical importance of credible HTE findings was also assessed.

Data Synthesis

The numbers of reports, especially risk modeling reports, increased year-on-year. Consistency with consensus statements was high, except for two: only 15 of 32 studies with positive overall findings included a risk model; and most effect models explored many candidate covariates with little prior evidence for effect modification. Risk modeling was more likely than effect modeling to identify both credible HTE (14/19 vs 5/26) and clinically important HTE (10/19 vs 4/26).

Limitations

Risk of reviewer bias: reviewers assessing credibility and clinical importance were not blinded to adherence to PATH recommendations.

Conclusions

The PATH Statement appears to be influencing research practice. Risk modeling often uncovered clinically important HTE; effect modeling was more often exploratory.

Multidomain interventions based on a life-course model to prevent dementia in at-risk Chinese older adults: A randomized controlled trial

BACKGROUND

Due to the time-dependent effect of specific risk factors for dementia, multidomain interventions based on a life-course model might achieve optimal preventive effects against dementia.

OBJECTIVE

The purpose of this study was to investigate the effectiveness of multidomain interventions based on a life-course model of modifiable risk factors for dementia in at-risk Chinese older adults.

DESIGN

This was a two-arm, proof-of-concept, randomized controlled trial.

SETTING AND PARTICIPANTS

We randomly assigned 96 community-dwelling at-risk adults aged 60 years or older in a 1:1 ratio to either the 6-month multidomain intervention group (dementia literacy, physical activity, cognitive training, social activity and optional modules) or the control group (health education).

METHODS

The primary outcomes were the dementia risk score and cognitive composite Z score. The secondary outcomes included the individual components of the dementia risk score (protective and risk factors) and cognitive composite Z score (global cognition, memory, executive function and language), social isolation (loneliness, social contact, and social participation), dementia literacy and prevention belief. Linear mixed models with maximum likelihood estimation were used to calculate the outcomes between the groups over time.

RESULTS

The primary analyses showed that the dementia risk score was significantly lower (p < 0.001) and that the cognitive composite Z score was significantly higher (p = 0.013) in the multidomain intervention group than in the control group. Baseline characteristics did not modify the effects of the multidomain interventions (p value for interaction > 0.05). For secondary outcomes, statistically significant group × time interactions were observed for the protective (p = 0.001) and risk factors (p = 0.049), as well as in executive function (p = 0.020), loneliness (p = 0.029), dementia literacy (p < 0.001) and prevention belief (p < 0.001).

CONCLUSIONS

Multidomain interventions based on a life-course model are feasible and have the potential to reduce dementia risk and improve cognitive function in at-risk Chinese older adults.

REGISTRATION

The trial was registered at the Chinese Clinical Trials Registry (ChiCTR2100053417).

Prevalence of physical violence against people in insecure migration status: A systematic review and meta-analysis

OBJECTIVES

This study summarised evidence on the prevalence of interpersonal, community and state physical violence against people in insecure migration status.

METHODS

We conducted a systematic review and meta-analysis of primary studies that estimated prevalence of physical violence against a population in insecure migration status. We searched Embase, Social Policy and Practice, Political Science Complete, SocINDEX and Web of Science Social Sciences Citation Index for reports published from January 2000 until 31 May 2023. Study quality was assessed using an adapted version of the Joanna Briggs assessment tool for cross-sectional studies. Two reviewers carried out screening, data extraction, quality assessment and analysis. Meta-analysis was conducted in Stata 17, using a random effects model and several exploratory subgroup analyses.

RESULTS

We retrieved 999 reports and included 31 retrospective cross-sectional studies with 25,997 migrants in insecure status. The prevalence estimate of physical violence was 31.16% (95% CI 25.62-36.70, p < .00). There was no statistically significant difference in the estimates for prevalence of violence for men (35.30%, 95% CI 18.45-52.15, p < .00) and for women (27.78%, 95% CI 21.42-34.15, p < .00). The highest point estimate of prevalence of violence was where insecure status was related to employment (44.40%, 95% CI 18.24-70.57, p < .00), although there were no statistically significant difference in the subgroup analysis. The prevalence of violence for people in undocumented status was not significantly different (29.13%, 95% CI 19.86-38.41, p < .00) than that for refugees and asylum seekers (33.29%, 95% CI 20.99-45.59, p < .00). The prevalence of violence in Asia was 56.01% (95% CI 22.47-89.55, p < .00). Europe had the lowest point prevalence estimate (17.98%, 95% CI 7.36-28.61, p < .00), although the difference was not statistically significant. The prevalence estimate during the migration journey was 32.93% (95% CI 24.98-40.88, p < .00). Intimate partner violence attached to insecure status was estimated at 29.10%, (95% CI 8.37-49.84, p = .01), and state violence at 9.19% (95% CI 6.71-11.68, p < .00).

CONCLUSIONS

The prevalence of physical violence is a concern among people in a range of insecure migration statuses. Prevalence of violence is not meaningfully higher for people in undocumented status than for people in other types of insecure status.

REVIEW REGISTRATION

PROSPERO (CRD42021268772).

Assessing the properties of patient-specific treatment effect estimates from causal forest algorithms under essential heterogeneity

BACKGROUND

Treatment variation from observational data has been used to estimate patient-specific treatment effects. Causal Forest Algorithms (CFAs) developed for this task have unknown properties when treatment effect heterogeneity from unmeasured patient factors influences treatment choice - essential heterogeneity.

METHODS

We simulated eleven populations with identical treatment effect distributions based on patient factors. The populations varied in the extent that treatment effect heterogeneity influenced treatment choice. We used the generalized random forest application (CFA-GRF) to estimate patient-specific treatment effects for each population. Average differences between true and estimated effects for patient subsets were evaluated.

