Identifying back pain subgroups: developing and applying approaches using individual patient data collected within clinical trials

Preventive drug treatments for adults with chronic migraine: a systematic review with economic modelling

Background

Chronic migraine is a disabling condition, affecting 2-4% of adults globally. With the introduction of expensive calcitonin gene-related peptide monoclonal antibodies, it is timely to compare the clinical effectiveness and cost-effectiveness of preventive drugs for chronic migraine.

Objective

To assess the clinical effectiveness and cost-effectiveness of medications used for chronic migraine through systematic reviews and economic modelling.

Eligibility criteria

Randomised controlled trials of drug treatments for efficacy with > 100 participants with chronic migraine per arm; for adverse events > 100 participants with episodic or chronic migraine per arm. Previous economic analyses of preventive drugs for chronic migraine.

Data sources

Eight databases.

Reviews methods

Systematic reviews, network meta-analysis and economic modelling.

Outcomes

Monthly headache days, monthly migraine days, headache-related quality of life, cost-effectiveness.

Results

We found 51 individual articles, reporting 11 randomised controlled trials, testing 6 drugs (topiramate, Botox, eptinezumab, erenumab, fremanezumab, galcanezumab), versus placebo, on 7352 adults with chronic migraine. Calcitonin gene-related peptide monoclonal antibodies, Botox and topiramate reduced headache/migraine days by 2.0-2.5, just under two, or by less than 1.5 days per month, respectively. In the network meta-analysis, eptinezumab 300 mg and fremanezumab monthly ranked in first place in both monthly headache day and monthly migraine day analyses. The calcitonin gene-related peptide monoclonal antibodies were consistently the best choices for headache/migraine days and headache-related quality of life. Topiramate was very unlikely to be the best choice for headache/migraine days and headache-related quality of life when compared to calcitonin gene-related peptide monoclonal antibodies or Botox. We found no trials of the commonly used drugs, such as propranolol or amitriptyline, to include in the analysis. The adverse events review included 40 randomised controlled trials with 25,891 participants; 3 additional drugs, amitriptyline, atogepant and rimegepant, were included. There were very few serious adverse events - none of which were linked to the use of these medications. Adverse events were common. Most people using some calcitonin gene-related peptide monoclonal antibodies reported injection site issues; and people using topiramate or amitriptyline had nervous system or gastrointestinal issues. The cost-effectiveness review identified 16 studies evaluating chronic migraine medications in adults. The newer, injected drugs are more costly than the oral preventatives, but they were cost-effective. Our economic model showed that topiramate was the least costly option and had the fewest quality-adjusted life-year gains, whereas eptinezumab 300 mg was more costly but generated the most quality-adjusted life-year gains. The cost-effectiveness acceptability frontier showed that topiramate was the most cost-effective medication if the decision maker is willing to pay up to £50,000 per quality-adjusted life-year. Our consensus workshop brought together people with chronic migraine and headache experts. Consensus was reached on the top three recommendations for future research on medications to prevent chronic migraine: (1) calcitonin gene-related peptide monoclonal antibodies and Botox versus calcitonin gene-related peptide monoclonal antibodies, (2) candesartan versus placebo and (3) flunarizine versus placebo.

Limitations

Topiramate was the only oral drug for which we were able to include data. We did not find sufficient quality evidence to support the use of other oral drugs.

Conclusions

We did not find evidence that the calcitonin gene-related peptide monoclonal antibodies are more clinically and cost-effective when compared to topiramate or Botox. We identified directions for future research these drugs might take.

Study registration

This study is registered as PROSPERO CRD42021265990, CRD42021265993 and CRD42021265995.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: NIHR132803) and is published in full in Health Technology Assessment; Vol. 28, No. 63. See the NIHR Funding and Awards website for further award information.

Comparing algorithms for characterizing treatment effect heterogeneity in randomized trials

The identification and estimation of heterogeneous treatment effects in biomedical clinical trials are challenging, because trials are typically planned to assess the treatment effect in the overall trial population. Nevertheless, the identification of how the treatment effect may vary across subgroups is of major importance for drug development. In this work, we review some existing simulation work and perform a simulation study to evaluate recent methods for identifying and estimating the heterogeneous treatments effects using various metrics and scenarios relevant for drug development. Our focus is not only on a comparison of the methods in general, but on how well these methods perform in simulation scenarios that reflect real clinical trials. We provide the R package benchtm that can be used to simulate synthetic biomarker distributions based on real clinical trial data and to create interpretable scenarios to benchmark methods for identification and estimation of treatment effect heterogeneity.