RESULTS

CFA-GRF performed well across the population when treatment effect heterogeneity did not influence treatment choice. Under essential heterogeneity, however, CFA-GRF yielded treatment effect estimates that reflected true treatment effects only for treated patients and were on average greater than true treatment effects for untreated patients.

CONCLUSIONS

Patient-specific estimates produced by CFAs are sensitive to why patients in real-world practice make different treatment choices. Researchers using CFAs should develop conceptual frameworks of treatment choice prior to estimation to guide estimate interpretation ex post.

Contributions of early detection and cancer prevention to colorectal cancer mortality reduction by screening colonoscopy: a validated modeling study

BACKGROUND AND AIMS

Screening colonoscopy, recommended every 10 years, reduces mortality from colorectal cancer (CRC) by early detection of prevalent but undiagnosed CRC, as well as by removal of precursor lesions. The aim of this study was to assess the relative contribution of both components to total CRC mortality reduction over time.

METHODS

Using a validated multistate Markov model, we simulated hypothetical cohorts of 100,000 individuals aged 55 to 64 years with and without screening at baseline. Main outcomes included proportions of prevented CRC deaths arising from (asymptomatic) CRC already present at baseline and from newly developed CRC during 15 years of follow-up, and mortality rate ratios of screened versus nonscreened groups over time.

RESULTS

Early detection of prevalent cases accounted for 52%, 30%, and 18% of deaths prevented by screening colonoscopy within 5, 10, and 15 years, respectively. Relative reduction of mortality was estimated to be much larger for mortality from incident cancers than for mortality from cancers that were already present and detected early at screening endoscopy and for total CRC mortality (ie, 88% versus 67% and 79%, respectively, within 10 years from screening).

CONCLUSIONS

Reduction of CRC mortality mainly arises from early detection of prevalent cancers during the early years after screening colonoscopy, but prevention of incident cases accounts for the majority of prevented deaths in the longer run. Prevention of incident cases leads to sustained strong reduction of CRC mortality, possibly warranting an extension of screening intervals.

Transforming nursing assessment in acute hospitals: A cluster randomised controlled trial of an evidence-based nursing core assessment (the ENCORE trial)

BACKGROUND

Patient safety is threatened when early signs of clinical deterioration are missed or not acted upon. This research began as a clinical-academic partnership established around a shared concern of nursing physical assessment practices on general wards and delayed recognition of clinical deterioration. The outcome was the development of a complex intervention facilitated at the ward level for proactive nursing surveillance.

METHODS

The evidence-based nursing core assessment (ENCORE) trial was a pragmatic cluster-randomised controlled trial. We hypothesised that ward intervention would reduce the incidence of patient rescue events (medical emergency team activations) and serious adverse events. We randomised 29 general wards in a 1:2 allocation, across 5 Australian hospitals to intervention (n = 10) and usual care wards (n = 19). Skilled facilitation over 12 months enabled practitioner-led, ward-level practice change for proactive nursing surveillance. The primary outcome was the rate of medical emergency team activations and secondary outcomes were unplanned intensive care unit admissions, on-ward resuscitations, and unexpected deaths. Outcomes were prospectively collected for 6 months following the initial 6 months of implementation. Analysis was at the patient level using generalised linear mixed models to account for clustering by ward.

RESULTS

We analysed 29,385 patient admissions to intervention (n = 11,792) and control (n = 17,593) wards. Adjusted models for overall effects suggested the intervention increased the rate of medical emergency team activations (adjusted incidence rate ratio 1.314; 95 % confidence interval 0.975, 1.773), although the confidence interval was compatible with a marginal decrease to a substantial increase in rate. Confidence intervals for secondary outcomes included a range of plausible effects from benefit to harm. However, considerable heterogeneity was observed in intervention effects by patient comorbidity. Among patients with few comorbid conditions in the intervention arm there was a lower medical emergency team activation rate and decreased odds of unexpected death. Among patients with multimorbidity in the intervention arm there were higher rates of medical emergency team activation and intensive care unit admissions.

CONCLUSION

Trial outcomes have refined our assumptions about the impact of the ENCORE intervention. The intervention appears to have protective effects for patients with low complexity where frontline teams can respond locally. It also appears to have redistributed medical emergency team activations and unplanned intensive care unit admissions, mobilising higher rates of rescue for patients with multimorbidity.

TRIAL REGISTRATION NUMBER

ACTRN12618001903279 (Date of registration: 22/11/2018; First participant recruited: 01/02/2019).

Effect of Coenzyme Q10 Supplementation on Vascular Endothelial Function: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

INTRODUCTION

Coenzyme Q10 (CoQ10) has gained attention as a potential therapeutic agent for improving endothelial function. Several randomized clinical trials have investigated CoQ10 supplementation's effect on endothelial function. However, these studies have yielded conflicting results, therefore this systematic review and meta-analysis were conducted.

AIM

This systematic review and meta-analysis were conducted to assess the effects of CoQ10 supplementation on endothelial factors.

METHODS

A comprehensive search was done in numerous databases until July 19th, 2023. Quantitative data synthesis was performed using a random-effects model, with weight mean difference (WMD) and 95% confidence intervals (CI). Standard methods were used for the assessment of heterogeneity, meta-regression, sensitivity analysis, and publication bias.

RESULTS

12 studies comprising 489 subjects were included in the meta-analysis. The results demonstrated significant increases in Flow Mediated Dilation (FMD) after CoQ10 supplementation (WMD: 1.45; 95% CI: 0.55 to 2.36; p < 0.02), but there is no increase in Vascular cell adhesion protein (VCAM), and Intercellular adhesion molecule (ICAM) following Q10 supplementation (VCAM: SMD: - 0.34; 95% CI: - 0.74 to - 0.06; p < 0.10) (ICAM: SMD: - 0.18; 95% CI: - 0.82 to 0.46; p < 0.57). The sensitivity analysis showed that the effect size was robust in FMD and VCAM. In meta-regression, changes in FMD percent were associated with the dose of supplementation (slope: 0.01; 95% CI: 0.004 to 0.03; p = 0.006).

CONCLUSIONS

CoQ10 supplementation has a positive effect on FMD in a dose-dependent manner. Our findings show that CoQ10 has an effect on FMD after 8 weeks of consumption. Additional research is warranted to establish the relationship between CoQ10 supplementation and endothelial function.

Use of conditional estimates of effect in cancer epidemiology: An application to lung cancer treatment

BACKGROUND

In oncology clinical trials, there is the assumption that randomization sufficiently balances confounding covariates and therefore average treatment effects are usually reported. This paper explores the wider benefits provided by conditioning on covariates for reasons other than mitigation of confounding.

METHODS

We reanalyzed the data from primary randomized controlled trials listed in two meta-analyses to explore the significance of conditioning on smoking status in terms of the effect magnitude of treatment on progression free survival in non-small cell lung cancer.

RESULTS

The reanalysis revealed that conditioning on smoking status using sub-group analyses provided the closest empiric estimate of individual treatment effect based on smoking status and significantly reduced the heterogeneity of treatment effect observed across studies. In addition, smoking status was determined to be a modifier of the effect of treatment.

CONCLUSION

Conditioning on prognostic covariates in randomized trials in oncology helps generate the closest empiric estimates of individual treatment benefit, addresses heterogeneity due to varying covariate distributions across trials and facilitates future decision making as well as evidence synthesis. Conditioning using sub-group analyses also allows examination for effect modification in meta-analysis.

Racial/Ethnic Differences in Association Between Medicaid Expansion and Causes and Costs of Readmission After Acute Ischemic Stroke

OBJECTIVE

The purpose of this study was to examine whether the relative frequency of leading causes and total associated costs of readmission after acute ischemic stroke changed with Medicaid expansion, and how these changes differed by racial/ethnic group.

METHODS

We used a difference-in-differences approach to compare changes in the relative frequency of leading causes of unplanned 30-day readmission and to examine changes in the costs associated with unplanned readmission between expansion states (AR, MD, NM, and WA) and non-expansion states (FL and GA). To estimate the differential effect of Medicaid expansion by race/ethnicity on the causes and cost of readmission, we added a time*treatment*race interaction. Multinomial logistic regression was performed to analyze the changes in readmission cause. Gamma log-link modeling was used to study changes in readmission costs for expansion compared to non-expansion states.

RESULTS

The final multinomial model showed an association between expanded Medicaid and the relative frequency of sepsis readmission for White patients. According to predictive margins, White patients in expansion states had an estimated increase of 3.3 percentage points in the share of readmissions for sepsis but not for White patients in non-expansion states. In contrast, non-White patients in expansion states had a decrease of 1.8 percentage points in the share of readmissions for sepsis. Overall, Medicaid expansion was associated with a net increase of 6.7 percentage points in the share of readmissions for sepsis among non-Hispanic Whites relative to all other groups. In the final gamma model, Medicaid expansion was associated with a decrease in readmission costs overall. According to predictive margins, the net cost reduction in expansion versus non-expansion states was an average of $2509.

CONCLUSIONS

Medicaid expansion is associated with an overall decrease in unplanned readmission costs and an increase among readmitted White patients in the likelihood of readmission for sepsis.

Estimating Subgroup Effects in Generalizability and Transportability Analyses

Methods for extending-generalizing or transporting-inferences from a randomized trial to a target population involve conditioning on a large set of covariates that is sufficient for rendering the randomized and nonrandomized groups exchangeable. Yet, decision makers are often interested in examining treatment effects in subgroups of the target population defined in terms of only a few discrete covariates. Here, we propose methods for estimating subgroup-specific potential outcome means and average treatment effects in generalizability and transportability analyses, using outcome model--based (g-formula), weighting, and augmented weighting estimators. We consider estimating subgroup-specific average treatment effects in the target population and its nonrandomized subset, and we provide methods that are appropriate both for nested and non-nested trial designs. As an illustration, we apply the methods to data from the Coronary Artery Surgery Study (North America, 1975-1996) to compare the effect of surgery plus medical therapy versus medical therapy alone for chronic coronary artery disease in subgroups defined by history of myocardial infarction.

A platform for comparing subgroup identification methodologies

Since the advent of the phrase "subgroup identification," there has been an explosion of methodologies that seek to identify meaningful subgroups of patients with exceptional response in order to further the realization of personalized medicine. However, to perform fair comparison and understand what methods work best under different clinical trials situations, a common platform is needed for comparative effectiveness of these various approaches. In this paper, we describe a comprehensive project that created an extensive platform for evaluating subgroup identification methods as well as a publicly posted challenge that was used to elicit new approaches. We proposed a common data-generating model for creating virtual clinical trial datasets that contain subgroups of exceptional responders encompassing the many dimensions of the problem or null scenarios in which there are no such subgroups. Furthermore, we created a common scoring system for evaluating performance of purported methods for identifying subgroups. This makes it possible to benchmark methodologies in order to understand what methods work best under different clinical trial situations. The findings from this project produced considerable insights and allow us to make recommendations for how the statistical community can better compare and contrast old and new subgroup identification methodologies.