Subgroup identification in individual participant data meta-analysis using model-based recursive partitioning

Model-based recursive partitioning (MOB) can be used to identify subgroups with differing treatment effects. The detection rate of treatment-by-covariate interactions and the accuracy of identified subgroups using MOB depend strongly on the sample size. Using data from multiple randomized controlled clinical trials can overcome the problem of too small samples. However, naively pooling data from multiple trials may result in the identification of spurious subgroups as differences in study design, subject selection and other sources of between-trial heterogeneity are ignored. In order to account for between-trial heterogeneity in individual participant data (IPD) meta-analysis random-effect models are frequently used. Commonly, heterogeneity in the treatment effect is modelled using random effects whereas heterogeneity in the baseline risks is modelled by either fixed effects or random effects. In this article, we propose metaMOB, a procedure using the generalized mixed-effects model tree (GLMM tree) algorithm for subgroup identification in IPD meta-analysis. Although the application of metaMOB is potentially wider, e.g. randomized experiments with participants in social sciences or preclinical experiments in life sciences, we focus on randomized controlled clinical trials. In a simulation study, metaMOB outperformed GLMM trees assuming a random intercept only and model-based recursive partitioning (MOB), whose algorithm is the basis for GLMM trees, with respect to the false discovery rates, accuracy of identified subgroups and accuracy of estimated treatment effect. The most robust and therefore most promising method is metaMOB with fixed effects for modelling the between-trial heterogeneity in the baseline risks.

Moderators of the Effect of Spinal Manipulative Therapy on Pain Relief and Function in Patients with Chronic Low Back Pain: An Individual Participant Data Meta-analysis

STUDY DESIGN

Individual participant data (IPD) meta-analysis.

OBJECTIVE

The aim of this study was to identify which participant characteristics moderate the effect of spinal manipulative therapy (SMT) on pain and functioning in chronic LBP.

SUMMARY OF BACKGROUND

The effects of SMT are comparable to other interventions recommended in guidelines for chronic low back pain (LBP); however, it is unclear which patients are more likely to benefit from SMT compared to other therapies.

METHODS

IPD were requested from randomized controlled trials (RCTs) examining the effect of SMT in adults with chronic LBP for pain and function compared to various other therapies (stratified by comparison). Potential patient moderators (n = 23) were a priori based on their clinical relevance. We investigated each moderator using a one-stage approach with IPD and investigated this interaction with the intervention for each time point (1, 3, 6, and 12 months).

RESULTS

We received IPD from 21 of 46 RCTs (n = 4223). The majority (12 RCTs, n = 2249) compared SMT to recommended interventions. The duration of LBP, baseline pain (confirmatory), smoking, and previous exposure to SMT (exploratory) had a small moderating effect across outcomes and follow-up points; these estimates did not represent minimally relevant differences in effects; for example, patients with <1 year of LBP demonstrated more positive point estimates for SMT versus recommended therapy for the outcome pain (mean differences ranged from 4.97 (95% confidence interval, CI: -3.20 to 13.13) at 3 months, 10.76 (95% CI: 1.06 to 20.47) at 6 months to 5.26 (95% CI: -2.92 to 13.44) at 12 months in patients with over a year LBP. No other moderators demonstrated a consistent pattern across time and outcomes. Few moderator analyses were conducted for the other comparisons because of too few data.

CONCLUSION

We did not identify any moderators that enable clinicians to identify which patients are likely to benefit more from SMT compared to other treatments.Level of Evidence: 2.

The Patient Perspective on Patient-Reported Outcome Measures Following Elective Hand Surgery: A Convergent Mixed-Methods Analysis

PURPOSE

Patient-reported outcome measures (PROMs) have traditionally been used for research purposes, but are now being used to evaluate outcomes from the patient's perspective and inform ongoing management and quality of care. We used quantitative and qualitative approaches to evaluate the short-version Disabilities of the Arm, Shoulder, and Hand (QuickDASH) and the Patient-Specific Functional Scale (PSFS) with regard to patient preference and measurement of patient goals and their responsiveness after treatment.

METHODS

Patients 18 years or older undergoing elective hand surgery received the QuickDASH and PSFS questionnaires before and at 6 weeks after surgery. Two additional questions intended to elicit patients' preferences regarding the QuickDASH and PSFS were included. Responsiveness was measured by change in pre- to postoperative score. We analyzed patients' responses to the 2 additional questions to identify themes in PROM preferences. Results from the quantitative and qualitative analyses were combined into a convergent mixed-methods (eg, quantitative and qualitative) analysis.