Pregnant Populations which Benefit from Vaginal Progesterone for Preventing Preterm Birth at <34 Weeks and Neonatal Morbidities: A Systematic Review and Meta-analysis

This study aimed to assess vaginal progesterone's effect on different populations and performed comparation between women with varied risk factors. Embase, PubMed, Cochrane library (CENTRAL) were searched without restriction to language up to February 25, 2021. Randomized controlled trials (RCTs) assessing vaginal progesterone administered to women at risk of preterm birth at <37 weeks. Two reviewers independently extracted data, and pooled relative risk (RR) with 95% confidence intervals (CIs) was calculated as well. Women with short cervix have a significantly lower risk of preterm birth at <34 weeks (pooled RR = 0.65; 95% CI: 0.55-0.77; I 2 = 0; p < 0.001; nine studies) and some neonatal morbidities; interaction tests showed that effect of vaginal progesterone differs significantly between women with short cervix and those with other risk factors (history of preterm birth, exclusive twin gestation, and vaginal bleeding). Evidences of this study showed that singleton gestations, as well as women with short cervix, benefit from vaginal progesterone in preventing preterm birth at <34 weeks and some neonatal morbidities. Women with short cervix are populations who benefit the most among other risk populations. KEY POINTS: · Vaginal progesterone reduces preterm birth and neonatal morbidities.. · Vaginal progesterone effects on some specific populations.. · Women with short cervix benefit the most..

Dynamic spinal orthoses self-reported effects in patients with back pain due to vertebral fragility fractures: A multi-center prospective cohort study

BACKGROUND

Vertebral fragility fractures (VFFs) commonly result from low bone mass and microarchitecture deterioration of bone tissue. spinal orthoses are common non-pharmacological options for managing vertebral fracture pain. However, the effects of spinal orthoses on pain, physical functioning, and quality of life (QoL) are still debated.

OBJECTIVE

This survey aimed to investigate the patients-reported outcomes of a dynamic spinal orthosis prescribed in the routine clinical practice of VFFs management.

METHODS

This multi-center national-wide prospective cohort study assessed older patients (aged > 60 years) diagnosed with acute VFFs and prescribed with a dynamic spinal orthosis (Spinfast®). A survey questionnaire was realized and included sections on patient characterization, osteoporosis characterization, spinal orthosis, clinical outcomes, pain medications, and osteoporosis medications. The questionnaire was administered at baseline and after three months. A total of 68 patients completed the questionnaire at three months. Most patients had one or two VFFs and were treated with pain medications and osteoporosis medications. Compliance and tolerability of the spinal orthosis were assessed, and clinical outcomes such as pain intensity, physical functioning, and QoL were measured.

RESULTS

The results showed no significant differences in outcomes between age subgroups. Italian physical medicine and rehabilitation physicians were commonly involved in the management of VFFs patients. Sixty-six patients completed the questionnaire. The results showed that pain intensity, physical functioning and QoL improved after three months of spinal orthosis wearing (p< 0.0001).

CONCLUSION

The correct management of VFFs is mandatory to improve pain and reduce disability, and our findings suggested a positive role of dynamic spinal orthosis to improve the comprehensive management of VFFs patients. However, high-quality research trials are warranted to provide clear recommendations for the correct clinical management of VFF.

Quantifying and reducing inequity in average treatment effect estimation

BACKGROUND

Across studies of average treatment effects, some population subgroups consistently have lower representation than others which can lead to discrepancies in how well results generalize.

METHODS

We develop a framework for quantifying inequity due to systemic disparities in sample representation and a method for mitigation during data analysis. Assuming subgroup treatment effects are exchangeable, an unbiased sample average treatment effect estimator will have lower mean-squared error, on average across studies, for subgroups with less representation when treatment effects vary. We present a method for estimating average treatment effects in representation-adjusted samples which enables subgroups to optimally leverage information from the full sample rather than only their own subgroup's data. Two approaches for specifying representation adjustment are offered-one minimizes average mean-squared error for each subgroup separately and the other balances minimization of mean-squared error and equal representation. We conduct simulation studies to compare the performance of the proposed estimators to several subgroup-specific estimators.

RESULTS

We find that the proposed estimators generally provide lower mean squared error, particularly for smaller subgroups, relative to the other estimators. As a case study, we apply this method to a subgroup analysis from a published study.

CONCLUSIONS

We recommend the use of the proposed estimators to mitigate the impact of disparities in representation, though structural change is ultimately needed.

The 3-Meter Backward Walk Test (3MBWT): Reliability and validity in individuals with subacute and chronic stroke

INTRODUCTION

Backward walking (BW) is an important gait adaptation and BW speed may be an important indicator of walking function and fall risk. However, the measurement characteristics of a standardized assessment of BW post-stroke have not been fully established.

OBJECTIVES

To determine intra- and interrater reliability, concurrent validity and minimal detectable change (MDC) scores for the 3-Meter Backward Walk Test (3MBWT) post-stroke.

METHODS

Thirty-four individuals with subacute and 29 individuals with chronic stroke participated. Two trials of comfortable BW was measured over a total distance of 5-meters, while speed was calculated during the middle 3-meters of the walking distance. Intra and interrater reliability were determined by comparing the two trials from one rater and simultaneous assessment of two raters, respectively. Two additional trials were performed and BW speed was calculated using 3MBWT and an instrumented walkway to determine concurrent validity. Intraclass correlation coefficients (ICC) estimated reliability and validity. The MDC was calculated from the standard error of measurement.

RESULTS

Excellent ICC values were obtained for the 3MBWT in the subacute (interrater: ICC2,1 = 0.99; intrarater: ICC2,1 = 0.96; validity: ICC2,1 = 0.96) and chronic (interrater: ICC2,1 = 0.99; intrarater: ICC2,1 = 0.94; validity: ICC2,1 = 0.97) groups. The MDC was 0.07 m/s (subacute) and 0.11 m/s (chronic).

CONCLUSIONS

Establishment of the 3MBWT as a reliable and valid measure in assessing BW speed is an important addition to the assessment toolbox for rehabilitation post-stroke.