RESULTS

Thirty-eight patients completed preoperative questionnaires; 25 (66%) completed postoperative questionnaires. Seventeen patients (77%) preferred the PSFS, 3 (14%) had no preference, 2 (9%) preferred the QuickDASH. The average change from pre- to postoperative QuickDASH was -10 (SD, 20), and that of the PSFS was -27 (SD, 26). Ten patients (40%) reported QuickDASH score changes above the minimal clinically importance difference (MCID), 17 patients (68%) reported PSFS score changes above the MCID. Content analysis revealed 4 themes in preference for a PROM: instrument simplicity (ease of instrument understanding and completion), personalized assessment (individualization and relevance), goal directed (having measurable aims or objectives), distinct items (concrete or specific instrument items or functions).

CONCLUSIONS

Most patients felt the PSFS better measured their goals because it is a simple, personalized instrument with distinct domains.

CLINICAL RELEVANCE

Whereas standardized PROMs may better compare across populations, physicians, or conditions, employing PROMs that address patient-specific goals may better assess aspects of care most important to patients. A combination of these 2 types of PROMs can be used to assess outcomes and inform quality of care.

A comparison of subgroup identification methods in clinical drug development: Simulation study and regulatory considerations

With advancement of technologies such as genomic sequencing, predictive biomarkers have become a useful tool for the development of personalized medicine. Predictive biomarkers can be used to select subsets of patients, which are most likely to benefit from a treatment. A number of approaches for subgroup identification were proposed over the last years. Although overviews of subgroup identification methods are available, systematic comparisons of their performance in simulation studies are rare. Interaction trees (IT), model-based recursive partitioning, subgroup identification based on differential effect, simultaneous threshold interaction modeling algorithm (STIMA), and adaptive refinement by directed peeling were proposed for subgroup identification. We compared these methods in a simulation study using a structured approach. In order to identify a target population for subsequent trials, a selection of the identified subgroups is needed. Therefore, we propose a subgroup criterion leading to a target subgroup consisting of the identified subgroups with an estimated treatment difference no less than a pre-specified threshold. In our simulation study, we evaluated these methods by considering measures for binary classification, like sensitivity and specificity. In settings with large effects or huge sample sizes, most methods perform well. For more realistic settings in drug development involving data from a single trial only, however, none of the methods seems suitable for selecting a target population. Using the subgroup criterion as alternative to the proposed pruning procedures, STIMA and IT can improve their performance in some settings. The methods and the subgroup criterion are illustrated by an application in amyotrophic lateral sclerosis.

Facet joint injections for people with persistent non-specific low back pain (Facet Injection Study): a feasibility study for a randomised controlled trial

BACKGROUND

The National Institute for Health and Care Excellence (NICE) 2009 guidelines for persistent low back pain (LBP) do not recommend the injection of therapeutic substances into the back as a treatment for LBP because of the absence of evidence for their effectiveness. This feasibility study aimed to provide a stable platform that could be used to evaluate a randomised controlled trial (RCT) on the clinical effectiveness and cost-effectiveness of intra-articular facet joint injections (FJIs) when added to normal care.

OBJECTIVES

To explore the feasibility of running a RCT to test the hypothesis that, for people with suspected facet joint back pain, adding the option of intra-articular FJIs (local anaesthetic and corticosteroids) to best usual non-invasive care is clinically effective and cost-effective.

DESIGN

The trial was a mixed design. The RCT pilot protocol development involved literature reviews and a consensus conference followed by a randomised pilot study with an embedded mixed-methods process evaluation.

SETTING

Five NHS acute trusts in England.

PARTICIPANTS

Participants were patients aged ≥ 18 years with moderately troublesome LBP present (> 6 months), who had failed previous conservative treatment and who had suspected facet joint pain. The study aimed to recruit 150 participants (approximately 30 per site). Participants were randomised sequentially by a remote service to FJIs combined with 'best usual care' (BUC) or BUC alone.

INTERVENTIONS

All participants were to receive six sessions of a bespoke BUC rehabilitation package. Those randomised into the intervention arm were, in addition, given FJIs with local anaesthetic and steroids (at up to six injection sites). Randomisation occurred at the end of the first BUC session.

MAIN OUTCOME MEASURES

Process and clinical outcomes. Clinical outcomes included a measurement of level of pain on a scale from 0 to 10, which was collected daily and then weekly via text messaging (or through a written diary). Questionnaire follow-up was at 3 months.