The credibility of subgroup analyses reported in stroke trials is low: A systematic review

BACKGROUND

Subgroup analyses are widely used to evaluate the heterogeneity of treatment effects in randomized clinical trials. However, there is a limited investigation of the quality of prespecified and reported subgroup analyses in stroke trials. This study evaluated the credibility of subgroup analyses in stroke trials.

METHODS AND ANALYSIS

We searched Medline/PubMed, Embase, the Cochrane Central Register of Controlled Trials, and the Web of Science from inception to 24 March 2021. Three reviewers screened, extracted, and analyzed the data from the publications. Primary publications of stroke trials that reported at least one subgroup effect and had published corresponding study protocols were included. The Instrument for Assessing the Credibility of Effect Modification Analyses (ICEMAN) was used to examine the quality of the subgroup effects reported, with each subgroup effect assigned a credibility rating ranging from very low to high. Subgroup effects with two or more "definitely no" responses received a low credibility rating. The risk of bias was assessed using the Cochrane Risk-of-Bias tool for randomized trials version 2.

RESULTS

Seventy-four articles met the inclusion criteria and reported a combined total of 647 subgroup effects. The median sample size was 1264 (interquartile range (IQR): 380-3876), and the median number of subgroups prespecified in the protocol was 6 (IQR: 2-10). Sixty-one (82%) studies used the univariate test of interaction. Of the total 647 subgroup effects reported in these studies, 319 (49%) were reported in acute stroke trials, while 423 (65%) had low credibility.

CONCLUSION

The quality of subgroup analysis reporting in stroke trials remains poor. More effort is needed to train trialists on the best methods for designing and performing subgroup analyses, and how to report the results.

TRIAL REGISTRATION NUMBER

We prospectively registered the review with International Prospective Register for Systematic Reviews (registration number: CRD42020223133).

Reflections on the concept of optimality of single decision point treatment regimes

In many areas, applied researchers as well as practitioners have to choose between different solutions for a problem at hand; this calls for optimal decision rules to settle the choices involved. As a key example, one may think of the search for optimal treatment regimes (OTRs) in clinical research, that specify which treatment alternative should be administered to each patient under study. Motivated by the fact that the concept of optimality of decision rules in general and treatment regimes in particular has received so far relatively little attention and discussion, we will present a number of reflections on it, starting from the basics of any optimization problem. Specifically, we will analyze the search space and the to be optimized criterion function underlying the search of single decision point OTRs, along with the many choice aspects that show up in their specification. Special attention is paid to formal characteristics and properties as well as to substantive concerns and hypotheses that may guide these choices. We illustrate with a few empirical examples taken from the literature. Finally, we discuss how the presented reflections may help sharpen statistical thinking about optimality of decision rules for treatment assignment and to facilitate the dialogue between the statistical consultant and the applied researcher in search of an OTR.

Inference on tree-structured subgroups with subgroup size and subgroup effect relationship in clinical trials

When multiple candidate subgroups are considered in clinical trials, we often need to make statistical inference on the subgroups simultaneously. Classical multiple testing procedures might not lead to an interpretable and efficient inference on the subgroups as they often fail to take subgroup size and subgroup effect relationship into account. In this paper, built on the selective traversed accumulation rules (STAR), we propose a data-adaptive and interactive multiple testing procedure for subgroups which can take subgroup size and subgroup effect relationship into account under prespecified tree structure. The proposed method is easy-to-implement and can lead to a more interpretable and efficient inference on prespecified tree-structured subgroups. Possible accommodations to post hoc identified tree-structure subgroups are also discussed in the paper. We demonstrate the merit of our proposed method by re-analyzing the panitumumab trial with the proposed method.

Ticagrelor Versus Clopidogrel in Minor Stroke or Transient Ischemic Attack With Intracranial Artery Stenosis: A Post Hoc Analysis of CHANCE-2

Background This study aimed to investigate the efficacy and safety of ticagrelor-aspirin versus clopidogrel-aspirin in Chinese patients by the presence and clinical presentation of intracranial artery stenosis (ICAS) using randomized trial data from the CHANCE-2 (Clopidogrel in High-Risk Patients With Acute Nondisabling Cerebrovascular Events-II) trial. Methods and Results A total of 6412 patients with minor stroke or transient ischemic attack who carried CYP2C19 loss-of-function alleles were randomized to either the ticagrelor-aspirin or clopidogrel-aspirin group. Patients without imaging of the intracranial artery were excluded from the nonprespecified subgroup analysis of CHANCE-2. All patients included were classified into the following groups: without ICAS, symptomatic ICAS, or asymptomatic ICAS. The primary efficacy outcome was new strokes within 90 days. There were 5893 patients (median age, 64.8 years; 33.9% women) included, and 172 (4.9%), 171 (10.5%), and 57 (7.7%) cases of new strokes occurred within 90 days in the without ICAS, with symptomatic ICAS, and with asymptomatic ICAS groups, respectively. Ticagrelor-aspirin was associated with reduced risk of new stroke in patients without ICAS (62 [3.5%] versus 110 [6.3%]; hazard ratio [HR], 0.57 [95% CI, 0.41-0.78]) but not in those with symptomatic ICAS (HR, 0.77 [95% CI, 0.56-1.05]) or in those with asymptomatic ICAS (HR, 0.77 [95% CI, 0.43-1.38]) compared with clopidogrel-aspirin (P for interaction=0.14). There were no significant differences in the proportion of severe or moderate bleeding events among different ICAS groups. Conclusions Patients without ICAS received a significantly greater benefit from ticagrelor-aspirin than clopidogrel-aspirin after minor ischemic stroke or transient ischemic attack, and there was no statistically significant difference between treatments in patients with symptomatic ICAS or asymptomatic ICAS. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04078737.

Understanding categories or subgroups and a common clinical reasoning error: the example of aneurysm size and neck width

BACKGROUND

Individualized clinical decisions are often made by considering some patient or lesion characteristics that are thought to have an impact on the efficacy or safety of treatment. For example, aneurysm size and neck width have often been determinants of treatment choices in neurovascular practice.

METHODS

We review observational and randomized data on the influence of aneurysm or neck size on angiographic results of coiling, stent-assisted coiling, or surgical clipping. New RCT data are used to demonstrate the shortcomings of managing patients using clinical judgment regarding patient or lesion characteristics. We discuss why clinical decisions should not be based on comparisons of different patients treated by the same treatment. Clinical decision making requires a comparison between the same patients treated with different treatments in a randomized trial.

RESULTS

The results of endovascular treatment of large or wide-necked aneurysms are always inferior to those of small or narrow-necked aneurysms, in observational as well as in randomized studies. However, this fact alone is not sufficient to infer that patients with small aneurysms should be coiled, while those with large aneurysms should be managed with stenting or surgical clipping. The purported superiority of clipping for large aneurysms could not be demonstrated in recent RCTs (while surgery was found superior for small aneurysms). Similarly, the superiority of stent-assisted coiling for wide-necked aneurysms was not shown in another recent RCT.

CONCLUSION

Clinical experience and observational studies alone can mislead practice. Proper clinical decisions for individuals requires randomized evidence.

Who Benefits from School-Based Teen Pregnancy Prevention Programs? Examining Multidimensional Moderators of Program Effectiveness Across Four Studies

Recent research has suggested the importance of understanding for whom programs are most effective (Supplee et al., 2013) and that multidimensional profiles of risk and protective factors may moderate the effectiveness of programs (Lanza & Rhoades, 2012). For school-based prevention programs, moderators of program effectiveness may occur at both the individual and school levels. However, due to the relatively small number of schools in most individual trials, integrative data analysis across multiple studies may be necessary to fully understand the multidimensional individual and school factors that may influence program effectiveness. In this study, we applied multilevel latent class analysis to integrated data across four studies of a middle school pregnancy prevention program to examine moderators of program effectiveness on initiation of vaginal sex. Findings suggest that the program may be particularly effective for schools with USA-born students who speak another language at home. In addition, findings suggest potential positive outcomes of the program for individuals who are lower risk and engaging in normative dating or individuals with family risk. Findings suggest potential mechanisms by which teen pregnancy prevention programs may be effective.

Characteristics of post hoc subgroup analyses of oncology clinical trials: a systematic review

BACKGROUND

Subgroup analyses in clinical trials assess intervention effects on specific patient subgroups, ensuring generalizability. However, they are usually only able to generate hypotheses rather than definitive conclusions. This study examined the prevalence and characteristics of post hoc subgroup analysis in oncology.

METHODS

We systematically reviewed published subgroup analyses from 2000 to 2022. We included articles presenting secondary, post hoc, or subgroup analyses of interventional clinical trials in oncology, cancer survivorship, or cancer screening, published separately from the original clinical trial publication. We collected cancer type, year of publication, where and how subgroup analyses were reported, and funding.

RESULTS

Out of 16 487 screened publications, 1612 studies were included, primarily subgroup analyses of treatment trials for solid tumors (82%). Medical writers contributed to 31% of articles, and 58% of articles reported conflicts of interest. Subgroup analyses increased significantly over time, with 695 published between 2019 and 2022, compared to 384 from 2000 to 2014. Gastrointestinal tumors (25%) and lymphoid lineage tumors (39%) were the most frequently studied solid and hematological malignancies, respectively. Industry funding and reporting of conflicts of interest increased over time. Subgroup analyses often neglected to indicate their secondary nature in the title. Most authors were from high-income countries, most commonly North America (45%).

CONCLUSIONS

This study demonstrates the rapidly growing use of post hoc subgroup analysis of oncology clinical trials, revealing that the majority are supported by pharmaceutical companies, and they frequently fail to indicate their secondary nature in the title. Given the known methodological limitations of subgroup analyses, caution is recommended among authors, readers, and reviewers when conducting and interpreting these studies.

Exploring treatment effect heterogeneity of a PROMs alert intervention in knee and hip arthroplasty patients: A causal forest application

Patient reported outcome measures (PROMs) experience an uptake in use for hip (HA) and knee arthroplasty (KA) patients. As they may be used for patient monitoring interventions, it remains unclear whether their use in HA/KA patients is effective, and which patient groups benefit the most. Nonetheless, knowledge about treatment effect heterogeneity is crucial for decision makers to target interventions towards specific subgroups that benefit to a greater extend. Therefore, we evaluate the treatment effect heterogeneity of a remote PROM monitoring intervention that includes ∼8000 HA/KA patients from a randomized controlled trial conducted in nine German hospitals. The study setting gave us the unique opportunity to apply a causal forest, a recently developed machine learning method, to explore treatment effect heterogeneity of the intervention. We found that among both HA and KA patients, the intervention was especially effective for patients that were female, >65 years of age, had a blood pressure disease, were not working, reported no backpain and were adherent. When transferring the study design into standard care, policy makers should make use of the knowledge obtained in this study and allocate the treatment towards subgroups for which the treatment is especially effective.

Renin-Angiotensin Inhibition and Outcomes in HFrEF and Advanced Kidney Disease

BACKGROUND

Renin-angiotensin system inhibitors improve outcomes in patients with heart failure with reduced ejection fraction (HFrEF). However, less is known about their effectiveness in patients with HFrEF and advanced kidney disease.