RESULTS

Fifty-two stakeholders attended the consensus meeting. Agreement informed several statistical questions and three design considerations: diagnosis, the process of FJI and the BUC package and informing the design for the randomised pilot study. Recruitment started on 26 June 2015 and was terminated by the funder (as a result of poor recruitment) on 11 December 2015. In total, 26 participants were randomised. Process data illuminate some of the reasons for recruitment problems but also show that trial processes after enrolment ran smoothly. No between-group analysis was carried out. All pain-related outcomes show the expected improvement between baseline and follow-up. The mean total cost of the overall treatment package (injection £419.22 and BUC £264.00) was estimated at £683.22 per participant. This is similar to a NHS tariff cost for a course of FJIs of £686.84.

LIMITATIONS

Poor recruitment was a limiting factor.

CONCLUSIONS

This feasibility study achieved consensus on the main challenges in a trial of FJIs for people with persistent non-specific low back pain.

FUTURE WORK

Further work is needed to test recruitment from alternative clinical situations.

TRIAL REGISTRATION

EudraCT 2014-000682-50 and Current Controlled Trials ISRCTN93184143.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 21, No. 30. See the NIHR Journals Library website for further project information.

Differential Treatment Response to Insulin Intensification Therapy: A Post Hoc Analysis of a Randomized Trial Comparing Premixed and Basal-Bolus Insulin Regimens

INTRODUCTION

Identification of subgroups of patients that may benefit most from certain treatment is important because individual treatment response varies due to multiple contributing factors. The present study used the subgroup identification based on the differential effect search (SIDES) algorithm to identify subgroups with different treatment responses to insulin intensification therapies.

METHODS

This was a post hoc analysis of a 24-week, multicenter, open-label, randomized, parallel study comparing prandial premixed therapy (PPT) to basal-bolus therapy (BBT). Patients with type 2 diabetes mellitus were randomized to PPT (insulin lispro mix 50/50 thrice daily with meals) or BBT (glargine at bedtime plus mealtime insulin lispro) insulin intensification therapies. The SIDES algorithm was used to identify the subgroups from at-goal patients [glycated hemoglobin (HbA1c) <7.0% (53.0 mmol/mol) at the end of 24 weeks; n = 182] who could have benefitted from insulin intensification therapies.

RESULTS

Baseline characteristics of overall at-goal patients were comparable between PPT and BBT groups. The SIDES algorithm identified patients with race other than Caucasian (i.e., African-American, Asian, and Hispanic) and baseline fasting blood glucose (FBG) <8.89 mmol/L as a subgroup that could respond better to PPT relative to BBT than the overall at-goal patient population. In this identified subgroup population, the HbA1c mean (standard deviation) changes from baseline to endpoint in PPT and BBT groups were -2.27 (0.88)% versus -2.05 (0.75)%; p = 0.40, respectively; while in the overall at-goal patients, the HbA1c changes were -2.17 (0.79)% versus -2.34 (1.00)%; p = 0.19, respectively.

CONCLUSIONS

The preliminary results showed that the subgroup of patients with race other than Caucasian and FBG <8.89 mmol/L may respond better to premixed intensification therapy. This result provides some preliminary information for further investigation in prospective studies.

FUNDING

Eli Lilly and Company.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov ID number: NCT00110370.

Development of a repository of individual participant data from randomized controlled trials of therapists delivered interventions for low back pain

Background

Individual patient data (IPD) meta‐analysis of existing randomized controlled trials (RCTs) is a promising approach to achieving sufficient statistical power to identify sub‐groups. We created a repository of IPD from multiple low back pain (LBP) RCTs to facilitate a study of treatment moderators. Due to sparse heterogeneous data, the repository needed to be robust and flexible to accommodate millions of data points prior to any subsequent analysis.

Methods

We systematically identified RCTs of therapist delivered intervention for inclusion to the repository. Some were obtained through project publicity. We requested both individual items and aggregate scores of all baseline characteristics and outcomes for all available time points. The repository is made up of a hybrid database: entity‐attribute‐value and relational database which is capable of storing sparse heterogeneous datasets. We developed a bespoke software program to extract, transform and upload the shared data.

Results

There were 20 datasets with more than 3 million data points from 9328 participants. All trials collected covariates and outcomes data at baseline and follow‐ups. The bespoke standardized repository is flexible to accommodate millions of data points without compromising data integrity. Data are easily retrieved for analysis using standard statistical programs.

Conclusions

The bespoke hybrid repository is complex to implement and to query but its flexibility in supporting datasets with varying sets of responses and outcomes with different data types is a worthy trade off. The large standardized LBP dataset is also an important resource useable by other LBP researchers.

Significance

A flexible adaptive database for pain studies that can easily be expanded for future researchers to map, transform and upload their data in a safe and secure environment. The data are standardized and harmonized which will facilitate future requests from other researchers for secondary analyses.