METHODS

In the Medicare-linked Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF), 1582 patients with HFrEF (ejection fraction ≤40%) had advanced kidney disease (estimated glomerular filtration rate <30 mL/min/1.73 m2). Of these, 829 were not receiving angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) prior to admission, of whom 214 were initiated on these drugs prior to discharge. We calculated propensity scores for receipt of these drugs for each of the 829 patients and assembled a matched cohort of 388 patients, balanced on 47 baseline characteristics (mean age 78 years; 52% women; 10% African American; 73% receiving beta-blockers). Hazard ratios (HR) and 95% confidence intervals (CI) were estimated comparing 2-year outcomes in 194 patients initiated on ACE inhibitors or ARBs to 194 patients not initiated on those drugs.

RESULTS

The combined endpoint of heart failure readmission or all-cause mortality occurred in 79% and 84% of patients initiated and not initiated on ACE inhibitors or ARBs, respectively (HR associated with initiation, 0.79; 95% CI, 0.63-0.98). Respective HRs (95% CI) for the individual endpoints of - Respective HRs (95% CI) for the individual endpoints of all-cause mortality and heart failure readmission were 0.81 (0.63-1.03) and 0.63 (0.47-0.85).

CONCLUSIONS

The findings from our study add new information to the body of cumulative evidence that suggest that renin-angiotensin system inhibitors may improve clinical outcomes in patients with HFrEF and advanced kidney disease. These hypothesis-generating findings need to be replicated in contemporary patients.

Single-group studies in leading physical therapy journals commonly make inappropriate conclusions regarding treatment effect modifiers. A systematic review

BACKGROUND

Characteristics that identify patients who respond differently to certain interventions are called treatment effect modifiers. Some studies inappropriately report the presence of treatment effect modifiers without adequate study designs.

OBJECTIVES

To evaluate what proportion of single-group studies published in leading physical therapy journals inappropriately report treatment effect modifiers, and to assess whether the proportion varies over time or between journals.

METHODS

A systematic review was conducted of studies published in eight leading physical therapy journals since 2000. Eligible studies were single-group studies (e.g., cohort study or secondary analysis of treatment arm of randomised controlled trial) that investigated any condition, treatment or outcome. Studies that suggested participants with certain baseline characteristics responded better/or worse to the treatment, were considered to have reported inappropriately. Studies reporting that participants with certain baseline characteristics had improved outcomes but did not state it was due to the treatment were considered to have reported appropriately. The proportion of inappropriate reporting was compared over time and between journals.

RESULTS

Of the 145 included studies, 73 (50.3%) were categorised as inappropriately reporting treatment effect modifiers. The proportion of inappropriate reporting was highest in the most recent period, 2018 - 2022 (59.6%) and 2006 - 2011 (55.6%). The proportion of inappropriate reporting varied substantially between journals from 0% (Journal of Physiotherapy) to 91.7% (Journal of Neurologic Physical Therapy).

CONCLUSIONS

A large proportion (50.3%) of single-arm studies in leading physical therapy journals inappropriately report treatment effect modifiers. This inappropriate reporting risks misleading clinicians when selecting interventions for individual patients.

Elastic integrative analysis of randomised trial and real-world data for treatment heterogeneity estimation

We propose a test-based elastic integrative analysis of the randomised trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers. When the real-world data are not subject to bias, our approach combines the trial and real-world data for efficient estimation. Utilising the trial design, we construct a test to decide whether or not to use real-world data. We characterise the asymptotic distribution of the test-based estimator under local alternatives. We provide a data-adaptive procedure to select the test threshold that promises the smallest mean square error and an elastic confidence interval with a good finite-sample coverage property.

Prediction of delayed reperfusion in patients with incomplete reperfusion following thrombectomy

BACKGROUND

The clinical course of patients with incomplete reperfusion after thrombectomy, defined as an expanded Thrombolysis in Cerebral Infarction (eTICI) score of 2a-2c, is heterogeneous. Patients showing delayed reperfusion (DR) have good clinical outcomes, almost comparable to patients with ad-hoc TICI3 reperfusion. We aimed to develop and internally validate a model that predicts DR occurrence in order to inform physicians about the likelihood of a benign natural disease progression.

PATIENTS AND METHODS

Single-center registry analysis including all consecutive, study-eligible patients admitted between 02/2015 and 12/2021. Preliminary variable selection for the prediction of DR was performed using bootstrapped stepwise backward logistic regression. Interval validation was performed with bootstrapping and the final model was developed using a random forests classification algorithm. Model performance metrics are reported with discrimination, calibration, and clinical decision curves. Primary outcome was concordance statistics as a measure of goodness of fit for the occurrence of DR.

RESULTS

A total of 477 patients (48.8% female, mean age 74 years) were included, of whom 279 (58.5%) showed DR on 24 follow-up. The model's discriminative ability for predicting DR was adequate (C-statistics 0.79 [95% CI: 0.72-0.85]). Variables with strongest association with DR were: atrial fibrillation (aOR 2.06 [95% CI: 1.23-3.49]), Intervention-To-Follow-Up time (aOR 1.06 [95% CI: 1.03-1.10]), eTICI score (aOR 3.49 [95% CI: 2.64-4.73]), and collateral status (aOR 1.33 [95% CI: 1.06-1.68]). At a risk threshold of R = 30%, use of the prediction model could potentially reduce the number of additional attempts in one out of four patients who will have spontaneous DR, without missing any patients who do not show spontaneous DR on follow-up.

CONCLUSIONS

The model presented here shows fair predictive accuracy for estimating chances of DR after incomplete thrombectomy. This may inform treating physicians on the chances of a favorable natural disease progression if no further reperfusion attempts are made.

Transcriptomic signature defines two subtypes of locally advanced PCa with distinct neoadjuvant therapy benefits

Background

Patients with locally advanced prostate cancer (LAPCa) received docetaxel-based neoadjuvant chemo-hormonal therapy (NCHT) had better clinical outcomes after surgery compared to neoadjuvant hormonal therapy (NHT) groups, but not all patients experienced favorable clinical outcomes with NCHT, raising the necessity for potential biomarker assessment. The transcriptomic profiling offers a unique opportunity to interrogate the accurate response to NCHT and NHT treatment and to identify the predictive biomarkers for neoadjuvant therapy.

Methods

The whole transcriptomic profiling was performed on baseline biopsies and surgical tissue specimens from 64 patients with LAPCa at Renji Hospital between 2014 and 2018. Biochemical progression-free survival (bPFS)-based gene-by-treatment interaction effects were used to identify predictive biomarkers for guiding treatment selection.

Results

Comparing the transcriptome profiling of pre- and post-treatment LAPCa specimens, NHT and NCHT shared 1917 up- and 670 down-regulated DEGs at least 2-fold. Pathway enrichment analysis showed up-regulated pathways in response to NHT and NCHT were both enriched in cytokine receptor interaction pathways, and down-regulated pathways in response to NCHT were enriched in cell cycle pathways. By comprehensive transcriptome profiling of 64 baseline specimens, ten predictive markers were identified. We integrated them into the signature to evaluate the relative benefits of neoadjuvant therapy, which categorizes patients into two subgroups with relative bPFS benefits from either NHCT or NHT. In the high-score (≥ -95.798) group (n = 37), NCHT treatment led to significantly longer bPFS (P< 0.0001), with a clear and early separation of the Kaplan-Meier curves. In the low-score (< -95.798) group (n = 27), NHT also led to significantly longer bPFS (P=0.0025).

Conclusions

In this study, we proposed the first predictive transcriptomic signature might potentially guide the effective selection of neoadjuvant therapy in LAPCa and might provide precise guidance toward future personalized adjuvant therapy.

Trial registration

The study was approved by the Ethics Committee of Renji Hospital affiliated to Shanghai Jiao Tong University (Ky2019-087).

Completeness of reporting in abstracts of randomized controlled trials assessing interventional radiology for liver disease

PURPOSE

To assess the completeness of reporting in abstracts of published randomized controlled trials (RCTs) assessing interventional radiology (IR) for liver disease; to assess whether publication of the 2017 CONSORT update for nonpharmacological treatments (NPT) resulted in changes in abstract reporting; and to identify factors associated with better reporting.

MATERIAL AND METHODS

MEDLINE and Embase were searched to identify RCTs of IR for liver disease (January 2015-September 2020). Two reviewers assessed the completeness of abstract reporting according to the CONSORT-NPT-2017-update. The primary outcome was the mean number of CONSORT items completely reported among 10 items reported in <50% of the abstracts published in 2015. A time series analysis assessed the evolution trend over time. A multivariate regression model was used to identify factors associated with better reporting.

RESULTS

A total of 107 abstracts of RCTs published in 61 journals were included. Overall, 74% (45/61) of journals endorsed the main CONSORT guidelines, of which 60% (27/45) had a policy to implement them. The mean number of primary outcome items completely reported increased by 0.19 over the study period. The publication of the CONSORT-NPT update did not lead to an increase in the trend of items reported (increase of 0.04 items/month before vs. 0.02 after, P=0.41). Factors associated with more complete reporting were impact factor (OR=1.13; 95%CI:1.07-1.18) and endorsement of CONSORT with an implementation policy (OR=8.29; 95%CI:2.04-33.65).

CONCLUSION

Completeness of reporting is incomplete in abstracts of trials of IR liver disease and did not improve after publication of the CONSORT-NPT-2017 update with abstract guidance.

Aerobic Exercise Training Response in Preterm-Born Young Adults with Elevated Blood Pressure and Stage 1 Hypertension: A Randomized Clinical Trial

Rationale: Premature birth is an independent predictor of long-term cardiovascular risk. Individuals affected are reported to have a lower rate of [Formula: see text]o2 at peak exercise intensity ([Formula: see text]o2PEAK) and at the ventilatory anaerobic threshold ([Formula: see text]o2VAT), but little is known about their response to exercise training. Objectives: The primary objective was to determine whether the [Formula: see text]o2PEAK response to exercise training differed between preterm-born and term-born individuals; the secondary objective was to quantify group differences in [Formula: see text]o2VAT response. Methods: Fifty-two preterm-born and 151 term-born participants were randomly assigned (1:1) to 16 weeks of aerobic exercise training (n = 102) or a control group (n = 101). Cardiopulmonary exercise tests were conducted before and after the intervention to measure [Formula: see text]o2PEAK and the [Formula: see text]o2VAT. A prespecified subgroup analysis was conducted by fitting an interaction term for preterm and term birth histories and exercise group allocation. Measurements and Main Results: For term-born participants, [Formula: see text]o2PEAK increased by 3.1 ml/kg/min (95% confidence interval [CI], 1.7 to 4.4), and the [Formula: see text]o2VAT increased by 2.3 ml/kg/min (95% CI, 0.7 to 3.8) in the intervention group versus controls. For preterm-born participants, [Formula: see text]o2PEAK increased by 1.8 ml/kg/min (95% CI, -0.4 to 3.9), and the [Formula: see text]o2VAT increased by 4.6 ml/kg/min (95% CI, 2.1 to 7.0) in the intervention group versus controls. No significant interaction was observed with birth history for [Formula: see text]o2PEAK (P = 0.32) or the [Formula: see text]o2VAT (P = 0.12). Conclusions: The training intervention led to significant improvements in [Formula: see text]o2PEAK and [Formula: see text]o2VAT, with no evidence of a statistically different response based on birth history. Clinical trial registered with www.clinicaltrials.gov (NCT02723552).